In this session, we investigate some of the methods used by scientists to measure evolution. A whiteboard animation introduces Hardy-Weinberg equilibrium (HWE) and explains how it can be used to calculate frequencies of specific alleles in a population. This whiteboard also suggests reasons why allele frequencies in a population may evolve or change over time. Three short video clips (from Drs. Hale, Tishkoff, and Newman) explain methods for generating phylogenetic trees and what they can tell us about the relatedness of species and how long ago they diverged. In our last video, David Haussler shares his excitement about the chance to compare multiple sequenced genomes and identify the genetic innovations that made us who we are today.
- Duration: 10:25
00:00:07.24 Hi. My name is Melina Hale.
00:00:09.08 I'm a professor at the University of Chicago.
00:00:11.14 In my lab, we study neurobiology,
00:00:14.22 and evolution.
00:00:16.09 I'm going to present two different topics.
00:00:18.12 The first is an introduction to evolution.
00:00:22.12 Then we'll go on to talk about
00:00:24.10 a specific example from my lab
00:00:26.26 of how we map the nervous system
00:00:29.20 and aspects of the nervous system
00:00:31.12 onto the evolution of animals.
00:00:33.18 We work in my lab, specifically,
00:00:35.06 on vertebrate animals,
00:00:36.18 things like fish and tetrapods,
00:00:38.17 mammals, and reptiles,
00:00:40.27 and so I'm going to focus on that
00:00:43.07 part of biodiversity
00:00:45.07 in my talks.
00:00:46.22 There's a lot of other organisms out there, of course,
00:00:49.08 invertebrates, and insects, and plants,
00:00:51.18 and microbes,
00:00:52.26 that we won't touch on in these lectures.
00:00:55.26 So, we'll start with this introduction into evolution.
00:00:58.10 What is evolution?
00:01:00.05 Now, Charles Darwin
00:01:02.13 originally proposed the theory of evolution,
00:01:05.00 which can be summarized
00:01:06.27 in a very succinct phrase:
00:01:08.14 descent with modification.
00:01:10.05 Now, let's break that down a little bit, though,
00:01:12.17 to a broader definition,
00:01:14.22 which is change in the heritable characteristics
00:01:17.10 of organisms
00:01:18.29 from generation to generation.
00:01:20.29 We can break that down
00:01:22.13 even further to look at
00:01:24.11 the component parts of that sentence.
00:01:25.18 First, if we think about
00:01:27.03 this idea of generation to generation,
00:01:29.12 that means that when we look at evolution,
00:01:31.05 we're really not talking about changes
00:01:33.00 in individuals
00:01:34.17 or over short time frames.
00:01:36.01 Instead, we're talking about
00:01:38.04 changes that we see
00:01:39.28 over a long history
00:01:41.23 of the descent of an organism over time.
00:01:45.11 What about heritable characteristics?
00:01:47.04 Well, we all have lots of characteristics
00:01:49.01 to our bodies.
00:01:51.02 We may have big muscles
00:01:52.24 if we exercise a lot,
00:01:54.09 we may have had injuries in our lifetime
00:01:56.11 that have given us scars.
00:01:57.21 Those are not heritable characteristics.
00:02:00.10 Heritable characteristics
00:02:02.02 are the types of traits
00:02:03.19 that we pass on to subsequent generations,
00:02:06.11 or that we inherited from our parents
00:02:08.29 and grandparents.
00:02:10.18 Heritable characteristics
00:02:12.15 are an important part of evolution,
00:02:14.11 because it allows transmission
00:02:17.12 from one generation to the next,
00:02:18.24 and on and on through evolutionary history.
00:02:21.23 Now, the last part of this is change,
00:02:23.29 and change is also really important.
00:02:26.08 There has to be the ability in evolution
00:02:29.05 for these heritable characteristics
00:02:30.29 to vary,
00:02:32.21 to change in response to environmental factors
00:02:35.13 that might favor one type of characteristic
00:02:38.09 or another,
00:02:39.16 and we'll come back to that.
00:02:40.25 And that's what Darwin was getting at
00:02:42.21 with this idea of modification,
00:02:44.13 that there's going to be change
00:02:46.01 in how organisms are organized
00:02:47.24 and how they look over time.
00:02:52.03 So, here's an example,
00:02:53.18 a cute picture of a pair of dogs
00:02:56.07 and their puppies,
00:02:57.19 where you can really see
00:02:59.07 the variation in characteristics,
00:03:00.25 even in one generation.
00:03:02.23 If you look at the parents
00:03:04.11 and you look at the pups,
00:03:05.21 you can see some of the puppies
00:03:07.03 look like one parent,
00:03:08.21 with, you know, pure light fur,
00:03:11.03 others look like the other parent,
00:03:12.27 with very dark fur around the face,
00:03:15.03 but yet there are other puppies in the litter
00:03:17.13 that look different yet again,
00:03:19.04 that have a mix of the characteristics
00:03:21.29 of those two adults.
00:03:24.05 So, you can get a sense
00:03:25.29 of the variation in this image
00:03:27.26 that can be explored in evolution
00:03:30.29 and capitalized upon
00:03:33.06 through evolutionary time.
00:03:35.29 One example of variation
00:03:38.05 that's been really important for us
00:03:40.11 to understand how we can
00:03:43.17 change the characteristics,
00:03:45.07 the features of a species,
00:03:47.14 over time,
00:03:48.28 is the peppered moth.
00:03:50.12 So, these two moths,
00:03:51.23 that look very, very different
00:03:53.06 -- the light one on the left
00:03:54.24 and the dark one on the right --
00:03:56.01 are the same species.
00:03:57.12 They can interbreed.
00:03:58.23 Now, the dark one and the light one,
00:04:00.04 as you might expect,
00:04:02.07 do better in different types of environments.
00:04:06.03 This color characteristic
00:04:08.03 varies, of course,
00:04:10.00 and in some environments
00:04:11.29 it benefits the organisms
00:04:13.21 to be light or to be dark.
00:04:15.02 In other environments,
00:04:16.21 that same characteristic
00:04:18.16 may be detrimental to the animal.
00:04:20.14 So, these peppered moths
00:04:22.10 provided a classic example
00:04:24.01 of how characteristics can vary
00:04:27.07 with environment,
00:04:28.12 and how populations of a particular species
00:04:30.28 can vary.
00:04:32.22 So, this was noted
00:04:34.07 particularly in the industrial revolution.
00:04:36.19 At that time,
00:04:38.00 we went from manufacturing
00:04:39.22 using people
00:04:41.21 sewing or create objects
00:04:43.08 to using a lot of machines
00:04:44.26 to make products.
00:04:47.01 With the use of machines
00:04:48.21 came the use of coal,
00:04:50.25 and with coal came soot,
00:04:52.19 or pollution in the air.
00:04:54.06 Now, with that soot and pollution,
00:04:55.24 you could imagine that structures in the environment,
00:04:59.03 like trees,
00:05:00.19 would become darker,
00:05:01.28 and the peppered moth populations
00:05:04.05 changed in order to accommodate that.
00:05:06.27 And the darker morph
00:05:09.05 of the peppered moth
00:05:11.14 survived better. Right?
00:05:12.26 It was better camouflaged
00:05:14.23 against potential predators in the environment.
00:05:17.08 When the environment cleared up
00:05:19.21 and pollution decreased,
00:05:21.08 the tree barks became lighter
00:05:23.26 and the lighter version of the moth
00:05:25.25 actually survived better.
00:05:27.17 So, we can see variation
00:05:29.00 in the characteristics in a population,
00:05:31.19 even over this short amount of time,
00:05:34.20 and due to a human-induced
00:05:37.07 artifact in the environment,
00:05:38.09 this pollution from coal.
00:05:41.01 Now, just to show you how striking
00:05:43.05 this difference can be in the camouflage
00:05:45.05 of these moths on trees,
00:05:46.29 we can see some here.
00:05:48.19 So, here's our dark morph and our light morph,
00:05:50.17 and if we look at this tree,
00:05:51.28 we can see both the dark morph
00:05:53.15 and the light morph.
00:05:54.19 Here's the light one right down here,
00:05:56.20 and you can see it better camouflages
00:05:58.00 against the light bark
00:05:59.17 in this healthy tree.
00:06:01.05 The dark morph stands out against that light tree,
00:06:03.27 expect in this area over here,
00:06:05.22 where it's against this injury to the tree,
00:06:08.09 which shows up darker.
00:06:10.03 Another example in variation in populations
00:06:14.08 that we've probably all had experience with
00:06:16.14 is in bacteria
00:06:18.19 and the treatment of bacteria with antibiotics.
00:06:21.06 So, when we go to our doctor's office
00:06:22.26 with a bacterial infection,
00:06:24.08 we're prescribed antibiotics,
00:06:26.06 medicine to kill those bacteria,
00:06:28.19 and doctors are often very specific
00:06:31.09 about the need to take that medicine
00:06:34.11 over a precise time course,
00:06:36.11 and in particularly they say,
00:06:37.27 "Don't stop the medicine early.
00:06:40.12 You have to take the full course of medicine.
00:06:42.19 Even if you're feeling better,
00:06:44.21 take the full course of medicine."
00:06:46.07 It's important to do that.
00:06:47.25 Why is that?
00:06:49.02 It's because of the selection
00:06:51.00 that's acting on the variation in the population.
00:06:54.13 So, when we have a bacterial infection,
00:06:57.00 the species of bacteria
00:06:58.27 that's in our bodies
00:07:00.07 may have lots of variants to it,
00:07:02.04 and this is shown in number 1 on the left.
00:07:04.06 They might vary in aspects of their biology,
00:07:07.16 including how strong they are,
00:07:09.01 how resistant they are
00:07:11.01 to antibiotic medicines.
00:07:12.27 If we treat them,
00:07:15.06 shown in point 2 over here,
00:07:17.05 but we don't treat them long enough,
00:07:19.14 which are the bacteria
00:07:21.03 that are going to survive?
00:07:22.12 It's going to be the ones that are the strongest,
00:07:23.28 that are the most resistant
00:07:25.25 to the medication.
00:07:27.06 So, if we don't kill them
00:07:29.03 and we stop taking the medicine,
00:07:30.26 they'll be able to multiply
00:07:32.24 and will take on a larger part
00:07:34.28 of the population
00:07:36.20 of the bacteria.
00:07:37.25 It's not unless we kill them all
00:07:39.17 that we can prevent those resistant bacteria
00:07:42.06 from then multiplying
00:07:43.28 and becoming a problem
00:07:45.15 for our antibiotic medications
00:07:47.16 down the road.
00:07:49.07 So, I've shown you several examples
00:07:51.08 of how populations of a species can vary,
00:07:55.07 whether it's peppered moths or bacteria,
00:07:58.05 but how do we go from that
00:07:59.23 population-level variation
00:08:01.26 to the evolution of new species?
00:08:05.11 This is called speciation,
00:08:07.13 and in general
00:08:09.15 what happens is that populations
00:08:11.08 of a species
00:08:12.28 will be separated
00:08:14.13 and unable to interbreed,
00:08:16.03 and if they're separated
00:08:18.01 for a long enough period of time,
00:08:19.17 when they come back together
00:08:21.02 they may not be able to interbreed,
00:08:23.27 and then we would call them
00:08:25.25 different species.
00:08:27.02 One of the ways
00:08:28.25 that interbreeding is prevented
00:08:30.16 is through geographic isolation.
00:08:35.06 One of the students in my lab,
00:08:36.18 Andrew Trandai,
00:08:38.07 actually helped me out
00:08:40.13 by developing this hypothetical example
00:08:42.14 that I'm going to show you
00:08:44.23 on what a speciation event
00:08:46.13 might look like,
00:08:47.23 so I have to thank Andrew
00:08:49.19 for all of the images
00:08:50.28 that are coming up in the next series.
00:08:54.06 Okay, so in our hypothetical example,
00:08:56.29 what we're looking at is
00:08:58.29 some rodent squirrel-like animal
00:09:01.00 in an environment
00:09:02.19 -- one species --
00:09:04.06 all together as one population.
00:09:07.20 So, how do we separate them
00:09:09.16 and get new populations to evolve?
00:09:11.17 Well, in Andrew's example, here,
00:09:13.23 we have flooding
00:09:15.29 and an aquatic barrier
00:09:17.27 that these animals cannot cross,
00:09:20.01 so effectively
00:09:21.29 the population in the trees
00:09:23.12 and the population in the sand
00:09:25.19 are separated now
00:09:27.16 and will be evolving independently.
00:09:30.21 Over time, if we look at each of them,
00:09:32.23 we may see differences
00:09:34.12 being incorporated
00:09:37.17 into their biology.
00:09:38.25 Just superficially,
00:09:40.06 we might see the animals
00:09:41.29 that are in the forest
00:09:43.23 turning a different color,
00:09:45.19 other aspects of their anatomy
00:09:47.15 might change
00:09:49.17 to live in the trees.
00:09:51.04 On the opposite side of our river,
00:09:54.18 we may see the populations
00:09:56.07 that are in more of a sandy desert environment
00:09:59.18 change coat color
00:10:01.09 to match that environment,
00:10:02.20 or change size
00:10:04.15 to better adjust physiologically
00:10:06.10 to this drier environment.
00:10:08.13 Then ultimately,
00:10:10.00 once these differences have occurred
00:10:12.06 over, again, a very, very long period of time,
00:10:15.01 through evolution,
00:10:16.08 what would happen if the river dried up
00:10:18.16 and these animals
00:10:20.24 were able to come back together?
00:10:22.27 Well, they might come back together
00:10:25.07 and be able to interbreed,
00:10:27.10 but they may come back together
00:10:28.29 and not recognize each other
00:10:30.18 as the same species,
00:10:32.00 and therefore,
00:10:33.16 even though they're together
00:10:34.25 in this environment,
00:10:35.29 they would not interbreed
00:10:37.18 and their independent characteristics
00:10:39.04 would be carried on
00:10:40.25 from generation to generation
00:10:42.12 in those species.
00:10:47.14 So, that was an example
00:10:49.04 of geographic isolation,
00:10:51.04 and the biggest example of geographic isolation
00:10:53.22 happened about 200 million years ago,
00:10:56.18 when Pangaea,
00:10:58.06 which was this big super continental landmass,
00:11:00.25 broke apart to give us
00:11:03.16 the different continents that we know today.
00:11:05.28 So, South America and Africa
00:11:09.16 broke apart from North America and Europe,
00:11:13.08 and those continents
00:11:15.03 moved and separated around the globe.
00:11:17.22 With that separation,
00:11:20.00 the species that were together
00:11:22.08 prior to this breakup
00:11:23.25 then became separated,
00:11:25.16 and so if we look at species
00:11:27.10 that are in Africa versus South America,
00:11:29.20 for example,
00:11:30.28 we can see animals that
00:11:32.27 perhaps came from the same lineage,
00:11:34.14 but now are very, very different,
00:11:37.06 and are in fact different species.
00:11:43.20 Okay, so we've talked about this
00:11:46.04 process of evolution
00:11:47.16 and how it can occur.
00:11:49.28 What if we want to understand
00:11:51.16 the evolutionary history
00:11:53.11 of the animals that are
00:11:55.22 alive on earth today?
00:11:58.09 Well, we have to use a different set of techniques
00:12:00.28 to do that.
00:12:02.14 Here's just some of vertebrate diversity
00:12:04.16 and, as I said at the beginning of the lecture,
00:12:07.11 we also have lots of plants
00:12:09.16 and invertebrates and insects.
00:12:11.10 So I'm just showing you a very small part
00:12:12.14 of biodiversity here.
00:12:14.14 How do we figure out,
00:12:16.06 with animals so diverse as these,
00:12:18.17 how they're related to one another?
00:12:20.16 And how they evolved through time?
00:12:23.10 Well, we can take
00:12:25.04 a very simple example
00:12:27.03 of how we construct our own family trees
00:12:29.24 over very short time periods,
00:12:31.23 over several generations, say.
