Using blocks of linked single nucleotide polymorphisms as highly polymorphic genetic markers for parentage analysis

Single nucleotide polymorphisms (SNPs) are plentiful in most genomes and amenable to high throughput genotyping, but they are not yet popular for parentage or paternity analysis. The markers are bi-allelic, so individually they contain little information about parentage, and in nonmodel organisms the process of identifying large numbers of unlinked SNPs can be daunting. We explore the possibility of using blocks of between three and 26 linked SNPs as highly polymorphic molecular markers for reconstructing male genotypes in polyandrous organisms with moderate (five offspring) to large (25 offspring) clutches of offspring. Haplotypes are inferred for each block of linked SNPs using the programs Haplore and Phase 2.1. Each multi-SNP haplotype is then treated as a separate allele, producing a highly polymorphic, 'microsatellite-like' marker. A simulation study is performed using haplotype frequencies derived from empirical data sets from Drosophila melanogaster and Mus musculus populations. We find that the markers produced are competitive with microsatellite loci in terms of single parent exclusion probabilities, particularly when using six or more linked SNPs to form a haplotype. These markers contain only modest rates of missing data and genotyping or phasing errors and thus should be seriously considered as molecular markers for parentage analysis, particularly when the study is interested in the functional significance of polymorphisms across the genome.     

A large‐scale genomic association analysis identifies the candidate causal genes conferring stripe rust resistance under multiple field environments

The incorporation of resistance genes into wheat commercial varieties is the ideal strategy to combat stripe or yellow rust (YR). In a search for novel resistance genes, we performed a large‐scale genomic association analysis with high‐density 660K single nucleotide polymorphism (SNP) arrays to determine the genetic components of YR resistance in 411 spring wheat lines. Following quality control, 371 972 SNPs were screened, covering over 50% of the high‐confidence annotated gene space. Nineteen stable genomic regions harbouring 292 significant SNPs were associated with adult‐plant YR resistance across nine environments. Of these, 14 SNPs were localized in the proximity of known loci widely used in breeding. Obvious candidate SNP variants were identified in certain confidence intervals, such as the cloned gene Yr18 and the major locus on chromosome 2BL, despite a large extent of linkage disequilibrium. The number of causal SNP variants was refined using an independent validation panel and consideration of the estimated functional importance of each nucleotide polymorphism. Interestingly, four natural polymorphisms causing amino acid changes in the gene TraesCS2B01G513100 that encodes a serine/threonine protein kinase (STPK) were significantly involved in YR responses. Gene expression and mutation analysis confirmed that STPK played an important role in YR resistance. PCR markers were developed to identify the favourable TraesCS2B01G513100 haplotype for marker‐assisted breeding. These results demonstrate that high‐resolution SNP‐based GWAS enables the rapid identification of putative resistance genes and can be used to improve the efficiency of marker‐assisted selection in wheat disease resistance breeding.     

Molecular screening and association study of IL15 gene polymorphisms in rheumatoid arthritis

Interleukin 15 (IL-15) is a pleiotropic pro-inflammatory cytokine known to play a relevant role in rheumatoid arthritis (RA) pathogenesis. In this study we aimed to investigate for the first time the contribution of IL15 gene to RA susceptibility. We screened 13 single nucleotide polymorphisms (SNPs) localised within IL15 regulatory regions (promoter, 5' UTR region and 3' UTR region) in a total of 420 individuals, who were genotyped by direct sequencing of PCR products. In addition, an association study of these IL15 SNPs was conducted in three independent case-control cohorts of Spanish Caucasian origin, including a total of 645 RA patients and 656 healthy controls. The presence of the 13 selected IL15 SNPs in our population was confirmed and no new genetic variants were found. The distribution of the IL15 selected SNPs in RA patients and controls showed no statistically significant deviation in any of the populations studied. Additionally, we performed a haplotype analysis that revealed three IL15 haplotype blocks. None of the haplotype blocks was associated with RA susceptibility or severity in the three cohorts analysed. Our results suggest that the IL15 gene polymorphisms do not appear to play a major role in RA genetic predisposition in our population.     

