Extent Of Linkage Disequilibrium Research Articles

Identification of regions under selection and loci controlling agronomic traits in a soft red winter wheat population.

Comprehensive information of a breeding population is a necessity to design promising crosses. This study was conducted to characterize a soft red winter wheat breeding population that was subject of intensive germplasm introductions and introgression from exotic germplasm. We used genome-wide markers and phenotypic assessment to identify signatures of selection and loci controlling agronomic traits in a soft red winter wheat population. The study of linkage disequilibrium (LD) revealed that the extent of LD and its decay varied among chromosomes with chromosomes 2B and 7D showing the most extended islands of high-LD with slow rates of decay. Four sub-populations, two with North American origin and two with Australian and Chinese origins, were identified. Genome-wide scans for selection signatures using FST and hapFLK identified 13 genomic regions under selection, of which five loci (LT, Fr-A2, Vrn-A1, Vrn-B1, Vrn3) were associated with environmental adaptation and two loci were associated with disease resistance genes (Sr36 and Fhb1). Genome-wide association studies identified major loci controlling yield and yield related traits. For days to heading and plant height, major loci with effects sizes of 2.2 days and 5cm were identified on chromosomes 7B and 6A respectively. For test weight, number of spikes per square meter, and number of kernels per square meter, large effect loci were identified on chromosomes 1A, 4B, and 5A, respectively. However, for yield alone, no major loci were detected. A combination of selection for large effect loci for yield components and genomic selection could be a promising approach for yield improvement.

Estimation of Linkage Disequilibrium and Effective Population Size in Three Italian Autochthonous Beef Breeds.

Simple SummaryLinkage disequilibrium (LD) of genomic markers is related to various evolutionary forces, such as inbreeding, nonrandom mating, population bottleneck, drift, recombination, and mutations, and hence is an essential parameter to examine population history. In this analysis, we examined the LD pattern of three Italian local beef breeds (Calvana, Mucca Pisana, and Pontremolese) facing the risk of extinction, using the commercial Limousin beef breed as a control. Our results provide important information on the population history and the current status of the breeds and they can be further used for conservation and breeding purposes.The objective was to investigate the pattern of linkage disequilibrium (LD) in three local beef breeds, namely, Calvana (n = 174), Mucca Pisana (n = 270), and Pontremolese (n = 44). As a control group, samples of the Italian Limousin breed (n = 100) were used. All cattle were genotyped with the GeneSeek GGP-LDv4 33k SNP chip containing 30,111 SNPs. The genotype quality control for each breed was conducted separately, and SNPs with call rate < 0.95 and minor allele frequency (MAF) > 1% were used for the analysis. LD extent was estimated in PLINK v1.9 using the squared correlation between pairs of loci (r2) across autosomes. Moreover, r2 values were used to calculate historical and contemporary effective population size (Ne) in each breed. Average r2 was similar in Calvana and Mucca Pisana (~0.14) and higher in Pontremolese (0.17); Limousin presented the lowest LD extent (0.07). LD up to 0.11–0.15 was persistent in the local breeds up to 0.75 Mbp, while in Limousin, it showed a more rapid decay. Variation of different LD levels across autosomes was observed in all the breeds. The results demonstrated a rapid decrease in Ne across generations for local breeds, and the contemporary population size observed in the local breeds, ranging from 41.7 in Calvana to 17 in Pontremolese, underlined the demographic alarming situation.

Effect of genomic selection on rate of inbreeding and coancestry and effective population size of Holstein and Jersey cattle populations

