Chapter 22
hill Evolutionary Biology: I 11.11 I~ i The Next 150 Years
1, Hopi E. Hoekstra
Darwin was arguably the most prescient thinker that biology has ever wit nessed. But, if someone had asked him in 1859 where evolutionary biology would be in 150 years, would he have guessed correctly? He might have predicted that we would have a better understanding of how traits are in herited-a prediction borne nut almost 30 years later with the rediscovery of Mendel's laws in 1900. Darwin considered the Jack of understanding for how traits are inherited to be the missing link in his argument fnr evolution I by natural selection, and when pushed, he devised his own theory (i.e., ~jl !I pangenesis), which was one of his few major errors. Yet, the ramifications .I of Mendel's experiments or of subsequent discoveries, like that of the three dimensionaJ DNA structure by Watson and Crick (1953) a century after Tlzc Origin of Species was published, along with the resultant technological advances, such as the ability to sequence a complete genome in another 50 years, were unknowable in his day. \Jor could Darwin have anticipated the questions that have dominated the field since, such as the relative role of drift and selection in driving molecular evolution (Kimura 1968). With the acknowledgement that technologies, discoveril'S, and questions will arise that, likewise, ca1mnt be imagined, it is useful-perhaps even stimulating to speculate about what the next 150 (or more modestly, 50 or even 20) years will hold for evolutionary biology. The organizers of the Darwin 2009 Workshop asked me to speculate on what may lie ahead. My crystal ball, if 1have one, is colored by evolutionary genetics and genomics-my main research area-and so necessarily are my predictions. To predict the advances in the field of evolutionary biology, we (i.e., evolutionary biologists) must first set a direction. One overarching goal of evolutionary biology is to understand how the diversity of life t>volved, "l.11: 1'Jl1 and more specifically to understand how this variation, both genetic and ill phenotypic, is generated and maintained in nature. This aim spans sub- r ______J 1
632 Chapter 22 Hoekstra Evolutionary Biology: The Next 150 Years 633
disciplines, ranging from the origin of life (see Lazcano, Chapter 14) Drosophila demonstrated that genes are carried on chromosomes, provid lcontology (sec P. Wagner,- Chapter 17), and phylugenctics. (see Billi'~ ing a material basis for heredity. Together, these discoveries also high Chapter l~) tu theoretical population genetics (see Wakeley, Chapter;) lighted how phenotypic variation-whether it be the shape of peas or the and evolutionary ecology (sec Agrawal ct aL, Chapter 10). Acquiring this eye color of flies-can be sh1died in the laboratory (and eventually in the know ledge may also help us address some ut the most pressing problems of field). Around the same time, the role of natural selection acting in the our time, which include concerns about the future evolution (or extinction) wild was being further documented. For example, using a simple general of this biudivefoity (see Gould, Chapter 21; Davis et al., Commentary 6). selection model, J.B. S. Haldane calculated the selective advantage neces The question of how diversity evolved is of course nut a simple one and sary for the observed evolution of industrial melanism in peppered moths therefore, must be attacked from multiple angles and at several levels. At (Haldane 1924). However, it was the combination of critical contributions the most proximate level, we would like to know what mutations give rise by Haldane, Sewall Wright, and most notably R. A. fisher who showed to variation and how that genetic variability is maintained in populations how the action of many discrete genetic loci studied in the lab could result (see Zhang, Chapter 4). Next, the question arises of how genetic variation in continuous trait variation observed in nature. l:lut, arguably, it was Dob actually produces variation in organisms, for example, through changes in zh;msky's 1937book Genetics and the Origin of Species that played a key role developmental events, pathways, or processes (see Wray, Chapter 9). Deci in bridging the gap between population geneticists and field naturalists. phering how evolutionmy forces act on this phenotypic variation in a given These works and others culminated in the modern evolutionary synthesis, ecological context (see Agrawal et al., Chapter 10; Berenbaum and Schuler, that is, the union of ideas from scientists across several disciplines (from Chapter 11)-and how different properties may constrain (see Kirkpatrick, laboratory genetics to field ecology, systematics, and paleontology) about Chapter 7) or promote (see G. Wagner, Chapter 8) phenotypic change the way evolution proceeds. remains a major challenge. While the study of morphological variation from here, as is often the case, it was a technological advance that offers a logical starting point, we also want to uncover the mechanisms pushed the field forward. In the 1960s, Richard Lewontin moved to the responsible for variation and evolution of other characters (e.g., behavior) University of Chicago, where he met Jack Hubby. I ,ewontin was an evo and understand how and why behavioral evolution may be similar to or lutionary geneticist with a