Performance of single nucleotide polymorphisms versus haplotypes for genome-wide association analysis in barley

Genome-wide association studies (GWAS) may benefit from utilizing haplotype information for making marker-phenotype associations. Several rationales for grouping single nucleotide polymorphisms (SNPs) into haplotype blocks exist, but any advantage may depend on such factors as genetic architecture of traits, patterns of linkage disequilibrium in the study population, and marker density. The objective of this study was to explore the utility of haplotypes for GWAS in barley (Hordeum vulgare) to offer a first detailed look at this approach for identifying agronomically important genes in crops. To accomplish this, we used genotype and phenotype data from the Barley Coordinated Agricultural Project and constructed haplotypes using three different methods. Marker-trait associations were tested by the efficient mixed-model association algorithm (EMMA). When QTL were simulated using single SNPs dropped from the marker dataset, a simple sliding window performed as well or better than single SNPs or the more sophisticated methods of blocking SNPs into haplotypes. Moreover, the haplotype analyses performed better 1) when QTL were simulated as polymorphisms that arose subsequent to marker variants, and 2) in analysis of empirical heading date data. These results demonstrate that the information content of haplotypes is dependent on the particular mutational and recombinational history of the QTL and nearby markers. Analysis of the empirical data also confirmed our intuition that the distribution of QTL alleles in nature is often unlike the distribution of marker variants, and hence utilizing haplotype information could capture associations that would elude single SNPs. We recommend routine use of both single SNP and haplotype markers for GWAS to take advantage of the full information content of the genotype data.     

Selection of haplotype variables from a high-density marker map for genomic prediction

Background

Using haplotype blocks as predictors rather than individual single nucleotide polymorphisms (SNPs) may improve genomic predictions, since haplotypes are in stronger linkage disequilibrium with the quantitative trait loci than are individual SNPs. It has also been hypothesized that an appropriate selection of a subset of haplotype blocks can result in similar or better predictive ability than when using the whole set of haplotype blocks. This study investigated genomic prediction using a set of haplotype blocks that contained the SNPs with large effects estimated from an individual SNP prediction model. We analyzed protein yield, fertility and mastitis of Nordic Holstein cattle, and used high-density markers (about 770k SNPs). To reach an optimum number of haplotype variables for genomic prediction, predictions were performed using subsets of haplotype blocks that contained a range of 1000 to 50 000 main SNPs.

Results

The use of haplotype blocks improved the prediction reliabilities, even when selection focused on only a group of haplotype blocks. In this case, the use of haplotype blocks that contained the 20 000 to 50 000 SNPs with the highest effect was sufficient to outperform the model that used all individual SNPs as predictors (up to 1.3 % improvement in prediction reliability for mastitis, compared to individual SNP approach), and the achieved reliabilities were similar to those using all haplotype blocks available in the genome data (from 0.6 % lower to 0.8 % higher reliability).

Conclusions

Haplotype blocks used as predictors can improve the reliability of genomic prediction compared to the individual SNP model. Furthermore, the use of a subset of haplotype blocks that contains the main SNP effects from genomic data could be a feasible approach to genomic prediction in dairy cattle, given an increase in density of genotype data available. The predictive ability of the models that use a subset of haplotype blocks was similar to that obtained using either all haplotype blocks or all individual SNPs, with the benefit of having a much lower computational demand.     

A genome-wide survey reveals a deletion polymorphism associated with resistance to gastrointestinal nematodes in Angus cattle

Gastrointestinal (GI) nematode infections are a worldwide threat to human health and animal production. In this study, we performed a genome-wide association study between copy number variations (CNVs) and resistance to GI nematodes in an Angus cattle population. Using a linear regression analysis, we identified one deletion CNV which reaches genome-wide significance after Bonferroni correction. With multiple mapped human olfactory receptor genes but no annotated bovine genes in the region, this significantly associated CNV displays high population frequencies (58.26 %) with a length of 104.8 kb on chr7. We further investigated the linkage disequilibrium (LD) relationships between this CNV and its nearby single nucleotide polymorphisms (SNPs) and genes. The underlining haplotype blocks contain immune-related genes such as ZNF496 and NLRP3. As this CNV co-segregates with linked SNPs and associated genes, we suspect that it could contribute to the detected variations in gene expression and thus differences in host parasite resistance.     

Evaluating coverage of exons by HapMap SNPs

Genome-wide association (GWA) studies are currently one of the most powerful tools in identifying disease-associated genes or variants. In typical GWA studies, single-nucleotide polymorphisms (SNPs) are often used as genetic makers. Therefore, it is critical to estimate the percentage of genetic variations which can be covered by SNPs through linkage disequilibrium (LD). In this study, we use the concept of haplotype blocks to evaluate the coverage of five SNP sets including the HapMap and four commercial arrays, for every exon in the human genome. We show that although some Chips can reach similar coverage as the HapMap, only about 50% of exons are completely covered by haplotype blocks of HapMap SNPs. We suggest further high-resolution genotyping methods are required, to provide adequate genome-wide power for identifying variants.     