Genetic diversity in livestock populations is a significant contributor to the sustainability of animal production. Also, genetic diversity allows animal production to become more responsive to environmental changes and market demands. The loss of genetic diversity can result in a plateau in production and may also result in loss of fitness or viability in animal production. In this study, we investigated the rate of inbreeding (ΔF), rate of coancestry (Δf), and effective population size (Ne) as important quantitative indicators of genetic diversity and evaluated the effect of the recent implementation of genomic selection on the loss of genetic diversity in North American Holstein and Jersey dairy cattle. To estimate the rate of inbreeding and coancestry, inbreeding and coancestry coefficients were calculated using the traditional pedigree method and genomic methods estimated from segment- and marker-based approaches. Furthermore, we estimated Ne from the rate of inbreeding and coancestry and extent of linkage disequilibrium. A total of 205,755 and 89,238 pedigreed and genotyped animals born between 1990 and 2018 inclusively were available for Holsteins and Jerseys, respectively. The estimated average pedigree inbreeding coefficients were 7.74 and 7.20% for Holsteins and Jerseys, respectively. The corresponding values for the segment and marker-by-marker genomic inbreeding coefficients were 13.61, 15.64, and 31.40% for Holsteins and 21.16, 22.54, and 42.62% for Jerseys, respectively. The average coancestry coefficients were 8.33 and 15.84% for Holsteins and 9.23 and 23.46% for Jerseys with pedigree and genomic measures, respectively. Generation interval for the whole 29-yr time period averaged approximately 5 yr for all selection pathways combined. The ΔF per generation based on pedigree, segment, and marker-by-marker genomic measures for the entire 29-yr period was estimated to be 0.75, 1.10, 1.16, and 1.02% for Holstein animals and 0.67, 0.62, 0.63, and 0.59% for Jersey animals, respectively. The Δf was estimated to be 0.98 and 0.98% for Holsteins and 0.73 and 0.78% for Jerseys with pedigree and genomic measures, respectively. These ΔF and Δf translated to an Ne that ranged from 43 to 66 animals for Holsteins and 64 to 85 animals for Jerseys. In addition, the Ne based on linkage disequilibrium was 58 and 120 for Holsteins and Jerseys, respectively. The 10-yr period that involved the application of genomic selection resulted in an increased ΔF per generation with ranges from 1.19 to 2.06% for pedigree and genomic measures in Holsteins. Given the rate at which inbreeding is increasing after the implementation of genomic selection, there is a need to implement measures and means for controlling the rate of inbreeding per year, which will help to manage and maintain farm animal genetic resources.

IntAssoPlot: An R Package for Integrated Visualization of Genome-Wide Association Study Results With Gene Structure and Linkage Disequilibrium Matrix.

Genome-wide association study (GWAS), exploring the historical and evolutionary recombinations at the population level, is a major method adopted to identify quantitative trait loci (QTL) for complex traits. However, to summarize GWAS results, gene structure, and linkage disequilibrium (LD) in a single view, multiple tools are required. It is tedious to generate these three results and manually put them together; moreover, it may eventually lead to inaccuracies. On the other hand, genotype markers are usually detected by DNA- and/or RNA-Seq. For GWAS analysis based on RNA-Seq, markers from DNA-Seq provide more genetic information when displaying LD. The currently released software package does not have this function for an integrated analysis of LD, using genotypic markers different from that in association analysis. Here, we present an R package, IntAssoPlot, which provides an integrated visual display of GWAS results, along with LD and gene structure information, in a publication-ready format. The main panel of an IntAssoPlot plot has a connecting line linking the genome-wide association P-values on the -log10 scale with the gene structure and LD matrix. Importantly, IntAssoPlot is designed to plot GWAS results with LD calculated from genotypes different from those in GWAS analysis. IntAssoPlot provides a powerful visualization tool to gain an integrated insight into GWAS results. The functions provided by IntAssoPlot increase the efficiency by revealing GWAS results in a publication-ready format. Inspection of the output image can provide important biological information, including the loci that passed the genome-wide significance threshold, genes located at or near the significant loci, and the extent of LD within the selected region.

