Jeffrey D. Jensen

A draft sequence of the Neandertal genome.

Kissing Cousins Neandertals, our closest relatives, ranged across Europe and Southwest Asia before their extinction approximately 30,000 years ago. Green et al. (p. 710) report a draft sequence of the Neandertal genome, created from three individuals, and compare it with genomes of five modern humans. The results suggest that ancient genomes of human relatives can be recovered with acceptably low contamination from modern human DNA. Because ancient DNA can be contaminated with microbial DNA, Burbano et al. (p. 723) developed a target sequence capture approach to obtain 14 kilobases of Neandertal DNA from a fairly poorly preserved sample with a high microbial load. A number of genomic regions and genes were revealed as candidates for positive selection early in modern human history. The genomic data suggest that Neandertals mixed with modern human ancestors some 120,000 years ago, leaving traces of Neandertal DNA in contemporary humans. Gene flow has occurred from Neandertals to humans of Eurasian descent, but not to Africans. Neandertals, the closest evolutionary relatives of present-day humans, lived in large parts of Europe and western Asia before disappearing 30,000 years ago. We present a draft sequence of the Neandertal genome composed of more than 4 billion nucleotides from three individuals. Comparisons of the Neandertal genome to the genomes of five present-day humans from different parts of the world identify a number of genomic regions that may have been affected by positive selection in ancestral modern humans, including genes involved in metabolism and in cognitive and skeletal development. We show that Neandertals shared more genetic variants with present-day humans in Eurasia than with present-day humans in sub-Saharan Africa, suggesting that gene flow from Neandertals into the ancestors of non-Africans occurred before the divergence of Eurasian groups from each other.

Resequencing 50 accessions of cultivated and wild rice yields markers for identifying agronomically important genes.

Rice is a staple crop that has undergone substantial phenotypic and physiological changes during domestication. Here we resequenced the genomes of 40 cultivated accessions selected from the major groups of rice and 10 accessions of their wild progenitors (Oryza rufipogon and Oryza nivara) to >15 × raw data coverage. We investigated genome-wide variation patterns in rice and obtained 6.5 million high-quality single nucleotide polymorphisms (SNPs) after excluding sites with missing data in any accession. Using these population SNP data, we identified thousands of genes with significantly lower diversity in cultivated but not wild rice, which represent candidate regions selected during domestication. Some of these variants are associated with important biological features, whereas others have yet to be functionally characterized. The molecular markers we have identified should be valuable for breeding and for identifying agronomically important genes in rice.

Complete Resequencing of 40 Genomes Reveals Domestication Events and Genes in Silkworm (Bombyx)

The Taming of the Silkworm Silkworms, Bombyx mori, represent one of the few domesticated insects, having been domesticated over 10,000 years ago. Xia et al. (p. 433, published online 27 August) sequenced 29 domestic and 11 wild silkworm lines and identified genes that were most likely to be selected during domestication. These genes represent those that enhance silk production, reproduction, and growth. Furthermore, silkworms were probably only domesticated once from a large progenitor population, rather than on multiple occasions, as has been observed for other domesticated animals. Silkworm genomes show signatures of selection associated with domestication. A single–base pair resolution silkworm genetic variation map was constructed from 40 domesticated and wild silkworms, each sequenced to approximately threefold coverage, representing 99.88% of the genome. We identified ~16 million single-nucleotide polymorphisms, many indels, and structural variations. We find that the domesticated silkworms are clearly genetically differentiated from the wild ones, but they have maintained large levels of genetic variability, suggesting a short domestication event involving a large number of individuals. We also identified signals of selection at 354 candidate genes that may have been important during domestication, some of which have enriched expression in the silk gland, midgut, and testis. These data add to our understanding of the domestication processes and may have applications in devising pest control strategies and advancing the use of silkworms as efficient bioreactors.

Population genetic inference from genomic sequence variation

Population genetics has evolved from a theory-driven field with little empirical data into a data-driven discipline in which genome-scale data sets test the limits of available models and computational analysis methods. In humans and a few model organisms, analyses of whole-genome sequence polymorphism data are currently under way. And in light of the falling costs of next-generation sequencing technologies, such studies will soon become common in many other organisms as well. Here, we assess the challenges to analyzing whole-genome sequence polymorphism data, and we discuss the potential of these data to yield new insights concerning population history and the genomic prevalence of natural selection.

On the Origin and Spread of an Adaptive Allele in Deer Mice

Adapting Coat Color Simple phenotypic changes can often be the target of selection—for example, variations in coat color that provide protection against detection by predators. Linnen et al. (p. 1095) explore the underlying molecular mechanisms behind the production of pale deer mice living on the light-colored Nebraska Sand Hills. The mice that live on the sand are significantly lighter in color than conspecifics living nearby on darker soils. This lighter color was found to be due to de novo changes at the Agouti coat color locus. Thus, rapid adaptive change does not always rely on preexisting genetic variation. The light coat-color variant in deer mice is a mutation selected for its adaptive value for living in sand hills. Adaptation is a central focus of biology, although it can be difficult to identify both the strength and agent of selection and the underlying molecular mechanisms causing change. We studied cryptically colored deer mice living on the Nebraska Sand Hills and show that their light coloration stems from a novel banding pattern on individual hairs produced by an increase in Agouti expression caused by a cis-acting mutation (or mutations), which either is or is closely linked to a single amino acid deletion in Agouti that appears to be under selection. Furthermore, our data suggest that this derived Agouti allele arose de novo after the formation of the Sand Hills. These findings reveal one means by which genetic, developmental, and evolutionary mechanisms can drive rapid adaptation under ecological pressure.