Association mapping of morphological traits in wild and captive zebra finches: reliable within,but not between populations

Identifying causal genetic variants underlying heritable phenotypic variation is a long‐standing goal in evolutionary genetics. We previously identified several quantitative trait loci (QTL) for five morphological traits in a captive population of zebra finches (Taeniopygia guttata) by whole‐genome linkage mapping. We here follow up on these studies with the aim to narrow down on the quantitative trait variants (QTN) in one wild and three captive populations. First, we performed an association study using 672 single nucleotide polymorphisms (SNPs) within candidate genes located in the previously identified QTL regions in a sample of 939 wild‐caught zebra finches. Then, we validated the most promising SNP–phenotype associations (n = 25 SNPs) in 5228 birds from four populations. Genotype–phenotype associations were generally weak in the wild population, where linkage disequilibrium (LD) spans only short genomic distances. In contrast, in captive populations, where LD blocks are large, apparent SNP effects on morphological traits (i.e. associations) were highly repeatable with independent data from the same population. Most of those SNPs also showed significant associations with the same trait in other captive populations, but the direction and magnitude of these effects varied among populations. This suggests that the tested SNPs are not the causal QTN but rather physically linked to them, and that LD between SNPs and causal variants differs between populations due to founder effects. While the identification of QTN remains challenging in nonmodel organisms, we illustrate that it is indeed possible to confirm the location and magnitude of QTL in a population with stable linkage between markers and causal variants.     

Analyses of sequence polymorphism and haplotype diversity of LEAFY genes revealed post-domestication selection in the Chinese elite maize inbred lines

Post-domestication selection refers to the artificial selection on the loci controlling important agronomic traits during the process of genetic improvement in a population. The maize genes Zfl1 and Zfl2, duplicate orthologs of Arabidopsis LEAFY, are key regulators in plant branching, inflorescence and flower development, and reproduction. In this study, the full gene sequences of Zfl1 and Zfl2 from 62 Chinese elite inbred lines were amplified to evaluate their nucleotide polymorphisms and haplotype diversities. A total of 254 and 192 variants that included SNPs and indels were identified from the full sequences of Zfl1 and Zfl2, respectively. Although most of the variants were found to be located in the non-coding regions, the polymorphisms of CDS sequences classified Zfl1 into 16 haplotypes encoding 16 different proteins and Zfl2 into 18 haplotypes encoding eight different proteins. The population of Huangzaosi and its derived lines showed statistically significant signals of post-domestication selection on the Zfl1 CDS sequences, as well as lower nucleotide polymorphism and haplotype diversity than the whole set. However, the Zfl2 locus was only selected for in the heterotic group Reid. Further evidence revealed that at least 17 recombination events contributed to the genetic and haplotype diversities at the Zfl1 locus and 16 recombination events at the Zfl2 locus.     

Comparative assessment of the association information captured by SNP tagging

Exploiting the association between single nucleotide polymorphisms (SNP) can potentially reduce the costs of association mapping of common disease genes. Different methods have been proposed for defining subsets of SNPs as proxies (or tagSNPs) for other SNPs, some of which rely upon a model of haplotype blocks. Other approaches only consider the pair-wise correlation between markers as a basis for selecting tagSNPs. Yet another, recently proposed model-based method takes marker heterozygosity and genetic distance into account in order to maximize the expected utility of a marker set to map frequent, but unobserved genetic variants. We compared these tagging approaches with regard to their ability to correlate tagSNPs and bi-allelic, potentially disease-causing genetic variants. We used the CEU sample of chromosome 19 from the HapMap project for an initial comparison, and demonstrated a comparable performance of both approaches but a difference in terms of tagSNPs selected and variants captured. In any case, we conclude that a considerable loss of information appears to be inherent to any type of SNP tagging, even when dense marker sets are available for SNP selection.     

