Biodiversity of 20 chicken breeds assessed by SNPs located in gene regions

Twenty-five single nucleotide polymorphisms (SNPs) were analyzed in 20 distinct chicken breeds. The SNPs, each located in a different gene and mostly on different chromosomes, were chosen to examine the use of SNPs in or close to genes (g-SNPs), for biodiversity studies. Phylogenetic trees were constructed from these data. When bootstrap values were used as a criterion for the tree repeatability, doubling the number of SNPs from 12 to 25 improved tree repeatability more than doubling the number of individuals per population, from five to ten. Clustering results of these 20 populations, based on the software STRUCTURE, are in agreement with those previously obtained from the analysis of microsatellites. When the number of clusters was similar to the number of populations, affiliation of birds to their original populations was correct (>95%) only when at least the 22 most polymorphic SNP loci (out of 25) were included. When ten populations were clustered into five groups based on STRUCTURE, we used membership coefficient (Q) of the major cluster at each population as an indicator for clustering success level. This value was used to compare between three marker types; microsatellites, SNPs in or close to genes (g-SNPs) and SNPs in random fragments (r-SNPs). In this comparison, the same individuals were used (five to ten birds per population) and the same number of loci (14) used for each of the marker types. The average membership coefficients (Q) of the major cluster for microsatellites, g-SNPs and r-SNPs were 0.85, 0.7, and 0.64, respectively. Analysis based on microsatellites resulted in significantly higher clustering success due to their multi-allelic nature. Nevertheless, SNPs have obvious advantages, and are an efficient and cost-effective genetic tool, providing broader genome coverage and reliable estimates of genetic relatedness.     

Single nucleotide polymorphism genotyping by mini-primer allele-specific amplification with universal reporter primers for identification of degraded DNA

Single nucleotide polymorphism (SNP) is informative for human identification, and much shorter regions are targeted in analysis of biallelic SNP compared with highly polymorphic short tandem repeat (STR). Therefore, SNP genotyping is expected to be more sensitive than STR genotyping of degraded human DNA. To achieve simple, economical, and sensitive SNP genotyping for identification of degraded human DNA, we developed 18 loci for a SNP genotyping technique based on the mini-primer allele-specific amplification (ASA) combined with universal reporter primers (URP). The URP/ASA-based genotyping consisted of two amplifications followed by detection using capillary electrophoresis. The sizes of the target genome fragments ranged from 40 to 67 bp in length. In the Japanese population, the frequencies of minor alleles of 18 SNPs ranged from 0.36 to 0.50, and these SNPs are informative for identification. The success rate of SNP genotyping was much higher than that of STR genotyping of artificially degraded DNA. Moreover, we applied this genotyping method to case samples and showed successful SNP genotyping of severely degraded DNA from a 4-year buffered formalin-fixed tissue sample for human identification.     

Precision and accuracy of divergence time estimates from STR and SNPSTR variation

Inference of intraspecific population divergence patterns typically requires genetic data for molecular markers with relatively high mutation rates. Microsatellites, or short tandem repeat (STR) polymorphisms, have proven informative in many such investigations. These markers are characterized, however, by high levels of homoplasy and varying mutational properties, often leading to inaccurate inference of population divergence. A SNPSTR is a genetic system that consists of an STR polymorphism closely linked (typically < 500 bp) to one or more single-nucleotide polymorphisms (SNPs). SNPSTR systems are characterized by lower levels of homoplasy than are STR loci. Divergence time estimates based on STR variation (on the derived SNP allele background) should, therefore, be more accurate and precise. We use coalescent-based simulations in the context of several models of demographic history to compare divergence time estimates based on SNPSTR haplotype frequencies and STR allele frequencies. We demonstrate that estimates of divergence time based on STR variation on the background of a derived SNP allele are more accurate (3% to 7% bias for SNPSTR versus 11% to 20% bias for STR) and more precise than STR-based estimates, conditional on a recent SNP mutation. These results hold even for models involving complex demographic scenarios with gene flow, population expansion, and population bottlenecks. Varying the timing of the mutation event generating the SNP revealed that estimates of divergence time are sensitive to SNP age, with more recent SNPs giving more accurate and precise estimates of divergence time. However, varying both mutational properties of STR loci and SNP age demonstrated that multiple independent SNPSTR systems provide less biased estimates of divergence time. Furthermore, the combination of estimates based separately on STR and SNPSTR variation provides insight into the age of the derived SNP alleles. In light of our simulations, we interpret estimates from data for human populations.     

