Multiple experimental evolution studies on D. melanogaster in the 1980s and 1990s indicated that enhanced competitive ability evolved primarily through increased larval tolerance to nitrogenous wastes and increased larval feeding and foraging rate, at the cost of efficiency of food conversion to biomass, and this became the widely accepted view of how adaptation to larval crowding evolves in fruitflies. We recently showed that populations of D. ananassae and D. n. nasuta subjected to extreme larval crowding evolved greater competitive ability without evolving higher feeding rates, primarily through a combination of reduced larval duration, faster attainment of minimum critical size for pupation, greater efficiency of food conversion to biomass, increased pupation height and, perhaps, greater urea/ammonia tolerance. This was a very different suite of traits than that seen to evolve under similar selection in D. melanogaster and was closer to the expectations from the theory of K-selection. At that time, we suggested two possible reasons for the differences in the phenotypic correlates of greater competitive ability seen in the studies with D. melanogaster and the other two species. First, that D. ananassae and D. n. nasuta had a very different genetic architecture of traits affecting competitive ability compared to the long-term, laboratory populations of D. melanogaster used in the earlier studies, either because the populations of the former two species were relatively recently wild-caught, or by virtue of being different species. Second, that the different evolutionary trajectories in D. ananassae and D. n. nasuta versus D. melanogaster were a reflection of differences in the manner in which larval crowding was imposed in the two sets of selection experiments. The D. melanogaster studies used a higher absolute density of eggs per unit volume of food, and a substantially larger total volume of food, than the studies on D. ananassae and D. n. nasuta. Here, we show that long-term laboratory populations of D. melanogaster, descended from some of the populations used in the earlier studies, evolve essentially the same set of traits as the D. ananassae and D. n. nasuta crowding-adapted populations when subjected to a similar larval density at low absolute volumes of food. As in the case of D. ananassae and D. n. nasuta, and in stark contrast to earlier studies with D. melanogaster, these crowding-adapted populations of D. melanogaster did not evolve greater larval feeding rates as a correlate of increased competitive ability. The present results clearly suggest that the suite of phenotypes through which the evolution of greater competitive ability is achieved in fruitflies depends critically not just on larval density per unit volume of food, but also on the total amount of food available in the culture vials. We discuss these results in the context of an hypothesis about how larval density and the height of the food column in culture vials might interact to alter the fitness costs and benefits of increased larval feeding rates, thus resulting in different routes to the evolution of greater competitive ability, depending on the details of exactly how the larval crowding was implemented.

Although single genes underlying several evolutionary adaptations have been identified, the genetic basis of complex, polygenic adaptations has been far more challenging to pinpoint. Here we report that the budding yeast Saccharomyces paradoxus has recently evolved resistance to citrinin, a naturally occurring mycotoxin. Applying a genome-wide test for selection on cis-regulation, we identified five genes involved in the citrinin response that are constitutively up-regulated in S. paradoxus. Four of these genes are necessary for resistance, and are also sufficient to increase the resistance of a sensitive strain when over-expressed. Moreover, cis-regulatory divergence in the promoters of these genes contributes to resistance, while exacting a cost in the absence of citrinin. Our results demonstrate how the subtle effects of individual regulatory elements can be combined, via natural selection, into a complex adaptation. Our approach can be applied to dissect the genetic basis of polygenic adaptations in a wide range of species.

The Heliconius butterflies are a widely studied adaptive radiation of 46 species spread across Central and South America, several of which are known to hybridise in the wild. Here, we present a substantially improved assembly of the Heliconius melpomene genome, developed using novel methods that should be applicable to improving other genome assemblies produced using short read sequencing. Firstly, we whole genome sequenced a pedigree to produce a linkage map incorporating 99% of the genome. Secondly, we incorporated haplotype scaffolds extensively to produce a more complete haploid version of the draft genome. Thirdly, we incorporated ~20x coverage of Pacific Biosciences sequencing and scaffolded the haploid genome using an assembly of this long read sequence. These improvements result in a genome of 795 scaffolds, 275 Mb in length, with an L50 of 2.1 Mb, an N50 of 34 and with 99% of the genome placed and 84% anchored on chromosomes. We use the new genome assembly to confirm that the Heliconius genome underwent 10 chromosome fusions since the split with its sister genus Eueides, over a period of about 6 million years.

Genetic studies of African-Americans identify functional variants, elucidate historical and genealogical mysteries, and reveal basic biology. However, African-Americans have been under-represented in genetic studies, and little is known about nation-wide patterns of genomic diversity in the population. Here, we present a comprehensive assessment of African-American genomic diversity using genotype data from nationally and regionally representative cohorts. We find higher African ancestry in southern United States compared to the North and West. We show that relatedness patterns track north- and west-bound routes followed during the Great Migration, suggesting that admixture occurred predominantly in the South prior to the Civil War and that ancestry-biased migration is responsible for regional differences in ancestry. Rare genetic traits among African-Americans can therefore be shared over long geographic distances along the Great Migration routes, yet their distribution over short distances remains highly structured. This study clarifies the role of re- cent demography in shaping African-American genomic diversity.