question: how much genetic variation exists in different from morphological evolution (see Kokko and Jennions, Chapter natural populations? Hubby was a biochemist with a new technique: pro 12). Moreover, we are not limited to processes occurring within a lineage; tein electrophoresis. It was the perfect union. Together, they surveyed 18 ,' rather, our thinking must be extended to the genetic and ecological changes loci in Drosophila pseudoobscura and reported that a large fraction was poly ,;[i associated with speciation (sec Harrison, Chapter 13) and macroevolution morphic (Lewontin and Hubby 1966). This result had a great impact, as the ary diversification (see Losos and Mahler, Chapter 15; Foote, Chapter 18). discovery of high levels of molecular polymorphism raised the question of I:,1 finally, a temporal component must be added-changes in allele frequen wh<1t evolutionary forces maintain this variation-a question that preoc cies at specific loci (e.g., ancient DNA studies), genome composition (e.g., cupied population geneticists for decades. The ability to survey allozymes comparative gcnomics), phenotypes (e.g., fossils and characler mapping in wild populations also offered an exciting opportunity to connect genetic using phylogenetics) and the environment-to understand change through variation to fitness in nature. One of the earliest examples was reported time. Only when all of these pieces are taken together can we start to for by Wall (1977), who showed that variation at the phosphoglucoisomerasc mulate a complete picture of evolutionary change. (PGI) locus is associated with fitness differences in natural populations Integration of these diverse approaches has long been an ideal in evolu of Colias butterflies. Yet, in the following three decades, tlwre have been tionary biology. for example, in the introductory chapter (notably entitled only modest steps toward cementing the link between genotype, pheno "The Problem") of his 1974 book The Grnel ic Basis of Evolutionan; Change, type, and the environment in any one system, that is, until very recently. Richard Lewontin advocated a merger between scientists working on the In the last few years, case studies have started to accumulate that provide genetic processes (e.g., population geneticists studying the impact of dif a near complete picture of acfapti ve change, that is, the genes and mutations ferent evolutionary forces on changes in allele frequency) and those fo that underlie variation and divergence in traits that have documented fit cusing on forces acting on phenotypes (e.g., field naturalists studying the ness consequences in nature have been identified (figure 22.1). To some, this role of differential survival and reproduction on phenotypic change across represents the holy grail of evolutionary biology. In threcspine stickleback generations). (Casterosteus aculeatus), changes in armor are associated with the invasion of Before proceeding, however, let us review briefly some major advances freshwater lakes following the last glacial cycle, starting about 20,000 years that have led to this point. Not long after the rediscovery of Mendel's ago, and a reduction in armor has measurable fitness consequences (Bar laws of inheritance, Thomas Hunt Morgan's mutational experiments in rett et al. 2008; Marchinko 2009). At the genetic level, changes in armor are 634 Chapter 22 Hoekstra Evolutionary Biology: The Next 150 Years 635
Florida (beach) to suutheastern Alabama (inland) . ,____..___, ..J
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2'" ~1 ~88888~~~ associated with changes in the t:ctodysplnsin (Edn; Colossimo et al. 2005) and <1'.'5 CJ ~ the PitXl loci (Shapiro et al. 2004). Moreover, deletions of a cis-regulatory :2 "'>- b element in the PitX1 locus alter pelvis-specific expression of PitXJ dur '"' z f ~ ~8rnl)~Jooo~ ing development (Chan et al. 2010). These phenotvpic (and inferred allele) w v 0 ~ frequencies can be tracked through time, using both museum specimens (Bell et al. 2004; Kitano ct al. 2008) and the fossil record (Hunt et al. 2008; 0§7: 1 ·~ ~ ~0808EJ001 l>ell 2009). In a second example, oldfield mice (Prmmyscus polivnotus) have VJC''-l~ dorsal coal colors that closely match their local substrate, and the degree of <( ·~ ' q; color matching has a measurable effect on inferred predation rates (Vignieri > ~ ~ 2. ~ ~ et al., in press). Differences between a dark mainland and pale beach moube -a Ll"' -I' c..; Cj c u "ci 8 c -.:=} c 5 8 bubspecies have be<'n attributed to three major genes (Steiner et al. 2007), ~ ~ km;:mb.-'lJ} .-'lFl{ll?. ,\'lcq and in one case, to a single amino acid mutation in the Melanocortin-1 recep tor (Mclr) gene, which affects ligand binding and receptor signaling that is : 4!fl.J,•• LI. . •