Analysis of single nucleotide polymorphisms in three chromosomes of European sea bass Dicentrarchus labrax

Single nucleotide polymorphisms (SNPs) are believed to contain relevant information and have been therefore extensively used as genetic markers in population and conservation genetics, and molecular ecology studies. This study reports on the identification of potential SNPs in a diploid European sea bass Dicentrarchus labrax genome by using reference sequences from three assembled chromosomes and mapping all WGS datasets onto them (3× Sanger, 3× 454 and 20× SOLEXA). A total of 20,779 SNPs were identified over the 1469 gene loci and intergenic space analysed. Within chromosomes the occurrence of SNPs was the lowest in exons and higher in introns and intergenic regions, which may be explained by the fact, that coding regions are under strong selective pressure to maintain their biological function. The ratio of nonsynonymous to synonymous mutations was smaller than one for all the chromosomes, suggesting that most of deleterious nonsynonymous mutations were eliminated by negative selection. SNPs were not uniformly distributed over the chromosomes. Two chromosomes exhibited large regions with extremely low SNP density, which might represent homozygous regions in the diploid genome. The results of this study show how SNP detection can take profit from sequencing a single diploid individual, but also uncover the limits of such an approach. SNPs that have been identified will support marker development for genetic linkage mapping, population genetics and aquaculture related questions in general.     

A pipeline for high throughput detection and mapping of SNPs from EST databases

Single nucleotide polymorphisms (SNPs) represent the most abundant type of genetic variation that can be used as molecular markers. The SNPs that are hidden in sequence databases can be unlocked using bioinformatic tools. For efficient application of these SNPs, the sequence set should be error-free as much as possible, targeting single loci and suitable for the SNP scoring platform of choice. We have developed a pipeline to effectively mine SNPs from public EST databases with or without quality information using QualitySNP software, select reliable SNP and prepare the loci for analysis on the Illumina GoldenGate genotyping platform. The applicability of the pipeline was demonstrated using publicly available potato EST data, genotyping individuals from two diploid mapping populations and subsequently mapping the SNP markers (putative genes) in both populations. Over 7000 reliable SNPs were identified that met the criteria for genotyping on the GoldenGate platform. Of the 384 SNPs on the SNP array approximately 12% dropped out. For the two potato mapping populations 165 and 185 SNPs segregating SNP loci could be mapped on the respective genetic maps, illustrating the effectiveness of our pipeline for SNP selection and validation.     

Expressed sequence tags for the chicken genome from a normalized 10-day-old white leghorn whole-embryo cDNA library. 3. DNA sequence analysis of genetic variation in commercial chicken populations.

Single nucleotide polymorphisms (SNPs) have emerged as a major class of DNA markers with the advantage of permitting the development of high-density genetic maps adequate for quantitative trait loci (QTL) identification by linkage-disequilibrium analysis. Here we describe results of a relatively high-depth survey of chicken broiler and layer populations for SNPs in targeted genomic regions of chicken expressed sequence tag (EST) sites. The sequences scanned, representing the composite sequence of 12 amplified fragments for a total of 6489 bp, were randomly distributed, occurring on six different chromosomes or linkage groups in the chicken genome. Although one of the genomic DNA sequences did not match the reference cDNA sequence, another contained an intron that separated two putative exons. The number of SNPs observed within each of the 12 EST-targeted genomic regions ranged from 0 to 10 for a total of 44 and a frequency of 0.7%. About 70% of the polymorphisms were shared between layer and broiler populations. The average heterozygosity within the populations ranged from 0.15 to 0.48, with the layer populations showing the higher heterozygosity. SNPs and oligonucleotides described will provide a resource for genetic analysis in commercial chicken populations. The data appear to indicate that the relative frequency of SNPs in the targeted regions scanned is higher than the frequency reported for any of the other regions scanned to date in other eukaryotic genomes. Additionally, the results suggest that the use of DNA pools may offer an efficient approach to SNP detection in chickens, as has been shown in other vertebrates.     

