Deleterious amino acid polymorphisms in Arabidopsis thaliana and rice

Patterns of the Predicted Mutation Burden in 19,778 Domesticated Barley Accessions Conserved Ex Situ

Long-term conservation of more than 7 million plant germplasm accessions in 1750 genebanks worldwide is a challenging mission. The extent of deleterious mutations present in conserved germplasm and the genetic risk associated with accumulative mutations are largely unknown. This study took advantage of published barley genomic data to predict sample-wise mutation burdens for 19,778 domesticated barley (Hordeum vulgare L.) accessions conserved ex situ. It was found that the conserved germplasm harbored 407 deleterious mutations and 337 (or 82%) identified deleterious alleles were present in 20 (or 0.1%) or fewer barley accessions. Analysis of the predicted mutation burdens revealed significant differences in mutation burden for several groups of barley germplasm (landrace > cultivar (or higher burden estimate in landrace than in cultivar); winter barley > spring barley; six-rowed barley > two-rowed barley; and 1000-accession core collection > non-core germplasm). Significant differences in burden estimate were also found among seven major geographical regions. The sample-wise predicted mutation burdens were positively correlated with the estimates of sample average pairwise genetic difference. These findings are significant for barley germplasm management and utilization and for a better understanding of the genetic risk in conserved plant germplasm.

Deleterious and Adaptive Mutations in Plant Germplasm Conserved Ex Situ

Conserving more than 7 million plant germplasm accessions in 1,750 genebanks worldwide raises the hope of securing the food supply for humanity for future generations. However, there is a genetic cost for such long-term germplasm conservation, which has been largely unaccounted for before. We investigated the extent and variation of deleterious and adaptive mutations in 490 individual plants representing barley, wheat, oat, soybean, maize, rapa, and sunflower collections in a seed genebank using RNA-Seq technology. These collections were found to have a range of deleterious mutations detected from 125 (maize) to 83,695 (oat) with a mean of 13,537 and of the averaged sample-wise mutation burden per deleterious locus from 0.069 to 0.357 with a mean of 0.200. Soybean and sunflower collections showed that accessions acquired earlier had increased mutation burdens. The germplasm with more years of storage in several collections carried more deleterious and fewer adaptive mutations. The samples with more cycles of germplasm regeneration revealed fewer deleterious and more adaptive mutations. These findings are significant for understanding mutational dynamics and genetic cost in conserved germplasm and have implications for long-term germplasm management and conservation.

Evolutionary dynamics and adaptive benefits of deleterious mutations in crop gene pools

Mutations with deleterious consequences in nature may be conditionally deleterious in crop plants. That is, while some genetic variants may reduce fitness under wild conditions and be subject to purifying selection, they can be under positive selection in domesticates. Such deleterious alleles can be plant breeding targets, particularly for complex traits. The difficulty of distinguishing favorable from unfavorable variants reduces the power of selection, while favorable trait variation and heterosis may be attributable to deleterious alleles. Here, we review the roles of deleterious mutations in crop breeding and discuss how they can be used as a new avenue for crop improvement with emerging genomic tools, including HapMaps and pangenome analysis, aiding the identification, removal, or exploitation of deleterious mutations.

PPVED: A machine learning tool for predicting the effect of single amino acid substitution on protein function in plants

Single amino acid substitution (SAAS) produces the most common variant of protein function change under physiological conditions. As the number of SAAS events in plants has increased exponentially, an effective prediction tool is required to help identify and distinguish functional SAASs from the whole genome as either potentially causal traits or as variants. Here, we constructed a plant SAAS database that stores 12 865 SAASs in 6172 proteins and developed a tool called Plant Protein Variation Effect Detector (PPVED) that predicts the effect of SAASs on protein function in plants. PPVED achieved an 87% predictive accuracy when applied to plant SAASs, an accuracy that was much higher than those from six human database software: SIFT, PROVEAN, PANTHER-PSEP, PhD-SNP, PolyPhen-2, and MutPred2. The predictive effect of six SAASs from three proteins in Arabidopsis and maize was validated with wet lab experiments, of which five substitution sites were accurately predicted. PPVED could facilitate the identification and characterization of genetic variants that explain observed phenotype variations in plants, contributing to solutions for challenges in functional genomics and systems biology. PPVED can be accessed under a CC-BY (4.0) license via http://www.ppved.org.cn.