alleles generally dominant or recessive? Is evolutionary change limit d by mutation? To what extent is evolution constrained? How repeatablee· evolution-are the same or different genetic solutions responsible for sol~ Average Reported Estimated cost per ing similar ecological problems? J\nd, most recently, how do changes in or reported sequencing coverage consumables 40-fold regulation of prnteins during development produce phenotypic change? Year Technology Reference depth (fold) cost coverage Answers to these general questions will come only by studying many traits ------in myriad species. JHGSC 2004 SangPr 5 $300,000,000 While these exemplars are among our most complete stories, it has taken Levy et al. 2007 Sanger (Alli) 7 $10,000,000 $57,000,000 nearly a decade to make the connection between genes, phenotype, and Wheeler et al. 2008 Roche (454) 7 51,000,,000 $5,,700,000 environment for a single trait in a single species. Moreover, at least with the Bentley ct al. 2008 lllurnina 30 $250,000 $330,000 stickleback and mouse examples, these studies are not unbiased, as they rep Pushkorev et al. 2009 Helicos 28 $48,,000 $69,000 resent the best case scenario. In each case, there were a priori reasons to think Drrnanac el al. 2010 Nanoarrays 87 $8000 $3700 that trait variation impacts fitness, and these morphological traits were easy Drmanac et al. 2010 :\J"arnJdrrays 63 $:0500 $2200 to measure (and are influenced little, if at all, by the environment). Moreover, Drmanac ct al. 2010 .>Janoarrays 45 $1725 $1500 their genetic basis proved to be relatively simple-a few genes explain a large proportion of the phenotypic variation. How then can we be hopeful about making more progress in the future studying traits for which the functional the cost was estimated to be closer lo 5300 million (THGSC 2004). However, consequences are unclear, that are challenging to measure accurately, and as the rate of published complete genome sequences increased, the cost for which the genetic basis 1TI<1y be more complex? To do so, we face three decreased almost exponentially (Table 22.1 ). To underscore this point, on major challenges: (1) describe the genomic (and other -omic) variation within the first day of the Darwin 2009 Workshop that gave rise to thi;, volume, a and among species; (2) unravel how this genomic information is translated publication announced that three human genomes were sequenced at the into phenotypic information; and (3) understand how evolutionary forces cost of approximately $4400 (for consumables), with 45- to 87- fold cover drive differentiation (and ultimately fitness) in an ecological context, which age, identification of 3.2 to 4.5 million sequence variants per genome, and a 1 remains among the hardest tasks, even if (or perhap'> because) it is not cur 1-false-variant-per-100-kilobases accuracy (Drmanac et al. 2010) . The rapid rently possible to study using high-throughput technology. fall in sequencing prices is the genomic equivalent of Moore's Law, which describes the long-term trend in which the number of transistors that can be placed on computer chips doubles every 18 months, steadily driving The Rise of Genomics down the cost of computing power. Our ability to comprehensively describe genetic variation by sequencing Although this technology is largely driven by its applications to human complete genomes, the basic blueprint of an organism, represents an ex disease (i.e., personalized medical genomics), the newest technologies are traordinary technological ad\'ance that is remaking the field of biology. easily transferable to other species. At the time I write, the complete se The rate at which whole genome sequences are generated is astonishing. quence is known for about 2000 viruses, 600 bacterial species, and roughly Complete genome sequencing started only 30 years ago when the modest 200 eukaryotes including 60 chordate;,; these numbers will likely be dif 5368-base pair genome of bacteriophage fX174 was decoded (Sanger et al. ferent next week. As sequencing prices continue to foll, project proposals ii;!, -1977). Tt was quickly followed by several other, larger viral genomes. But, are becoming increasingly ambitious. For example, a recent proposal was "' it took almost another 20 years until the first complete genome sequence of put forth to sequence 10,000 vertebrate genomes in 5 years (Genome !OK Community of Scientists 2009). Arguably, all species2 have the potential to i,1 a free-living organism, Hae11wplti/11s infl11en211c (LS megabases), was finished because decoding a genome of this size required both technological and be genome-enabled, just as 20 ymrs ago it became routine to sequence the computational advances (Fleischmaim el al. 1995). mitochondrial cytochrome b gene in any eukaryote. Less than 6 years after this first complete genome sequence came the first complete human genome sequcnce---2.91 billion base pairs of euchromatic sequence (~5-fold coverage), with 2.1 million identified polymorphisms, 1 Published in Science Express on 5 November 2009. I at the reported cost of grpater than S10 million (International Human Ge 2 Genome sequencing of certain species undoubtedly will prove more challenging, nome Sequencing Consortium [IHGSCJ 2001; Venter et al. 2001) and when such as those with extraordinarily large repetitive genomes or high levels of finished (i.e., the fold-coverage was high enough to provide reliable data), heterozygosity and those that are recent or ancient polyploids. k. J 638 Chapter 22 Hoekstra Evolutionary Biology: The Next 150 Years 639