Adaptive Evolution of Multiple Traits Through Multiple Mutations at a Single Gene

Additive Effects Although specific genes involved in animal coloration have been identified, the underlying selection for genetic variation in color-specific adaptation is not well understood. Examining the Agouti gene and other loci in the deer mice of Nebraska, where predation selects for light-colored mice in light environments and dark-colored mice in dark environments, Linnen et al. (p. 1312) find evidence of multiple genetic variants under selection affecting coloration. The light color of Sand Hills mice is not the result of a single large-effect mutation, but is because of many accumulated mutations, each with a smaller phenotypic effect. The light color of mice living in the Nebraska Sand Hills is not the result of a single large-effect mutation. The identification of precise mutations is required for a complete understanding of the underlying molecular and evolutionary mechanisms driving adaptive phenotypic change. Using plasticine models in the field, we show that the light coat color of deer mice that recently colonized the light-colored soil of the Nebraska Sand Hills provides a strong selective advantage against visually hunting predators. Color variation in an admixed population suggests that this light Sand Hills phenotype is composed of multiple traits. We identified distinct regions within the Agouti locus associated with each color trait and found that only haplotypes associated with light trait values have evidence of selection. Thus, local adaptation is the result of independent selection on many mutations within a single locus, each with a specific effect on an adaptive phenotype, thereby minimizing pleiotropic consequences.

Experimental illumination of a fitness landscape

The genes of all organisms have been shaped by selective pressures. The relationship between gene sequence and fitness has tremendous implications for understanding both evolutionary processes and functional constraints on the encoded proteins. Here, we have exploited deep sequencing technology to experimentally determine the fitness of all possible individual point mutants under controlled conditions for a nine-amino acid region of Hsp90. Over the past five decades, limited glimpses into the relationship between gene sequence and function have sparked a long debate regarding the distribution, relative proportion, and evolutionary significance of deleterious, neutral, and advantageous mutations. Our systematic experimental measurement of fitness effects of Hsp90 mutants in yeast, evaluated in the light of existing population genetic theory, are remarkably consistent with a nearly neutral model of molecular evolution.

Controlling the false-positive rate in multilocus genome scans for selection

Rapid typing of genetic variation at many regions of the genome is an efficient way to survey variability in natural populations in an effort to identify segments of the genome that have experienced recent natural selection. Following such a genome scan, individual regions may be chosen for further sequencing and a more detailed analysis of patterns of variability, often to perform a parametric test for selection and to estimate the strength of a recent selective sweep. We show here that not accounting for the ascertainment of loci in such analyses leads to false inference of natural selection when the true model is selective neutrality, because the procedure of choosing unusual loci (in comparison to the rest of the genome-scan data) selects regions of the genome with genealogies similar to those expected under models of recent directional selection. We describe a simple and efficient correction for this ascertainment bias, which restores the false-positive rate to near-nominal levels. For the parameters considered here, we find that obtaining a test with the expected distribution of P-values depends on accurately accounting both for ascertainment of regions and for demography. Finally, we use simulations to explore the utility of relying on outlier loci to detect recent selective sweeps. We find that measures of diversity and of population differentiation are more effective than summaries of the site-frequency spectrum and that sequencing larger regions (2.5 kbp) in genome-scan studies leads to more power to detect recent selective sweeps.

Progress and prospects in mapping recent selection in the genome

One of the central goals of evolutionary biology is to understand the genetic basis of adaptive evolution. The availability of nearly complete genome sequences from a variety of organisms has facilitated the collection of data on naturally occurring genetic variation on the scale of hundreds of loci to whole genomes. Such data have changed the focus of molecular population genetics from making inferences about adaptive evolution at single loci to identifying which loci, out of hundreds to thousands, have been recent targets of natural selection. A major challenge in this effort is distinguishing the effects of selection from those of the demographic history of populations. Here we review some current progress and remaining challenges in the field.

Searching for footprints of positive selection in whole-genome SNP data from nonequilibrium populations

A major goal of population genomics is to reconstruct the history of natural populations and to infer the neutral and selective scenarios that can explain the present-day polymorphism patterns. However, the separation between neutral and selective hypotheses has proven hard, mainly because both may predict similar patterns in the genome. This study focuses on the development of methods that can be used to distinguish neutral from selective hypotheses in equilibrium and nonequilibrium populations. These methods utilize a combination of statistics on the basis of the site frequency spectrum (SFS) and linkage disequilibrium (LD). We investigate the patterns of genetic variation along recombining chromosomes using a multitude of comparisons between neutral and selective hypotheses, such as selection or neutrality in equilibrium and nonequilibrium populations and recurrent selection models. We perform hypothesis testing using the classical P-value approach, but we also introduce methods from the machine-learning field. We demonstrate that the combination of SFS- and LD-based statistics increases the power to detect recent positive selection in populations that have experienced past demographic changes.