Identification of novel single nucleotide polymorphisms (SNPs) in deer (Odocoileus spp.) using the BovineSNP50 BeadChip

Single nucleotide polymorphisms (SNPs) are growing in popularity as a genetic marker for investigating evolutionary processes. A panel of SNPs is often developed by comparing large quantities of DNA sequence data across multiple individuals to identify polymorphic sites. For non-model species, this is particularly difficult, as performing the necessary large-scale genomic sequencing often exceeds the resources available for the project. In this study, we trial the Bovine SNP50 BeadChip developed in cattle (Bos taurus) for identifying polymorphic SNPs in cervids Odocoileus hemionus (mule deer and black-tailed deer) and O. virginianus (white-tailed deer) in the Pacific Northwest. We found that 38.7% of loci could be genotyped, of which 5% (n = 1068) were polymorphic. Of these 1068 polymorphic SNPs, a mixture of putatively neutral loci (n = 878) and loci under selection (n = 190) were identified with the F(ST)-outlier method. A range of population genetic analyses were implemented using these SNPs and a panel of 10 microsatellite loci. The three types of deer could readily be distinguished with both the SNP and microsatellite datasets. This study demonstrates that commercially developed SNP chips are a viable means of SNP discovery for non-model organisms, even when used between very distantly related species (the Bovidae and Cervidae families diverged some 25.1-30.1 million years before present).     

A Recent Shift from Polygyny to Monogamy in Humans Is Suggested by the Analysis of Worldwide Y-Chromosome Diversity

Molecular genetic data contain information on the history of populations. Evidence of prehistoric demographic expansions has been detected in the mitochondrial diversity of most human populations and in a Y-chromosome STR analysis, but not in a previous study of 11 Y-chromosome SNPs in Europeans. In this paper, we show that mismatch distributions and tests of mutation/drift equilibrium based on up to 166 Y-chromosome SNPs, in 46 samples from all continents, also fail to support an increase of the male effective population size. Computer simulations show that the low nuclear versus mitochondrial mutation rates cannot explain these results. However, ascertainment bias, i.e., when only highly variable SNP sites are typed, may be concealing any Y SNPs evidence for a recent, but not an ancient, increase in male effective population sizes. The results of our SNP analyses can be reconciled with the expansion of male effective population sizes inferred from STR loci, and with mitochondrial evidence, by admitting that humans were essentially polygynous during much of their history. As a consequence, until recently only a few men may have contributed a large fraction of the Y-chromosome pool at every generation. The number of breeding males may have increased, and the variance of their reproductive success may have decreased, through a recent shift from polygyny to monogamy, which is supported by ethnological data and possibly accompanied the shift from mobile to sedentary communities.     

A powerful global test for spliceQTL effects

Statistical methods to test for effects of single nucleotide polymorphisms (SNPs) on exon inclusion exist but often rely on testing of associations between multiple exon–SNP pairs, with sometimes subsequent summarization of results at the gene level. Such approaches require heavy multiple testing corrections and detect mostly events with large effect sizes. We propose here a test to find spliceQTL (splicing quantitative trait loci) effects that takes all exons and all SNPs into account simultaneously. For any chosen gene, this score-based test looks for an association between the set of exon expressions and the set of SNPs, via a random-effects model framework. It is efficient to compute and can be used if the number of SNPs is larger than the number of samples. In addition, the test is powerful in detecting effects that are relatively small for individual exon–SNP pairs but are observed for many pairs. Furthermore, test results are more often replicated across datasets than pairwise testing results. This makes our test more robust to exon–SNP pair-specific effects, which do not extend to multiple pairs within the same gene. We conclude that the test we propose here offers more power and better replicability in the search for spliceQTL effects.     