00:12:33.21 We research our genealogy,
00:12:35.11 we use birth notices and death notices,
00:12:38.27 and we recalled history
00:12:40.27 from our parents or grandparents,
00:12:42.29 and we can use that
00:12:45.01 to construct relationships
00:12:46.21 among our relatives and ourselves.
00:12:49.13 This is a really interesting family tree
00:12:51.25 that's on the wall of a Czech castle, actually,
00:12:55.01 and shows the relatedness
00:12:56.19 of this family,
00:12:58.04 going from a founder
00:12:59.17 down at the base of the tree, in the trunk,
00:13:01.20 up to the descendants at the top of the tree.
00:13:05.24 So, if we take a hypothetical example,
00:13:09.01 of building a family tree,
00:13:11.05 and we start with
00:13:13.06 this family of green-ish and blue-ish,
00:13:15.13 big-eared and small-eared organisms,
00:13:18.04 and try to construct how they're related,
00:13:20.21 we can just look and see how family trees
00:13:23.05 are organized.
00:13:26.01 So, here I've taken that population
00:13:27.29 and put them onto their tree
00:13:29.25 -- that I made up --
00:13:32.01 and we can see that they're related to one another.
00:13:36.10 So, the individuals
00:13:39.12 that are connected at the first branch
00:13:41.21 are siblings.
00:13:43.11 They have the same parents.
00:13:45.21 If we move back in the tree,
00:13:48.01 we're looking at the different common ancestors
00:13:51.23 of these individuals.
00:13:54.17 So, if we go back,
00:13:56.21 these groups that are bracketed
00:13:58.23 in the orange boxes
00:14:00.14 are shared pairs of grandparents,
00:14:03.20 so they'd be cousins.
00:14:06.19 And if we look down near the base,
00:14:08.28 we can see that all of these organisms
00:14:11.07 share a pair of grandparents.
00:14:13.28 Now, because we're in recent history
00:14:16.25 and we have all sorts of ways
00:14:18.13 to record our history,
00:14:19.25 we may even know what these grandparents look like,
00:14:22.19 what our common ancestors of us,
00:14:24.15 and our sibling, and cousins, look like,
00:14:28.04 and I've reconstructed them this way.
00:14:30.01 If we look at at a group of animals
00:14:31.27 that's as broad as fish and mammals
00:14:33.27 and amphibians and reptiles, though,
00:14:36.04 we don't have that record,
00:14:38.18 to know what those common ancestors are
00:14:41.17 or what they looked like.
00:14:43.03 We have to use other types of approaches,
00:14:44.29 called phylogenetic approaches,
00:14:46.16 to basically try
00:14:48.26 to reconstruct the common ancestor
00:14:51.06 and how those species are related.
00:14:53.22 So, if we take this set of vertebrates,
00:14:56.22 this small number of animals,
00:14:58.20 and try to put them on a tree,
00:15:00.21 this is what it would look like,
00:15:02.04 and this is based on lots of peoples' research
00:15:04.08 over many, many years,
00:15:06.06 and I'll run you through it quickly.
00:15:08.20 On the far left,
00:15:10.18 we have the base of the vertebrate tree,
00:15:13.12 and these are lampreys,
00:15:14.28 these are animals that don't even have, really,
00:15:18.20 They have these suction discs
00:15:20.02 that rasp and grip onto other species.
00:15:22.26 As we move up the tree,
00:15:24.13 we get into things like sharks,
00:15:26.00 and skates, and rays,
00:15:27.16 that have jaws,
00:15:30.02 but they have a cartilaginous skeleton.
00:15:31.29 When we move up yet again,
00:15:33.14 we get to the bony organisms
00:15:35.03 that include the fishes,
00:15:36.18 shown with these anemone fish,
00:15:38.14 the third image from the left,
00:15:40.08 and then we get up into the tetrapods,
00:15:42.26 that include amphibians,
00:15:45.17 reptiles, birds, and mammals.
00:15:48.14 Now, how do we construct
00:15:50.10 this kind of tree when
00:15:52.14 we don't have these detailed records
00:15:53.29 that we have of families?
00:15:55.12 Well, we do it by looking at
00:15:57.23 what characteristics these organisms share
00:16:00.14 and what characteristics vary between them.
00:16:02.26 There are lots of different types of characteristics
00:16:04.15 that we can use.
00:16:08.04 So, one of the features that we look for
00:16:10.20 when we're looking at shared characteristics,
00:16:12.22 or similarities and differences among organisms,
00:16:15.20 are anatomical features,
00:16:17.22 things like the shape of bones
00:16:20.06 or where sutures
00:16:21.14 -- where bones connect to one another --
00:16:23.04 or where we see holes through our skull
00:16:25.03 or other parts of our anatomy.
00:16:27.12 Bone and other structures
00:16:29.09 from the body
00:16:30.26 provide really nice characters
00:16:32.11 that we can use to try to figure
00:16:34.03 the relatedness of organisms.
00:16:36.11 In addition to using anatomical features
00:16:39.10 to try to understand the evolutionary history
00:16:41.20 of organisms and their relatedness,
00:16:43.24 DNA is now also
00:16:46.14 providing a really powerful way
00:16:48.24 of generating characters
00:16:50.17 to try to understand
00:16:52.20 how organisms have evolved.
00:16:54.08 In particular, we can compare a single gene
00:16:56.24 among different organisms,
00:16:58.14 different animals and species,
00:17:00.17 and see how it varies and how it's similar,
00:17:03.05 and look for changes in that
00:17:07.17 organization of the gene itself
00:17:09.05 that might give us signals
00:17:11.07 about how close a species is
00:17:12.27 to another species
00:17:14.20 and the relationship among them
00:17:16.28 and to different species.
00:17:18.18 Now, another set of data
00:17:20.12 that's been useful in understanding evolutionary history,
00:17:22.28 of course, is fossils.
00:17:24.22 They're really important.
00:17:26.01 Now, fossils provide information
00:17:28.16 about when and how features arose.
00:17:30.26 They won't, though,
00:17:32.20 provide the common ancestor.
00:17:34.07 It would be very unlikely
00:17:35.21 to actually dig up a fossil
00:17:37.12 that gives you the exact common ancestor of a species
00:17:39.24 but, nevertheless,
00:17:41.20 what they can provide us,
00:17:42.28 how they can ground our understanding
00:17:45.29 of when an organism
00:17:47.24 or particular elements and characteristics
00:17:49.11 of an organism arose,
00:17:50.28 is incredibly important.
00:17:53.25 So, to summarize
00:17:56.23 our introduction to evolution
00:17:58.09 and some of the major points we've talked about...
00:18:00.11 first, evolution is change
00:18:02.13 in the heritable characteristics of organisms
00:18:05.00 from generation to generation,
00:18:06.17 descent with modification
00:18:08.21 as proposed by Darwin.
00:18:11.08 Variation in characteristics
00:18:13.09 allows some subsets of populations
00:18:15.18 to be selected for or against.
00:18:18.20 And selection can cause change
00:18:20.14 in the characteristics
00:18:22.11 that persist in a population,
00:18:23.26 and this can allow for populations to diverge.
00:18:28.27 Reconstructing how the diversity of organisms
00:18:33.09 involves making trees,
00:18:34.23 or these phylogenies that I talked about,
00:18:37.09 that show different organisms
00:18:39.12 are related to one another.
00:18:41.19 And phylogenies, though,
00:18:43.08 depend on identifying characteristics
00:18:45.29 that are shared between organisms
00:18:48.06 and that can suggest their common ancestry.
00:18:50.07 And, again, we can get those characteristics
00:18:52.22 from morphology, from genes,
00:18:54.24 from all sorts of different sources.
00:18:57.19 Thank you.
00:00:02.17 Hello, and welcome to iBioSeminars. My name is Dianne Newman, and I'm a professor in the Divisions of Biology
00:00:07.16 and Geology and Planetary Sciences at the California Institute of Technology,
00:00:11.26 and I am also an investigator at the Howard Hughes Medical Institute.
00:00:15.13 So I am going to be giving you a lecture in three parts today,
00:00:19.16 and this is part one, which will be a very general overview on microbial diversity and evolution.
00:00:25.09 In part two, I'll tell a specific story about a modern example of a microbial metabolism
00:00:30.29 that's quite interesting and very important in affecting the geochemistry of the environment with
00:00:36.04 regard to arsenic geochemistry.
00:00:38.06 And in part three, I'll talk about work we've been doing that is more directed
00:00:43.17 at understanding a metabolism that evolved in the past, namely oxygenic photosynthesis.
00:00:49.02 But let's start with an overview now
00:00:52.14 and consider four important points about
00:00:57.00 microorganisms and their history. And I am going to walk you through each of these four points.
00:01:02.14 So the microbial world is really quite remarkable
00:01:06.23 and my goal in this first overview is to leave you with an impression
00:01:10.22 of its diversity, its antiquity, and how abundant and ubiquitous
00:01:16.18 this world is. So let's begin with antiquity.
00:01:20.27 When we think about the evolution of life, oftentimes we think in terms of macroscopic
00:01:25.23 fossils such as the ones that you see here. And it is pretty clear when you look
00:01:30.01 at these rocks, that something living was present on Earth when they formed.
00:01:33.24 In this panel over here you see a fossil of some type of algae. It is not clear
00:01:39.26 exactly what type, but it is inferred to be an alga.
00:01:42.09 And this shape here is known as a trilobite.
00:01:45.06 And this section of rock that you are looking at is one of the most famous fossils on the plane.
00:01:50.12 It is called the Burgess Shale. It's found in Canada, and it dates to what we call the Cambrian explosion,
00:01:57.14 which occurred roughly half a billion years ago around
00:02:00.29 five hundred and sixty million years ago.
00:02:04.16 So we can certainly claim when we look at rocks of this age that life was present.
00:02:09.17 But if we want to think about the evolutionary history of life,
00:02:12.22 over a much larger time span of billions of years,
00:02:15.26 given that the Earth is 4.6 billion years old,
00:02:20.02 we need to step back in time and look at more ancient rocks.
00:02:22.12 And when we do this, the shapes suddenly change, and it becomes
00:02:26.03 not quite as evident that we are looking actually at fossilized versions of life,
00:02:30.09 and yet we are. So for instance, take this rock as an example.
00:02:34.07 Here you see these dome-like structures, and these are vestiges of a type of microbial community
00:02:41.29 forming in a shallow marine environment
00:02:44.16 that became lithified and left these domal structures,
00:02:48.07 and we call these structures stromatolites.
00:02:50.08 Now this particular rock that you are looking at
00:02:52.21 is about 3 billion years old and is from South Africa.
00:02:56.19 But these rocks can be found all over the world, and they occur
00:02:59.21 throughout Earth's history, going back as far as 3.4 billion years.
00:03:04.20 However, when we go even further back in time,
00:03:08.04 for example, back to 3.8 billion years,
00:03:10.17 you can see ore deposits that one might not intuit immediately had anything to do with
00:03:16.26 microorganisms, and yet they do. They indeed record a history of microbial activities that was quite profound,
00:03:24.24 so profound that it quite literally transformed the planet.
00:03:27.19 And this is one beautiful example. So what you are looking at here is actually a 2.4 billion year old quarry.
00:03:35.27 This is in Western Australia in the Hamersley formation, and this is known as a banded iron formation.
00:03:41.13 And they're extremely important today because they constitute the world's largest source of iron ore.
00:03:47.03 But they also record a remarkable history of the evolution of metabolism.
00:03:51.13 Now how can this be? How do these massive rock quarries tell us anything about microbial life?
00:03:57.14 Well, when you think about what they actually constitute
00:04:01.00 they are made up of iron minerals, as well as other minerals
00:04:04.21 cherts, which is a type of silicon oxide,
00:04:07.07 intermixed with these iron species, but for now let's just focus on the iron.
00:04:12.02 So how did this iron get into this big deposit that you see here?
00:04:15.12 Well, it began a long time ago in ancient seas, in the form of ferrous iron
00:04:20.23 that's called Fe2+.
00:04:22.17 And then some process, which I'll get to in just a minute, oxidized this ferrous iron to ferric iron,
00:04:29.00 and at that point it could react with constituents in the waters such as hydroxyl species,
00:04:34.26 to form iron minerals, such as this one: ferric oxyhydroxide, rust.
00:04:41.01 And over time this mineral transformed and changed
00:04:44.19 into different types of minerals, became compacted,
00:04:47.17 and mingled with others and wound up in these rocks that we today know as banded iron formations.
00:04:54.14 But this initial step here is the critical one in terms of giving us some insight into microbial
00:05:00.23 activities on the ancient Earth. And let's think about two scenarios where microorganisms
00:05:06.05 might have been involved. The first scenario
00:05:09.03 is one where a very primitive type of photosynthetic organism,
00:05:12.27 well, I should say primitive in quotes, because actually this metabolism is remarkably sophisticated.
00:05:17.16 Nonetheless, this is primitive in the sense that it is a type of photosynthesis
00:05:21.18 that does not generate oxygen. Rather it is called anoxygenic, meaning that there is
00:05:29.09 an electron donor, in this case ferrous iron, that is oxidized to ferric iron
00:05:35.29 and that powers the reduction of inorganic carbon, CO2, to biomass.
00:05:42.18 And you can see this is a very dramatic metabolism
00:05:46.25 when it occurs because all you need is light, microorganisms, and ferrous iron,
00:05:52.21 and a few other things to help them get going, but those are really the three most important ones
00:05:57.22 in a bottle here, with, as I said, a few nutrients added so they can do their thing,
00:06:04.19 and when light is shined on this bottle,
00:06:08.24 these organisms very rapidly are able to oxidize the iron.
00:06:12.19 And they produce rust, and you can see the rusty color here in this bottle.
00:06:16.14 And this rust is exactly the type of iron that is the predecessor of the minerals that constitute
00:06:22.04 these banded iron formations. Now in the middle you see these organism growing on a different
00:06:27.03 electron donor, and I'll get to what I mean by an electron donor and an electron acceptor later in this lecture.
00:06:33.17 And in this case they are utilizing hydrogen as an electron donor, and the pink color you see
00:06:39.13 is due to photosynthetic pigments in their membranes
00:06:42.16 that enable them to harvest light and grow in this way.
00:06:45.07 So this scenario, as I said, is one that is catalyzed by
00:06:51.01 organisms that do not generate oxygen. They are anoxygenic phototrophs
00:06:55.14 capable of oxidizing iron in a photosynthetically mediated
00:06:58.29 process under environments where no oxygen is present whatsoever, and yet these ferric minerals can form.
00:07:07.22 Now scenario two, that is entirely different
00:07:11.02 is one where the organisms that ultimately catalyze the precipitation
00:07:15.11 of these minerals were producers of molecular oxygen, and these are the cyanobacteria
00:07:21.24 that you can see here that were critically important in the history of the evolution of metabolism
00:07:27.08 and quite frankly also in changing the overall chemistry of the Earth including its atmosphere
00:07:33.04 because they evolved the ability, the remarkable ability, to use water as an electron donor in photosynthesis,
00:07:40.05 oxidize it to molecular oxygen, and through this process, power the reduction of CO2 to biomass.
00:07:48.19 Now once they produce this oxygen, the oxygen chemically would have been able to react
00:07:55.09 with ferrous iron, oxidizing it to ferric iron,
00:07:58.25 and then this in turn would go down the pathway to precipitate these rusty minerals I showed you.
00:08:03.06 So here we have two options: one scenario where no oxygen is involved,
00:08:10.11 and a second scenario where oxygen is mandatory.
00:08:12.21 And both of these are biological processes.
00:08:15.22 So how do we distinguish between them if we are interested in understanding
00:08:20.19 the types of organisms that were present on Earth in the remote past?
00:08:23.29 Well this is quite a challenge, indeed, and there will be many years of investigations in the future
00:08:31.07 in order to really pin this down.
00:08:32.29 And it is a great field to get into if you are a beginning student
00:08:36.07 and interested in both biochemistry and evolution,
00:08:39.16 but what I'll say just for now is that we know from a variety of indicators
00:08:43.23 that somewhere between 2 billion and 3 billion years old
00:08:47.26 it is very probable, indeed it is almost certain,
00:08:52.05 that the process of oxygenic photosynthesis arose.