But with these nC'w data flowing in at an unprecedented pace, we need triplet nature of the genetic code. He later went on to establish Carnorhab tools and infrastructure in place to make them both accessible and usable ditis elcgans as a model system for the study of development, for which he First, the need for well-mainb1ined and long-term data repositories ha~ recC'ived a Nobel Prize. Whethf'r then it was blind enthusiasm, the naivete never been greater (Robinson et al., in press). Second, for a genome se of the time, or the shrewd promotion of genetics, that led him to say:" .. quence to be truly useful, it must be assembled and annotated, which is give me the complete DNA sequence of any organism, and Tcan reconstruct non-trivial. If, for example, the 1 OK Vertebrate Genome Project goes for it"3 is unclear (R. C. Lewontin, personal communication). At the time (i.e., ward and reaches its goal of completion in 5 years, the processing rate will the 1980s), this sentiment was shared by many-the genome was the key need to hold steady at five genomes per day (with no weekend or holiday that would unlock the secrets of biological complexity. lt has become abun breaks). ls this possible? Luckily, the field of bioinformatics-sometimes dantly clear, however, that this assertion was indeed naive; without the referred to as the symbiotic harmony of computer science and biology instruction manual, even with all the parts in hand, it is impossible (even is burgeoning. For example, Ensembl, a web-based community resource at present) to reconstn1ct the whole organism. that pro\·ides genome data and analysis tools for a comprehensive set of Historically, molecular research has focused on identifying the parts chordate genomes, just celebrated its 10th anniversary and continues to individual genes and proteins-and understanding their functions. While evolve (Flicek et al. 2010). Moreover, the assembly and annotation of com the reductioni'it program has been both successful and enlightening, to plete genomes likely will become more straightforward as more scaffold understand how whole organisms work, we need to consider the indi genomes (i.e., existing genome sequences that can be used as a reference vidual components both through developmental time (Carroll et al. 2001) to aid genome assembly of a new, closely related species) are available and and in the context of their interactions and as part of large networks (Noble computational algorithms become further automated. In fact, the first ge 2006). By analogy, knowing all the parts of an airplane lends little to our nome sequence based primarily on short-read, next-generation sequences, understanding of how the plane actually functions. This daunting task falls that of the giant panda, is purported to have been assembled in only 2 largely under the joint purview of developmental biology and systems bi days, suggesting tl1af the tools are already in place to assemble de nova a ology, which is the study of organisms as an integrated and interacting genome's wmth of small DNA fragments even when a reference genome is network of genes, proteins, and biochemical reactions (Sauer et al. 2007). unavailable (Li et al. 2010). l'hus, the availability of genome sequences and Systems biology is still in its infancy, but is gaining momrntum due to a their assembly is unlikely to be a limiting factor as we move forward. host of new technologies that are high throughput, quantitative, and large Will the era of genomics end? Not any time soon. Instead I predict that, at scale (Zhu and Snyder 2002). least in the near future, it will continue to expand and do so exponentially. At the moment, many of these new systems-level approaches are fo furthermore, just as genome sequencing is becoming faster and cheaper, cused at the cellular kvel or conducted in relatively simple mndel organ so too will the next level of -omics: epigenomics, trancriptomics, proteom isms. More recentlv, the evolution of metabolic networks has been inves ics, meta bolomics, and so forth. But, these inventories of genomic parts are tigated, that is, hov~ selection acts to optimize fitness across a landscape of limited in their utility without knowledge of the functional consequences networks (Pfeiffer et al. 2005), which may have implications for the early of variation at any of these molecular levels (and we must be open to novel, stages in the origin of life. Eventually, however, new technologies aimed at perhaps unexpected, ways in which DNA sequence can confer function). organisms that are more complex will be required, especially to automate For example, future studies geared at uncovering the function of noncod the characterization of expression patterns (e.g., high-throughput in situ ing or so-called junk Dl\JA, epigenetic modification (e.g., mcthylation and hybridizations) and the implementation of functional assays (e.g., RN Ai, chromatin remodeling), and spatio-temporal changes in RNA abundance viral vectors, transformations, transgenesis; Kitano 2002). While some tools on phenotype (and fitness) will undoubtedly open many windows into will necessarily be species- or clade-specific, the most useful advances un the evolutionary process. But, there is no doubt that evolutionary biology doubtedly will be those that are easily transferable across organisms. Thus, currently is and will continue to be transformed by our ability to sequence with new tools, we may acquire acccss to a fuller understanding of how the genome of virtually any organism. genes and genomes produce phenotypes through changes in develop ment, how historical processes have shaped that transformation, and how How to Build an Organism from Its Genomic Blueprint !