Utilizing Genotype Imputation for the Augmentation of Sequence Data

Background

In recent years, capabilities for genotyping large sets of single nucleotide polymorphisms (SNPs) has increased considerably with the ability to genotype over 1 million SNP markers across the genome. This advancement in technology has led to an increase in the number of genome-wide association studies (GWAS) for various complex traits. These GWAS have resulted in the implication of over 1500 SNPs associated with disease traits. However, the SNPs identified from these GWAS are not necessarily the functional variants. Therefore, the next phase in GWAS will involve the refining of these putative loci.

Methodology

A next step for GWAS would be to catalog all variants, especially rarer variants, within the detected loci, followed by the association analysis of the detected variants with the disease trait. However, sequencing a locus in a large number of subjects is still relatively expensive. A more cost effective approach would be to sequence a portion of the individuals, followed by the application of genotype imputation methods for imputing markers in the remaining individuals. A potentially attractive alternative option would be to impute based on the 1000 Genomes Project; however, this has the drawbacks of using a reference population that does not necessarily match the disease status and LD pattern of the study population. We explored a variety of approaches for carrying out the imputation using a reference panel consisting of sequence data for a fraction of the study participants using data from both a candidate gene sequencing study and the 1000 Genomes Project.

Conclusions

Imputation of genetic variation based on a proportion of sequenced samples is feasible. Our results indicate the following sequencing study design guidelines which take advantage of the recent advances in genotype imputation methodology: Select the largest and most diverse reference panel for sequencing and genotype as many “anchor” markers as possible.     

Large-scale identification and characterization of genetic variants in asthma candidate genes

Asthma is a chronic inflammatory disorder of the airways, and a number of genetic loci are associated with the disease. Candidate gene association studies have been regarded as effective tools to study complex traits. Knowledge of the sequence variation and structure of the candidate genes is required for association studies. Thus, we investigated the genetic variants of 32 asthma candidate genes selected by colocalization of positional and functional candidate genes. We screened all exons and promoter regions of those genes using 12 healthy individuals and 12 asthma patients and identified a total of 418 single nucleotide polymorphisms (SNPs), including 270 known SNPs and 148 novel SNPs. Levels of nucleotide diversity varied from gene to gene (0.72×10⁻⁴–14.53×10⁻⁴), but the average nucleotide diversity between coding SNPs (cSNPs) and noncoding SNPs was roughly equivalent (4.63×10⁻⁴ vs 4.69×10⁻⁴). However, nucleotide diversity of cSNPs was strongly correlated to codon degeneracy. Nucleotide diversity was much higher at fourfold degenerate sites than at nondegenerate sites (9.42×10⁻⁴ vs 3.14×10⁻⁴). Gene-based haplotype analysis of asthma-associated genes in this study revealed that common haplotypes (frequency >5%) represented 90.5% of chromosomes, and they could be uniquely identified with five or fewer haplotype-tagging SNPs per gene. Therefore, our results may have important implications for the selection of asthma candidate genes and SNP markers for comprehensive association studies using large sample populations.     

The Effect of Genomic Inversions on Estimation of Population Genetic Parameters from SNP Data

In recent years it has emerged that structural variants have a substantial impact on genomic variation. Inversion polymorphisms represent a significant class of structural variant, and despite the challenges in their detection, data on inversions in the human genome are increasing rapidly. Statistical methods for inferring parameters such as the recombination rate and the selection coefficient have generally been developed without accounting for the presence of inversions. Here we exploit new software for simulating inversions in population genetic data, invertFREGENE, to assess the potential impact of inversions on such methods. Using data simulated by invertFREGENE, as well as real data from several sources, we test whether large inversions have a disruptive effect on widely applied population genetics methods for inferring recombination rates, for detecting selection, and for controlling for population structure in genome-wide association studies (GWAS). We find that recombination rates estimated by LDhat are biased downward at inversion loci relative to the true contemporary recombination rates at the loci but that recombination hotspots are not falsely inferred at inversion breakpoints as may have been expected. We find that the integrated haplotype score (iHS) method for detecting selection appears robust to the presence of inversions. Finally, we observe a strong bias in the genome-wide results of principal components analysis (PCA), used to control for population structure in GWAS, in the presence of even a single large inversion, confirming the necessity to thin SNPs by linkage disequilibrium at large physical distances to obtain unbiased results.     