00:08:54.19 But when exactly this happened and how the evolutionary events came together
00:09:00.19 such that these anoxygenic phototrophs that can utilized reduced substrates
00:09:06.05 such as hydrogen, or sulfur species, or iron as electron donors in photosynthesis
00:09:12.13 morphed into a more sophisticated type of phototroph,
00:09:18.00 that was capable of using water as an electron donor,
00:09:20.25 the cyanobacteria, which in turn, are what became the plastids,
00:09:26.22 the chloroplasts that we find in modern marine algae
00:09:30.10 and also of course, in plants that are very well known for their ability to do oxygenic photosynthesis.
00:09:36.09 We do not know. We do not know when this happened.
00:09:39.14 And in my third lecture in this series, I will discuss ways that we can begin to approach this problem.
00:09:44.22 But it's a profound question, and what I would like to leave you with now
00:09:47.27 is just the simple message that these very ancient rocks, such as these banded iron formations,
00:09:52.16 here are holding clues to a mystery that we have to unravel.
00:09:56.22 And it is through tools of modern biology that ultimately we hope to get there.
00:10:01.13 All right, now as I said the history of microbial life
00:10:06.19 extends very far back in time, as far as 3.8 billion years as we currently estimate,
00:10:12.22 but this might have been even earlier for all we know.
00:10:15.22 How do we decipher when particular microbial metabolisms evolved and what types they were?
00:10:22.04 Well, this indeed is extremely challenging.
00:10:24.09 And there are three primary ways that we can gain insight
00:10:28.04 into the microbiology of the past through using either
00:10:31.25 morphological, molecular, or genomic, which is of course a form of molecular biosignatures.
00:10:38.21 And these are very different in what they can tell us.
00:10:41.20 So the first two, morphological and molecular,
00:10:45.01 are important because they can be concretely linked to rocks, old rocks, that we can date.
00:10:51.02 And because of this when we see a particular form,
00:10:55.09 this is being held in the hand a sample of stromatolite.
00:10:58.29 This is at a very different scale here. You are looking at a thin section of a rock,
00:11:03.14 and that is true for these images below
00:11:05.28 where the scale is about 1 millimeter, in this image, and it is even smaller down here.
00:11:12.10 The structures that you observe have been interpreted as being vestiges of ancient life for various reasons.
00:11:19.13 But this interpretation is often ambiguous, and it is a challenge to be able to come up with unambiguous
00:11:25.06 biosignatures simply on the basis of their shape.
00:11:28.12 And so geobiologists, those interested in seeking to understand life in ancient times,
00:11:35.02 have turned recently to what we call molecular biosignatures that come in two forms:
00:11:39.27 either organic biosignatures, or some type of inorganic biosignature,
00:11:46.26 often expressed as a ratio of different isotopes in a sample.
00:11:51.04 Now this in turn is challenging as well,
00:11:54.25 but it may be the best way that we can gain more specific insight into
00:11:59.18 different types of metabolisms, by looking at actually the chemistry what is left in the rock
00:12:04.10 and being able to deduce through finer scale analyses whether or not
00:12:09.14 this chemistry was one that was uniquely imparted by a biological process.
00:12:13.13 Lastly we can think of genes as fossils, and the genomic record has been crucial
00:12:20.03 in establishing the diversity of life on the planet, as I'll get to in a little while in this lecture,
00:12:25.21 but it also helps us understand the relatedness of different enzymatic functions
00:12:30.22 and how they evolved from one another.
00:12:33.19 While this does not give us a concrete date when these metabolisms
00:12:37.14 evolved, it does provide us with an ability to look at
00:12:41.10 the relationship between different metabolisms, and come up with an order in which they likely were invented.
00:12:49.06 So that is all I am going to say right now on the antiquity of microbial life,
00:12:53.22 and if you are interested, tune in for lecture three in this series,
00:12:56.22 where I will spend some more detail talking about how we use a particular compound found in lipids
00:13:02.13 in modern cells as a potential indicator for oxygenic photosynthesis
00:13:06.19 and whether or not this is a valid thing to do.
00:13:10.01 The next point now I want to turn to is just how numerous microbes are.
00:13:14.22 So let's ask a very simple question. How many microbes are there on Earth?
00:13:18.11 And to bring this into a human reference point, let's begin with the number of the human population.
00:13:23.19 So I am from Los Angeles, which at the latest census,
00:13:27.27 was around 10 million people. And in the state of California, we are up to approximately 35 million,
00:13:34.11 and in the United States in general, nearly 300 million.
00:13:39.16 These are large numbers, but overall in the world we are up three orders of magnitude.
00:13:44.18 at 6 billion people. And that's a lot of folks.
00:13:47.27 However, this is nothing in comparison to the microbial population
00:13:51.18 as estimated by a wonderful paper that I am citing here at the bottom of the slide
00:13:55.22 called, "Prokaryotes, the Unseen Majority" that was published in PNAS in 1998.
00:14:01.29 These are very rough numbers, but give or take an order of magnitude
00:14:05.01 here or there, I think you are going to be impressed when you see the number that I am about to show you.
00:14:09.06 So the estimates for the microbial population are just enormous, 5 times 10 to the 30th cells.
00:14:15.08 And this indeed is such a large number that it is very difficult to wrap our minds around it.
00:14:20.21 So to try to make this a bit easier to do,
00:14:22.16 I did a very simple calculation, where I assumed that the length of a given micro-organism
00:14:27.01 was one micron and asked, "how many times would we need to go back and forth between the Earth
00:14:33.11 and the Sun if we lined up all of these organisms end to end in order to account for this number?"
00:14:38.29 And the answer, shockingly, is we would need to go back and forth 200 trillion times.
00:14:45.12 So hopefully that impresses you with just how many of these creatures there are on the planet.
00:14:49.28 Now where are they, if there are so many?
00:14:52.08 How come we don't think about this all the time?
00:14:54.27 Why aren't we overwhelmed?
00:14:56.04 Well, one reason is that oftentimes we are shockingly ignorant
00:14:59.19 about the fact that they are all around us, that we ourselves are walking micro-organisms.
00:15:04.04 So one of the first scientists to appreciate this profound fact
00:15:08.10 was the father of microscopy, Antony van Leeuwenhoek.
00:15:11.11 And this is a lovely image that he drew from his observations down his first microscope
00:15:18.01 in 1684, and you can see he drew some nice rods and cocci, and even pictures of probably motility
00:15:26.22 what is meant by these dotted lines from C to D.
00:15:30.29 And he reflected, as he was looking through the microscope about his own teeth, and this is I think a very funny quote.
00:15:37.28 He said, "Though my teeth are kept usually very clean,
00:15:40.24 nevertheless when I view them in a magnifying glass,
00:15:43.25 I find growing between them white matter as thick as a wetted flower.
00:15:47.09 The number of these animals in the scurf of a man's teeth,
00:15:50.05 are so many that I believe they exceed the number of men in a kingdom."
00:15:54.17 Well, this indeed is actually an underestimate.
00:15:58.28 Not only do they exceed the number of men and women in a kingdom,
00:16:02.13 they go far beyond that. So if we actually look at our own bodies...
00:16:06.13 just take a look at your wrist, at one square inch on the surface of your wrist.
00:16:10.23 Right there, we are estimated to have five to fifty thousand bacterial cells.
00:16:16.22 And it just increases in density as we move to other parts of the body, such as the groin and the underarms,
00:16:22.28 in our teeth, and really where it's mainly at in our bodies is in our colon.
00:16:29.06 And the overall total per person is seventy trillion.
00:16:33.25 That is quite a lot.
00:16:35.24 And one thing that I think is really important for you
00:16:38.18 to know about the microbial community within your own body,
00:16:42.16 is that there are ten times the number of microbial cells
00:16:47.04 in our system than there are human cells.
00:16:51.21 And not only that, when we look at the genetic potential of the DNA
00:16:56.09 within these organisms, the genetic potential of only those within our guts
00:17:02.15 is over one hundred times that of the human genome.
00:17:06.21 So you might begin to ask whether or not humans are not merely walking vats of microorganisms,
00:17:11.29 carriers serving their existence.
00:17:14.08 It is something to think about, and there's a great deal of research now emerging
00:17:18.20 that is beginning to illuminate just how crucial these organisms are
00:17:21.25 for human health, not only with regard to being able to help us digest our food,
00:17:27.07 but also interfacing and controlling our immune system,
00:17:30.09 in ways that are fascinating and profound.
00:17:32.29 Now despite the fact that this number, ten to the twelfth, seems really large, and indeed it is,
00:17:38.25 it's peanuts when we compare it to other domains where we find microorganisms.
00:17:44.09 So let's start with the least abundant, up in the air,
00:17:46.24 It is quite amazing to me that they've been detected as high as thirty four to forty six miles up
00:17:53.06 into the sky. But these concentrations are really small relative to other compartments.
00:18:00.00 As I told you, within the human body we have quite a few.
00:18:04.12 And when you add up all of the humans and domestic animals, and then termites,
00:18:08.08 which I'll get back to in just a bit,
00:18:09.20 the order of magnitude jumps up to about ten to the 23rd, to 24th
00:18:14.06 This is superceded by the quantities that you can find in soils,
00:18:20.06 in forests and grasslands, deserts, tundras, swamp environments.
00:18:24.10 These places are very fertile homes for microorganisms and there their activities can transform
00:18:29.23 the chemistry of their environment quite profoundly.
00:18:31.29 And this is of course also true in aquatic domains, where at similar orders of magnitude
00:18:38.08 we find microorganisms in both marine and freshwater environments.
00:18:42.01 But all of these numbers pale in comparison to the numbers that we find in the subsurface,
00:18:46.14 both in terrestrial and oceanic environments, where microorganisms
00:18:51.09 have been detected as deep as two miles.
00:18:54.22 Now, this really is a very interesting frontier area in microbiology
00:18:58.05 It is hard to go down into these depths, and yet nowadays, researchers are equipped with the tools
00:19:05.02 they need in order to access these remote communities.
00:19:07.26 And what remains to be learned is what exactly these organisms are doing in situ.
00:19:12.11 Are they active? And if so, what are their activities?
00:19:15.26 Are these activities affecting in a significant way
00:19:19.05 the physical and chemical properties of these environments?
00:19:22.07 We don't know, and we look forward in the coming decades to finding
00:19:25.04 the answers to these and other interesting questions.
00:19:27.19 So now let me just give you an example, a tour through various parts of the world
00:19:34.05 and other inhabitants of that world where we find these organisms.
00:19:39.17 Just to bring home to you how ubiquitous microbes are on the planet.
00:19:44.07 So to start with what might be a more familiar image, here what you are looking at is pond scum.
00:19:51.09 You are looking at a wonderful assemblage of phototrophs
00:19:54.27 and other microorganisms in this pond. And my favorites of course are these purple phototrophs.
00:20:00.03 These are the ones that I told you about earlier that are what we call the anoxygenic phototrophs
00:20:04.27 that are not utilizing water as a substrate in photosynthesis,
00:20:08.29 but are utilizing other more reduced compounds such as different types of sulfur species, hydrogen, or iron.
00:20:17.15 Now these organisms that we see in modern day ponds, as I told you at the beginning when I was illustrating
00:20:23.20 the antiquity of microbial life with the example of the banded iron formations,
00:20:27.25 are absolutely historically important for their metabolism,
00:20:33.19 and the diversity of their metabolism, and how it's changed the geochemistry of the Earth.
00:20:38.00 Not only has the evolution of photosynthesis contributed to evolving our atmosphere
00:20:43.20 to one that contains oxygen over the course of time,
00:20:46.14 but as I also showed you with the banded iron formations,
00:20:48.29 these types of organisms have likely shaped ore formation as well.
00:20:54.21 And many other important processes have been able to come about
00:21:00.21 thanks to these organisms doing what they do, and it should be noted
00:21:05.15 that this type of metabolic activity, photosynthesis, is one that today we are highly interested in
00:21:12.06 because of our need for coming up with alternative energy sources, and
00:21:16.25 certainly if chemists were able to mimic what these wonderful microbes in this pond do, we would
00:21:22.25 be able to not worry so much about our dependence on foreign oil
00:21:27.02 and our fossil fuel supplies being burnt, but that's a story for another day.
00:21:32.08 The point is, their metabolic diversity is old. We see it all around us, and the biochemistry is really quite fascinating.
00:21:39.18 Continuing on with the chemistry and the metabolism of these organisms
00:21:44.28 not only do they do important things when they are growing,
00:21:48.00 but they also do important things when they start hitting what we call stationary phase.
00:21:51.24 And this is a point in their development where they're not necessarily actively growing,
00:21:56.12 but they are at a higher density and they are just hanging out metabolically.
00:22:00.26 And when this occurs in their lifecycle,
00:22:04.09 sometimes metabolites and pigments begin to be excreted.
00:22:08.08 And these pigments, which are called secondary metabolites,
00:22:12.14 although that name itself may be a bit misleading, because they are only secondary in a temporal sense,
00:22:18.14 in that they are made after a phase of active growth,
00:22:21.21 but by no means are they secondary in terms of the physiology of the organisms that produce them.
00:22:27.00 None the less, these metabolites oftentimes are used today by pharmaceutical companies
00:22:32.14 as natural products that confer antibiotic activity.
00:22:35.13 And a terrific example of this are organisms in the Streptomycetes family that you see here
00:22:40.18 in this Petri dish that are producing a whole host of wonderful antibiotic compounds.
00:22:45.02 Now containing in the environment of the soil of course are roots of plants.
00:22:51.00 And in this part of soil known as the rhizosphere,
00:22:55.04 we can find microorganisms as well that are colonizing in a very beneficial way the plant roots.
00:23:00.28 And here is a tomato root seedling. This is an image taken by Guido Bloemberg.
00:23:06.25 And he showed in experiments in the laboratory that when he took tomato root seedlings
00:23:12.27 and mixed them with an organism called Pseudomonas,
00:23:16.01 that this bacterium was able to colonize the plant and form what we call biofilms on the surface of the root.
00:23:22.18 And this is just one example of organisms that interact with plants.
00:23:26.20 There are many that fall into this category with different names.
00:23:30.12 And the bottom line is that they have a very beneficial relationship with these plants,
00:23:34.11 where sometimes they produce natural products that fend the plant off from fungal predators
00:23:40.05 and so they serve as biocontrol agents.
00:23:42.24 Other times these organisms are capable of fixing molecular nitrogen
00:23:48.14 into a usable form and essentially acting as a natural fertilizer.
00:23:53.14 Now crawling around in not only soil environments,
00:23:58.00 but of course we are very familiar with these from our homes, are termites.
00:24:01.00 And the termites are a terrific source of microbial diversity
00:24:05.17 and one that is becoming an increasingly important micro-environment
00:24:10.07 in which to look because of our desire to understand microbial processes
00:24:16.00 that might be harnessed for lignocellulose degradation.
00:24:19.04 Again, out of a need to develop alternative sources of energy.
00:24:22.22 Now a colleague of mine, Professor Jared Leadbetter at Caltech
00:24:26.14 studies these termites, and he likes to call them "an ecosystem in a microliter".
00:24:31.05 And I think this is really a fantastic description of them because it is within their hindgut that you find a zoo
00:24:38.21 of microorganisms and protozoa that are swimming around
00:24:43.12 doing all sorts of important activities that make it possible for the termites
00:24:47.12 to digest their wood. And in the process they emit methane,
00:24:52.02 and not an insignificant fraction of this methane ultimately makes its way
00:24:55.16 up into the atmosphere and contributes to the overall chemistry on the planet.
00:25:02.17 So speaking of methanogens, here you see
00:25:05.08 a dramatic illustration of them at work.
00:25:07.18 This image that I am standing in front of is taken from Cedar Swamp in Woods Hole, Massachusetts.