Non-CG DNA methylation-deficiency mutations enhance mutagenesis rates during salt adaptation in cultured Arabidopsis cells

Much has been learned about how plants acclimate to stressful environments, but the molecular basis of stress adaptation and the potential involvement of epigenetic regulation remain poorly understood. Here, we examined if salt stress induces mutagenesis in suspension cultured plant cells and if DNA methylation affects the mutagenesis using whole genome resequencing analysis. We generated suspension cell cultures from two Arabidopsis DNA methylation-deficient mutants and wild-type plants, and subjected the cultured cells to stepwise increases in salt stress intensity over 40 culture cycles. We show that ddc (drm1 drm2 cmt3) mutant cells can adapt to grow in 175 mM NaCl-containing growth medium and exhibit higher adaptability compared to wild type Col-0 and nrpe1 cells, which can adapt to grow in only 125 mM NaCl-containing growth medium. Salt treated nrpe1 and ddc cells but not wild type cells accumulate more mutations compared with their respective untreated cells. There is no enrichment of stress responsive genes in the list of mutated genes in salt treated cells compared to the list of mutated genes in untreated cells. Our results suggest that DNA methylation prevents the induction of mutagenesis by salt stress in plant cells during stress adaptation.

Evolutionary Genomics of Structural Variation in Asian Rice (Oryza sativa) Domestication

Structural variants (SVs) are a largely unstudied feature of plant genome evolution, despite the fact that SVs contribute substantially to phenotypes. In this study, we discovered SVs across a population sample of 347 high-coverage, resequenced genomes of Asian rice (Oryza sativa) and its wild ancestor (O. rufipogon). In addition to this short-read data set, we also inferred SVs from whole-genome assemblies and long-read data. Comparisons among data sets revealed different features of genome variability. For example, genome alignment identified a large (∼4.3 Mb) inversion in indica rice varieties relative to japonica varieties, and long-read analyses suggest that ∼9% of genes from the outgroup (O. longistaminata) are hemizygous. We focused, however, on the resequencing sample to investigate the population genomics of SVs. Clustering analyses with SVs recapitulated the rice cultivar groups that were also inferred from SNPs. However, the site-frequency spectrum of each SV type-which included inversions, duplications, deletions, translocations, and mobile element insertions-was skewed toward lower frequency variants than synonymous SNPs, suggesting that SVs may be predominantly deleterious. Among transposable elements, SINE and mariner insertions were found at especially low frequency. We also used SVs to study domestication by contrasting between rice and O. rufipogon. Cultivated genomes contained ∼25% more derived SVs and mobile element insertions than O. rufipogon, indicating that SVs contribute to the cost of domestication in rice. Peaks of SV divergence were enriched for known domestication genes, but we also detected hundreds of genes gained and lost during domestication, some of which were enriched for traits of agronomic interest.

Deleterious Mutation Burden and Its Association with Complex Traits in Sorghum (Sorghum bicolor)

Sorghum (Sorghum bicolor (L.) Moench) is a major staple food cereal for millions of people worldwide. Valluru et al. identify putative deleterious mutations among ∼5.5M segregating variants of 229 diverse sorghum...