Characterizing genic and nongenic molecular markers: comparison of microsatellites and SNPs

The implications of transitioning to single nucleotide polymorphism (SNPs) from microsatellite markers (MSs) have been investigated in a number of population genetics studies, but the effect of genomic location on the amount of information each type of marker reveals has not been explored in detail. We developed novel SNP markers flanking 1 kb regions of 13 genic (within gene or <1 kb away from gene) and 13 nongenic (>10 kb from annotated gene) MSs in the threespine stickleback genome to obtain comparable data for both types of markers. We analysed patterns of genetic diversity and divergence on various geographic scales after converting the SNP loci within each genomic region into haplotypes. Marker type (SNP haplotype or MS) and location (genic or nongenic) significantly affected most estimates of population diversity and divergence. Between‐lineage divergence was significantly higher in SNP haplotypes (genic and nongenic), however, within‐lineage divergence was similar between marker types. Most divergence and diversity measures were uncorrelated between markers, except for population differentiation which was correlated between MSs and SNP haplotypes (both genic and nongenic). Broad‐scale population structure and assignment were similarly resolved by both marker types, however, only the MSs were able to delimit fine‐scale population structuring, particularly when genic and nongenic markers were combined. These results demonstrate that estimates of genetic variability and differentiation among populations can be strongly influenced by marker type, their genomic location in relation to genes and by the interaction of these two factors. This highlights the importance of having an awareness of the inherent strengths and limitations associated with different molecular tools to select the most appropriate methods for accurately addressing various ecological and evolutionary questions.     

香菇三个功能基因部分序列的单核苷酸多态性分析

以15个香菇栽培品种为材料,对尿嘧啶核苷酸-胞嘧啶核苷酸激酶基因(UMP-CMP kinase gene,uck1)、分裂原活化蛋白激酶基因(mitogen-activated protein kinase gene,mapk)和外切β-1,3葡聚糖酶基因(exo-β-1,3-glucanase-encoding gene,exg1)进行了部分序列的单核苷酸多态性(single nucleotide polymorphism,SNP)分析。结果表明,测序中出现的双峰,是菌丝双核体细胞中两细胞核之间的差异造成的。在采用uck1、mapk和exg1的3,126bp中,共发现48处多态性位点,发生频率为1/65bp,其中36个属于转换、12个为颠换。从群体发生频率上,38个属于超过10%的常见SNP,10个属于罕见SNP。不同基因的SNP发生频率不同,uck1、mapk和exg1的SNP发生频率分别为1.40%、0.82%和2.41%。外显子区SNP数量高于内含子,3个基因在外显子区域分布28个,内含子分布20个。外显子的28个SNP位点中,11个为错义突变,17个为同义突变。错义突变引起了编码氨基酸的改变。对SNP位点的聚类分析表明,15个栽培品种间存在的多态性位点在1–36之间,15个品种的SNP类型不同。uck1,mapk,exg1的SNP可用于香菇栽培品种的鉴别。     

Gene-associated single nucleotide polymorphism discovery in perennial ryegrass (Lolium perenne L.)

Molecular genetic marker development in perennial ryegrass has largely been dependent on anonymous sequence variation. The availability of a large-scale EST resource permits the development of functionally-associated genetic markers based on SNP variation in candidate genes. Genic SNP loci and associated haplotypes are suitable for implementation in molecular breeding of outbreeding forage species. Strategies for in vitro SNP discovery through amplicon cloning and sequencing have been designed and implemented. Putative SNPs were identified within and between the parents of the F₁(NA₆ × AU₆) genetic mapping family and were validated among progeny individuals. Proof-of-concept for the process was obtained using the drought tolerance-associated LpASRa2 gene. SNP haplotype structures were determined and correlated with predicted amino acid changes. Gene-length LD was evaluated across diverse germplasm collections. A survey of SNP variation across 100 candidate genes revealed a high frequency of SNP incidence (c. 1 per 54 bp), with similar proportions in exons and introns. A proportion (c. 50%) of the validated genic SNPs were assigned to the F₁(NA₆ × AU₆) genetic map, showing high levels of coincidence with previously mapped RFLP loci. The perennial ryegrass SNP resource will enable genetic map integration, detailed LD studies and selection of superior allele content during varietal development.     