00:25:12.15 And it is an image from a group of students from the microbial diversity class,
00:25:18.02 which is a fantastic course for about twenty students, half from the United States and half from overseas,
00:25:24.07 who come together every summer to understand how
00:25:27.00 microorganisms are able to perform these various metabolic activities
00:25:32.08 that I have been describing in these lectures.
00:25:34.26 And what you can see here is that the students have gone waist deep into this swamp
00:25:39.19 and they have stomped around, and as they have done this they have collected the bubbles that come up
00:25:46.03 as they stomp the sediment, and collected them in these inverted funnels.
00:25:51.11 And then some brave individual holds that funnel
00:25:54.14 and removes their hand just at the moment when a friend comes by with a flame,
00:25:59.09 and ignites it, and here you see a lovely illustration of methane at work.
00:26:04.25 So methanogenesis led to the creation of the methane gas that was ignited here.
00:26:10.06 Now in the past the activity of these organisms that generate this methane
00:26:15.23 that are called methanogens, might have been important in shaping the chemistry of the Earth's environment.
00:26:19.27 And the reason we suspect this may be the case is because early in Earth's history the environment
00:26:25.00 contained appreciably more methane than it does today.
00:26:28.18 Now a different example of a habitat where microorganisms are very important
00:26:33.21 is in Chile and in other places on Earth,
00:26:37.19 but this example here is taken from the Andina Copper mine in the Andes in Chile
00:26:44.23 where microorganisms are exploited for their abilities to help
00:26:48.27 with bioleaching. And so what happens is that in these mines there are piles
00:26:54.06 that are built up, and they are fertilized essentially with indigenous microbial populations
00:27:01.08 that are able to live in shockingly low pH levels,
00:27:05.17 down to pH as low as one, and sometimes even lower.
00:27:08.23 And these organisms are essentially eating the minerals in this mine pile
00:27:14.14 and the process of metabolizing it, changing the mineralogy, in such a way
00:27:19.06 that copper is solubilized and leached. So here is another example of an environment
00:27:25.27 that is quite extraordinary and yet microorganisms have been able to adapt and even to thrive in this extreme condition.
00:27:33.04 So on our tour of extreme pHs, we just saw an example of low pH, so let's go to a high pH environment.
00:27:39.24 This one I am showing you is Mono Lake that is in Northern California.
00:27:44.09 And Mono Lake is quite an extraordinary place. It looks almost like it is from another planet.
00:27:49.25 You see these beautiful tufa towers that are calcium carbonate minerals forming,
00:27:55.05 and it is because the pH is so high and the alkalinity is so high that they naturally precipitate from these waters.
00:28:01.19 In addition to having these carbonate minerals, contained within this lake environment
00:28:07.09 is a ton of arsenic, and I will get to this in part two of my lecture today.
00:28:11.07 And what I want to point out right now is that in this very high pH environment, and also one
00:28:17.14 that's replete with arsenic, nevertheless we find organisms called alkaliphiles
00:28:21.23 that thrive here, that are able to make a living utilizing arsenic as a terminal electron receptor in respiration.
00:28:30.05 This is the subject of my second lecture. And in so doing account for 14% of the carbon turnover in this system.
00:28:38.23 Now let's go on to another example of an extreme environment.
00:28:42.14 Here now we are looking at an extreme of salt.
00:28:45.26 And there is no better example of this than the Dead Sea in Israel, but
00:28:50.06 you can find organisms such as those that inhabit the Dead Sea also in the Great Salt Lake,
00:28:56.04 and other places on Earth such as salt flats, where you have very high salt content.
00:29:04.19 And the organisms living here are capable of growing despite this high salt
00:29:08.21 and have adapted particular molecular strategies to cope with it.
00:29:12.15 One very elegant example of this is their ability to use special photopigments called rhodopsin
00:29:18.23 and these are colored purple.
00:29:21.24 And these rhodopsins, they have in their membranes, and enable them to generate energy
00:29:27.11 under conditions where they need to use slightly different
00:29:30.02 strategies than organisms that are growing under
00:29:33.28 conditions that we would consider more normal.
00:29:36.27 Now, so approaching the end of our tour through microbial diversity and ubiquity, I want to end with a few other extremes
00:29:44.00 now that are based on temperature and pressure.
00:29:46.04 If we think about the extremes of cold there is no better place to go than Antarctica.
00:29:50.27 And you might be surprised to realize that even in this environment you have microorganisms thriving in the crust.
00:29:57.02 And these organisms are psychrophiles, and they're ability to grow is dependent upon dust
00:30:02.26 from winds carrying nutrients picked up from the continents surrounding Antarctica, South America, Australia, Africa,
00:30:14.24 that reach Antarctica, deposit their dust and fertilize these upper crusts of the ice
00:30:20.14 where we have intrepid pioneer organisms that are able to utilize these nutrients
00:30:26.03 and grow, even in these very cold regimes.
00:30:28.02 So another extreme is that of temperature and pressure, and there is no better environment in which to observe this
00:30:34.24 than at the bottom of the ocean, in environments where we have hydrothermal vents
00:30:39.21 that are releasing nutrients into the deep. And here is an example of one of these vents. It is called a black smoker
00:30:46.17 because the nutrients that it releases, including manganese and iron,
00:30:51.14 often precipitate in the conditions of the oceans at these sites
00:30:57.16 such that they look black.
00:30:59.22 Now around these vents there is abundant life,
00:31:04.07 really extraordinary life, not just microbial life.
00:31:06.08 but giant tube worms, and fish, and other macroscopic organisms.
00:31:10.10 So the ability of all of this abundant life to be in this environment
00:31:15.10 crucially depends upon the activities of microorganisms that are chemosynthetic.
00:31:20.01 that are able to grow by the oxidation of sulfur and other compounds that you have
00:31:25.03 present in this environment, and couple that oxidation of these reduced substrates to
00:31:31.05 the fixation of CO2 into biomass.
00:31:34.15 And this is at the base of the food chain that then sustains the growth of other marine organisms.
00:31:40.12 such as these tube worms. And here you see an example of that
00:31:43.10 in these beautiful tubeworms. If you cut them open and you look at one of their organs,
00:31:50.29 called the trophosome within these organs are bacterial symbionts
00:31:55.27 that are doing the process that I just mentioned.
00:31:58.08 So my final example that I will end with
00:32:01.12 is one that might be the most familiar to you
00:32:04.02 if you have ever done any PCR in molecular biology.
00:32:06.25 So most of you have heard of the enzyme Taq polymerase,
00:32:10.06 and this polymerase is what allows us to do an amplification reaction when we are doing PCR.
00:32:18.21 Now this enzyme, Taq, derives from a bacterium called Thermus aquaticus,
00:32:24.28 that is where the Taq comes from. The "T" is from the Thermus and the "aq" from aquaticus.
00:32:31.05 And this is a thermophile that was isolated in Yellowstone
00:32:35.14 at a hot spring, many decades ago.
00:32:38.03 And it was presciently realized by Kary Mullis
00:32:41.18 and others that the enzymes contained within it could be useful for various biotechnological applications
00:32:47.26 because they wouldn't denature at the temperatures that would kill most other types of cells.
00:32:54.02 So these thermophiles are a very fascinating group of organisms
00:32:57.28 whose molecular adaptations include not only DNA polymerases,
00:33:03.26 but also a wide variety of other enzymes that might be of industrial use.
00:33:10.01 So let's now end with diversity, which is really my favorite part
00:33:14.14 of the microbial world. And I want to cover a few different areas of this.
00:33:18.18 The first is phylogenetic diversity.
00:33:20.03 Now one of the most important lessons to be learned in evolutionary theory
00:33:25.03 was learned several decades ago from work by Carl Woese and his colleagues,
00:33:30.03 including Norman Pace, who applied Carl Woese's fundamental
00:33:34.07 insights into the diversity of life to the natural world.
00:33:38.02 And these individuals together with others were able to demonstrate very clearly
00:33:44.05 that when we think about the diversity of life out there on the planet,
00:33:48.16 we are really talking about a microbial world, whether we call these
00:33:52.22 microorganisms Bacteria or Archaea or even Eucaryotes.
00:33:58.23 What I want you to appreciate is that when you look at the tree of life,
00:34:03.11 that's what this is. It is a tree that is drawn based upon comparing the sequences of a very particular molecule
00:34:11.06 that every living organism has, that is ribosomal RNA, that is necessary for the process of translating
00:34:19.07 messenger RNA into protein.
00:34:21.07 Because this is a very universal and highly conserved molecule
00:34:24.28 Carl Woese and colleagues were able to deduce that it was a beautiful molecular chronometer
00:34:31.01 that we can employ to look at the evolutionary relatedness between different organisms.
00:34:36.16 And when he and his colleagues did this , he recognized that
00:34:39.19 there were three primary domains of life, the Bacteria, the Archaea, and the Eucarya.
00:34:43.16 And moreover, what I want to stress now is that our entire universe of Homo sapiens
00:34:52.12 and humans and plants and animals, the macroscopic eucaryotic world,
00:34:57.12 is only occupying in terms of this space on the tree,
00:35:01.27 which is known as a phylogenetic tree, meaning a tree of evolutionary distances
00:35:06.21 between different types of life forms, a very tiny miniscule branch.
00:35:12.00 And everything else that I am showing here is microbial.
00:35:14.13 So hopefully that impresses you, but before we leave this tree let me point out two more
00:35:19.20 facts that are very important.
00:35:20.29 All of the metabolism on the planet was invented by microorganisms
00:35:26.05 including the metabolism that we perform in our bodies today in our mitochondria.
00:35:31.11 So the mitochondrion is nothing more than an ancient bacterial cell
00:35:36.28 that invented the ability to do oxidative phosphorylation, which I'll tell you about in a little bit,
00:35:42.24 that was engulfed or brought into symbiosis with some other type of cell,
00:35:47.23 and over the course of time involved into the organelle that we call the mitochondrion.
00:35:52.28 But it was a microorganism first, and that is where the beautiful metabolism that it goes through was generated.
00:36:02.14 The same story is true for the chloroplast. This is nothing more
00:36:06.03 than cyanobacteria that over time turned into plastids and became incorporated into other cells.
00:36:11.25 Now the next important point I want to make is that microbial diversity also manifests itself morphologically.
00:36:18.19 And this is something that only recently we are coming to appreciate in its full glory.
00:36:24.02 Back in the days of Leeuwenhoek, when he had a simple microscope, all he could really see were different shapes of microbes,
00:36:30.24 and to be quite honest, that is not terribly spectacular and includes rods and spirals and some cocci.
00:36:37.11 Once in a while you see higher structures forming of communities however,
00:36:41.25 and Leeuwenhouk didn't necessarily know about these,
00:36:44.05 but here is an example of one here. This is a beautiful example
00:36:48.13 of fruiting bodies beginning to form by the soil organism Myxobacteria
00:36:53.10 that does all sorts of interesting things when it comes together in a group
00:36:57.01 that it wouldn't do as any individual cell.
00:37:00.25 This is social behavior. So this is an example of bacteria acting in a multicellular fashion, if you will.
00:37:06.11 Microorganisms, however, can get remarkably large. They are not just on the scale of microns.
00:37:11.21 And here is a good example of this.
00:37:13.20 This is, to my knowledge, one of the largest microbial
00:37:16.28 cells known to date. It is called Thiomargarita namibiensis,
00:37:19.29 which means the sulfur pearl of Namibia.
00:37:22.17 And it is on the same scale as the eye of a fruit fly.
00:37:25.13 And when you look at it in more detail, the reason it is so big is that it contains this huge vacuole
00:37:31.21 filled inside with nitrate, which is one of the substrates it uses to power its metabolism.
00:37:38.02 And it couples the reduction of nitrate to a more reduced form of nitrogen
00:37:43.07 to the oxidation of sulfide, and in this way it powers energy for growth.
00:37:48.00 But let's leave the metabolism aside and stay focused now just on the form.
00:37:52.03 Here is an example of one of my favorite organisms, Rhodopseudonomas palustris,
00:37:57.02 and the reason I am showing you this is simply to illustrate
00:37:59.24 that it has quite an amazing membrane structure within it.
00:38:05.27 One that is reminiscent even of the Golgi in higher organisms.
00:38:09.09 And indeed it might have been the progenitor of that at the cell biological level.
00:38:14.17 And how these various structures form, these are what we call
00:38:18.06 the inner cytoplasmic membranes where the photosynthetic machinery is housed in this case,
00:38:22.19 in terms of the detail of what creates their shape is an open and exciting question
00:38:27.08 that future microbial cell biologists will no doubt solve.
00:38:30.17 But the final example, which is probably my all time favorite, is of an organism called a magnetotactic bacterium.
00:38:38.16 And here you see if you just look at it in a light microscope,
00:38:41.15 although this is actually an image of fluorescence where we have put some GFP into the bug,
00:38:46.04 it looks like just a common spiral.
00:38:48.09 If you take a fancier microscope, a transmission electron micrograph, and cut it
00:38:53.01 open and do a thin section, you can see that it has this beautiful chain of magnetic particles inside it.
00:39:00.00 And now what I am going to show you is, I think, the best advertisement for the beauty of bacterial cell biology
00:39:05.28 that I know, and it is a cryo-electron tomogram of one cell.
00:39:13.10 And this was work done by Arash Komeili who is now a professor at UC Berkeley
00:39:18.26 and his collaborator Zhuo Li in Grant Jensen's lab at Caltech. And together
00:39:23.17 we made this movie showing the internal structure of these organisms.
00:39:27.26 So what you are going to see now is coming up through the bacteria different sections,
00:39:32.11 and here you see the magnetosomes coming into view. Those are the membranes that contain the magnetite.
00:39:39.10 If you missed them, now look, OK.
00:39:41.02 Here they are in red, those magnetosome membranes, and then there is this yellow filament surrounding them.
00:39:46.27 And what we have come to appreciate is that this filament is a protein that is very similar to actin.
00:39:52.11 And it is necessary for these magnetosomes, for these organelle-like,
00:39:58.01 although they never separate from the membrane, so they are not true organelles.
00:40:01.14 Here you see they're attached by a neck that's only 5 nanometers in diameter, which is quite amazing, to this inner membrane.
00:40:10.24 They invaginate and form these vesicles within which a beautiful single domain crystal of magnetite can form.
00:40:19.19 And this order, the fact that they are linear in a chain,
00:40:22.21 is enabled by a cytoskeletal filament, an actin-like protein.
00:40:28.17 OK. So the next to the last point that I want to make on diversity
00:40:33.09 is behavioral diversity, and there is another lecture in this iBioSeminar series
00:40:37.06 by Professor Bonnie Bassler from Princeton that can give you more information about this if you are interested.
00:40:41.28 But what I wanted to point out here while we are going through a tour through diversity
00:40:46.13 is simply that microorganisms can act in ways that are quite extraordinary
00:40:51.15 when they are acting as a group.
00:40:53.11 And you can see that illustrated by the activities of the bacterium Vibrio fischeri within the light organ of a squid.
00:41:01.10 And here is an image that is from the beautiful pioneering work of Margaret Mefal-Ngai
00:41:06.18 and Ned Ruby at the University of Wisconsin, Madison where they have been studying for decades the interactions
00:41:12.01 between the microorganisms in the light organ of the squid and the squid,
00:41:16.28 and the ability of these organisms to colonize this environment,
00:41:20.06 and when the lights go out at night, emit a beautiful luminescence. Here you can see pictures of these organisms
00:41:28.12 that have just been streaked out on a plate in the dark.
00:41:30.11 They are glowing. Well, they glow as well here at night in the belly of the squid.
00:41:35.27 And it shields these squids from predators below
00:41:39.00 because the light of the moonlight coming down from the top
00:41:41.28 is roughly of the same luminescence as the light that they are emitting.
00:41:45.26 So it allows them to have a stealth function and glide around in the oceans
00:41:50.19 and be unseen to predators deeper below them.
00:41:56.07 Now, this isn't just a phenomenon that affects the squid. This is a phenomenon that can get quite enormous in its scope.