Sydney 8renner is a brilliant scientist, probably best known for his con 3 tribution to the then emerging field of molecular biology in the 1960s, in-· This is not an exact quote, but has been recounted by many, who were in attendance at Brenner's keynote address at the Cambridge University eluding his collaboration with Prancis Crick to experimentally reveal the Symposium (1982) on the occasion of the lOOth anniversary of Darwin's death. 640 Chapter 22 Hoekstra Evolutionary Biology: The Next 150 Years 641
constraints and opportunities may limit or promote future evolutiona biology's lexicon. Tirns, as a diversity of species with appropriate genetic, change (Schwenk et al. 2009). ry genomic, developmental, and fun,tional tools emerge, we will soon be able Thus, just as molt>cular biology has t>xpanded beyond a focus on sin to ask questions at a number of lfvels, from variation among individuals 1 genes or proteins, so too h
! 642 Chapter 22 Hoekstra Evolutionary Biology: The Next 150 Years 643
Yet, population genomic descriptions of nucleotide variation, while a evolution. Large-scale terrestrial environmental data may soon become tremendously exciting advance, represent a first step. Importantly, meth available through the National Ecological Observatory Network ('.\JEON; ods for the functional validation of candidate genes and mutations identi www.neoninc.org). While still in its infancy, NEON holds the promise of fied by genome-wide approaches are needed (see previous discussion), providing both environmental information for terrestrial biomes and a and to assign any adaptive function at all, one must be certain that fitness model for characterizing additional biomes. However, describing environ is carefully measured in nature and the selective agent is established (see mental variation through tin1c and space will not alone provide a compre the following section). hensive picture because organisms evolve in response to both abiotic and biotic factors, including those that pertain to each species individually (see Phenomics Davis et al., Commentary 6). Thus, we also want to know how individuals Compared to our knowledge of genomes, our knowledge of phenotypes arc interacting within an environment, especially with other species. remains cursory. Part of the explanation for this imbalance is certainly that While developing high-throughput ecological experiments is not phenotype space is vastly more expansive than genotype space (Houle 2010); straightforward, some initial steps are already being taken to monitor re in other words, genotypes arc more easily defined. However, fhe ability to motely the movcmcnts, survival, and reproduction of hundreds of both make the link betwee1~ genotype and phenotype rests, in part, on our capac plant and animal individuals . .\Jew miniaturized transmitters exist to re ity to measure phenotypes accurately and consistently. Ideally, we want to cord continuously the activity and performance of organisms in nature. For be able to measure objectively the same (homologous) trait in many individ example, the International Cooperation for Animal Research l:sing Space uals as well as many traits in a few individuals. Vv'hile our textbook example (ICARUS) initiative aims to establish a remote sensing platform that can of a phenotype is often height or weight, it can be useful to deconsh·uct these track even small animals globally, enabling observations and experiments complex phenotypes into more precise traits. At the extreme, functional ge over large spatial scales (Wikelski et al. 2007). future instrumcntiltion to nomic outputs (e.g., mRNA or protein expression levels) may serve as read measure not only movement, but also physiological state and whole-organ ily measured quantitative phenotypes (i.e., endo-phenotype) and also can ism performance and behavior, may capitalize on advances in microfluidics be used to assess genotype-phenotype associations. At the organismal level, (Whitesides 2006) and imaging (Bimber 2006), which already are proving high-throughput morphometrics (and accompanying databases) may be powerful in laboratory settings. Thus, organismal movement, physiology, another boon, as such approaches allow for the linking of macroevolution and performance may soon be tracked remotely and recorded ilUlomati level collections of fossils, microevolution-level dJta collected from nJtural cally in large databases. As with increasing amounts of -omic data, a major populations, and experimental-level altered morphologies of mutants. For challenge in generating such organismal and environmental data is Jn cf example, commercial facilities now specialize in phenomics and are well fective cyberinfrastructure. One model, the iPlant Collaborative (iPlant; equipped to do high-throughput screens for rare mutants (e.g., greenhouses www.iplantcollaborative.org) has been developed by plunl biologists. Done that can raise thousands of seedlings) or, alternatively, multi-phenotype right, such programs will cncourage communication among disciplines and screens for a mutant strain (e.g., hundreds of behavioral assays run on a the reuse of data models, file formats, application software, and algorithms, few mutant/transgenic animals). These high-throughput screens are revo while fostering cross-disciplinary exchange of ideas. lutioni.