Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

Advances in next generation technologies have driven the costs of DNA sequencing down to the point that genotyping-by-sequencing (GBS) is now feasible for high diversity, large genome species. Here, we report a procedure for constructing GBS libraries based on reducing genome complexity with restriction enzymes (REs). This approach is simple, quick, extremely specific, highly reproducible, and may reach important regions of the genome that are inaccessible to sequence capture approaches. By using methylation-sensitive REs, repetitive regions of genomes can be avoided and lower copy regions targeted with two to three fold higher efficiency. This tremendously simplifies computationally challenging alignment problems in species with high levels of genetic diversity. The GBS procedure is demonstrated with maize (IBM) and barley (Oregon Wolfe Barley) recombinant inbred populations where roughly 200,000 and 25,000 sequence tags were mapped, respectively. An advantage in species like barley that lack a complete genome sequence is that a reference map need only be developed around the restriction sites, and this can be done in the process of sample genotyping. In such cases, the consensus of the read clusters across the sequence tagged sites becomes the reference. Alternatively, for kinship analyses in the absence of a reference genome, the sequence tags can simply be treated as dominant markers. Future application of GBS to breeding, conservation, and global species and population surveys may allow plant breeders to conduct genomic selection on a novel germplasm or species without first having to develop any prior molecular tools, or conservation biologists to determine population structure without prior knowledge of the genome or diversity in the species.

/pdf/a-robust-simple-genotyping-by-sequencing-gbs-approach-for-2orahkct9n.pdf

A Robust, Simple Genotyping-by-Sequencing (GBS) Approach for High Diversity Species

Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.

/pdf/evolution-of-genes-and-genomes-on-the-drosophila-phylogeny-or4qd372xr.pdf

Evolution of genes and genomes on the Drosophila phylogeny.

Detecting selective sweeps from genomic SNP data is complicated by the intricate ascertainment schemes used to discover SNPs, and by the confounding influence of the underlying complex demographics and varying mutation and recombination rates. Current methods for detecting selective sweeps have little or no robustness to the demographic assumptions and varying recombination rates, and provide no method for correcting for ascertainment biases. Here, we present several new tests aimed at detecting selective sweeps from genomic SNP data. Using extensive simulations, we show that a new parametric test, based on composite likelihood, has a high power to detect selective sweeps and is surprisingly robust to assumptions regarding recombination rates and demography (i.e., has low Type I error). Our new test also provides estimates of the location of the selective sweep(s) and the magnitude of the selection coefficient. To illustrate the method, we apply our approach to data from the Seattle SNP project and to Chromosome 2 data from the HapMap project. In Chromosome 2, the most extreme signal is found in the lactase gene, which previously has been shown to be undergoing positive selection. Evidence for selective sweeps is also found in many other regions, including genes known to be associated with disease risk such as DPP10 and COL4A3.

/pdf/genomic-scans-for-selective-sweeps-using-snp-data-4hi65gete4.pdf

Genomic scans for selective sweeps using SNP data

Natural selection, which can be defined as the differential contribution of genetic variants to future generations (Aquadro et al. 2001), is the driving force of Darwinian evolution. Despite intense research, only a relatively small number of regions and genes have been directly implicated as targets of selection in the human genome (Kitano and Saitou 1999; Rana et al. 1999; Huttley et al. 2000; Hollox et al. 2001; Hull et al. 2001; Hurst and Pal 2001; Koda et al. 2001; Sullivan et al. 2001; Tishkoff et al. 2001; Baum et al. 2002; Fullerton et al. 2002; Gilad et al. 2002; Hamblin et al. 2002). A more comprehensive and genomic understanding of how and where natural selection has shaped patterns of genetic variation may provide important insights into the mechanisms of evolutionary change (Otto 2000), guide selection of loci for inclusion in population genetic studies (Vitalis et al. 2001), facilitate the annotation of functionally significant genomic regions (Nielsen 2001), and help elucidate genotype-phenotype correlations in complex diseases (Przeworski et al. 2000; Nielsen 2001).