Evaluation of linkage disequilibrium and its effect on non-parametric multipoint linkage analysis using two high density single-nucleotide polymorphism mapping panels

Genotype data from the Illumina Linkage III SNP panel (n = 4,720 SNPs) and the Affymetrix 10 k mapping array (n = 11,120 SNPs) were used to test the effects of linkage disequilibrium (LD) between SNPs in a linkage analysis in the Collaborative Study on the Genetics of Alcoholism pedigree collection (143 pedigrees; 1,614 individuals). The average r2 between adjacent markers across the genetic map was 0.099 +/- 0.003 in the Illumina III panel and 0.17 +/- 0.003 in the Affymetrix 10 k array. In order to determine the effect of LD between marker loci in a nonparametric multipoint linkage analysis, markers in strong LD with another marker (r2 > 0.40) were removed (n = 471 loci in the Illumina panel; n = 1,804 loci in the Affymetrix panel) and the linkage analysis results were compared to the results using the entire marker sets. In all analyses using the ALDX1 phenotype, 8 linkage regions on 5 chromosomes (2, 7, 10, 11, X) were detected (peak markers p < 0.01), and the Illumina panel detected an additional region on chromosome 6. Analysis of the same pedigree set and ALDX1 phenotype using short tandem repeat markers (STRs) resulted in 3 linkage regions on 3 chromosomes (peak markers p < 0.01). These results suggest that in this pedigree set, LD between loci with spacing similar to the SNP panels tested may not significantly affect the overall detection of linkage regions in a genome scan. Moreover, since the data quality and information content are greatly improved in the SNP panels over STR genotyping methods, new linkage regions may be identified due to higher information content and data quality in a dense SNP linkage panel.     

Differentiating salmon populations at broad and fine geographical scales with microsatellites and single nucleotide polymorphisms

Single nucleotide polymorphisms (SNPs) are appealing genetic markers due to several beneficial attributes, but uncertainty remains about how many of these bi-allelic markers are necessary to have sufficient power to differentiate populations, a task now generally accomplished with highly polymorphic microsatellite markers. In this study, we tested the utility of 37 SNPs and 13 microsatellites for differentiating 29 broadly distributed populations of Chinook salmon ( n  = 2783). Information content of all loci was determined by In and     , and the top 12 markers ranked by In were microsatellites, but the 6 highest, and 7 of the top 10     ranked markers, were SNPs. The mean ratio of random SNPs to random microsatellites ranged from 3.9 to 4.1, but this ratio was consistently reduced when only the most informative loci were included. Individual assignment test accuracy was higher for microsatellites (73.1%) than SNPs (66.6%), and pooling all 50 markers provided the highest accuracy (83.2%). When marker types were combined, as few as 15 of the top ranked loci provided higher assignment accuracy than either microsatellites or SNPs alone. Neighbour-joining dendrograms revealed similar clustering patterns and pairwise tests of population differentiation had nearly identical results with each suite of markers. Statistical tests and simulations indicated that closely related populations were better differentiated by microsatellites than SNPs. Our results indicate that both types of markers are likely to be useful in population genetics studies and that, in some cases, a combination of SNPs and microsatellites may be the most effective suite of loci.     

Ecologically and evolutionarily important SNPs identified in natural populations

Evolution by natural selection acts on natural populations amidst migration, gene-by-environmental interactions, constraints, and tradeoffs, which affect the rate and frequency of adaptive change. We asked how many and how rapidly loci change in populations subject to severe, recent environmental changes. To address these questions, we used genomic approaches to identify randomly selected single nucleotide polymorphisms (SNPs) with evolutionarily significant patterns in three natural populations of Fundulus heteroclitus that inhabit and have adapted to highly polluted Superfund sites. Three statistical tests identified 1.4-2.5% of SNPs that were significantly different from the neutral model in each polluted population. These nonneutral patterns in populations adapted to highly polluted environments suggest that these loci or closely linked loci are evolving by natural selection. One SNP identified in all polluted populations using all tests is in the gene for the xenobiotic metabolizing enzyme, cytochrome P4501A (CYP1A), which has been identified previously as being refractory to induction in the three highly polluted populations. Extrapolating across the genome, these data suggest that rapid evolutionary change in natural populations can involve hundreds of loci, a few of which will be shared in independent events.     