<:ing the scale at which geneticists and neurobiologists design and However, understanding changes in the environment and even the implement experiments (e.g., Tecott and Nestler 2004). While evolutionary movement and interactions of organisms within the environment is still biologists have yet to fully capitalize on these lurge-scJIE' upprmchcs, it is not quite enough. ln addition, we want to measure fitness, or at least com easy to imagine that such an approach can be adapted to address questions ponents of fitness, in nature. But how? Measuring fitness in the wild for about evolutionary diversification and constraint. large numbers of individuals through time represents one of the most im port;mt and largest challenges to evolutionary biologists. No matter how Fitness in the Wild advanced technology and tools become, it is difficult to imagine being able Measuring phenotypes in controlled laboratory environments has many to replace fieldwork and the study of natural history, both at a practical and advantages, but what we really want to know is how morphological, physi philosophical level. ological, and behavioral variation translates to fitness differences in the wild. As a first step, we would like to carefully characterize changes in the The Genotype-Phenotype Synthesis environment at both the micro- and macro- spatial and temporal scales. Long term ecological research (L TI:R) studies have been set up to study Darwin lived in a very opportune time, a time of exploration, wl1en new changes in ecologica I processes over time, yet these studies rarely integrate specimens were continuously arriving from around the world and new 644 Chapter 22 Hoekstra Evolutionary Biology: The Next 150 Years 645
geological data were being amassed. At present, evolutionary biologists and functionally verified. The taxonomic breath of such investigations is are arguably in a comparable position, as new 1~0.l~cular data are being also expanding, as is, most importantly, the complexity of traits that are generated at an ummagmable rate, and the poss1b1hty of gathering fine being dissected. As one example, the role of genetic constraint due to plciot scale environmental data is on the hori7on. However, the real question, of ropy and the importance of epistasis in adaptation are difficult to ascer course, is how will these data change the way we think about evol11tionary tain until we have enough data, both genetic and phenotypic, to test these biology, if at all? I focused previously on the technological advances that hypotheses in a statistically rigorous manner (see c;. Wagner, Chapter 8). make it possible to imagine (perhaps optimistically) that we will have an Thus, the lessons we have learned so far by studying a few simple traits in ever increasing ability to link changes in the genome to changes in phe a handful of species may not be fully representative of adaptive change in notype and/ or in the environment. In the following, I will focus on four general, and consequently, a comprehensive view of the adaptive process genera I areas (from among many), in which Darwin was clearly interested, is yet to emerge. but for which he could never have anticipated even our current depth of Therefore, I predict (and hope) that "gene hunting" studies do not end knowledge. These four areas also represent topics in which connecting simply with the identification of a gene, but rather continue on to deter genotype and phenotype may be especially illuminating in our quest to mine the consequences of mutations for gene function (Dean and Thornton h!1 more fully understand the evolutionary process. 2007), to understand how changes in gene function and regulation through '~ i The Mechanistic Basis of Adaptation development produce phenotypic change (Carroll et al. 2001), and most importantly, perhaps, to truly understand how genetic variation translates Darwin's magnum opus wa;, "one long argument" for the ultimate cause to fitness differences in the wild (Nielsen 2009; Linnen and Hoekstra, in of adaptive change, that is, natural selection. But, even Darwin was curious press). With this information in hand, we should be well positioned to not about the mechanistic basis of phenotypic change-how arc traits encoded only understand what happened in the past, but also start to make predic and passed on from one generation to the next? Perhaps, it was a propi tions about the genetic and phenotypic responses to known environmental tious augury then that Darwin's last publication arose from a collaboration change in the future. with a young British naturalist by the name of Waller Drawbridge Crick (Ridley 2004), the grandfather of Francis Crick, who would contribute to From Instinct to Neurobiology the discovery of the precise mechanism of inheritance, by deciphering the Darwin devoted an entire chapter of The Origin of Species to behavior. He three-dimensional structure of DNA. concludes that because "no one will dispute that instincts are of the highest Technological advances have had a fundamental impact on the way we importance to each animal" (p. 243) and that behaviors can be heritable, study adaptation. In T auder and Rose's 1996 book entitled Adaptation, only that they can evolve by natural selection in the same way as do morphologi a single chapter was devoted to molecular data, whereas a decade later cal characters. lndeed, while much research has focused on morphological we are ha rd pressed to find new advances in the study of phcnotypic ad adaptation, one classic view posits that change in animals' morphology is aptation without some molecular genetic contribution. Combinations of often preceded by that in behavior: "a shift into a new niche or adaptive genomic and transcriptomic approaches are being applied to variation in zone is, almost without exception, initiated by a change in behavior" (Mayr nature, and will allow us to address fundamental questions about the adap 1963: 604). An understanding of the ultimate causes of behavioral variation tive process, as previously discussed. Moreover, our increasing knowledge has been the subject of study first made popular by the classic ethologists of the genetics of adaptation in wild populations is, in turn, expanding our (e.g., Niko Tinbcrgcn), who were interested in understanding both the knowledge about natural selection (Schluter et al., in press). More specifi causes and consequences of behaviora I variation across many organisms in cally, genes contain information about the form, strength, timing, history, their natural environments (see Kokko and Jenn ions, Chapter 12). and (sometimes) the agent of natural selection (e.g., I'itzpatrick et al. 2007; However, despite its importance, we still know very little about the Barrett et al. 