Detecting unambiguous evidence for natural selection remains challenging because the effect of selection on the distribution of genetic variation can be mimicked by population demographic history (i.e., the size, structure, and mating pattern of a population). For instance, both adaptive hitchhiking and population expansion can cause an excess of rare variants observed in DNA sequence data compared with what is expected under a standard neutral model (Tajima 1989; Przeworski et al. 2000). Despite these difficulties, the recent deluge of publicly available single nucleotide polymorphisms (SNPs) provides an exciting opportunity to identify genome-wide signatures of selection (Sunyaev et al. 2000; Fay et al. 2001; Sachidanandam et al. 2001).

To this end, examining the variation in SNP allele frequencies between populations, which can be quantified by the statistic FST, is a promising strategy for detecting signatures of natural selection (Lewontin and Krakauer 1973; Rana et al. 1999; Hollox et al. 2001; Fullerton et al. 2002; Gilad et al. 2002; Hamblin et al. 2002). Under selective neutrality, FST is determined by genetic drift, which will affect all loci across the genome in a similar and predictable fashion. On the other hand, natural selection is a locus-specific force that can cause systematic deviations in FST values for a selected gene and nearby genetic markers. For example, geographically restricted directional selection may lead to an increase in FST of a selected locus, whereas balancing or species-wide directional selection may lead to a decrease in FST compared with neutrally evolving loci (Cavalli-Sforza 1966; Bowcock et al. 1991; Andolfatto 2001). Previous studies that have attempted to identify natural selection based on patterns of population differentiation relied on simulations to obtain the expected distribution of FST under selective neutrality (Lewontin and Krakauer 1973; Bowcock et al. 1991; Beaumont and Nichols 1996). However, the simulated distribution of FST strongly depends on the assumed population demographic history, which is rarely known with any degree of certainty.

As an expanding number of SNPs are genotyped across multiple populations, a complimentary approach that does not require tenuous assumptions about population demographic history is now becoming feasible. Specifically, by sampling a large number of SNPs throughout the genome, loci that have been affected by natural selection can simply be identified as outliers in the extreme tails of the empirical distribution of FST (Cavalli-Sforza 1966; Black et al. 2001; Goldstein and Chikhi 2002). Recently, this strategy has been used to infer natural selection in the CAPN10 gene; however, the empirical distribution of FST contained <100 loci (Fullerton et al. 2002).

In this work, we describe an analysis of 26,530 SNPs with allele frequencies that were determined in three populations: African-American, East Asian, and European-American. The density of this SNP allele frequency map provides a unique and powerful opportunity to interrogate the genome for signatures of natural selection. Through a variety of analyses, we have found statistically significant evidence supporting the hypothesis that selection has influenced extant patterns of human genetic variation. Furthermore, we have identified 174 candidate genes that demonstrate signatures of selection when contrasted to the empirical genome-wide distribution of FST. This analysis provides the conceptual foundation for constructing a high-resolution natural selection map, which will be an important resource in understanding the recent evolutionary history of our species, and will facilitate detailed studies on the identified candidate genes.

/pdf/interrogating-a-high-density-snp-map-for-signatures-of-1qh39pe50i.pdf

Interrogating a High-Density SNP Map for Signatures of Natural Selection

In 2002 Kim and Stephan proposed a promising composite-likelihood method for localizing and estimating the fitness advantage of a recently fixed beneficial mutation. Here, we demonstrate that their composite-likelihood-ratio (CLR) test comparing selective and neutral hypotheses is not robust to undetected population structure or a recent bottleneck, with some parameter combinations resulting in a false positive rate of nearly 90%. We also propose a goodness-of-fit test for discriminating rejections due to directional selection (true positive) from those due to population and demographic forces (false positives) and demonstrate that the new method has high sensitivity to differentiate the two classes of rejections.

https://www.genetics.org/content/genetics/170/3/1401.full.pdf

Distinguishing Between Selective Sweeps and Demography Using DNA Polymorphism Data