SSCP-SNP in pearl millet—a new marker system for comparative genetics

A considerable array of genomic resources are in place in pearl millet, and marker-aided selection is already in use in the public breeding programme at ICRISAT. This paper describes experiments to extend these publicly available resources to a single nucleotide polymorphism (SNP)-based marker system. A new marker system, single-strand conformational polymorphism (SSCP)-SNP, was developed using annotated rice genomic sequences to initially predict the intron-exon borders in millet expressed sequence tags (ESTs) and then to design primers that would amplify across the introns. An adequate supply of millet ESTs was available for us to identify 299 homologues of single-copy rice genes in which the intron positions could be precisely predicted. PCR primers were then designed to amplify approximately 500-bp genomic fragments containing introns. Analysis of these fragments on SSCP gels revealed considerable polymorphism. A detailed DNA sequence analysis of variation at four of the SSCP-SNP loci over a panel of eight inbred genotypes showed complex patterns of variation, with about one SNP or indel (insertion-deletion) every 59 bp in the introns, but considerably fewer in the exons. About two-thirds of the variation was derived from SNPs and one-third from indels. Most haplotypes were detected by SSCP. As a marker system, SSCP-SNP has lower development costs than simple sequence repeats (SSRs), because much of the work is in silico, and similar deployment costs and through-put potential. The rates of polymorphism were lower but useable, with a mean PIC of 0.49 relative to 0.72 for SSRs in our eight inbred genotype panel screen. The major advantage of the system is in comparative applications. Syntenic information can be used to target SSCP-SNP markers to specific chromosomal regions or, conversely, SSCP-SNP markers can be used to unravel detailed syntenic relationships in specific parts of the genome. Finally, a preliminary analysis showed that the millet SSCP-SNP primers amplified in other cereals with a success rate of about 50%. There is also considerable potential to promote SSCP-SNP to a COS (conserved orthologous set) marker system for application across species by more specifically designing primers to precisely match the model genome sequence.Electronic Supplementary Material Supplementary material is available for this article at     

Using the dog genome to find single nucleotide polymorphisms in red foxes and other distantly related members of the Canidae

Single nucleotide polymorphisms (SNP) are the ideal marker for characterizing genomic variation but can be difficult to find in nonmodel species. We explored the usefulness of the dog genome for finding SNPs in distantly related nonmodel canids and evaluated so-ascertained SNPs. Using 40 primer pairs designed from randomly selected bacterial artificial chromosome clones from the dog genome, we successfully sequenced 80-88% of loci in a coyote (Canis latrans), grey fox (Urocyon cinereoargenteus), and red fox (Vulpes vulpes), which compared favourably to a 60% success rate for each species using 10 primer pairs conserved across mammals. Loci were minimally heterogeneous with respect to SNP density, which was similar, overall, in a discovery panel of nine red foxes to that previously reported for a panel of eight wolves (Canis lupus). Additionally, individual heterozygosity was similar across the three canids in this study. However, the proportion of SNP sites shared with the dog decreased with phylogenetic divergence, with no SNPs shared between red foxes and dogs. Density of interspecific SNPs increased approximately linearly with divergence time between species. Using red foxes from three populations, we estimated F(ST) based on each of 42 SNPs and 14 microsatellites and simulated null distributions conditioned on each marker type. Relative to SNPs, microsatellites systematically underestimated F(ST) and produced biased null distributions, indicating that SNPs are superior markers for these functions. By reconstituting the frequency spectrum of SNPs discovered in nine red foxes, we discovered an estimated 77-89% of all SNPs (within the region screened) present in North American red foxes. In sum, these findings indicate that information from the dog genome enables easy ascertainment of random and gene-linked SNPs throughout the Canidae and illustrate the value of SNPs in ecological and evolutionary genetics.     