Many questions about human genetic history can be addressed by examining the patterns of shared genetic variation between sets of populations. A useful methodological framework for this purpose are F-statistics, that measure shared genetic drift between sets of two, three and four populations, and can be used to test simple and complex hypotheses about admixture between populations. Here, we put these statistics in context of phylogenetic and population genetic theory. We show how measures of genetic drift can be interpreted as branch lengths, paths through an admixture graph or in terms of the internal branches in coalescent trees. We show that the admixture tests can be interpreted as testing general properties of phylogenies, allowing us to generalize applications for arbitrary phylogenetic trees. Furthermore, we derive novel expressions for the F-statistics, which enables us to explore the behavior of F-statistic under population structure models. In particular, we show that population substructure may complicate inference.

Phenotypic plasticity is an evolutionary driving force in diverse biological processes, including the adaptive immune system, the development of neoplasms, and the bacterial acquisition of drug resistance. It is essential, therefore, to understand the evolutionary advantage of an allele that confers cells the ability to express a range of phenotypes. Of particular importance is to understand how this advantage of phenotypic plasticity depends on the degree of heritability of non-genetically encoded phenotypes between generations, which can induce irreversible evolutionary changes in the population. Here, we study the fate of a new mutation that allows the expression of multiple phenotypic states, introduced into a finite population otherwise composed of individuals who can express only a single phenotype. We analyze the fixation probability of such an allele as a function of the strength of inter-generational phenotypic heritability, called memory, the variance of expressible phenotypes, the rate of environmental changes, and the population size. We find that the fate of a phenotypically plastic allele depends fundamentally on the environmental regime. In a constant environment, the fixation probability of a plastic allele always increases with the degree of phenotypic memory. In periodically fluctuating environments, by contrast, there is an optimum phenotypic memory that maximizes the probability of the plastic allele’s fixation. This same optimum value of phenotypic memory also maximizes geometric mean fitness, in steady state. We interpret these results in the context of previous studies in an infinite-population framework. We also discuss the implications of our results for the design of therapies that can overcome resistance, in a variety of diseases.

Expression quantitative trait locus (eQTL) analysis relates genetic variation to gene expression, and it has been shown that power to detect eQTLs is substantially increased by adjustment for measures of expression variability derived from singular value decomposition-based procedures (referred to as expression factors, or EFs). A potential downside to this approach is that power will be reduced for eQTL that are correlated with one or more EFs, but these approaches are commonly used in human eQTL studies on the assumption that this risk is low for cis (i.e. local) eQTL associations. Using two independent blood eQTL datasets, we show that this assumption is incorrect and that, in fact, 10-25% of eQTL that are significant without adjustment for EFs are no longer detected after EF adjustment. In addition, the majority of these lost eQTLs replicate in independent data, indicating that they are not spurious associations. Thus, in the ideal case, EFs would be re-estimated for each eQTL association test, as has been suggested by others; however, this is computationally infeasible for large datasets with densely imputed genotype data. We propose an alternative, buffet-style approach in which a series of EF and non-EF eQTL analyses are performed and significant eQTL discoveries are collected across these analyses. We demonstrate that standard methods to control the false discovery rate perform similarly between the single EF and buffet-style approaches, and we provide biological support for eQTL discovered by this approach in terms of immune cell-type specific enhancer enrichment in Roadmap Epigenomics and ENCODE cell lines.

Massively parallel sequencing has revolutionized many areas of biology but sequencing large amounts of DNA in many individuals is cost-prohibitive and unnecessary for many studies. Genomic complexity reduction techniques such as sequence capture and restriction enzyme-based methods enable the analysis of many more individuals per unit cost. Despite their utility, current complexity reduction methods have limitations, especially when large numbers of individuals are analyzed. Here we develop a much improved restriction site associated DNA (RAD) sequencing protocol and a new combinatorial method called Rapture (RAD capture). The new RAD protocol improves versatility by separating RAD tag isolation and sequencing library preparation into two distinct steps. This protocol also recovers more unique (non-clonal) RAD fragments and produces better data for both standard RAD and Rapture analysis. Rapture then uses an in-solution capture of chosen RAD tags to target sequencing reads to desired loci. Rapture combines the benefits of both RAD and sequence capture, i.e. very inexpensive and rapid library preparation for many individuals as well as high specificity in the number and location of genomic loci analyzed. Our results demonstrate that Rapture is a rapid and flexible technology capable of analyzing a very large number of individuals with minimal sequencing and library preparation cost. The methods presented here should improve the efficiency of genetic analysis for many aspects of agricultural, environmental, and medical science.

Leishmania, a genus of parasites transmitted to human hosts and mammalian/reptilian reservoirs by an insect vector, is the causative agent of the human disease complex leishmaniasis. The evolutionary relationships within the genus Leishmania and its origins are the source of ongoing debate, reflected in conflicting phylogenetic and biogeographic reconstructions. This study employs a recently described bioinformatics method, SISRS, to identify over 200,000 informative sites across the genome from newly sequenced and publicly available Leishmania data. This dataset is used to reconstruct the evolutionary relationships of this genus. Additionally, we constructed a large multi-gene dataset; we used this dataset to reconstruct the phylogeny and estimate divergence dates for species. We conclude that the genus Leishmania evolved at least 90-100 million years ago. Our results support the hypothesis that Leishmania clades separated prior to, and during, the breakup of Gondwana. Additionally, we confirm that reptile-infecting Leishmania are derived from mammalian forms, and that the species that infect porcupines and sloths form a clade long separated from other species. We also firmly place the guinea-pig infecting species, L. enrietti, the globally dispersed L. siamensis, and the newly identified Australia species from kangaroos as sibling species whose distribution arises from the ancient connection between Australia, Antarctica, and South America.