We present a likelihood method for estimating codon usage bias parameters along the lineages of a phylogeny. The method is an extension of the classical codon-based models used for estimating d N /d S ratios along the lineages of a phylogeny. However, we add one extra parameter for each lineage: the selection coefficient for optimal codon usage (S), allowing joint maximum likelihood estimation of S and the d N /d S ratio. We apply the method to previously published data from Drosophila melanogaster, Drosophila simulans, and Drosophila yakuba and show, in accordance with previous results, that the D. melanogaster lineage has experienced a reduction in the selection for optimal codon usage. However, the D. melanogaster lineage has also experienced a change in the biological mutation rates relative to D. simulans, in particular, a relative reduction in the mutation rate from A to G and an increase in the mutation rate from C to T. However, neither a reduction in the strength of selection nor a change in the mutational pattern can alone explain all of the data observed in the D. melanogaster lineage. For example, we also confirm previous results showing that the Notch locus has experienced positive selection for previously classified unpreferred mutations.

/pdf/maximum-likelihood-estimation-of-ancestral-codon-usage-bias-217p9xp778.pdf

Maximum likelihood estimation of ancestral codon usage bias parameters in Drosophila.

Genome-wide variation in the human and fruitfly: a comparison

Natural selection favors efficient expression of encoded proteins, but the causes, mechanisms, and fitness consequences of evolved coding changes remain an area of aggressive inquiry. We report a large-scale reversal in the relative translational accuracy of codons across 12 fly species in the Drosophila/Sophophora genus. Because the reversal involves pairs of codons that are read by the same genomically encoded tRNAs, we hypothesize, and show by direct measurement, that a tRNA anticodon modification from guanosine to queuosine has coevolved with these genomic changes. Queuosine modification is present in most organisms but its function remains unclear. Modification levels vary across developmental stages in D. melanogaster, and, consistent with a causal effect, genes maximally expressed at each stage display selection for codons that are most accurate given stage-specific queuosine modification levels. In a kinetic model, the known increased affinity of queuosine-modified tRNA for ribosomes increases the accuracy of cognate codons while reducing the accuracy of near-cognate codons. Levels of queuosine modification in D. melanogaster reflect bioavailability of the precursor queuine, which eukaryotes scavenge from the tRNAs of bacteria and absorb in the gut. These results reveal a strikingly direct mechanism by which recoding of entire genomes results from changes in utilization of a nutrient.

/pdf/a-nutrient-driven-trna-modification-alters-translational-4wcczemg6u.pdf

A Nutrient-Driven tRNA Modification Alters Translational Fidelity and Genome-wide Protein Coding across an Animal Genus

That natural selection affects molecular evolution at synonymous sites in protein-coding sequences is well established and is thought to predominantly reflect selection for translational efficiency/accuracy mediated through codon bias. However, a recently developed maximum likelihood framework, when applied to 18 coding sequences in 3 species of Drosophila, confirmed an earlier report that the Notch gene in Drosophila melanogaster was evolving under selection in favor of those codons defined as unpreferred in this species. This finding opened the possibility that synonymous sites may be subject to a variety of selective pressures beyond weak selection for increased frequencies of the codons currently defined as "preferred" in D. melanogaster. To further explore patterns of synonymous site evolution in Drosophila in a lineage-specific manner, we expanded the application of the maximum likelihood framework to 8,452 protein coding sequences with well-defined orthology in D. melanogaster, Drosophila sechellia, and Drosophila yakuba. Our analyses reveal intragenomic and interspecific variation in mutational patterns as well as in patterns and intensity of selection on synonymous sites. In D. melanogaster, our results provide little statistical evidence for recent selection on synonymous sites, and Notch remains an outlier. In contrast, in D. sechellia our findings provide evidence in support of selection predominantly in favor of preferred codons. However, there is a small subset of genes in this species that appear to be evolving under selection in favor of unpreferred codons, which indicates that selection on synonymous sites is not limited to the preferential fixation of mutations that enhance the speed or accuracy of translation in this species.

Vanessa L. Bauer DuMont

Papers

Distinguishing Between Selective Sweeps and Demography Using DNA Polymorphism Data

Maximum likelihood estimation of ancestral codon usage bias parameters in Drosophila.

Genome-wide variation in the human and fruitfly: a comparison

A Nutrient-Driven tRNA Modification Alters Translational Fidelity and Genome-wide Protein Coding across an Animal Genus

Patterns of Mutation and Selection at Synonymous Sites in Drosophila