00:42:03.19 And the best example to illustrate this is this satellite image here taken off of the Somalian coast,
00:42:09.11 where you see an image that quite literally is of milky seas as described by the ancient mariners,
00:42:17.21 but what today we understand as glowing bacteria.
00:42:21.26 In this case an organism, likely called Vibrio harveyi, associating with micro-algae in this environment
00:42:28.22 that for whatever reasons that are not fully understood at this particular point in time
00:42:33.22 when this satellite image was taken, had a bloom and began luminescing like crazy, and filled up a volume the size of Connecticut.
00:42:41.27 All right, so, to end I want to just mention a few rules of microbial diversity
00:42:47.23 because almost everything that I have talked about so far
00:42:51.11 in this lecture ultimately comes back to the ability of organisms to generate energy in ways that are quite amazing.
00:42:59.06 And I would stipulate that microbes are by far the best chemists on the planet.
00:43:02.25 And so if you are a chemist, pay attention, because a lot of lessons can be learned from these guys.
00:43:07.06 All right. Now when we are talking about the phase of active growth,
00:43:11.13 the bottom-line that microbes are facing is they simply want to divide.
00:43:15.12 And to do this they need two things. They need energy, and they need carbon.
00:43:20.08 And beyond that, they are virtually unconstrained, although there are a few constraints,
00:43:26.25 and we will come back to that in a moment.
00:43:29.03 They need substrates, and these substrates can be organic or inorganic compounds.
00:43:36.11 This is now for the part where they are going to be generating energy.
00:43:40.22 Those substrates are converted to products through catabolic reactions, or energy generation, if you will.
00:43:49.09 And often times we think of energy generation in the form of ATP,
00:43:52.20 the most important energy carrying molecule within the cell.
00:43:57.06 Now this part of metabolism, catabolism, is coupled to anabolism,
00:44:03.12 which is the part of metabolism that is concerned with energy consumption, or biosynthesis.
00:44:08.12 And now down here what we are talking about is the conversion of
00:44:12.01 carbon, often in the monomeric form, to biomolecules that are far more complex, so protein, DNA, lipid, for example.
00:44:22.27 Now if we are thinking just about the substrates, as I said they can come from a variety of sources.
00:44:30.06 Always they're chemical, although light can help enable cells
00:44:34.21 to actually utilize those chemicals in ways that they otherwise wouldn't be able to do.
00:44:39.10 But when we are talking about the growth of organisms just purely on chemicals, without needing
00:44:46.15 a boost from light, the name we give to this metabolism is chemotrophy.
00:44:50.18 And that in turn is classified into two different types, inorganic and organic.
00:44:57.06 And when we are talking about inorganic sources of energy like hydrogen, and sulfide, and iron minerals,
00:45:03.18 this is called chemolithotrophy. And when we are talking about growing on organic substrates like glucose, or glycerol, or acetate,
00:45:11.23 this is called chemoorganotrophy.
00:45:14.04 And of course, as I said, while chemistry is always at the basis for any type of metabolism,
00:45:20.20 there is a photochemical boost that is often necessary,
00:45:25.09 when activating a compound that otherwise might not be biologically utilizable
00:45:30.16 for energy, and that is when we call that process a phototrophic one.
00:45:36.10 So the final part of this that I want to just mention is that the carbon source,
00:45:42.02 which is distinct or can be distinct from the energy source...
00:45:44.28 sometimes they are the same thing, but they don't have to be the same thing...
00:45:47.26 is either coming from inorganic carbon, CO2, or organic carbon.
00:45:52.19 And when it is coming from inorganic carbon that is called autotrophy,
00:45:55.21 and when it is coming from organic carbon, that is called heterotrophy.
00:45:58.22 So we are heterotrophs, we need to eat some type of organic carbon whether we are vegetarians
00:46:04.28 or meat eaters, but microorganisms are far more sophisticated.
00:46:09.12 They can eat minerals. They can just take CO2 from the air, and they'll be on their way.
00:46:17.14 So finally the last part I want to mention about metabolic diversity writ quite large
00:46:22.29 is that you can generate ATP through one of two different ways.
00:46:26.13 The first way is through what is called substrate level phosphorylation.
00:46:29.15 And this is also termed fermentation, and essentially is the process
00:46:33.22 where different types of reactions between chemicals within a cell
00:46:39.26 enable transfer of an inorganic phosphate ultimately to ADP to produce ATP.
00:46:49.21 And this process is enabled by chemical rearrangements within the cell
00:46:55.05 and reactions one on one between compounds.
00:46:57.18 The next major way that ATP can be formed in a cell is through the remarkable process of oxidative phosphorylation.
00:47:03.10 Basically this is about electron transport chains in membranes
00:47:07.23 that are coupled to generating a battery around a membrane
00:47:11.08 by extruding protons to one side and polarizing it so that there is an electrochemical potential gradient
00:47:18.00 across this membrane that can be harnessed to do the work of making ATP.
00:47:22.06 Now something that I am not showing you on this diagram,
00:47:25.03 but I want to introduce as terms are an electron donor and an electron acceptor.
00:47:31.00 So in metabolism there is always a substrate that is used as the primary electron donor
00:47:36.14 that can be metabolized through various pathways
00:47:39.08 and reduced to a compound that can donate electrons
00:47:43.17 to the electron transport chain in the membrane.
00:47:45.20 And then there is always something that serves as the acceptor of those electrons at the end of the chain,
00:47:52.10 and that is called the terminal electron acceptor.
00:47:54.28 And it is the path of electron transfer and proton translocation
00:47:58.22 between this electron donor and this terminal electron acceptor that is really harnessed by the membrane to do work.
00:48:05.05 And so that is what you see here pictured very generically without a whole lot of detail
00:48:10.08 in the sense that through this electron transport process,
00:48:13.20 which imagine if you will, is coupled as I said to proton translocation,
00:48:18.00 and that is achieved by different things within this membrane.
00:48:22.15 They can be proteins, or small molecules that are able to simultaneously
00:48:26.25 pass electrons through the membrane to something else
00:48:29.24 in the electron transport chain and push protons, or translocate protons
00:48:34.15 across the membrane so that there is this gradient that arises where there is more positive charge on the outside
00:48:42.07 than on the inside. Now once this happens this gradient can be used to drive ATP synthesis.
00:48:49.21 And this happens through a really amazing molecular machine called the ATP synthase,
00:48:54.09 which allows the traversal through the membrane of a proton,
00:48:58.27 that concomitantly gives the energy to phosphorylate ADP, adding that inorganic phosphate on, and making ATP.
00:49:09.08 And as this happens, the electrochemical potential gradient lessens.
00:49:15.00 And so that is what I am showing here: the energized membrane
00:49:16.25 due to proton transport coupled to electron transfer through the membrane,
00:49:22.10 and then this being expended and used in order to drive ATP synthesis.
00:49:26.12 Now while you can imagine a whole variety of things that can be electron donors
00:49:32.02 and electron acceptors from microbial metabolism,
00:49:34.27 metabolic diversity does have to conform to some rules.
00:49:37.06 And there are three that I want to point out that I think are particularly important.
00:49:41.02 The first is that the amount of energy has to be at a very minimal level,
00:49:47.14 at least in order to sustain the cell, both with regard to active growth, where you need a high level of energy,
00:49:53.27 at some threshold amount in order to double, but also at the level where you are generating enough energy simply to maintain
00:50:01.18 basic cellular processes even if they are not coupled directly to growth.
00:50:05.11 Now what is this number and how do we constrain it?
00:50:09.13 Thermodynamically, this can be expressed in this very straight forward equation here,
00:50:14.20 which is saying that the standard free energy that can be gained
00:50:18.04 from a process where there is electron transfer between the electron donor and the electron acceptor
00:50:23.13 is a function of the number of electrons transferred,
00:50:26.22 multiplied by the Faraday constant, and this in turn multiplied by
00:50:32.21 the difference in redox potential between the electron donor and the electron acceptor.
00:50:37.21 So for example, a common intracellular reductant, is NADH,
00:50:43.09 and in its oxidized state this is NAD+.
00:50:45.10 The redox potential of this redox pair is very low.
00:50:51.07 It is very negative on the electron potential scale that is typically expressed in millivolts.
00:50:57.07 On the other side of this scale are the electron acceptors with very high redox potentials, like oxygen.
00:51:04.20 And so when you couple through the membrane
00:51:09.27 a process of electron transfer from NADH to oxygen, thermodynamically you have the potential to generate
00:51:16.16 a lot of energy, and this is captured through a beautiful sequence of proton carriers and electron
00:51:24.14 transfer biomolecules contained within these membranes.
00:51:28.28 But these electron transport chains need not be between NADH and oxygen,
00:51:33.26 you can have a whole assemblage of things that can interrelate and so the minimum amount of energy
00:51:39.13 that needs to be supplied has been calculated. And this is a very crude estimation,
00:51:45.03 but it is an interesting study, and I refer you to below where you can see the reference.
00:51:49.05 Where for organisms operating in very low energy regime,
00:51:55.03 it was inferred that the minimum free energy required to sustain them and their growth
00:52:00.29 was about -4 kilojoules per mole, and that is about as low as you can go at least as experimentally measured.
00:52:06.21 Finally, regardless of the thermodynamic potential there are two other very important factors to keep in mind.
00:52:14.02 The second point is that the substrates themselves must be bioavailable. And so this is more of a kinetic problem
00:52:21.07 where we need to consider accessibility and transport of substrates
00:52:25.17 across the membrane to the site in the cell where they are used.
00:52:28.21 Or the ability of the cell to figure out a way to access them even if they can't transport them inside.
00:52:34.05 And the final point is that these substrates or the products after the metabolism has done its thing
00:52:42.00 must not themselves be toxic. So in the next couple of sections of this lecture,
00:52:47.26 I am going to give you examples of different microbial metabolisms to illustrate
00:52:52.12 these general points I have been making,
00:52:55.02 but I hope what you will remember from this seminar is the four big points about microbial diversity.
00:53:01.03 One, that it is incredibly ancient and over this long period of Earth history
00:53:06.08 numerous microorganisms in ubiquitous environments
00:53:09.18 have evolved diverse metabolisms that allow them
00:53:13.00 to catalyze fascinating chemical reactions and that these reactions
00:53:16.23 have affected not only the ability of the cells to grow and divide,
00:53:20.07 but in many instances have profoundly affected their environment,
00:53:24.09 be that environment one in an ancient ocean,
00:53:27.05 or today inside the human body.
00:53:30.18 Thank you.
00:00:07.17 For the last part of my lecture series,
00:00:10.11 I wanna talk about examples of natural selections in humans,
00:00:14.29 and the two particular examples
00:00:17.01 that I'm going to be talking about
00:00:19.00 are the evolution or lactose tolerance in east Africa,
00:00:22.10 and of pygmy short stature.
00:00:25.04 So if we're going to be talking about natural selection,
00:00:27.11 we have to first of course
00:00:28.29 acknowledge Charles Darwin,
00:00:31.12 who came up with the theory of natural selection.
00:00:36.10 In fact, to quote from Darwin, he said,
00:00:39.13 "This preservation of favourable variations
00:00:42.03 and the rejection of injurious variations,
00:00:44.21 I call Natural Selection.
00:00:47.06 Variations neither useful nor injurious
00:00:49.27 would not be affected by natural selection,
00:00:52.18 and would be left a fluctuating element,
00:00:55.01 as perhaps we see in the species called polymorphic."
00:00:58.10 And that was from his classic book
00:01:00.06 On The Origin of Species,
00:01:01.24 published in 1859,
00:01:03.25 and you might recognize from our first lecture,
00:01:07.03 that this is really talking about genetic drift,
00:01:09.27 random fluctuations.
00:01:13.13 However, part of the evolutionary change that we see
00:01:18.12 is not just going to be due to random genetic drift,
00:01:21.03 it's also going to be due to natural selection.
00:01:24.18 And so, according to that theory,
00:01:27.10 natural variation exists and is heritable,
00:01:30.02 more organisms are born than can survive,
00:01:32.11 and therefore organisms best suited to the environment
00:01:35.07 survive more often,
00:01:36.25 and slight differences can accumulate in a species over time.
00:01:40.24 So this is the idea of gradual evolution of a species
00:01:43.27 by natural selection.
00:01:45.18 And this is Huxley,
00:01:47.03 who was also known as Darwin's bulldog
00:01:50.11 because he was the big proponent of his theory,
00:01:52.17 and he said,
00:01:54.05 "How extremely stupid not to have thought of that!"
00:01:57.12 So when Darwin first came up with his theory of natural selection,
00:02:01.08 there was really no concept of genetics
00:02:04.12 as we know it today.
00:02:06.02 In fact, it wasn't until the late 1800s
00:02:08.12 that Mendel proposed his theory of genetics.
00:02:13.02 So in the 1930s and 1940s
00:02:15.22 there was sort of a synthesis of natural selection
00:02:19.09 and genetics and mathematics,
00:02:22.16 population genetics,
00:02:23.25 and at that time it was proposed that genetic variation in populations
00:02:27.05 arises by chance through mutation and recombination,
00:02:31.15 that evolution consists primarily of changes in the
00:02:34.12 frequencies of alleles between one generation and another,
00:02:37.25 largely as a result of genetic drift,
00:02:40.24 gene flow,
00:02:42.05 and natural selection.
00:02:43.27 And that speciation occurs gradually when populations
00:02:46.00 are reproductively isolated, for example,
00:02:48.20 by geographic barriers.
00:02:52.14 And so if we look at this timeline,
00:02:54.12 starting with the Origin of Species,
00:02:56.21 and then Mendelian inheritance
00:02:59.04 is actually rediscovered in 1900,
00:03:01.19 it was first proposed in the late 1880s,
00:03:04.01 but very few people knew about it at that time.
00:03:06.27 And then in the early 1900s
00:03:09.09 we have the theoretical foundations of population genetics
00:03:12.21 and then, as I mentioned,
00:03:14.09 the modern synthesis in the 30s.
00:03:16.19 And then in the 70s we have Kimura's theory of neutral evolution,
00:03:21.19 which was proposing that most changes and speciation events
00:03:25.07 are simply due to random genetic drift
00:03:27.22 and to new mutation events.
00:03:29.20 And I think that today we would say
00:03:31.14 it's a combination of all of the above.
00:03:33.19 There's certainly a lot of genetic drift that occurs,
00:03:36.02 but we know that natural selection
00:03:37.29 is having a very important influence
00:03:40.26 on the variation that we see
00:03:43.05 in terms of phenotypic variation and even disease susceptibility.
00:03:48.04 So let's look what happens
00:03:49.08 when a neutral mutation occurs in a population,
00:03:52.07 as indicated by this individual in green.
00:03:55.25 Let's look what happens as we proceed forward in generations,
00:03:59.08 and you can see there's not too many changes
00:04:01.21 in allele frequency.
00:04:03.29 But what happens when we have a beneficial mutation,
00:04:09.05 which means that it increases the fitness of the individual,
00:04:12.20 meaning that they're more likely to produce children,
00:04:16.12 and their children are more likely to produce more children,
00:04:19.00 and so on and so forth.
00:04:21.15 And so we can see that each generation,
00:04:24.04 this beneficial mutation is going to spread,
00:04:27.22 until eventually it may be nearly fixed
00:04:32.06 in the population.
00:04:34.17 So I want to tell you about some of our studies
00:04:37.20 focused in African populations
00:04:39.14 in which we're trying to identify
00:04:41.02 genetic signatures of natural selection,
00:04:43.19 and regions of the genome that are targets of natural selection.
00:04:47.29 And this is important
00:04:49.22 because it's thought that mutations associated with diseases
00:04:52.16 in modern populations,
00:04:54.13 like hypertension
00:04:56.03 , diabetes,
00:04:58.10 and asthma,
00:04:59.08 may have been selectively advantageous or adaptive
00:05:01.23 in past hunter-gatherer environments.
00:05:04.04 So if we can identify these regions
00:05:06.25 that are targets of selection, or actual variable sites
00:05:09.18 that are targets of selection,
00:05:11.16 those may be functionally important
00:05:13.14 and may give us a clue about disease risk.
