Genetic Code: What Can We Learn From Sequencing Our Genomes?

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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.

This Talk

Speaker: David Haussler

Audience:

Educators of H. School / Intro Undergrad
Student
Educators of Adv. Undergrad / Grad
Researcher
Educators

Recorded: October 2014

Talk Overview

David Haussler explores the question, “What information is hidden inside your genome?” By comparing the sequenced genomes of different organisms, researchers can identify changes in the genetic code that led to specific evolutionary innovations in the past. The implications for medicine and biology are profound. However, as Haussler mentions, more computational talent is required to analyze such a large number of genomes, especially as more genomes continue to be sequenced at an increasingly rapid pace.

Speaker Bio

David Haussler

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