2008; Linnen et al. 2009). Thus, I would suggest that some of proximate evolutionary mechanisms that give rise to behavioral diversity the most enlightening future studies will combine studies of proximate found in nature. Thus, we remain largely ignorant of how behavior evolves (i.e., molecular and developmental mechanisms) and ultimate (i.e., selec and are left with many fundamental questions unanswered. For example: tive mechanism) causes of evolutionary change, as both approaches are What are the relative contributions of genetic and environmental effects (or mutually enlightening. learning) to behavioral differences? What are the genetic changes that un While some hard-earned progress has been made identifying a handful derlie the differences in behavior found both within and between species? of genes underlying adaptive variation, new genomic technologies and ap Do these genetic changes act early in development to alter neural circuitry, :1' I proaches arc increasing the rate at which such genes are being identified I or does the circuitry remain constant and changes in physiology (e.g., .i 11! _J j lilL 646 Chapter 22 Hoekstra Evolutionary Biology: The Next 150 Years 647
neurotransmitters) underlie behavioral variation? How do such changes behavior in one species will earn us some predictive power when studying happen at a mechanistic level? Are "behavior genes" specific to behavior? other species. How has the extraordinary complexity of l1uman culture evolvcd fro~ simpler behavior repertoires of our primate ancestors (see Richerson and Genomic Approaches to Studying The Origin of Species Boyd, Chapter 20)? The connections among genes, neural circuitry, and In the opening paragraph of The Origin of Species, Darwin suggests his tome Lhe evolution of complex and adaptive behaviors remain a major frontier will "throw some light on the origin of species-that mystery of mysteries, in biology. as it ha:; been called by one of our greatest philosophers" (Darwin 1859: 1). 111C study of behavior, unfortunately, shares many of the same obstacles Despite some modest progress in understanding how new species originate as the study of the genetic basis of morphological traits but also introduces (Coyne and Orr 2004; see Harrison, Chapter 13), surprises still abound, and a host of new ones. Many behaviors have low heritability, and some are thus, future work in speciation may demand considerable changes in our culturally inherited or have a learncd component. Behavior is particularly views, not just minor modifications (Orr et a 1. 2007). prone to environmental etfects; at the extreme, some behaviors require an How species originate remains one of the most fundamental questions environmental stimulus (Robinson ct al. 2008). Finally, many of the most in evolutionary biology and thus is likely to be a subject of much growth interesting behaviors (e.g., behaviors that seem to have a dear fitness con in the corning years. Perhaps the most exciting progress will be made by sequence in lhe wild) occur in non-model organisms, which have been the using genomic approaches to elucidate the processes and molecular basis focus of field-based behavioral ecologists (see Kokko and Jcnnions, Chapter underlying speciation. In particular, we would like to know: What are the 12). However, optimistically, some of these obstacles can be overcome by forces that drive species formation, and in particular, what is the role of an increase in experimental scale, automated phenotyping in controlled natural selection? How often can differentiation occur in the face of con environments, and the application of genomic technologies to non-model tinuous or intermittent gene Aow? What mechanisms of reproductive isola species. In addition, just as studies by developmcnta 1 systems biologists are tion are most important and which ones evolve first? What specific genes helping lo elucidate the link between genes and morphology, new large are involved in preventing gene flow between incipient species? And how sale and high-throughput approaches being adopted by neurobiologists do these patterns vary across organisms with different ecology, mating are setting the stage to link genes and behavior. systems, reproductive biology, and sex chromosomes? :\leurobiologists, too, have been bitten with the gcnomics bug and have Genomic approaches offer some new insights into these questions in recently spawned a field of study entitled neurogenomics, which is the two ways. First, technical advances are increasing the rate at which spe study of how the genome contributes to the evolution, development, struc cific mutations and genes responsible for reproductive isolation are being ture, and function of the nervous system (Boguski and Jones 2004). This identified. Second, genomic surveys of natural populations have allowed approach is already being adopted by those studying behavior in diverse researchers to investigate barriers to gene flow, genomic interactions, and species. Por example, the songbird neurogenornics initiative (SoNC) aims to the genetic permeability of species boundarie-; in the wild (Noor and Feder develop technical resources to study gene--brain-behavior relationships us 2006). While much of lhe progress involves increases in scale and speed, as ing song and songbirds as model systems. Already, transcriptorne surveys these approaches are extended to additional species, general patterns and and large-sea le neuroanatomical mapping of gene expression are underway, rules might emerge. In doing so, we arc no longer asking questions about and may define a new functional anatomy of the brain. Ncurogcnomicists whether specific types of genes and type;, of processes occur. but rather may, in fact, provide the bridge between reductionist (behavioral genetics) what their relative frequency and importance arc for speciation in general and holist (behavioral ecology) approaches lo the study of nervous system (Schluter 2009). evolution, analogous to developmental genornics in morphology. If we arc truly