Sorghum (Sorghum bicolor L.) is a major food cereal for millions of people worldwide. The sorghum genome, like other species, accumulates deleterious mutations, likely impacting its fitness. The lack of recombination, drift, and the coupling with favorable loci impede the removal of deleterious mutations from the genome by selection. To study how deleterious variants impact phenotypes, we identified putative deleterious mutations among ∼5.5 M segregating variants of 229 diverse biomass sorghum lines. We provide the whole-genome estimate of the deleterious burden in sorghum, showing that ∼33% of nonsynonymous substitutions are putatively deleterious. The pattern of mutation burden varies appreciably among racial groups. Across racial groups, the mutation burden correlated negatively with biomass, plant height, specific leaf area (SLA), and tissue starch content (TSC), suggesting that deleterious burden decreases trait fitness. Putatively deleterious variants explain roughly one-half of the genetic variance. However, there is only moderate improvement in total heritable variance explained for biomass (7.6%) and plant height (average of 3.1% across all stages). There is no advantage in total heritable variance for SLA and TSC. The contribution of putatively deleterious variants to phenotypic diversity therefore appears to be dependent on the genetic architecture of traits. Overall, these results suggest that incorporating putatively deleterious variants into genomic models slightly improves prediction accuracy because of extensive linkage. Knowledge of deleterious variants could be leveraged for sorghum breeding through either genome editing and/or conventional breeding that focuses on the selection of progeny with fewer deleterious alleles.

Comparative Genomics Approaches Accurately Predict Deleterious Variants in Plants

Recent advances in genome resequencing have led to increased interest in prediction of the functional consequences of genetic variants. Variants at phylogenetically conserved sites are of particular interest, because they are more likely than variants at phylogenetically variable sites to have deleterious effects on fitness and contribute to phenotypic variation. Numerous comparative genomic approaches have been developed to predict deleterious variants, but the approaches are nearly always assessed based on their ability to identify known disease-causing mutations in humans. Determining the accuracy of deleterious variant predictions in nonhuman species is important to understanding evolution, domestication, and potentially to improving crop quality and yield. To examine our ability to predict deleterious variants in plants we generated a curated database of 2,910 Arabidopsis thaliana mutants with known phenotypes. We evaluated seven approaches and found that while all performed well, their relative ranking differed from prior benchmarks in humans. We conclude that deleterious mutations can be reliably predicted in A. thaliana and likely other plant species, but that the relative performance of various approaches does not necessarily translate from one species to another.

A Pipeline for Classifying Deleterious Coding Mutations in Agricultural Plants

The impact of deleterious variation on both plant fitness and crop productivity is not completely understood and is a hot topic of debates. The deleterious mutations in plants have been solely predicted using sequence conservation methods rather than function-based classifiers due to lack of well-annotated mutational datasets in these organisms. Here, we developed a machine learning classifier based on a dataset of deleterious and neutral mutations in Arabidopsis thaliana by extracting 18 informative features that discriminate deleterious mutations from neutral, including 9 novel features not used in previous studies. We examined linear SVM, Gaussian SVM, and Random Forest classifiers, with the latter performing best. Random Forest classifiers exhibited a markedly higher accuracy than the popular PolyPhen-2 tool in the Arabidopsis dataset. Additionally, we tested whether the Random Forest, trained on the Arabidopsis dataset, accurately predicts deleterious mutations in Orýza sativa and Pisum sativum and observed satisfactory levels of performance accuracy (87% and 93%, respectively) higher than obtained by the PolyPhen-2. Application of Transfer learning in classifiers did not improve their performance. To additionally test the performance of the Random Forest classifier across different angiosperm species, we applied it to annotate deleterious mutations in Cicer arietinum and validated them using population frequency data. Overall, we devised a classifier with the potential to improve the annotation of putative functional mutations in QTL and GWAS hit regions, as well as for the evolutionary analysis of proliferation of deleterious mutations during plant domestication; thus optimizing breeding improvement and development of new cultivars.

Bioinformatically predicted deleterious mutations reveal complementation in the interior spruce hybrid complex

BACKGROUND

Mutation load is expected to be reduced in hybrids via complementation of deleterious alleles. While local adaptation of hybrids confounds phenotypic tests for reduced mutation load, it may be possible to assess variation in load by analyzing the distribution of putatively deleterious alleles. Here, we use this approach in the interior spruce (Picea glauca x P. engelmannii) hybrid complex, a group likely to suffer from high mutation load and in which hybrids exhibit local adaptation to intermediate conditions. We used PROVEAN to bioinformatically predict whether non-synonymous alleles are deleterious, based on conservation of the position and abnormality of the amino acid change.