复杂疾病的遗传易感基因区域的精细定位

以单核苷酸多态性(Single-nucleotide polymorphism, SNP)为遗传标记, 采用全基因组关联研究(Genome-wide association studies, GWAS)的策略, 已经在660多种疾病(或性状)中发现了3800多个遗传易感基因区域。但是, 其中最显著关联的遗传变异或致病性的遗传变异位点及其生物学功能并不完全清楚。这些位点的鉴定有助于阐明复杂疾病的生物学机制, 以及发现新的疾病标记物。后GWAS时代的主要任务之一就是通过精细定位研究找到复杂疾病易感基因区域内最显著关联的易感位点或致病性的易感位点并阐明其生物学功能。针对常见变异, 可通过推断或重测序增加SNP密度, 寻找最显著关联的SNP位点, 并通过功能元件分析、表达数量性状位点(Expression quantitative trait locus, eQTL)分析和单体型分析等方法寻找功能性的SNP位点和易感基因。针对罕见变异, 则可采用重测序、罕见单体型分析、家系分析和负荷检验等方法进行精细定位。文章对这些策略和所面临的问题进行了综述。     

Balancing selection and wild gene pool contribute to resistance in global rice germplasm against planthopper

Interactions and co-evolution between plants and herbivorous insects are critically important in agriculture. Brown planthopper (BPH) is the most severe insect of rice, and the biotypes adapt to feed on different rice genotypes. Here, we present genomics analyses on 1,520 global rice germplasms for resistance to three BPH biotypes. Genome-wide association studies identified 3,502 single nucleotide polymorphisms (SNPs) and 59 loci associated with BPH resistance in rice. We cloned a previously unidentified gene Bph37 that confers resistance to BPH. The associated loci showed high nucleotide diversity. Genome-wide scans for trans-species polymorphisms revealed ancient balancing selection at the loci. The secondarily evolved insect biotypes II and III exhibited significantly higher virulence and overcame more rice varieties than the primary biotype I. In response, more SNPs and loci evolved in rice for resistance to biotypes II and III. Notably, three exceptional large regions with high SNP density and resistance-associated loci on chromosomes 4 and 6 appear distinct between the resistant and susceptible rice varieties. Surprisingly, these regions in resistant rice might have been retained from wild species Oryza nivara. Our findings expand the understanding of long-term interactions between rice and BPH and provide resistance genes and germplasm resources for breeding durable BPH-resistant rice varieties.     

A multicenter study confirms CD226 gene association with systemic sclerosis-related pulmonary fibrosis

Introduction

CD226 genetic variants have been associated with a number of autoimmune diseases and recently with systemic sclerosis (SSc). The aim of this study was to test the influence of CD226 loci in SSc susceptibility, clinical phenotypes and autoantibody status in a large multicenter European population.

Methods

A total of seven European populations of Caucasian ancestry were included, comprising 2,131 patients with SSc and 3,966 healthy controls. Three CD226 single nucleotide polymorphisms (SNPs), rs763361, rs3479968 and rs727088, were genotyped using Taqman 5''allelic discrimination assays.

Results

Pooled analyses showed no evidence of association of the three SNPs, neither with the global disease nor with the analyzed subphenotypes. However, haplotype block analysis revealed a significant association for the TCG haplotype (SNP order: rs763361, rs34794968, rs727088) with lung fibrosis positive patients (P_Bonf = 3.18E-02 OR 1.27 (1.05 to 1.54)).

Conclusion

Our data suggest that the tested genetic variants do not individually influence SSc susceptibility but a CD226 three-variant haplotype is related with genetic predisposition to SSc-related pulmonary fibrosis.     

Patterns of linkage disequilibrium in the MHC region on human chromosome 6p

Single nucleotide polymorphisms (SNPs) in the human genome are thought to be organised into blocks of high internal linkage disequilibrium (LD), separated by intermittent recombination hotspots. Since understanding haplotype structure is critical for an accurate assessment of inter-individual genetic differences, we investigated up to 968 SNPs from a 10-Mb region on chromosome 6p21, including the human major histocompatibility complex (MHC), in five different population samples (45–550 individuals). Regions of well-defined block structure were found to coexist alongside large areas lacking any clear structure; occasional long-range LD was observed in all five samples. The four white populations analysed were remarkably similar in terms of the extend and spatial distribution of local LD. In US African Americans, the distribution of LD was similar to that in the white populations but the observed haplotype diversity was higher. The existence of large regions without any clear block structure renders the systematic and thorough construction of SNP haplotype maps a crucial prerequisite for disease-association studies.Electronic Supplementary Material Supplementary material is available in the online version of this article at Electronic database information: URLs for the data in this article are as follows: