A genome-wide map of diversity in Plasmodium falciparum

Genetic variation allows the malaria parasite Plasmodium falciparum to overcome chemotherapeutic agents, vaccines and vector control strategies and remain a leading cause of global morbidity and mortality. Here we describe an initial survey of genetic variation across the P. falciparum genome. We performed extensive sequencing of 16 geographically diverse parasites and identified 46,937 SNPs, demonstrating rich diversity among P. falciparum parasites (pi = 1.16 x 10(-3)) and strong correlation with gene function. We identified multiple regions with signatures of selective sweeps in drug-resistant parasites, including a previously unidentified 160-kb region with extremely low polymorphism in pyrimethamine-resistant parasites. We further characterized 54 worldwide isolates by genotyping SNPs across 20 genomic regions. These data begin to define population structure among African, Asian and American groups and illustrate the degree of linkage disequilibrium, which extends over relatively short distances in African parasites but over longer distances in Asian parasites. We provide an initial map of genetic diversity in P. falciparum and demonstrate its potential utility in identifying genes subject to recent natural selection and in understanding the population genetics of this parasite.     

Plasmodium cynomolgi genome sequences provide insight into Plasmodium vivax and the monkey malaria clade

P. cynomolgi, a malaria-causing parasite of Asian Old World monkeys, is the sister taxon of P. vivax, the most prevalent malaria-causing species in humans outside of Africa. Because P. cynomolgi shares many phenotypic, biological and genetic characteristics with P. vivax, we generated draft genome sequences for three P. cynomolgi strains and performed genomic analysis comparing them with the P. vivax genome, as well as with the genome of a third previously sequenced simian parasite, Plasmodium knowlesi. Here, we show that genomes of the monkey malaria clade can be characterized by copy-number variants (CNVs) in multigene families involved in evasion of the human immune system and invasion of host erythrocytes. We identify genome-wide SNPs, microsatellites and CNVs in the P. cynomolgi genome, providing a map of genetic variation that can be used to map parasite traits and study parasite populations. The sequencing of the P. cynomolgi genome is a critical step in developing a model system for P. vivax research and in counteracting the neglect of P. vivax.     

Genomic insights into the other malaria

Plasmodium vivax has received less attention and study than Plasmodium falciparum, due in part to difficulties in culturing this pathogen. Whole-genome sequencing of both P. vivax and Plasmodium cynomolgi and characterization of genetic variation in these species provide a genetic toolbox for tertian malaria and new insights into the monkey malaria clade.     

Yersinia pestis genome sequencing identifies patterns of global phylogenetic diversity

Plague is a pandemic human invasive disease caused by the bacterial agent Yersinia pestis. We here report a comparison of 17 whole genomes of Y. pestis isolates from global sources. We also screened a global collection of 286 Y. pestis isolates for 933 SNPs using Sequenom MassArray SNP typing. We conducted phylogenetic analyses on this sequence variation dataset, assigned isolates to populations based on maximum parsimony and, from these results, made inferences regarding historical transmission routes. Our phylogenetic analysis suggests that Y. pestis evolved in or near China and spread through multiple radiations to Europe, South America, Africa and Southeast Asia, leading to country-specific lineages that can be traced by lineage-specific SNPs. All 626 current isolates from the United States reflect one radiation, and 82 isolates from Madagascar represent a second radiation. Subsequent local microevolution of Y. pestis is marked by sequential, geographically specific SNPs.     

Lessons in the genomic diversity of malaria

Genome-wide characterization of Plasmodium falciparum genetic diversity represents an important step in malaria genetics. The organizational and collaborative efforts to reach this goal and the results on linkage disequilibrium and genetic diversity among worldwide isolates provide general lessons.     

Genome-wide variation and identification of vaccine targets in the Plasmodium falciparum genome

One goal in sequencing the Plasmodium falciparum genome, the agent of the most lethal form of malaria, is to discover vaccine and drug targets. However, identifying those targets in a genome in which approximately 60% of genes have unknown functions is an enormous challenge. Because the majority of known malaria antigens and drug-resistant genes are highly polymorphic and under various selective pressures, genome-wide analysis for signatures of selection may lead to discovery of new vaccine and drug candidates. Here we surveyed 3,539 P. falciparum genes ( approximately 65% of the predicted genes) for polymorphisms and identified various highly polymorphic loci and genes, some of which encode new antigens that we confirmed using human immune sera. Our collections of genome-wide SNPs ( approximately 65% nonsynonymous) and polymorphic microsatellites and indels provide a high-resolution map (one marker per approximately 4 kb) for mapping parasite traits and studying parasite populations. In addition, we report new antigens, providing urgently needed vaccine candidates for disease control.     