to understand how new species originate, two goals must While elucidating the mechanistic details of the behavioral evolution i:; be accomplished. First, the speciation process can be fully explained only if I( still in its infancy, Tpredict we will soon be able to draw a more complete we identify the heritable underpinnings of species formation and the forces picture of how many behaviors evolve, from the ultimate forces driving responsible for their origins. Thus, understanding genomic patterns of and behavioral evolution down to its molecular details. This prediction assumes specific genetic changes driving speciation likely will change the way we that with improving technologies, genes that underlie behavioral variation understand the fundamentals of diversification. Second, it is equally im will become increasingly easy to identify, and that behavioral evolution portant to recognize, that with the growing appreciation for the role of (like morphology) may rely on changes to a common genetic toolkit (i.e., a , selection in species formation, it is impossible to ignore the role of ecology "' nf g~~ 'hoccd by ,11,.,;m,1'), "' tlrnt genomic and ecological approaches will be the key to solving Darwin's "mystery of mysteries." (Note the genome sequencing wa;, completed in just two and a half months at a cost of about $500,000.) TI1e authors deduced that this individual was Molecular Fossils: Reconstructing Evolution's Path a male m<'mber of the Arctic Saqqaq, the first known culture to settle in Greenland. He likely had brown eyes, non-light skin, thick dark hair (al Evolutionary biology is in large part phylogt>netics (sec Hillis, Chapter 16), coalescent theory (see Wakeley A Note Chaptt>r S), genomics (sec Kolaczkowski and Kern, Chapter 6), and (4) th~ incorporation of new fields, such as genetics (see Zhang, Chapter 4) and The responses by the participants of the Darwin 2009 Workshop to my most rpcently, developmental biology (see Wray, Chapter 9). Such interdis presentation were surprisingly bimodal. Some said that my predictions ciplinary research efforts can reap large benefits (Wake 2008). For example, were too cautious-that we would "know it all" in 10 years, rather than paleontology and developmental genetics, two seemingly disparate fields 50 or 100. Others were far less optimistic, claiming that organisms were can illuminate each other-fossils may suggest developmental processe~ too complicated to dissect, and thus questioned if we would ever be able in basal forms, and developmental studies can aid in interpretation of the to know it all. Perhaps not surprisingly, the type of response was highly characters of extinct taxa, such as the gain of limbs of tetrapod ancestors associated with the scientists' field of study: geneticists (i.e., reductionists) (Shubin el al. 2009) or the loss of fins in a fish (Chan et al. 2010). Thus tended to be more optimistic, whereas organismal biologists (i.e., holists) integrative research that crosses traditional boundaries will undoubted!~ were generally more cautious. I look forward to looking back to see who, continue to push our understanding of evolutionary biology further. if either, was right. Because evolutionary biologists pride themselves on being hypothesis driven scientists, the practice of systematically collecting data, even before Acknowledgments knowing all of the precise ways it may be used, has often been frowned upon. However, it is important to recognize the countless evolutionary 1 wish to sincerely thank the organizers of the Darwin 2009 Workshop and studies that already take advantage of existing comparative data, including resulting volume, in particular Mike Bell, \A/alt Eanes, Doug Futuyma, and life history characters, physiological tolerances, behavior, habitat associa Jeff Levinton. Never before have I been given such a flattering, yet utterly tions, diet, geographic distribution, and morphologies (Futuyma 1998). In daunting, task. I also wish to thank the meeting participants for engaging 1' almost all cases, these data were collected by systematists or other biologists and stimulating discussions. Additional discussions with and comments without any anticipation of their future use in testing new hypotheses. This from Andrew Berry, David Hillis, and Jonathan Losos were critical to the descriptive natural history at the organismal level has been invaluable and development of many of the ideas presented here. 11 now is being replayed at the genomic level. In both cases, data repositories are built and can be used for purposes not yet envisioned. Thus, researchers Literature Cited pursuing hypothesis-driven versus discovery-driven approaches have (or soon may) come to sec each other as allies rather than antagonists (Boguski Abzhanov A., C. G. Extavour, A. Groover, and 4 others. 2008. Are we there yet7 and Jones 2004). At the very least, -omic data, when viewed in the context Tracking the development of new model systems. Trends Genet. 24: 353-360. of an appropriate evolutionary model for rigorous statistical testing, can be Barrett, R. D. H., S, M. Rogers, and lJ. Schluter. 2008. Natural selection on a major armor gene in threespine stickleback. Scie11cc 322: 255-257. extremely powerful. I I ow ever, large data sets will never replace imagina Llarrett, RD. B., S. M. Rogers, and D. Schluter. 2009. Environment specific pleiot tive hypotheses-the engines of scientific progress. ropy facilitates divergence at the Ectody.'plasin locus in threespine stickleback. What seems increasingly novel as we move forward is the scale at which Evolution 63: 2831-2837. we can ask questions. We are not likely to be limited by genomic data, and Bell, M. A. 2009. Implications of fossil threespine stickleback for Darwinian grad both large-scale phenotypic and environmental data acquisition are not far ualism./, Fish Biol. 75: 1997-1999. behind. We may expect that in 50 years major progress in understanding Bell, M. A., W. E. AgLLirrc, and N. ). Buck. 2004. 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