RESULTS

As expected, we found that predicted deleterious alleles were at lower average allele frequencies than alleles not predicted to be deleterious. We were unable to detect a phenotypic effect on juvenile growth rate of the many rare alleles predicted to be deleterious. Both the proportion of alleles predicted to be deleterious and the proportion of loci homozygous for predicted deleterious alleles were higher in P. engelmannii (Engelmann spruce) than in P. glauca (white spruce), due to higher diversity and frequencies of rare alleles in Engelmann. Relative to parental species, the proportion of alleles predicted to be deleterious was intermediate in hybrids, and the proportion of loci homozygous for predicted deleterious alleles was lowest.

CONCLUSION

Given that most deleterious alleles are recessive, this suggests that mutation load is reduced in hybrids due to complementation of deleterious alleles. This effect may enhance the fitness of hybrids.

The interplay of demography and selection during maize domestication and expansion

BACKGROUND

The history of maize has been characterized by major demographic events, including population size changes associated with domestication and range expansion, and gene flow with wild relatives. The interplay between demographic history and selection has shaped diversity across maize populations and genomes.

RESULTS

We investigate these processes using high-depth resequencing data from 31 maize landraces spanning the pre-Columbian distribution of maize, and four wild teosinte individuals (Zea mays ssp. parviglumis). Genome-wide demographic analyses reveal that maize experienced pronounced declines in effective population size due to both a protracted domestication bottleneck and serial founder effects during post-domestication spread, while parviglumis in the Balsas River Valley experienced population growth. The domestication bottleneck and subsequent spread led to an increase in deleterious alleles in the domesticate compared to the wild progenitor. This cost is particularly pronounced in Andean maize, which has experienced a more dramatic founder event compared to other maize populations. Additionally, we detect introgression from the wild teosinte Zea mays ssp. mexicana into maize in the highlands of Mexico, Guatemala, and the southwestern USA, which reduces the prevalence of deleterious alleles likely due to the higher long-term effective population size of teosinte.

CONCLUSIONS

These findings underscore the strong interaction between historical demography and the efficiency of selection and illustrate how domesticated species are particularly useful for understanding these processes. The landscape of deleterious alleles and therefore evolutionary potential is clearly influenced by recent demography, a factor that could bear importantly on many species that have experienced recent demographic shifts.

The interplay of demography and selection during maize domestication and expansion

BACKGROUND

The history of maize has been characterized by major demographic events, including population size changes associated with domestication and range expansion, and gene flow with wild relatives. The interplay between demographic history and selection has shaped diversity across maize populations and genomes.

RESULTS

We investigate these processes using high-depth resequencing data from 31 maize landraces spanning the pre-Columbian distribution of maize, and four wild teosinte individuals (Zea mays ssp. parviglumis). Genome-wide demographic analyses reveal that maize experienced pronounced declines in effective population size due to both a protracted domestication bottleneck and serial founder effects during post-domestication spread, while parviglumis in the Balsas River Valley experienced population growth. The domestication bottleneck and subsequent spread led to an increase in deleterious alleles in the domesticate compared to the wild progenitor. This cost is particularly pronounced in Andean maize, which has experienced a more dramatic founder event compared to other maize populations. Additionally, we detect introgression from the wild teosinte Zea mays ssp. mexicana into maize in the highlands of Mexico, Guatemala, and the southwestern USA, which reduces the prevalence of deleterious alleles likely due to the higher long-term effective population size of teosinte.

CONCLUSIONS

These findings underscore the strong interaction between historical demography and the efficiency of selection and illustrate how domesticated species are particularly useful for understanding these processes. The landscape of deleterious alleles and therefore evolutionary potential is clearly influenced by recent demography, a factor that could bear importantly on many species that have experienced recent demographic shifts.

The Role of Deleterious Substitutions in Crop Genomes

Populations continually incur new mutations with fitness effects ranging from lethal to adaptive. While the distribution of fitness effects of new mutations is not directly observable, many mutations likely either have no effect on organismal fitness or are deleterious. Historically, it has been hypothesized that a population may carry many mildly deleterious variants as segregating variation, which reduces the mean absolute fitness of the population. Recent advances in sequencing technology and sequence conservation-based metrics for inferring the functional effect of a variant permit examination of the persistence of deleterious variants in populations. The issue of segregating deleterious variation is particularly important for crop improvement, because the demographic history of domestication and breeding allows deleterious variants to persist and reach moderate frequency, potentially reducing crop productivity. In this study, we use exome resequencing of 15 barley accessions and genome resequencing of 8 soybean accessions to investigate the prevalence of deleterious single nucleotide polymorphisms (SNPs) in the protein-coding regions of the genomes of two crops. We conclude that individual cultivars carry hundreds of deleterious SNPs on average, and that nonsense variants make up a minority of deleterious SNPs. Our approach identifies known phenotype-altering variants as deleterious more frequently than the genome-wide average, suggesting that putatively deleterious variants are likely to affect phenotypic variation. We also report the implementation of a SNP annotation tool BAD_Mutations that makes use of a likelihood ratio test based on alignment of all currently publicly available Angiosperm genomes.

Genomic and phenotypic differentiation of Arabidopsis thaliana along altitudinal gradients in the North Italian Alps

Altitudinal gradients in mountain regions are short-range clines of different environmental parameters such as temperature or radiation. We investigated genomic and phenotypic signatures of adaptation to such gradients in five Arabidopsis thaliana populations from the North Italian Alps that originated from 580 to 2350 m altitude by resequencing pools of 19-29 individuals from each population. The sample includes two pairs of low- and high-altitude populations from two different valleys. High-altitude populations showed a lower nucleotide diversity and negative Tajima's D values and were more closely related to each other than to low-altitude populations from the same valley. Despite their close geographic proximity, demographic analysis revealed that low- and high-altitude populations split between 260 000 and 15 000 years before present. Single nucleotide polymorphisms whose allele frequencies were highly differentiated between low- and high-altitude populations identified genomic regions of up to 50 kb length where patterns of genetic diversity are consistent with signatures of local selective sweeps. These regions harbour multiple genes involved in stress response. Variation among populations in two putative adaptive phenotypic traits, frost tolerance and response to light/UV stress was not correlated with altitude. Taken together, the spatial distribution of genetic diversity reflects a potentially adaptive differentiation between low- and high-altitude populations, whereas the phenotypic differentiation in the two traits investigated does not. It may resemble an interaction between adaptation to the local microhabitat and demographic history influenced by historical glaciation cycles, recent seed dispersal and genetic drift in local populations.

Recent demography drives changes in linked selection across the maize genome

Genetic diversity is shaped by the interaction of drift and selection, but the details of this interaction are not well understood. The impact of genetic drift in a population is largely determined by its demographic history, typically summarized by its long-term effective population size (Ne). Rapidly changing population demographics complicate this relationship, however. To better understand how changing demography impacts selection, we used whole-genome sequencing data to investigate patterns of linked selection in domesticated and wild maize (teosinte). We produce the first whole-genome estimate of the demography of maize domestication, showing that maize was reduced to approximately 5% the population size of teosinte before it experienced rapid expansion post-domestication to population sizes much larger than its ancestor. Evaluation of patterns of nucleotide diversity in and near genes shows little evidence of selection on beneficial amino acid substitutions, and that the domestication bottleneck led to a decline in the efficiency of purifying selection in maize. Young alleles, however, show evidence of much stronger purifying selection in maize, reflecting the much larger effective size of present day populations. Our results demonstrate that recent demographic change-a hall-mark of many species including both humans and crops-can have immediate and wide-ranging impacts on diversity that conflict with expectations based on long-term Ne alone.

Genetic shift in local rice populations during rice breeding programs in the northern limit of rice cultivation in the world

The rapid accumulation of pre-existing mutations may play major roles in the establishment and shaping of adaptability for local regions in current rice breeding programs. The cultivated rice, Oryza sativa L., which originated from tropical regions, is now grown worldwide due to the concerted efforts of breeding programs. However, the process of establishing local populations and their origins remain unclear. In the present study, we characterized DNA polymorphisms in the rice variety KITAAKE from Hokkaido, one of the northern limits of rice cultivation in the world. Indel polymorphisms were attributed to transposable element-like insertions, tandem duplications, and non-TE deletions as the original mutation events in the NIPPONBARE and KITAAKE genomes. The allele frequencies of the KITAAKE alleles markedly shifted to the current variety types among the local population from Hokkaido in the last two decades. The KITAAKE alleles widely distributed throughout wild rice and cultivated rice over the world. These have accumulated in the local population from Hokkaido via Japanese landraces as the ancestral population of Hokkaido. These results strongly suggested that combinations of pre-existing mutations played a role in the establishment of adaptability. This approach using the re-sequencing of local varieties in unique environmental conditions will be useful as a genetic resource in plant breeding programs in local regions.

The Accumulation of Deleterious Mutations as a Consequence of Domestication and Improvement in Sunflowers and Other Compositae Crops

For populations to maintain optimal fitness, harmful mutations must be efficiently purged from the genome. Yet, under circumstances that diminish the effectiveness of natural selection, such as the process of plant and animal domestication, deleterious mutations are predicted to accumulate. Here, we compared the load of deleterious mutations in 21 accessions from natural populations and 19 domesticated accessions of the common sunflower using whole-transcriptome single nucleotide polymorphism data. Although we find that genetic diversity has been greatly reduced during domestication, the remaining mutations were disproportionally biased toward nonsynonymous substitutions. Bioinformatically predicted deleterious mutations affecting protein function were especially strongly over-represented. We also identify similar patterns in two other domesticated species of the sunflower family (globe artichoke and cardoon), indicating that this phenomenon is not due to idiosyncrasies of sunflower domestication or the sunflower genome. Finally, we provide unequivocal evidence that deleterious mutations accumulate in low recombining regions of the genome, due to the reduced efficacy of purifying selection. These results represent a conundrum for crop improvement efforts. Although the elimination of harmful mutations should be a long-term goal of plant and animal breeding programs, it will be difficult to weed them out because of limited recombination.

The pattern and distribution of deleterious mutations in maize

Most nonsynonymous mutations are thought to be deleterious because of their effect on protein sequence and are expected to be removed or kept at low frequency by the action of natural selection. Nonetheless, the effect of positive selection on linked sites or drift in small or inbred populations may also impact the evolution of deleterious alleles. Despite their potential to affect complex trait phenotypes, deleterious alleles are difficult to study precisely because they are often at low frequency. Here, we made use of genome-wide genotyping data to characterize deleterious variants in a large panel of maize inbred lines. We show that, despite small effective population sizes and inbreeding, most putatively deleterious SNPs are indeed at low frequencies within individual genetic groups. We find that genes associated with a number of complex traits are enriched for deleterious variants. Together, these data are consistent with the dominance model of heterosis, in which complementation of numerous low-frequency, weak deleterious variants contribute to hybrid vigor.

Mutational bias and gene conversion affect the intraspecific nitrogen stoichiometry of the Arabidopsis thaliana transcriptome

The transcriptome and proteome of Arabidopsis thaliana are reduced in nitrogen content when compared with other taxa, which may result from ecological nitrogen limitation. We hypothesized that if the A. thaliana transcriptome is selected for a low nitrogen content, nitrogen-reducing derived alleles of single nucleotide polymorphisms (SNPs) should segregate at higher frequencies than nitrogen-increasing alleles. This pattern should be stronger in populations with a larger effective population size (N(e)) if natural selection is more efficient in large than in small populations. We analyzed variation in the nitrogen content in the transcriptome of 80 natural accessions of A. thaliana. In contrast to our expectations, derived alleles increase the nitrogen content in all accessions, and there is a positive correlation between nitrogen difference and derived allele frequency, which is strongest with nonsynonymous SNPs (nsSNPs). Also, there is a positive correlation between nitrogen difference and N(e) that was mainly caused by nsSNPs. These observations led us to reject the hypothesis that the transcriptome of A. thaliana is currently under selection to reduce nitrogen content. Instead, we show that a change in nitrogen content is a side effect of interacting evolutionary factors that influence base composition and include mutational bias, purifying selection of functionally deleterious alleles, and GC-biased gene conversion. We provide strong evidence that GC-biased gene conversion may play an important role for base composition in the highly selfing plant A. thaliana.

SIFT web server: predicting effects of amino acid substitutions on proteins

The Sorting Intolerant from Tolerant (SIFT) algorithm predicts the effect of coding variants on protein function. It was first introduced in 2001, with a corresponding website that provides users with predictions on their variants. Since its release, SIFT has become one of the standard tools for characterizing missense variation. We have updated SIFT’s genome-wide prediction tool since our last publication in 2009, and added new features to the insertion/deletion (indel) tool. We also show accuracy metrics on independent data sets. The original developers have hosted the SIFT web server at FHCRC, JCVI and the web server is currently located at BII. The URL is http://sift-dna.org (24 May 2012, date last accessed).

Whole-genome sequencing of multiple Arabidopsis thaliana populations

The plant Arabidopsis thaliana occurs naturally in many different habitats throughout Eurasia. As a foundation for identifying genetic variation contributing to adaptation to diverse environments, a 1001 Genomes Project to sequence geographically diverse A. thaliana strains has been initiated. Here we present the first phase of this project, based on population-scale sequencing of 80 strains drawn from eight regions throughout the species' native range. We describe the majority of common small-scale polymorphisms as well as many larger insertions and deletions in the A. thaliana pan-genome, their effects on gene function, and the patterns of local and global linkage among these variants. The action of processes other than spontaneous mutation is identified by comparing the spectrum of mutations that have accumulated since A. thaliana diverged from its closest relative 10 million years ago with the spectrum observed in the laboratory. Recent species-wide selective sweeps are rare, and potentially deleterious mutations are more common in marginal populations.

Integrating Rare-Variant Testing, Function Prediction, and Gene Network in Composite Resequencing-Based Genome-Wide Association Studies (CR-GWAS)

High-density array-based genome-wide association studies (GWAS) are complemented by exome sequencing and whole-genome resequencing-based association studies. Here we present a composite resequencing-based genome-wide association study (CR-GWAS) strategy that systematically exploits collective biological information and analytical tools for a robust analysis. We showcased the utility of this strategy by using Arabidopsis (Arabidopsis thaliana) resequencing data. Bioinformatic predictions of biological function alteration at each locus were integrated into the process of association testing of both common and rare variants for complex traits with a suite of statistics. Significant signals were then filtered with a priori candidate loci generated from genome database and gene network models to obtain a posteriori candidate loci. A probabilistic gene network (AraNet) that interrogates network neighborhoods of genes was then used to expand the filtering power to examine the significant testing signals. Using this strategy, we confirmed the known true positives and identified several new promising associations. Promising genes (AP1, FCA, FRI, FLC, FLM, SPL5, FY, and DCL2) were shown to control for flowering time through either common variants or rare variants within a diverse set of Arabidopsis accessions. Although many of these candidate genes were cloned earlier with mutational studies, identifying their allele variation contribution to overall phenotypic variation among diverse natural accessions is critical. Our rare allele testing established a greater number of connections than previous analyses in which this issue was not addressed. More importantly, our results demonstrated the potential of integrating various biological, statistical, and bioinformatic tools into complex trait dissection.