Genome-wide SNP discovery through genotyping by sequencing, population structure, and linkage disequilibrium in Brazilian peach breeding germplasm

Genotyping by sequencing (GBS) is a flexible and cost-effective strategy for genome-wide SNP discovery and high-throughput genotyping. Here, we employed the GBS approach to explore population structure, genetic variability, and patterns of linkage disequilibrium (LD) among 220 peach genotypes (Prunus persica), representative of the Brazilian breeding germplasm. This selected panel is mainly composed by locally adapted peaches developed in mild winter and high relative humidity conditions, and represents a worldwide reference of peach germplasm for low-chilling areas. A total of 93,353 SNP markers were discovered, and after filtering, 18,373 high-quality SNPs were used in analyses. Thirty-four percent of selected SNPs were located in genic regions and about 70% of these in the coding sequence. Principal coordinate analysis (PCoA) and Bayesian clustering (fastSTRUCTURE) successfully detected population genetic structure in our germplasm panel, supporting the identification of three main distinct subpopulations. The distribution of the genotypes within subpopulations reflected their fruit-related traits: melting and non-melting flesh cultivars. LD patterns revealed a medium LD level in peach, with the extent of LD highly dependent on the subpopulation and genome regions. The use of GBS-SNPs to perform genome-wide association studies (GWAS) was also exploited by using phenotypic information from five fruit quality traits. The observed significant SNP-trait associations were always in the regions previously predicted by linkage and association mapping analysis, providing valuable insights to incorporate the use of marker-assisted selection in the breeding program.

LD-annot: A Bioinformatics Tool to Automatically Provide Candidate SNPs With Annotations for Genetically Linked Genes.

A multitude of model and non-model species studies have now taken full advantage of powerful high-throughput genotyping advances such as SNP arrays and genotyping-by-sequencing (GBS) technology to investigate the genetic basis of trait variation. However, due to incomplete genome coverage by these technologies, the identified SNPs are likely in linkage disequilibrium (LD) with the causal polymorphisms, rather than be causal themselves. In addition, researchers could benefit from annotations for the identified candidate SNPs and, simultaneously, for all neighboring genes in genetic linkage. In such case, LD extent estimation surrounding the candidate SNPs is required to determine the regions encompassing genes of interest. We describe here an automated pipeline, “LD-annot,” designed to delineate specific regions of interest for a given experiment and candidate polymorphisms on the basis of LD extent, and furthermore, provide annotations for all genes within such regions. LD-annot uses standard file formats, bioinformatics tools, and languages to provide identifiers, coordinates, and annotations for genes in genetic linkage with each candidate polymorphism. Although the focus lies upon SNP arrays and GBS data as they are being routinely deployed, this pipeline can be applied to a variety of datasets as long as genotypic data are available for a high number of polymorphisms and formatted into a vcf file. A checkpoint procedure in the pipeline allows to test several threshold values for linkage without having to rerun the entire pipeline, thus saving the user computational time and resources. We applied this new pipeline to four different sample sets: two breeding populations GBS datasets, one within-pedigree SNP set coming from whole genome sequencing (WGS), and a very large multi-varieties SNP dataset obtained from WGS, representing variable sample sizes, and numbers of polymorphisms. LD-annot performed within minutes, even when very high numbers of polymorphisms are investigated and thus will efficiently assist research efforts aimed at identifying biologically meaningful genetic polymorphisms underlying phenotypic variation. LD-annot tool is available under a GPL license from https://github.com/ArnaudDroitLab/LD-annot.

Detection of Haplotypic Structure for Genome of Azerbaijani Buffalo Using High Density SNP Markers

The aim of this study was to determine genome-wide haplotype block structure, extent of linkage disequilibrium (LD) and effective population size using the information obtained from 243 Azerbaijani buffalo (Axiom® Buffalo Genotyping 90 K) using a high density SNP panel. After quality control, 62,141 SNP markers remained for population structure analysis and identification of haplotype blocks. The extent of LD was measured by the square of correlation coefficient (r2) between alleles. The maximum LD varied from 0.25 to 0.29 at a distance of <2.5 kb, and the minimum average values of r2 varied from 0.012 to 0.014 at distances ranging from 900 to 1000 kb. Overall, 1693 blocks were observed through the genome. Eleven percent of all SNPs were clustered into haplotype blocks, covering 202 ± 3.4 Mb of the total autosomal genome size. Using formula which relate expected LD to effective population size (Ne), and assuming a constant actual population size, Ne was 422 in our population.