Dichotomy of single-nucleotide polymorphism haplotypes in olfactory receptor genes and pseudogenes

Substantial efforts are focused on identifying single-nucleotide polymorphisms (SNPs) throughout the human genome, particularly in coding regions (cSNPs), for both linkage disequilibrium and association studies. Less attention, however, has been directed to the clarification of evolutionary processes that are responsible for the variability in nucleotide diversity among different regions of the genome. We report here the population sequence diversity of genomic segments within a 450-kb cluster of olfactory receptor (OR) genes on human chromosome 17. We found a dichotomy in the pattern of nucleotide diversity between OR pseudogenes and introns on the one hand and the closely interspersed intact genes on the other. We suggest that weak positive selection is responsible for the observed patterns of genetic variation. This is inferred from a lower ratio of polymorphism to divergence in genes compared with pseudogenes or introns, high non-synonymous substitution rates in OR genes, and a small but significant overall reduction in variability in the entire OR gene cluster compared with other genomic regions. The dichotomy among functionally different segments within a short genomic distance requires high recombination rates within this OR cluster. Our work demonstrates the impact of weak positive selection on human nucleotide diversity, and has implications for the evolution of the olfactory repertoire.     

Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population

Nested association mapping (NAM) offers power to resolve complex, quantitative traits to their causal loci. The maize NAM population, consisting of 5,000 recombinant inbred lines (RILs) from 25 families representing the global diversity of maize, was evaluated for resistance to southern leaf blight (SLB) disease. Joint-linkage analysis identified 32 quantitative trait loci (QTLs) with predominantly small, additive effects on SLB resistance. Genome-wide association tests of maize HapMap SNPs were conducted by imputing founder SNP genotypes onto the NAM RILs. SNPs both within and outside of QTL intervals were associated with variation for SLB resistance. Many of these SNPs were within or near sequences homologous to genes previously shown to be involved in plant disease resistance. Limited linkage disequilibrium was observed around some SNPs associated with SLB resistance, indicating that the maize NAM population enables high-resolution mapping of some genome regions.     

A model-based approach for analysis of spatial structure in genetic data

Characterizing genetic diversity within and between populations has broad applications in studies of human disease and evolution. We propose a new approach, spatial ancestry analysis, for the modeling of genotypes in two- or three-dimensional space. In spatial ancestry analysis (SPA), we explicitly model the spatial distribution of each SNP by assigning an allele frequency as a continuous function in geographic space. We show that the explicit modeling of the allele frequency allows individuals to be localized on the map on the basis of their genetic information alone. We apply our SPA method to a European and a worldwide population genetic variation data set and identify SNPs showing large gradients in allele frequency, and we suggest these as candidate regions under selection. These regions include SNPs in the well-characterized LCT region, as well as at loci including FOXP2, OCA2 and LRP1B.     

Human genome sequence variation and the influence of gene history,mutation and recombination

Variation in the human genome sequence is key to understanding susceptibility to disease in modern populations and the history of ancestral populations. Unlocking this information requires knowledge of the patterns and underlying causes of human sequence diversity. By applying a new population-genetic framework to two genome-wide polymorphism surveys, we find that the human genome contains sizeable regions (stretching over tens of thousands of base pairs) that have intrinsically high and low rates of sequence variation. We show that the primary determinant of these patterns is shared genealogical history. Only a fraction of the variation (at most 25%) is due to the local mutation rate. By measuring the average distance over which genealogical histories are typically preserved, these data provide the first genome-wide estimate of the average extent of correlation among variants (linkage disequilibrium). The results are best explained by extreme variability in the recombination rate at a fine scale, and provide the first empirical evidence that such recombination 'hot spots' are a general feature of the human genome and have a principal role in shaping genetic variation in the human population.     

High-throughput sequencing provides insights into genome variation and evolution in Salmonella Typhi

Isolates of Salmonella enterica serovar Typhi (Typhi), a human-restricted bacterial pathogen that causes typhoid, show limited genetic variation. We generated whole-genome sequences for 19 Typhi isolates using 454 (Roche) and Solexa (Illumina) technologies. Isolates, including the previously sequenced CT18 and Ty2 isolates, were selected to represent major nodes in the phylogenetic tree. Comparative analysis showed little evidence of purifying selection, antigenic variation or recombination between isolates. Rather, evolution in the Typhi population seems to be characterized by ongoing loss of gene function, consistent with a small effective population size. The lack of evidence for antigenic variation driven by immune selection is in contrast to strong adaptive selection for mutations conferring antibiotic resistance in Typhi. The observed patterns of genetic isolation and drift are consistent with the proposed key role of asymptomatic carriers of Typhi as the main reservoir of this pathogen, highlighting the need for identification and treatment of carriers.     