00:05:16.11 So here I'm showing you a few of the populations
00:05:18.12 that we've studied in Africa,
00:05:20.23 and we have people who are living at very different climates,
00:05:23.15 high altitude, low altitude,
00:05:26.03 savannah, and tropical environments, for example.
00:05:30.10 We have people who have very different diets,
00:05:32.22 so agriculturalists,
00:05:35.23 or pastoralists.
00:05:37.14 And they have very different infectious disease exposures,
00:05:40.05 so they've likely undergone local adaptation
00:05:42.13 to different environments.
00:05:45.25 And I'm going to, as I mentioned,
00:05:47.16 tell you about two examples today.
00:05:49.15 The first one is the evolution of lactose tolerance
00:05:51.29 in east African pastoralist populations.
00:05:57.07 So, the ability to digest the sugar lactose,
00:06:00.21 which is quite common in milk,
00:06:03.07 is due to an enzyme called lactase-phlorizine hydrolase,
00:06:07.15 or known as lactase for short.
00:06:09.28 And lactase is expressed specifically
00:06:13.01 in the brush border cells of the small intestine,
00:06:16.25 and in individuals who maintain high levels of this enzyme
00:06:20.29 as adults,
00:06:22.23 they're able to break down the complex sugar lactose
00:06:26.16 into glucose and galactose,
00:06:29.14 which is rapidly taken up into the bloodstream.
00:06:35.19 most mammals, and most humans,
00:06:38.19 shut down lactase activity
00:06:40.23 shortly after weaning.
00:06:42.28 So, as adults, they do not have an active form of this enzyme.
00:06:46.24 And what's going to happen is
00:06:48.19 they're not going to be able to break down that complex sugar.
00:06:51.26 It's going to go down into the lower gut,
00:06:54.13 it's going to be attacked by bacteria,
00:06:56.25 and you're going to have severe intestinal distress.
00:07:01.00 Now, it has been noted for many years by anthropologists
00:07:04.27 that there is a very strong correlation
00:07:06.27 between the lactose tolerance trait,
00:07:09.19 or you could think of it also as the lactase persistence trait,
00:07:13.26 because there's persistence of the enzyme activity as adults.
00:07:18.15 And they've seen a strong correlation
00:07:20.20 between the prevalence of that trait
00:07:23.14 with populations who traditionally practice cattle domestication
00:07:28.04 and dairying.
00:07:30.05 So for example, this trait is most common in northern Europe,
00:07:33.19 it decreases in frequency as one moves
00:07:36.23 into southern Europe
00:07:38.29 and into the Middle East.
00:07:40.24 It's very uncommon in eastern Asia
00:07:43.26 and in the Americas,
00:07:46.13 and it's uncommon in western Africa,
00:07:48.26 which is one of the reasons that we see high levels
00:07:51.17 of lactose intolerance in African Americans, for example.
00:07:55.24 But in regions of Africa where there's a high prevalence
00:07:59.04 of cattle domestication, pastoralism, and dairying,
00:08:03.14 we see a high prevalence of this trait.
00:08:07.15 So, in 2002,
00:08:10.18 there was an elegant study done
00:08:12.20 by Leena Peltonen's group in Finland,
00:08:14.28 in which they identified a genetic mutation
00:08:17.08 that regulates lactose tolerance in Europeans.
00:08:20.20 And it was located near the...
00:08:23.25 upstream of the lactase gene.
00:08:26.01 When we sequenced that region in east African pastoralists,
00:08:29.04 they didn't have it,
00:08:31.10 so we knew they must have something else.
00:08:33.13 So in order to identify those mutations,
00:08:35.21 we did something that's called a lactose tolerance test.
00:08:38.29 So, basically what we do is
00:08:42.11 we give people the sugar lactose in a powdered form,
00:08:46.20 we add water, and it basically tastes like orange Kool-Aid,
00:08:51.09 and then we have to line people up
00:08:54.17 and have them drink the lactose at the same time.
00:08:57.27 This is a group of Maasai women from Tanzania.
00:09:03.28 This is a group of pastoralists from southern Ethiopia.
00:09:11.23 And then we can use a standard diabetes monitoring kit,
00:09:16.03 and what we can do is to measure the blood glucose,
00:09:19.29 starting at baseline before they drink the lactose,
00:09:23.29 and then every 20 minutes we're gonna measure this,
00:09:27.06 over a period of about an hour.
00:09:30.02 And then we're gonna look at the maximum rise
00:09:32.25 in blood glucose.
00:09:35.15 If individuals have a rise
00:09:37.09 that is greater than 1.7 millimolar (mM)
00:09:39.20 we consider them to be lactose tolerant,
00:09:42.20 or to have the lactase persistent trait,
00:09:45.03 shown in light blue.
00:09:47.07 And if they have a rise that is less than 1.1 mM,
00:09:51.12 they're considered to be intolerant,
00:09:53.25 shown in dark blue.
00:09:55.18 So, we measured this trait
00:09:57.12 in nearly 500 individuals
00:09:59.17 from Tanzania, Kenya, and the Sudan,
00:10:02.00 and then we looked for association
00:10:04.10 with genetic variation that we identified
00:10:06.21 by resequencing the region
00:10:08.28 where the European variant had been identified.
00:10:13.13 And in doing so we identified
00:10:15.12 three novel genetic polymorphisms
00:10:18.21 that are associated with the lactose tolerance trait in east Africa,
00:10:22.17 and those are shown here by the boxes.
00:10:26.29 The most common was this one at position 14010,
00:10:31.06 but we also saw those others
00:10:32.24 at positions 13915 and 13907,
00:10:36.03 located roughly 14,000 basepairs
00:10:38.25 upstream of the lactase gene
00:10:41.18 which is located on chromosome 2.
00:10:44.07 Now, one of the really interesting things about this is that,
00:10:48.11 one, these regulatory mutations were pretty far away,
00:10:51.28 about 14,000 basepairs from the gene,
00:10:54.26 and they were located in an intron
00:10:57.25 in a non-coding region of a neighboring gene called MCM6.
00:11:03.00 So this is demonstrating that
00:11:04.25 functionally important variation
00:11:07.13 can actually be located in non-coding regions,
00:11:10.21 and we were able to show,
00:11:13.13 using in vitro cell line studies,
00:11:16.20 that these variants that are derived,
00:11:20.19 shown in the different colors here,
00:11:23.22 that they regulate expression
00:11:26.15 of the lactase gene using the lactase promoter.
00:11:31.10 Now, they're located very close to the mutation
00:11:35.01 associated with lactose tolerance in Europeans,
00:11:38.20 located at position 13910,
00:11:41.14 but they arose independently
00:11:43.17 due to a process called convergent evolution,
00:11:46.13 and probably due to a very strong
00:11:48.27 selective force to be able to drink milk that contains lactose,
00:11:56.15 in these different regions of the world.
00:12:00.27 What's also interesting
00:12:02.19 is that the variants that we identified
00:12:04.16 have a very distinct geographic distribution.
00:12:07.09 So the one that we found that was most common in our study
00:12:10.06 was at position 14010,
00:12:12.08 and we can see that it is pretty localized
00:12:15.01 to east Africa, to Tanzania and Kenya,
00:12:17.26 and that's the most likely site of origin of that mutation.
00:12:21.11 Interestingly, we also see it a bit in south Africa,
00:12:26.01 probably reflecting migration of pastoralists
00:12:28.29 from east Africa into that region.
00:12:32.16 The variant position at 13915
00:12:35.08 appears to have originated in the Middle East,
00:12:37.21 and we could see that it was introduced into northeast Africa,
00:12:40.17 probably by migration.
00:12:43.10 And then the variant at position 13907
00:12:46.26 likely arose in northeast Africa.
00:12:49.21 But again, one of the important take-home points is that
00:12:53.02 we have a functionally important variant
00:12:55.07 that's occurring at high frequency, sometimes as high as 40%,
00:12:59.12 and it's very geographically restricted,
00:13:02.22 and there are likely to be other mutations like that,
00:13:05.06 some of which may have implications for disease susceptibility,
00:13:09.11 again emphasizing the importance
00:13:11.23 to look amongst ethnically diverse Africans.
00:13:16.29 So the next thing we wanted to do
00:13:19.21 was to look for a signature of positive selection,
00:13:23.17 and this is the method in which we can do that.
00:13:27.21 So imagine, here in red,
00:13:30.25 imagine that this is a new mutation that has occurred, say,
00:13:34.15 one of the mutations associated with lactose tolerance.
00:13:38.00 And it's adaptive,
00:13:39.10 meaning that it increases the fitness of individuals who have it,
00:13:43.25 meaning that they're more likely to have children,
00:13:45.27 and their children are more likely to have children,
00:13:47.22 and so on.
00:13:49.28 And so it's going to increase in frequency
00:13:52.24 in the population,
00:13:54.29 and it's going to drag with it
00:13:57.15 the neighboring variants nearby.
00:14:00.03 So, you can see that when it originated, it had...
00:14:02.29 it was on a chromosome with a green variant
00:14:05.18 and a black variant.
00:14:08.03 And now these got dragged along to high frequency,
00:14:11.04 through a process known as hitchhiking.
00:14:14.07 Now, if this had gone to fixation,
00:14:17.12 meaning that everybody has it,
00:14:19.00 we would have called it a full selective sweep.
00:14:21.20 In this case, it hasn't quite reached a full selective sweep,
00:14:26.15 so we call it a partial sweep.
00:14:29.24 Now, that could just mean that
00:14:31.17 there hasn't been time for it to go to a full sweep,
00:14:33.06 or it could be that for some reason
00:14:35.17 there may be some negative aspects of having it,
00:14:38.02 and there's a reason that both variants are maintained in the population.
00:14:43.17 Now, after the sweep occurs,
00:14:45.19 you're going to have new mutation events
00:14:47.26 and new recombination events
00:14:49.21 shuffling up the variants
00:14:52.04 that are linked to the mutation that's adaptive.
00:14:56.12 And so that will decrease the association
00:15:01.00 observed between the mutation and the flanking variation.
00:15:05.00 And in fact,
00:15:06.15 if we have an estimate of the recombination rate,
00:15:08.27 we can use computational methods
00:15:10.24 to estimate how old this mutation is.
00:15:14.18 And that's exactly what we did here.
00:15:17.12 So shown on top
00:15:19.28 is an example from the most common mutation
00:15:22.27 that we found associated with lactose tolerance,
00:15:25.03 at position 14010.
00:15:27.18 Individuals who have the C variant
00:15:29.26 are able to digest milk,
00:15:31.22 and individuals who are homozygous are shown as red.
00:15:35.28 And what we did is we genotyped markers
00:15:38.28 going a distance of about 3 million nucleotides,
00:15:42.26 and what we would do is that if someone is homozygous,
00:15:46.20 starting at the lactose tolerance mutation,
00:15:49.02 and then we go to the next mutation.
00:15:51.02 If they're homozygous,
00:15:53.00 then we continue going.
00:15:55.13 If they underwent a recombination,
00:15:57.05 we stop the line.
00:15:59.13 And what we can basically see is that homozygosity
00:16:02.28 extends about 2 million basepairs
00:16:06.01 on chromosomes that have the lactose tolerance mutation.
00:16:09.15 But if we look at chromosomes that have the ancestral mutation,
00:16:14.00 they have almost no extended haplotype homozygosity.
00:16:19.07 And so this is a classic signature of a selective sweep.
00:16:22.25 It means that this variant
00:16:24.16 was under very strong positive selection
00:16:28.14 and it rapidly increased in frequency in the population,
00:16:32.04 dragging with it the neighboring variation.
00:16:38.16 Now, here I'm showing the European variant,
00:16:41.17 in this case the T variant
00:16:43.20 is associated with lactose tolerance,
00:16:45.27 and it shows a very similar pattern.
00:16:50.22 So using computational approaches,
00:16:52.27 we were able to estimate the age of the African mutation
00:16:57.22 to be somewhere between about 3,000-7,000 years of age.
00:17:01.28 These are the populations
00:17:03.25 that had the oldest age estimates,
00:17:06.08 and they include individuals
00:17:08.07 who speak Cushitic languages.
00:17:10.04 They came from Ethiopia,
00:17:12.10 and they practiced agro-pastoralism.
00:17:15.01 They came into Kenya and Tanzania
00:17:17.16 within the past 5,000 years.
00:17:20.23 And then we saw it at very high prevalence
00:17:23.26 and an old age estimate in Nilo-Saharan-speaking groups,
00:17:27.11 and these would include, for example, the Maasai.
00:17:30.09 Now, they came into the region more recently,
00:17:32.17 from southern Sudan,
00:17:34.08 within the past 3,000 years, so if I were to guess,
00:17:37.05 I would think perhaps this mutation
00:17:39.04 arose in the Cushitic speaking populations.
00:17:42.03 But irregardless, it quickly, rapidly spread
00:17:45.07 to all of the populations in the area
00:17:47.21 because it was so selectively advantageous
00:17:51.22 and adaptive to have this mutation.
00:17:55.03 Now, because we see the correlation
00:17:59.18 between the practice of cattle domestication and pastoralism
00:18:04.11 and the rise in this mutations,
00:18:06.16 this is a really excellent example
00:18:08.22 of gene-culture co-evolution.
00:18:12.03 And in fact, what's really interesting is
00:18:15.01 that the date estimates that we came up with correlate really well
00:18:18.25 with the archaeological data,
00:18:20.17 which shows that cattle domestication
00:18:22.14 arose in the Middle East or north Africa
00:18:27.04 somewhere between 8,000-10,000 years ago,
00:18:29.26 and that corresponds with the age estimate for the European mutation,
00:18:33.18 which we inferred to be about 9,000 years old.
00:18:37.25 But cattle domestication was not introduced
00:18:40.25 south of the Saharan desert
00:18:44.20 until roughly 5,000 or 5,500 years ago,
00:18:48.21 correlating very well with the age estimate
00:18:52.03 for the mutation we found in eastern Africa.
00:18:54.24 And then it was introduced
00:18:56.13 much more recently into southern Africa.
00:19:00.12 But one could argue that perhaps Mendelian traits like lactose tolerance,
00:19:05.04 which are regulated by a single locus or gene of major effect,
00:19:10.23 are in a sense the low hanging fruit;
00:19:12.20 they're the easiest to identify.
00:19:15.04 So one thing that my lab is interesting in doing
00:19:17.10 is looking at more complex traits,
00:19:19.23 and perhaps one of the most classic complex traits is height.
00:19:23.28 So, height is highly heritable,
00:19:26.19 genome wide association studies in tens of thousands of Europeans
00:19:30.12 have identified hundreds of loci,
00:19:33.06 each of very small effect,
00:19:35.06 and explaining only a very small proportion of the variation in height.
00:19:39.20 Now, interestingly, most of these are not part of
00:19:42.22 the growth hormone/IGF1 pathway,
00:19:45.07 which we know plays a very important role in idiopathic short stature,
00:19:49.16 for example.
00:19:53.05 Now, in Africa, we see some of the broadest distributions,
00:19:56.21 or ranges in height,
00:19:59.02 ranging from the very short statured Pygmies in central Africa,
00:20:03.28 and then we see some of the tallest individuals
00:20:07.13 in the Sudan and in eastern Africa.
00:20:10.23 And it's thought that these differences
00:20:12.14 may be partly due to adaptation
00:20:14.29 to different environments.
00:20:16.27 So what I want to tell you today is about
00:20:18.19 our genetic studies of short stature
00:20:22.01 in Pygmy populations from central Africa.
00:20:25.14 And, for you to fully understand and appreciate the work we've done,
00:20:29.17 I think I should first tell you a little bit about
00:20:32.07 how we went about collecting these samples
00:20:34.07 and how challenging it could be.
00:20:35.25 So, this is...
00:20:37.18 to get to one of the groups that we studied in Cameroon,
00:20:39.27 you have to cross this river,
00:20:41.28 and you have a person who has a ferry,
00:20:44.05 he's actually using a hand crank here
00:20:47.13 to get us across.
00:20:50.12 And I guess I'm very fortunate
00:20:52.19 because as a woman, I was able to get shade,
00:20:54.15 but not everybody was that lucky.
00:20:56.28 And here are some other hazards that we run into,
00:20:59.15 but I'm smiling because the head is cut off of this snake.
00:21:03.01 But I actually have to give credit to Dr. Alain Froment,
00:21:06.24 who has been studying the Pygmy populations in Cameroon
00:21:09.16 for greater than 30 years,
00:21:11.20 and he did the majority of the sample collection
00:21:14.01 in this case.
00:21:16.21 So, the genetic basis of short stature in Pygmies
00:21:19.26 is a question that's been of tremendous interest
00:21:22.08 to endocrinologists and human geneticists alike
00:21:25.07 for most than 50 years.
00:21:27.08 The particular populations that we studied
00:21:29.25 are located in Cameroon, three different groups from Cameroon,
00:21:34.27 who mean male height is 152 cm.
00:21:40.11 And they live in very close connection and interaction
00:21:44.29 with neighboring populations who speak Bantu languages
00:21:47.29 and practice agriculture,
00:21:50.06 and their mean male height is 170 cm,
00:21:54.04 so that's quite a difference between the two.
00:21:58.16 So, the Pygmy short statured phenotype in humans
00:22:01.26 has arisen independently in different global populations.
00:22:05.12 Typically, these are populations
00:22:07.03 that live in tropical environments,
00:22:09.14 so there have been a number of hypotheses
00:22:11.11 about why this trait might be adaptive.
00:22:14.28 And these include thermoregulation,
00:22:19.04 limited food resources,
00:22:21.19 locomotion - that it may be easier to move
00:22:23.28 in a dense tropical environment if you're short,
00:22:26.18 and more recently there's a theory
00:22:30.10 that this is due to a life-history tradeoff,
00:22:32.10 and I'm going to focus on that theory.
00:22:35.08 And that has to do with the fact that
00:22:37.14 Pygmies have a remarkably short lifespan.
00:22:40.11 Their chance of living to age 15
00:22:42.06 is only about 40%,
00:22:44.18 and if they make it to age 15,
00:22:46.23 the expected lifespan is only around 25 years of age.
00:22:50.01 Now, that is due largely to very high infectious disease burden
00:22:54.05 and a very challenging life in dense tropical forests.
00:22:59.24 Now, what the study showed is that
00:23:02.18 Pygmies appear to be reaching reproduction...
00:23:05.25 they appear to be reproducing and reaching puberty
00:23:08.09 at a significantly earlier age
00:23:11.01 than other Africans.
00:23:13.13 And the growth trajectory in Pygmies
00:23:14.28 appears to be similar to other populations until the point of puberty,
00:23:19.21 and then they lack the adolescent growth spurt.
00:23:22.15 So this may be some sort of a tradeoff:
00:23:24.18 there's selection to reproduce earlier
00:23:26.22 because they're dying very young,
00:23:28.22 but that may be a tradeoff,
00:23:30.24 in that they're not undergoing the adolescent growth spurt.
00:23:35.20 Now, there have been only a handful
00:23:37.28 of physiologic and metabolic studies in Pygmies,
00:23:42.00 but nearly all of these are pointing towards
00:23:44.18 disruptions of the growth hormone/IGF1 pathway,
00:23:47.19 so this is in contrast to what we're seeing in European populations.
00:23:52.05 However, there's been quite a bit of dispute of
00:23:54.28 where along this pathway these disruptions are occurring.
00:24:00.04 So, in order to try to address these questions,
00:24:03.06 we genotyped one million single nucleotide polymorphisms
00:24:08.06 in 67 pygmy individuals
00:24:10.23 and 58 of the neighboring Bantu individuals.
00:24:14.14 And here we can see a plot,
00:24:17.10 similar to what I've shown you before,
00:24:19.09 based on structure analysis.
00:24:21.09 And to remind you,
00:24:23.02 this is composed of a series of lines,
00:24:24.23 and each line represents a person,
00:24:26.16 and they can have ancestry
00:24:28.08 from different ancestral populations,
00:24:31.01 represented by the different colors.
00:24:33.04 So here in orange
00:24:34.29 are individuals who speak the Bantu language
00:24:38.00 and practice agriculture,
00:24:40.08 and in dark green are individuals who self-identify as Pygmies.
00:24:44.19 And what you can see is that there's been
00:24:46.22 a lot of admixture between the Pygmies
00:24:49.29 and the neighboring Bantu people.
00:24:52.03 Now, interestingly, this tends to be unidirectional,
00:24:54.28 and it tends to be gene flow between males
00:24:57.27 from the Bantu population
00:25:00.03 with females of the Pygmy population.
00:25:02.22 This is largely due to socioeconomic factors.
00:25:06.23 Now, when we look at a correlation
00:25:08.26 between ancestry and height,
00:25:11.03 we observed a very strong and significant positive correlation.
00:25:15.04 So, we can see that Pygmies who have more of the Bantu ancestry
00:25:19.23 tend to be taller.
00:25:21.19 And, so this is showing
00:25:22.25 that there's a strong genetic component to this trait.
00:25:26.17 We've also worked with collaborators
00:25:28.11 to develop methods
00:25:30.19 to infer tracts of Pygmy and Bantu ancestry
00:25:35.11 across the chromosome.
00:25:36.29 So here, these are the different chromosomes,
00:25:38.18 starting with chromosome 1
00:25:40.05 and going up to chromosome 22,
00:25:42.25 and here I'm showing you an example from chromosome 3.
00:25:46.04 And in blue is showing tracts of the genome
00:25:49.03 that are Pygmy ancestry,
00:25:50.24 and in red are tracts of the genome that are Bantu ancestry,
00:25:54.23 and what we tend to see are very, very short tracts of Bantu ancestry.
00:25:58.28 And that's reflected in the fact that admixture
00:26:01.08 has been occurring over thousands of years.
00:26:06.11 Now, the next question that we wanted to address
00:26:08.17 is how do the genomes of the Pygmy hunter-gatherers
00:26:12.04 differ from the genomes of the Bantu agriculturalists
00:26:17.00 and from other groups, such as the Maasai pastoralists
00:26:20.28 from east Africa.
00:26:22.28 And to do that,
00:26:25.03 we use a number of scans of natural selection
00:26:27.28 across the genome.
00:26:29.29 Without getting into detail about the methods,
00:26:32.26 I'll just point out that you can see by the different colors here
00:26:37.00 across the different chromosomes,
00:26:39.00 here's chromosome 22 and going down to chromosome 1,
00:26:42.04 that we found a number of regions of the genome
00:26:44.22 that are targets of selection.
00:26:47.05 But there was one region in particular,
00:26:49.26 on chromosome 3,
00:26:52.04 where we saw a cluster of targets of natural selection.
00:26:57.01 And this was over about a 15 million basepair region.
00:27:01.14 Now, given our small sample size,
00:27:03.20 we have very little power
00:27:05.15 to detect a genome-wide association.
00:27:09.04 And so what we did is,
00:27:10.26 under the hypothesis that this is an adaptive trait,
00:27:13.17 we just focused on the regions of the genome
00:27:16.07 that are targets of selection, shown here,
00:27:19.11 and then we looked for an association with height.
00:27:22.10 And one of the strongest, most significant associations
00:27:25.09 was exactly in that same 15 million basepair region
00:27:29.19 of chromosome 3.
00:27:31.23 And indeed, it encompassed several genes,
00:27:34.15 one of which is DOCK3,
00:27:36.18 which has been shown to be associated with height
00:27:39.09 in non-African populations,
00:27:41.08 so we replicated that finding.
00:27:43.20 But nearby was another gene called CISH,
00:27:47.09 which is a member of the cytokine signaling family,
00:27:50.10 plays a very important role in regulating
00:27:52.28 IL-2 cytokine signaling pathway,
00:27:56.18 and studies have shown that it's associated
00:27:58.26 with resistance to a number of infectious diseases
00:28:01.18 in Africa.
00:28:04.01 Now, interestingly,
00:28:05.29 CISH also directly inhibits
00:28:07.14 human growth hormone receptor action
00:28:10.06 by blocking the STAT5 phosphorylation pathway.
00:28:13.15 And so we know that studies in mice
00:28:15.17 show that when this gene is overexpressed,
00:28:18.06 the mice are short statured.
00:28:20.23 Now, this led me to the hypothesis that,
00:28:24.14 could it be that there could actually be selection
00:28:26.19 for immune function
00:28:28.11 that is indirectly resulting
00:28:30.05 in short stature in Pygmies,
00:28:32.05 because that gene plays an important role in both.
00:28:35.29 And we need to do further functional studies,
00:28:38.20 and look at differences in gene expression
00:28:40.13 to test this hypothesis.
00:28:44.04 The last study I wanna tell you about is a study
00:28:46.20 in which we sequenced the entire genomes,
00:28:49.15 at high coverage,
00:28:51.07 of 15 African hunter-gatherers,
00:28:53.22 including 5 Pygmies,
00:28:55.28 5 Hadza,
00:28:57.10 and 5 Sandawe.
00:28:59.26 We identified over 13 million variants,
00:29:02.29 3 million of which are completely novel;
00:29:05.29 they have never previously been identified.
00:29:08.13 And that's just from 15 individuals,
00:29:10.14 so you can imagine how much variation is out there.
00:29:13.16 Many of these are novel variants...
00:29:15.27 many of these novel variants are in known regulatory sites.
00:29:21.04 So now, combining the two studies,
00:29:24.08 we wanted to ask the question,
00:29:26.03 which pathways are enriched for genes near targets of selection?
00:29:29.16 And these enriched pathways
00:29:31.25 include genes involved in neuro-endocrine signaling,
00:29:37.11 and immune function,
00:29:38.22 and interestingly, based on the whole genome sequencing study,
00:29:42.08 we saw an enrichment for genes
00:29:44.06 that play a role in pituitary function in Pygmies,
00:29:47.13 including follicle-stimulating hormone receptor,
00:29:50.13 growth hormone receptor,
00:29:52.11 HESX1, which I'll tell you more about in a moment,
00:29:55.11 and thyrotropin-releasing hormone receptor.
00:29:58.15 In fact, TRHR was one of the biggest hits
00:30:02.13 that we saw in terms of these studies of selection.
00:30:05.17 And what's interesting is that this gene
00:30:08.22 plays an important role in the hypothalamic-pituitary-thyroid axis,
00:30:12.28 influencing a number of traits that could potentially
00:30:15.14 be of adaptive significance in Pygmies.
00:30:18.26 And also of interest was that anthropologists
00:30:21.18 have noted that there is a significant difference
00:30:24.23 in the prevalence of Goiter
00:30:27.00 among Pygmies and neighboring Bantu groups.
00:30:29.24 So the Pygmies have a much lower frequency of Goiter
00:30:33.16 compared to the neighboring Bantu populations,
00:30:36.16 and this could reflect a biological adaptation in Pygmies
00:30:41.20 to a low iodine environment.
00:30:43.24 It's very deleterious to get Goiter
00:30:46.22 because it can also lead to a diseased called Cretinism,
00:30:49.27 which of course is going to be very deleterious.
00:30:52.18 So again, here's an example
00:30:54.10 where something like adaptation to diet
00:30:56.13 could indirectly influence growth
00:30:58.28 or other phenotypes in the Pygmy population.
00:31:04.01 The last thing we wanted to do
00:31:06.01 was to look for regions of the genome,
00:31:08.08 using the whole genome sequencing data,
00:31:10.13 that are specific to Pygmies,
00:31:12.20 and those are shown in green here.
00:31:16.02 Now, we identified 25 clusters in the genome,
00:31:19.23 and the largest cluster
00:31:22.27 was right in that same region of chromosome 3
00:31:25.14 that we had previously identified.
00:31:28.00 But we had missed it in the prior study,
00:31:30.11 and the reason why is because
00:31:32.17 it contains these Pygmy-specific variants,
00:31:35.08 that were not captured by the SNP array that we used,
00:31:39.17 and thus demonstrating the great importance
00:31:42.00 of doing resequencing for identifying novel
00:31:44.24 and potentially functionally important variation
00:31:47.15 in ethnically diverse populations.
00:31:50.28 Now, this cluster consisted of
00:31:55.10 44 SNPs in 100% association with each other
00:31:59.16 over 170,000 nucleotide,
00:32:03.06 shown here,
00:32:05.24 and it contained a very interesting candidate gene called HESX1.
00:32:10.10 HESX1 codes for a transcription factor
00:32:13.05 that plays a very important role
00:32:15.04 in regulating the development
00:32:17.15 at the anterior pituitary in the brain,
00:32:20.14 and that's the site of production of growth hormone,
00:32:22.23 as well as other reproductive hormones.
00:32:25.11 Now, interestingly,
00:32:27.06 we identified a non-synonymous,
00:32:29.28 so an amino acid change, basically,
00:32:33.23 in this gene
00:32:36.03 that had been previously associated
00:32:38.13 with idiopathic short stature in humans.
00:32:41.26 But it turns out that this varian
00:32:44.01 t is present at about a 20% frequency in other Africans.
00:32:47.12 So what we hypothesize is that
00:32:49.13 there's something about this region
00:32:51.22 that may be altering gene expression of HESX1
00:32:55.07 or other genes in that region.
00:32:58.01 Upstream, we found another cluster
00:33:01.18 near this gene POU1F1, also known at Pit-1 in mouse,
00:33:07.13 and again this codes for a transcription factor
00:33:09.18 that plays a critical role in regulating growth hormone expression.
00:33:14.23 So another excellent candidate gene.
00:33:17.28 Now, what is interesting is that
00:33:19.27 both of these clusters, or genes,
00:33:23.18 are amongst the most differentiated regions
00:33:26.27 of the Pygmy genomes,
00:33:28.27 compared to genomes from elsewhere in Africa.
00:33:31.29 So we then picked out some of the SNPs in these regions
00:33:37.13 and genotyped them in a larger set
00:33:39.19 of western and eastern Pygmies,
00:33:41.26 and we showed that they are statistically
00:33:44.02 associated with short stature in Pygmies.
00:33:47.29 So the next step is going to be
00:33:49.24 to try to make transgenic models
00:33:52.01 that express these variants using transgenic mouse models,
00:33:56.06 and see what the phenotype looks like.
00:34:00.19 So that leads us to a number of hypotheses.
00:34:03.19 One, is that alterations in the growth hormone/IGF1 pathway
00:34:07.15 play a role in the short stature trait in Pygmies.
00:34:13.01 Two, is that anterior pituitary hormones
00:34:15.10 may play a central role in the Pygmy phenotype,
00:34:18.09 influencing growth, reproduction,
00:34:20.15 metabolism, and immunity.
00:34:24.00 And thirdly, that short stature
00:34:26.16 could be a byproduct of selection
00:34:28.11 acting on pleiotropic loci.
00:34:31.04 So if we look here,
00:34:32.21 one of the candidate loci that we identified is HESX1.
00:34:36.13 That's going to influence expression and development
00:34:39.20 of the anterior pituitary,
00:34:42.02 site of production of growth hormone.
00:34:44.20 Growth hormone expression is also regulated
00:34:46.23 by this other gene we found, POU1F1.
00:34:50.04 And this CISH regulates growth hormone receptor.
00:34:54.17 Now, if we look at the downstream effects
00:34:56.24 of growth hormone,
00:34:59.07 growth hormone, when it binds to growth hormone receptor,
00:35:02.18 will trigger off expression of IGF1,
00:35:06.12 predominantly from the liver, but from other tissues as well.
00:35:10.06 IGF1 will have an effect on muscle growth
00:35:13.14 and also on bone growth and height,
00:35:16.02 but the other impact, or the other role of growth hormone
00:35:20.12 is that it also influences insulin metabolism,
00:35:24.06 it influences fat metabolism.