275years of forestry meets genomics in Pinus sylvestris.

Pinus sylvestris has a long history of basic and applied research that is relevant for both forestry and evolutionary studies. Its patterns of adaptive variation and role in forest economic and ecological systems have been studied extensively for nearly 275 years, detailed demography for a 100 years and mating system more than 50 years. However, its reference genome sequence is not yet available and genomic studies have been lagging compared to, for example, Pinus taeda and Picea abies, two other economically important conifers. Despite the lack of reference genome, many modern genomic methods are applicable for a more detailed look at its biological characteristics. For example, RNA‐seq has revealed a complex transcriptional landscape and targeted DNA sequencing displays an excess of rare variants and geographically homogenously distributed molecular genetic diversity. Current DNA and RNA resources can be used as a reference for gene expression studies, SNP discovery, and further targeted sequencing. In the future, specific consequences of the large genome size, such as functional effects of regulatory open chromatin regions and transposable elements, should be investigated more carefully. For forest breeding and long‐term management purposes, genomic data can help in assessing the genetic basis of inbreeding depression and the application of genomic tools for genomic prediction and relatedness estimates. Given the challenges of breeding (long generation time, no easy vegetative propagation) and the economic importance, application of genomic tools has a potential to have a considerable impact. Here, we explore how genomic characteristics of P. sylvestris, such as rare alleles and the low extent of linkage disequilibrium, impact the applicability and power of the tools.

Genetic Diversity of Indigenous Pigs from South China Area Revealed by SNP Array.

Simple SummaryThe pig is one of the most important livestock animals, providing the majority of protein for humans. The population genetics analysis of pigs not only helps humans understand the domestication of the pig but also helps breeders in the genetic improvement of pigs. In this study, the population genetics of 11 pig breeds of South China were analyzed with the help of single nucleotide polymorphism (SNP) chips. The results showed that the genetic diversity of South China indigenous pigs is declining rapidly, and gene introgression from commercial pigs to indigenous pigs was detected. Selection signature analysis showed differences among South China indigenous pig breeds, commercial pig breeds, and wild pig breeds were present for meat quality and growth. Our study deepened understanding of the conservation status and selection mechanisms of Chinese indigenous pigs.To investigate the genetic diversity, population structure, extent of linkage disequilibrium (LD), effective population size (Ne), and selection signatures in indigenous pigs from Guangdong and Guangxi in China, 226 pigs belonging to ten diverse populations were genotyped using single nucleotide polymorphism (SNP) chips. The genetic divergence between Chinese and Western pigs was determined based on the SNP chip data. Low genetic diversity of Dahuabai (DHB), Luchuan (LC), Lantang (LT), and Meihua (MH) pigs, and introgression of Western pigs into Longlin (LL), MH, and Yuedonghei (YDH) pigs were detected. Analysis of the extent of LD showed that indigenous pigs had low LD when pairwise SNP distance was short and high LD when pairwise SNP distance was long. Effective population size analysis showed a rapid decrease for Chinese indigenous pigs, and some pig populations had a relatively small Ne. This result indicated the loss of genetic diversity in indigenous pigs, and introgression from Western commercial pigs. Selection signatures detected in this study overlapped with meat quality traits, such as drip loss, intramuscular fat content, meat color b*, and average backfat thickness. Our study deepened understanding of the conservation status and domestication of Chinese indigenous pigs.

Drug-response related genetic architecture of Bangladeshi population

Many Single Nucleotide Polymorphisms (SNPs) have been discovered to be responsible for inter-individual variability in drug response. Since allelic distribution and extent of linkage disequilibrium (LD) blocks of SNPs vary among populations, frequencies of different SNP alleles associated with drug response and patterns of LD should be analyzed separately for different populations. In the present study, we listed the SNPs associated with drug response along with the responsive drugs and calculated the frequencies of the major and minor alleles in the genomes of Bangladeshi individuals. We then analyzed the genotypic data to find LD blocks, tag SNPs (tSNP), frequencies of different haplotypes and association (crossover rates) between different LD blocks of the drug response related SNPs. Among 156 non-redundant autosomal drug response related SNPs, there are nineteen LD blocks and five tSNPs in Bangladeshi population. Certain minor SNP alleles in worldwide population are present as the major ones (with frequencies ≥0.5) in Bangladeshi population. Based on the available SNP data in the 1000 genome database, these particular SNP alleles have similar distributions in other South Asian populations (Telegu and Gujrati Indian, Punjabi Pakistani and Sri Lankan Tamil).