A framework for variation discovery and genotyping using next-generation DNA sequencing data

Recent advances in sequencing technology make it possible to comprehensively catalog genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious, and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (i) initial read mapping; (ii) local realignment around indels; (iii) base quality score recalibration; (iv) SNP discovery and genotyping to find all potential variants; and (v) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We here discuss the application of these tools, instantiated in the Genome Analysis Toolkit, to deep whole-genome, whole-exome capture and multi-sample low-pass (～4×) 1000 Genomes Project datasets.     

Magnitude and distribution of linkage disequilibrium in population isolates and implications for genome-wide association studies

The genome-wide distribution of linkage disequilibrium (LD) determines the strategy for selecting markers for association studies, but it varies between populations. We assayed LD in large samples (200 individuals) from each of 11 well-described population isolates and an outbred European-derived sample, using SNP markers spaced across chromosome 22. Most isolates show substantially higher levels of LD than the outbred sample and many fewer regions of very low LD (termed 'holes'). Young isolates known to have had relatively few founders show particularly extensive LD with very few holes; these populations offer substantial advantages for genome-wide association mapping.     

Global patterns of human mitochondrial DNA and Y-chromosome structure are not influenced by higher migration rates of females versus males

Global-scale patterns of human population structure may be influenced by the rate of migration among populations that is nearly eight times higher for females than for males. This difference is attributed mainly to the widespread practice of patrilocality, in which women move into their mates' residences after marriage. Here we directly test this hypothesis by comparing global patterns of DNA sequence variation on the Y chromosome and mitochondrial DNA (mtDNA) in the same panel of 389 individuals from ten populations (four from Africa and two each from Europe, Asia and Oceania). We introduce a new strategy to assay Y-chromosome variation that identifies a high density of single-nucleotide polymorphisms, allows complete sequencing of all individuals rather than relying on predetermined markers and provides direct sequence comparisons with mtDNA. We found the overall proportion of between-group variation (Phi(ST)) to be 0.334 for the Y chromosome and 0.382 for mtDNA. Genetic differentiation between populations was similar for the Y chromosome and mtDNA at all geographic scales that we tested. Although patrilocality may be important at the local scale, patterns of genetic structure on the continental and global scales are not shaped by the higher rate of migration among females than among males.     

Genome-wide association identifies a susceptibility locus for coronary artery disease in the Chinese Han population

Coronary artery disease (CAD) causes more than 700,000 deaths each year in China. Previous genome-wide association studies (GWAS) in populations of European ancestry identified several genetic loci for CAD, but no such study has yet been reported in the Chinese population. Here we report a three-stage GWAS in the Chinese Han population. We identified a new association between rs6903956 in a putative gene denoted as C6orf105 on chromosome 6p24.1 and CAD (P = 5.00 × 10?3, stage 2 validation; P = 3.00 × 10?3, P = 1.19 × 10?? and P = 4.00 × 10?3 in three independent stage 3 replication populations; P = 4.87 × 10?12, odds ratio = 1.51 in the combined population). The minor risk allele A of rs6903956 is associated with decreased C6orf105 mRNA expression. We report the first GWAS for CAD in the Chinese Han population and identify a SNP, rs6903956, in C6orf105 associated with susceptibility to CAD in this population.     

Systematic assessment of copy number variant detection via genome-wide SNP genotyping

SNP genotyping has emerged as a technology to incorporate copy number variants (CNVs) into genetic analyses of human traits. However, the extent to which SNP platforms accurately capture CNVs remains unclear. Using independent, sequence-based CNV maps, we find that commonly used SNP platforms have limited or no probe coverage for a large fraction of CNVs. Despite this, in 9 samples we inferred 368 CNVs using Illumina SNP genotyping data and experimentally validated over two-thirds of these. We also developed a method (SNP-Conditional Mixture Modeling, SCIMM) to robustly genotype deletions using as few as two SNP probes. We find that HapMap SNPs are strongly correlated with 82% of common deletions, but the newest SNP platforms effectively tag about 50%. We conclude that currently available genome-wide SNP assays can capture CNVs accurately, but improvements in array designs, particularly in duplicated sequences, are necessary to facilitate more comprehensive analyses of genomic variation.