Genomic heterogeneity in the density of noncoding single-nucleotide and microsatellite polymorphisms in Plasmodium falciparum

The density and distribution of single-nucleotide polymorphisms (SNPs) across the genome has important implications for linkage disequilibrium mapping and association studies, and the level of simple-sequence microsatellite polymorphisms has important implications for the use of oligonucleotide hybridization methods to genotype SNPs. To assess the density of these types of polymorphisms in P. falciparum, we sampled introns and noncoding DNA upstream and downstream of coding regions among a variety of geographically diverse parasites. Across 36,229 base pairs of noncoding sequence representing 41 genetic loci, a total of 307 polymorphisms including 248 polymorphic microsatellites and 39 SNPs were identified. We found a significant excess of microsatellite polymorphisms having a repeat unit length of one or two, compared to those with longer repeat lengths, as well as a nonrandom distribution of SNP polymorphisms. Almost half of the SNPs localized to only three of the 41 genetic loci sampled. Furthermore, we find significant differences in the frequency of polymorphisms across the two chromosomes (2 and 3) examined most extensively, with an excess of SNPs and a surplus of polymorphic microsatellites on chromosome 3 as compared to chromosome 2 (P=0.0001). Furthermore, at some individual genetic loci we also find a nonrandom distribution of polymorphisms between coding and flanking noncoding sequences, where completely monomorphic regions may flank highly polymorphic genes. These data, combined with our previous findings of nonrandom distribution of SNPs across chromosome 2, suggest that the Plasmodium falciparum genome may be a mosaic with regard to genetic diversity, containing chromosomal regions that are highly polymorphic interspersed with regions that are much less polymorphic.     

Genome-Wide Characterization of Insertion and Deletion Variation in Chicken Using Next Generation Sequencing

Insertion and deletion (INDEL) is one of the main events contributing to genetic and phenotypic diversity, which receives less attention than SNP and large structural variation. To gain a better knowledge of INDEL variation in chicken genome, we applied next generation sequencing on 12 diverse chicken breeds at an average effective depth of 8.6. Over 1.3 million non-redundant short INDELs (1–49 bp) were obtained, the vast majority (92.48%) of which were novel. Follow-up validation assays confirmed that most (88.00%) of the randomly selected INDELs represent true variations. The majority (95.76%) of INDELs were less than 10 bp. Both the detected number and affected bases were larger for deletions than insertions. In total, INDELs covered 3.8 Mbp, corresponding to 0.36% of the chicken genome. The average genomic INDEL density was estimated as 0.49 per kb. INDELs were ubiquitous and distributed in a non-uniform fashion across chromosomes, with lower INDEL density in micro-chromosomes than in others, and some functional regions like exons and UTRs were prone to less INDELs than introns and intergenic regions. Nearly 620,253 INDELs fell in genic regions, 1,765 (0.28%) of which located in exons, spanning 1,358 (7.56%) unique Ensembl genes. Many of them are associated with economically important traits and some are the homologues of human disease-related genes. We demonstrate that sequencing multiple individuals at a medium depth offers a promising way for reliable identification of INDELs. The coding INDELs are valuable candidates for further elucidation of the association between genotypes and phenotypes. The chicken INDELs revealed by our study can be useful for future studies, including development of INDEL markers, construction of high density linkage map, INDEL arrays design, and hopefully, molecular breeding programs in chicken.     

Multi-locus inference of population structure: a comparison between single nucleotide polymorphisms and microsatellites

Although growing numbers of single nucleotide polymorphisms (SNPs) and microsatellites (short tandem repeat polymorphisms or STRPs) are used to infer population structure, their relative properties in this context remain poorly understood. SNPs and STRPs mutate differently, suggesting multi-locus genotypes at these loci might differ in ability to detect population structure. Here, we use coalescent simulations to measure the power of sets of SNPs and STRPs to identify population structure. To maximize the applicability of our results to empirical studies, we focus on the popular STRUCTURE analysis and evaluate the role of several biological and practical factors in the detection of population structure. We find that: (1) fewer unlinked STRPs than SNPs are needed to detect structure at recent divergence times <0.3 N_e generations; (2) accurate estimation of the number of populations requires many fewer STRPs than SNPs; (3) for both marker types, declines in power due to modest gene flow (N_em=1.0) are largely negated by increasing marker number; (4) variation in the STRP mutational model affects power modestly; (5) SNP haplotypes (θ=1, no recombination) provide power comparable with STRP loci (θ=10); (6) ascertainment schemes that select highly variable STRP or SNP loci increase power to detect structure, though ascertained data may not be suitable to other inference; and (7) when samples are drawn from an admixed population and one of its parent populations, the reduction in power to detect two populations is greater for STRPs than SNPs. These results should assist the design of multi-locus studies to detect population structure in nature.