Selection of trait-specific markers and multi-environment models improve genomic predictive ability in rice.

Developing high yielding rice varieties that are tolerant to drought stress is crucial for the sustainable livelihood of rice farmers in rainfed rice cropping ecosystems. Genomic selection (GS) promises to be an effective breeding option for these complex traits. We evaluated the effectiveness of two rather new options in the implementation of GS: trait and environment-specific marker selection and the use of multi-environment prediction models. A reference population of 280 rainfed lowland accessions endowed with 215k SNP markers data was phenotyped under a favorable and two managed drought environments. Trait-specific SNP subsets (28k) were selected for each trait under each environment, using results of GWAS performed with the complete genotype dataset. Performances of single-environment and multi-environment genomic prediction models were compared using kernel regression based methods (GBLUP and RKHS) under two cross validation scenarios: availability (CV2) or not (CV1) of phenotypic data for the validation set, in one of the environments. Trait-specific marker selection strategy achieved predictive ability (PA) of genomic prediction up to 22% higher than markers selected on the bases of neutral linkage disequilibrium (LD). Tolerance to drought stress was up to 32% better predicted by multi-environment models (especially RKHS based models) under CV2 strategy. Under the less favorable CV1 strategy, the multi-environment models achieved similar PA than the single-environment predictions. We also showed that reasonable PA could be obtained with as few as 3,000 SNP markers, even in a population of low LD extent, provided marker selection is based on pairwise LD. The implications of these findings for breeding for drought tolerance are discussed. The most resource sparing option would be accurate phenotyping of the reference population in a favorable environment and under a managed drought, while the candidate population would be phenotyped only under one of those environments.

Heterogeneity in the extent of linkage disequilibrium among exonic, intronic, non-coding RNA and intergenic chromosome regions.

Whole-genome sequence data enable construction of high-resolution linkage disequilibrium (LD) maps revealing the LD structure of functional elements within genic and subgenic sequences. The Malecot-Morton model defines LD map distances in linkage disequilibrium units (LDUs), analogous to the centimorgan scale of linkage maps. For whole-genome sequence-derived LD maps, we introduce the ratio of corresponding map lengths kilobases/LDU to describe the extent of LD within genome components. The extent of LD is highly variable across the genome ranging from ~38 kb for intergenic sequences to ~858 kb for centromeric regions. LD is ~16% more extensive in genic, compared with intergenic sequences, reflecting relatively increased selection and/or reduced recombination in genes. The LD profile across 18,268 autosomal genes reveals reduced extent of LD, consistent with elevated recombination, in exonic regions near the 5' end of genes but more extensive LD, compared with intronic sequences, across more centrally located exons. Genes classified as essential and genes linked to Mendelian phenotypes show more extensive LD compared with genes associated with complex traits, perhaps reflecting differences in selective pressure. Significant differences between exonic, intronic and intergenic components demonstrate that fine-scale LD structure provides important insights into genome function, which cannot be revealed by LD analysis of much lower resolution array-based genotyping and conventional linkage maps.

Linkage disequilibrium and within-breed genetic diversity in Iranian Zandi sheep.

This research aimed to measure the extent of linkage disequilibrium (LD), effective population size (), and runs of homozygosity (ROHs) in one of the major Iranian sheep breeds (Zandi) using 96 samples genotyped with Illumina Ovine SNP50 BeadChip. The amount of LD () for single-nucleotide polymorphism (SNP) pairs in short distances (10–20 kb) was but rapidly decreased to by increasing the distance between SNP pairs (40–60 kb). The of Zandi sheep in past (approximately 3500 generations ago) and recent (five generations ago) populations was estimated to be 6475 and 122, respectively. The ROH-based inbreeding was 0.023. We found 558 ROH regions, of which 37 % were relatively long ( Mb). Compared with the rate of LD reduction in other species (e.g., cattle and pigs), in Zandi, it was reduced more rapidly by increasing the distance between SNP pairs. According to the LD pattern and high genetic diversity of Zandi sheep, we need to use an SNP panel with a higher density than Illumina Ovine SNP50 BeadChip for genomic selection and genome-wide association studies in this breed.

Genome-wide genotyping uncovers genetic diversity, phylogeny, signatures of selection, and population structure of Chinese Jiangquhai pigs in a global perspective1.

Jiangquhai pigs are one of the 42 representative local breeds listed in the national livestock genetic resources conservation project of China. This breed is known for its prolificacy, desirable meat quality, and excellent adaptability to crude feed and local environments. In this study, we genotyped 105 Jiangquhai pigs from the state conservation farm using GeneSeek GGP Porcine 80K SNP chip, and explored the SNP data to unravel genetic diversity, evolutionary phylogeny, signatures of selection, and population structure of Jiangquhai pigs in a context of 33 global breeds. Five indices of observed heterozygosity, expected heterozygosity, effective population size, runs of homozygosity, and linkage disequilibrium extent indicate that the Jiangquhai breed are still rich in genetic diversity in comparison with other breeds also from East China despite the recent decline of its population size. Phylogenetic, principal component, TreeMix, and admixture analyses show that Jiangquhai pigs represent an authentic genetic resource and have close genetic relationships with East Chinese breeds, their geographical neighbors. A genome scan unravels a list of reproduction-related genes potentially under selection in Jiangquhai pigs. Using the neighbor-joining clustering approach, we reconstructed the family structure of the conservation population of Jiangquhai pigs. This finding allowed us to suggest a rotational mating scheme across the reconstructed families to reduce the risk of inbreeding depression in the population.

Evaluation of Linkage Disequilibrium, Effective Population Size and Haplotype Block Structure in Chinese Cattle.

Simple SummaryEvaluation of the population structure and linkage disequilibrium can offer important insights to fully understand the genetic diversity and population history of cattle, which can enable us to appropriately design and implement GWAS and GS in cattle. In this study, we characterized the extent of genome-wide LD and the haplotype block structure, and estimated the persistence of phase of Chinese indigenous cattle with Illumina BovineHD BeadChip. According to our study, 58K, 87K, 95K, 52K, and 52K markers would be necessary for SCHC, NCC, SWC, SIM, and WAG, respectively, in the implementation of GWAS and GS and combining a multipopulation with high persistence of phase is feasible for the implication of genomic selection for Chinese beef cattle.Understanding the linkage disequilibrium (LD) across the genome, haplotype structure, and persistence of phase between breeds can enable us to appropriately design and implement the genome-wide association (GWAS) and genomic selection (GS) in beef cattle. We estimated the extent of genome-wide LD, haplotype block structure, and the persistence of phase in 10 Chinese cattle population using high density BovinHD BeadChip. The overall LD measured by r2 between adjacent SNPs were 0.60, 0.67, 0.58, 0.73, and 0.71 for South Chinese cattle (SCHC), North Chinese cattle (NCC), Southwest Chinese cattle (SWC), Simmental (SIM), and Wagyu (WAG). The highest correlation (0.53) for persistence of phase across groups was observed for SCHC vs. SWC at distances of 0–50 kb, while the lowest correlation was 0.13 for SIM vs. SCHC at the same distances. In addition, the estimated current effective population sizes were 27, 14, 31, 34, and 43 for SCHC, NCC, SWC, SIM, and WAG, respectively. Our result showed that 58K, 87K, 95K, 52K, and 52K markers were required for implementation of GWAS and GS in SCHC, NCC, SWC, SIM, and WAG, respectively. Also, our findings suggested that the implication of genomic selection for multipopulation with high persistence of phase is feasible for Chinese cattle.

Population structure, genetic diversity and linkage disequilibrium in a macadamia breeding population using SNP and silicoDArT markers

Macadamia (Macadamia integrifolia Maiden & Betche, Macadamia tetraphylla L.A.S. Johnson and their hybrids) is grown commercially around the world for its high-quality edible kernel. Traditional breeding efforts involve crossing varieties to produce thousands of progeny seedlings for evaluation. Cultivar improvement for nut yield using component traits and genomics are options for macadamia breeding, but accurate knowledge of genetic diversity and structure of the breeding population is required. This study reports allelic diversity within and between families of 295 seedling offspring from 29 parents, population structure and the extent of linkage disequilibrium (LD) in the population. Genotyping generated 19,527 silicoDArT and 5329 SNP markers, and, after filtering, 16,171 silicoDArTs and 4113 SNPs were used for diversity analyses. LD decay was initially rapid at short distances, but low-level LD persisted for long distances, with an average r2 = 0.124 for SNPs within 1 kb of each other. The seedling population was relatively genetically diverse and very similar to that of the 29 parents. The diversity (HE = 0.255 for progeny and 0.250 for parents) among these individuals indicates the level of diversity at the wider population level in the breeding programme, though the population appears less diverse than other fruit crops. Macadamia progeny was moderately differentiated (FST = 0.401) and formed k = 3 distinct clusters, which represents M. integrifolia germplasm separating from two different hybrid groups. There was low to no relationship between heterozygosity and performance for nut yield among progeny. These findings will inform future genomic studies of the Australian macadamia breeding programme, such as genome-wide association studies and genomic selection, where knowledge and control of population structure are vital.

Impact of polymorphic transposable elements on linkage disequilibrium along chromosomes.

Recombination and selection drive the extent of linkage disequilibrium (LD) among loci and therefore affect the reshuffling of adaptive genetic variation. However, it is poorly known to what extent the enrichment of transposable elements (TEs) in recombinationally-inert regions reflects their inefficient removal by purifying selection and whether the presence of polymorphic TEs can modify the local recombination rate. In this study, we investigate how TEs and recombination interact at fine scale along chromosomes and possibly support linked selection in natural populations. Whole-genome sequencing data of 304 individuals from nearby alpine populations of Arabis alpina were used to show that the density of polymorphic TEs is specifically correlated with local LD along chromosomes. Consistent with TEs modifying recombination, the characterization of 28 such LD blocks of up to 5.5Mb in length revealed strong evidence of selective sweeps at a few loci through either site frequency spectrum or haplotype structure. A majority of these blocks were enriched in genes related to ecologically relevant functions such as responses to cold, salt stress or photoperiodism. In particular, the S-locus (i.e., supergene responsible for strict outcrossing) was identified in a LD block with high levels of polymorphic TEs and evidence of selection. Another such LD block was enriched in cold-responding genes and presented evidence of adaptive loci related to photoperiodism and flowering being increasingly linked by polymorphic TEs. These results are consistent with the hypothesis that TEs modify recombination landscapes and thus interact with selection in driving blocks of linked adaptive loci in natural populations.

Genomic structure of a crossbred Landrace pig population.

Single nucleotide polymorphism (SNP) markers are used to study population structure and conservation genetics, which permits assessing similarities regarding the linkage disequilibrium and information about the relationship among individuals. To investigate the population genomic structure of 300 females and 25 males from a commercial maternal pig line we analyzed linkage disequilibrium extent, inbreeding coefficients using genomic and conventional pedigree data, and population stratification. The average linkage disequilibrium (r2) was 0.291 ± 0.312 for all adjacent SNPs, distancing less than 100 Kb (kilobase) between markers. The average inbreeding coefficients obtained from runs of homozygosity (ROH) and pedigree analyses were 0.119 and 0.0001, respectively. Low correlation was observed between the inbreeding coefficients possibly as a result of genetic recombination effect accounted for the ROH estimates or caused by pedigree identification errors. A large number of long ROHs might indicate recent inbreeding events in the studied population. A total of 36 homozygous segments were found in more than 30% of the population and these ROH harbor genes associated with reproductive traits. The population stratification analysis indicated that this population was possibly originated from two distinct populations, which is a result from crossings between the eastern and western breeds used in the formation of the line. Our findings provide support to understand the genetic structure of swine populations and may assist breeding companies to avoid a high level of inbreeding coefficients to maintain genetic diversity, showing the effectiveness of using genome-wide SNP information for quantifying inbreeding when the pedigree was incomplete or incorrect.

Sliding window haplotype approaches overcome single SNP analysis limitations in identifying genes for meat tenderness in Nelore cattle

BackgroundTraditional single nucleotide polymorphism (SNP) genome-wide association analysis (GWAA) can be inefficient because single SNPs provide limited genetic information about genomic regions. On the other hand, using haplotypes in the statistical analysis may increase the extent of linkage disequilibrium (LD) between haplotypes and causal variants and may also potentially capture epistastic interactions between variants within a haplotyped locus, providing an increase in the power and robustness of the association studies. We performed GWAA (413,355 SNP markers) using haplotypes based on variable-sized sliding windows and compared the results to a single-SNP GWAA using Warner-Bratzler shear force measured in the longissimus thorasis muscle of 3161 Nelore bulls to ascertain the optimal window size for identifying the genomic regions that influence meat tenderness.ResultsThe GWAA using single SNPs identified eight variants influencing meat tenderness on BTA 3, 4, 9, 10 and 11. However, thirty-three putative meat tenderness QTL were detected on BTA 1, 3, 4, 5, 8, 9, 10, 11, 15, 17, 18, 24, 25, 26 and 29 using variable-sized sliding haplotype windows. Analyses using sliding window haplotypes of 3, 5, 7, 9 and 11 SNPs identified 57, 61, 42, 39, and 21% of all thirty-three putative QTL regions, respectively; however, the analyses using the 3 and 5 SNP haplotypes, cumulatively detected 88% of the putative QTL. The genes associated with variation in meat tenderness participate in myogenesis, neurogenesis, lipid and fatty acid metabolism and skeletal muscle structure or composition processes.ConclusionsGWAA using haplotypes based on variable-sized sliding windows allowed the detection of more QTL than traditional single-SNP GWAA. Analyses using smaller haplotypes (3 and 5 SNPs) detected a higher proportion of the putative QTL.

Genome-Wide SNP Data Revealed the Extent of Linkage Disequilibrium, Persistence of Phase and Effective Population Size in Purebred and Crossbred Buffalo Populations.

Linkage disequilibrium (LD) is a useful parameter for guiding the accuracy and power of both genome-wide association studies (GWAS) and genomic selection (GS) among different livestock species. The present study evaluated the extent of LD, persistence of phase and effective population size (Ne) for the purebred (Mediterranean buffalo; n = 411) and crossbred [Mediterranean × Jianghan × Nili-Ravi buffalo, n = 9; Murrah × Nili-Ravi × local (Xilin or Fuzhong) buffalo, n = 36] buffalo populations using the 90K Buffalo SNP genotyping array. The results showed that the average square of correlation coefficient (r2) between adjacent SNP was 0.13 ± 0.19 across all autosomes for purebred and 0.09 ± 0.13 for crossbred, and the most rapid decline in LD was observed over the first 200 kb. Estimated r2 ≥ 0.2 extended up to ~50 kb in crossbred and 170 kb in purebred populations, while average r2 values ≥0.3 were respectively observed in the ~10 and 60 kb in the crossbred and purebred populations. The largest phase correlation (RP, C = 0.47) was observed at the distance of 100 kb, suggesting that this phase was not actively preserved between the two populations. Estimated Ne for the purebred and crossbred population at the current generation was 387 and 113 individuals, respectively. These findings may provide useful information to guide the GS and GWAS in buffaloes.