00:35:28.01 And then we know that infectious disease
00:35:30.01 alters immune response and cytokine levels,
00:35:33.08 and that these can influence gene expression from CISH,
00:35:36.11 or other genes that are in this pathway.
00:35:40.09 So, when we go back to Africa to study the Pygmies,
00:35:42.28 what we would ultimately like to do next
00:35:45.16 is to measure all of the phenotypes,
00:35:48.01 because if you want to understand something
00:35:50.04 like the evolution of short stature in Pygmies,
00:35:52.19 I think you can't just be looking at stature
00:35:55.09 because the growth hormone pathway
00:35:58.25 plays a role in all of these different traits,
00:36:01.01 so we need to be looking at this as an integrative picture.
00:36:06.01 And in fact, our approach in the future
00:36:08.26 is to use an integrative genomics approach
00:36:11.24 combining whole genome data,
00:36:14.15 data on protein variation from blood,
00:36:17.25 epigenetic variation,
00:36:19.21 which can be influenced by diet and environment,
00:36:22.12 gene expression,
00:36:24.10 we're starting to look at the microbiome,
00:36:27.16 which is the spectrum of bacteria in the gut,
00:36:32.05 because that can not only be influenced by diet,
00:36:35.16 it can also have an influence on the metabolome,
00:36:38.12 or the set of all the metabolites, for example,
00:36:40.27 in blood.
00:36:42.20 And we want to combine that information
00:36:44.25 together with information on diet
00:36:46.22 and other environmental factors,
00:36:48.29 to try to identify genetic and environmental factors
00:36:52.15 that play a role in short stature
00:36:55.05 and in other anthropometric,
00:36:58.01 and metabolic traits.
00:37:00.20 One of the other approaches we can take
00:37:02.20 to distinguish the role of genetics and environment is, for example,
00:37:06.00 to look at individuals of the same or similar ethnic background,
00:37:10.29 but living in an urban versus a rural environment.
00:37:16.21 We can also take a different...
00:37:18.14 the opposite approach.
00:37:20.00 We can look at individuals who have
00:37:22.06 very different genetic ancestries,
00:37:25.03 but live in similar environments.
00:37:27.13 So for example,
00:37:29.20 this is a girl who is from the Fulani population,
00:37:33.17 and here's a neighboring...
00:37:35.19 an individual from the Tupuri population.
00:37:38.26 So they are genetically very differentiated,
00:37:41.20 but live in a similar environment,
00:37:43.16 yet the Fulani seem to have some innate resistance
00:37:47.06 to malaria infection.
00:37:50.03 By contrast, in the San,
00:37:53.09 from southern Africa,
00:37:54.29 are very differentiated from the Bantu,
00:37:57.15 but the San seem to have an innate susceptibility
00:38:01.09 to TB infection.
00:38:03.20 So again, by contrasting populations with different ancestry,
00:38:07.26 and living in different environments,
00:38:09.11 we may identify clues about the genetic basis
00:38:12.10 of differences in phenotypic variation
00:38:14.26 and disease susceptibility.
00:38:17.23 So in conclusion,
00:38:20.20 Africans have the highest levels of genetic diversity
00:38:23.04 within and among populations.
00:38:26.28 The demographic history of Africans
00:38:29.00 and local adaptation to different environments
00:38:31.04 has resulted in population
00:38:33.01 or region specific genetic variation.
00:38:36.25 And we need to be including
00:38:38.21 ethnically diverse Africans in genomic studies
00:38:41.17 to better identify both unique rare, and common variants
00:38:45.28 which may be of functional importance,
00:38:47.28 including those that play a role in disease risk
00:38:50.13 in these populations.
00:38:52.14 And I will just end by thanking
00:38:54.04 the many individuals
00:38:55.25 who contributed to these studies,
00:38:57.29 and my funding agencies,
00:39:00.16 and particular thanks to the Africans
00:39:02.20 who have contributed to these studies.
00:00:12.26 I'm David Haussler, scientific director
00:00:16.03 of the UC Santa Cruz Genomics Institute,
00:00:18.19 and Howard Hughes Medical Institute investigator.
00:00:21.13 It's my pleasure to be able to speak to you
00:00:24.26 on the great questions in biology.
00:00:27.13 I want to have you imagine
00:00:32.17 that you just got your genome sequenced.
00:00:35.06 Now, when we sequenced the first genome
00:00:37.21 in the year 2000, it cost about $300 million,
00:00:41.27 just for the sequencing reagents and activities.
00:00:44.25 But nowadays, it's a couple thousand bucks.
00:00:47.14 So let's assume, you went out and got your sequence done.
00:00:52.18 Now looking at that, it may be hard to interpret
00:00:58.23 but it's got to be a moving experience,
00:01:03.03 to look at that DNA sequence and think about
00:01:06.09 how it got there.
00:01:08.27 In particular the DNA in your genome
00:01:13.00 was passed on from generation to generation
00:01:16.11 for eons.
00:01:18.04 We all come out of the primordial ooze somewhere
00:01:21.24 billions of years ago
00:01:23.29 And it's stunning to think that a record
00:01:27.11 of many of those evolutionary events
00:01:29.24 is still present in the genomes today.
00:01:33.02 So what would you do? What would you look a
00:01:38.17 to start to understand where you came from?
00:01:41.19 And what is specifically interesting about your genome
00:01:46.14 versus all the other genomes on the planet?
00:01:49.09 Probably the first thing you would think about
00:01:54.16 in terms of the way that DNA is inherited
00:01:57.23 from parent to offspring is:
00:02:00.14 are there any new elements of your genome
00:02:04.03 that weren't even in your parents?
00:02:05.21 And statistics say there will be a few
00:02:09.00 So there will be a few changes in the way the DNA
00:02:12.16 was copied. You could think of them as errors,
00:02:16.01 but you could also think of them as fortuitous events
00:02:19.14 that caused something different in your genome
00:02:23.01 that wasn't in either of your parent's genome.
00:02:24.27 Those would be interesting, certainly.
00:02:27.18 And there are probably only a very small handful of those.
00:02:31.27 The next thing you would think about is
00:02:34.21 is there something I inherited from my parents
00:02:40.05 that's just specific to my family in some sense?
00:02:43.21 Maybe it's something special that happened in
00:02:47.12 a great grandparent and has been passed down
00:02:51.11 to me through all of these generations.
00:02:53.20 Now this is the very stuff of genetics.
00:02:57.20 To think about this, in particular, medical genetics
00:03:00.25 you would be very concerned if this actually
00:03:04.14 made you prone to a disease
00:03:05.18 You might also be protected from a disease
00:03:10.09 by a special version of a gene that's in your genome
00:03:13.13 that's specific, or private, to your specific family.
00:03:17.21 That would be exciting.
00:03:20.28 And as we start to get the era from just one genome
00:03:25.27 in the year 2000, to the coming era of millions of genomes,
00:03:29.25 we will be able to, by comparing genomes,
00:03:33.14 understand what's specific to certain families,
00:03:37.19 what's specific to certain ethnic groups,
00:03:39.24 what's specific to humans in general, but not
00:03:45.24 with other species.
00:03:47.09 It's an enormous computational problem
00:03:50.18 to compare all of these genomes, and this is probably
00:03:53.21 the most significant challenge facing the computational part
00:03:58.25 of genetics and genomics today.
00:04:01.20 If you understood what was specific to humans
00:04:05.21 that would be fascinating, you could start to think about
00:04:08.20 what happened since we diverged from our common ancestor
00:04:12.14 with our closest species, the neanderthal.
00:04:16.22 While the neanderthals are extinct,
00:04:19.17 we were able to sequence DNA from their bones
00:04:23.18 and hence, get an idea of their genomes looked like.
00:04:27.06 And we find that there are more than a million changes
00:04:31.27 that occurred in the human lineage
00:04:34.26 since we diverged from our common ancestor
00:04:37.18 to neanderthal.
00:04:38.28 What an exciting project at this point, to try to understand
00:04:42.05 those changes that almost everybody
00:04:47.24 almost all of humankind share,
00:04:49.22 as opposed to and distinguish them from the neanderthal.
00:04:54.23 Going back further, about 5-6 million years ago,
00:05:01.05 we shared a common ancestor with the chimpanzee
00:05:03.25 Since that time, there have been roughly 15 million changes
00:05:07.23 in our genome.
00:05:09.15 Which ones actually account for the difference
00:05:12.22 between a human and a chimp?
00:05:14.10 This is a substantial difference
00:05:16.22 and remarkably, we still know very little
00:05:19.29 about which of those changes actually make that huge difference
00:05:25.04 between a human and a chimp.
00:05:27.04 One thing that you'll run into, in this quest,
00:05:31.06 is the fact that most of these changes
00:05:35.16 are probably not important
00:05:39.03 in some sense.
00:05:40.18 If you look at the structure of your DNA
00:05:45.08 and in particular, if you look at it from this perspective
00:05:48.14 of going back and looking at where the DNA came from
00:05:52.16 what it's history is,
00:05:54.08 you see that there are some parts of your genome
00:05:56.28 that are shared with virtually all other life
00:06:00.11 on the planet.
00:06:01.21 The genes and the DNA in the genes
00:06:03.24 and the ribosome sequences,
00:06:05.20 DNA polymerase. Other fundamental molecules
00:06:11.07 that make life itself possible
00:06:13.02 are remarkably little changed
00:06:15.07 over the eons of evolutionary time.
00:06:17.26 And so when you look at one of those bases in your genome
00:06:21.22 you can sit back and say, "wow, that's a really ancient base!"
00:06:26.19 "That base of DNA was passed on to me
00:06:30.21 all the way back from the beginning
00:06:33.25 billions of years, copied faithfully
00:06:36.29 again and again and again.
00:06:38.15 And now it is a gift to me
00:06:41.18 so that my cells work."
00:06:45.01 In between that are all stages of evolutionary innovation.
00:06:51.00 So when you look at your genome
00:06:53.01 you'll find genes that were created essentially
00:06:58.12 as an evolutionary process in the bilaterian animals,
00:07:02.24 for example.
00:07:04.07 The set of animals that have bilateral symmetry
00:07:07.23 is a huge collection of animals on the planet
00:07:10.27 that they didn't exist 2 billion years ago.
00:07:13.17 So all of their genetic innovations happened
00:07:17.11 after that period.
00:07:19.06 If you look at vertebrates,
00:07:20.24 animals with a backbone,
00:07:22.12 they didn't exist 800 million years ago, but now
00:07:27.24 we can find all of the different innovations
00:07:31.03 that are specific to the vertebrates,
00:07:33.06 the backboned animals, that don't exist in other animals.
00:07:36.02 And each one of these beautiful genetic variations
00:07:39.20 happened at a particular time
00:07:42.05 in the marvelous history of life.
00:07:44.03 So when you're looking at every gene in your genome,
00:07:47.04 you can say "Aha! That's a bilaterian innovation."
00:07:51.02 "Oh, and this one was invented by vertebrates."
00:07:54.17 "And maybe this one was invented by primates."
00:07:57.27 "And maybe this one is specific to apes."
00:08:00.22 Understanding this, is probably the greatest challenge
00:08:07.16 to genomics, going forward at this point.
00:08:11.19 And we have an extraordinary opportunity
00:08:13.28 to look at every base in the genome
00:08:17.05 for the first time.
00:08:18.28 And more importantly, to compare it
00:08:22.23 to the bases in other genomes.
00:08:25.06 The lesson we've learned from first sequencing the human genome
00:08:30.04 in the year 2000, and subsequently looking
00:08:33.17 at the first chimpanzee genome,
00:08:35.09 the first mouse genome,
00:08:36.25 the first rat genome,
00:08:38.17 the first dog genome,
00:08:40.07 is that no genome is ever understandable
00:08:44.08 in isolation.
00:08:45.12 Every time we sequence the genome of a new species
00:08:48.25 we learn more about the genomes that we had previously
00:08:52.28 sequenced from other species.
00:08:55.08 And that is precisely because
00:08:57.20 we share a common heritage
00:08:59.26 and because we are sculpted by evolution.
00:09:03.07 By looking at these patterns of conservation,
00:09:06.27 and change within our genome,
00:09:08.18 we can often decode something about the function
00:09:13.07 of a region of DNA.
00:09:15.00 For example, if it codes for protein sequence,
00:09:19.03 then it has to have this triplet pattern of codons
00:09:22.25 and you'll find that while there are changes in the region
00:09:26.25 they preserve this fundamental property of being able to code
00:09:31.00 for a protein, and we can see that clearly
00:09:33.25 in the pattern of changes which are allowed
00:09:35.27 or not allowed.
00:09:38.00 So that gives us a window,
00:09:40.19 just by studying comparisons between many pieces of DNA,
00:09:44.19 into the function of those pieces of DNA.
00:09:47.17 But we're only seeing the tip of the iceberg here.
00:09:51.13 We're very much at the beginning
00:09:53.12 of a long journey, now that we're in the genomics era
00:09:57.13 and being able to look at all of these genomes
00:10:00.09 together, of decoding them through
00:10:03.11 their history, through comparison.
00:10:05.29 I hope you will consider taking this journey
00:10:09.03 with us. It's a journey that needs not only biologists,
00:10:14.16 but computer scientists.
00:10:15.24 Right now the world is struggling
00:10:18.16 to be able to write the software code
00:10:21.01 to create the computer architecture
00:10:22.29 to be able to compare the full genomes
00:10:26.01 from hundreds, or thousands, of different species
00:10:30.10 This is the very edge of our capabilities at this point.
00:10:35.13 And we can look forward to great innovations,
00:10:38.24 both in terms of computers and algorithms,
00:10:43.15 big data, cloud computing, all of these
00:10:46.18 things will have a say, along with traditional
00:10:50.17 fields like biology, molecular biology, biochemistry,
00:10:54.12 and evolution population genetics.
00:10:57.26 So it's a great time to be involved in this,
00:11:01.09 and I invite you to this wonderful adventure.
- If you want to learn more about how scientists measure trait heritability, please review the following paper: Estimating trait heritability Wray, N. & Visscher, P (2008) Nature Education 1(1):29
- Youreka Science: Hardy-Weinberg Equilibrium: Combining Darwinian Evolution and Mendelian Genetics to Study Population Genetics
- Melina Hale iBioSeminar: The Evolution of Neural Circuits and Behaviors
- Dianne Newman iBioSeminar: Microbial Diversity and Evolution
- Sarah Tishkoff iBioSeminar: African Genomics: Human Evolution and Migration
- David Haussler iBioMagazine: What Can We Learn From Sequencing Our Genomes?
Melina Hale is a professor of Organismal Biology and Anatomy and Neurobiology and Computational Neuroscience at the University of Chicago. Using predominantly zebra fish, Hale’s lab studies neural circuits that control limb and axis movement and how that movement changes over time. Movement changes can be seen both in the short time frame of development… Continue Reading
David Haussler is Scientific Director of the University of California Santa Cruz (UCSC) Genomics Institute and Investigator of the Howard Hughes Medical Institute (HHMI). Haussler uses mathematics, computer science, and biology to study the genomes of organisms with the goal of understanding disease and evolution. As part of the Human Genome Project, he led the… Continue Reading
Dr. Newman is a Professor in the Divisions of Biology and Geological and Planetary Sciences at the California Institute of Technology. When Newman began her undergraduate studies at Stanford University she wasn’t sure she was going to be a scientist because she was interested in a variety of different fields. In fact, she received her… Continue Reading
Sarah Tishkoff studied anthropology and genetics as an undergraduate at the University of California, Berkeley. She received her PhD in genetics from Yale University and was a post-doctoral fellow at Pennsylvania State University. From 2000-2007, she was a faculty member in the Department of Biology at the University of Maryland. Currently, Dr. Tishkoff is the… Continue Reading
Youreka Science was created by Florie Mar, PhD, while she was a cancer researcher at UCSF. While teaching 5th graders about the structure of a cell, Mar realized the importance of incorporating scientific findings into classroom in an easy-to-understand way. From that she started creating whiteboard drawings that explained recent papers in the scientific literature… Continue Reading