Assessment of linkage disequilibrium patterns between structural variants and single nucleotide polymorphisms in three commercial chicken populations

Abstract

Background Structural variants (SV) are causative for some prominent phenotypic traits of livestock as different comb types in chickens or color patterns in pigs. Their effects on production traits are also increasingly studied. Nevertheless, accurately calling SV remains challenging. It is therefore of interest, whether close-by single nucleotide polymorphisms (SNPs) are in strong linkage disequilibrium (LD) with SVs and can serve as markers. Literature comes to different conclusions on whether SVs are in LD to SNPs on the same level as SNPs to other SNPs. The present study aimed to generate a precise SV callset from whole-genome short-read sequencing (WGS) data for three commercial chicken populations and to evaluate LD patterns between the called SVs and surrounding SNPs. It is thereby the first study that assessed LD between SVs and SNPs in chickens. Results The final callset consisted of 12,294,329 bivariate SNPs, 4,301 deletions (DEL), 224 duplications (DUP), 218 inversions (INV) and 117 translocation breakpoints (BND). While average LD between DELs and SNPs was at the same level as between SNPs and SNPs, LD between other SVs and SNPs was strongly reduced (DUP: 40%, INV: 27%, BND: 19% of between-SNP LD). A main factor for the reduced LD was the presence of local minor allele frequency differences, which accounted for 50% of the difference between SNP – SNP and DUP – SNP LD. This was potentially accompanied by lower genotyping accuracies for DUP, INV and BND compared with SNPs and DELs. An evaluation of the presence of tag SNPs (SNP in highest LD to the variant of interest) further revealed DELs to be slightly less tagged by WGS SNPs than WGS SNPs by other SNPs. This difference, however, was no longer present when reducing the pool of potential tag SNPs to SNPs located on four different chicken genotyping arrays. Conclusions The results implied that genomic variance due to DELs in the chicken populations studied can be captured by different SNP marker sets as good as variance from WGS SNPs, whereas separate SV calling might be advisable for DUP, INV, and BND effects.

Fourth Report on Chicken Genes and Chromosomes 2022

“…Considering the constraints of SNP arrays and the reduction of DNA sequencing costs, NGS-based WGS approach is now the most popular tool to infer the evolutionary history of chicken genomes, to assess the genetic diversity and population genetic structure at regional, continental, and global scales, to identify the genetic controls of specific traits of interest, and to screen for the signatures of selection for productive traits and environmental adaptation [Rubin et al, 2010;Mugal et al, 2013;Wang MS et al, 2015, 2016a, 2016bGuo X, , 2022Guo Y et al, , 2021Zhang et al, 2016Zhang et al, , 2022Li D et al, , 2019Boschiero et al, 2018;Derks et al, 2018;Lawal et al, 2018Lawal et al, , 2020Sohrabi et al, 2018;Almeida et al, 2019;Talebi et al, 2020;Tiley et al, 2020;Wang Q et al, 2020;Gheyas et al, 2021Gheyas et al, , 2022Li YD et al, 2021;Mariadassou et al, 2021;Rostamzadeh Mahdabi et al, 2021;Tan et al, 2021;Yang Z et al, 2021;Asadollahpour Nanaei et al, 2022;Chen X et al, 2022;Gao et al, 2022;Geibel et al, 2022;Li Y et al, 2022;Sun et al, 2022;Wang S et al, 2022;Xu et al, 2022;Yuan J et al, 2022;Zeng et al, 2022].…”

“…These two analyses clearly demonstrated the power of the WGS data in CNV identification and functional annotation. Last but not least, the possibility of identifying SVs, though challenging for calling accuracy, was demonstrated from the NGS-WGS of commercial chicken genomes, among which deletions were believed to be more accurately detected compared with duplications, inversions, and translocation breakpoints [Geibel et al, 2022].…”

High-resolution structural variation catalogue in a large-scale whole genome sequenced bovine family cohort data

“…It is worth noting the unique pedigree structure in the data set (127 trios) provided an independent measure of quality evaluation (i.e. Mendelian errors), but also the sequencing was done at relatively high depth (mean sequencing depth = 26X), compared to other studies that investigated SVs in livestock species [33][34][35][36]. Detection of SVs can bene t from high coverage sequencing data in two ways.…”

The big challenge for livestock genomics is to make sequence data pay

“…Yan et al (2021) found that, in humans, about half of their structural variants were in what they term strong to moderate (r 2 > 0.5) linkage disequilibrium with at least one surrounding variant. In the chicken, Geibel et al (2022) found that deletions were well tagged by single nucleotide variants, with linkage disequilibrium comparable to the values between pairs of single nucleotide variants, but that other structural variants types (duplications, inversions, and translocations) were poorly tagged. In this case, however, the structural variants were called with short read sequencing and relatively low coverage, that likely has low accuracy for duplications, inversions and translocations.…”

“…Part of the problem is that structural variants tend to occur in repetitive regions of the genome that are hard to sequence and genotype, and part that structural variants can the genotyping of neighbouring variants, by changing flaking sequence, order of the genetic map, causing null alleles or artificial heterozygotes by duplication and so on. Thus, the low linkage disequilibrium around many structural variants may be partially due to biology and partially due to technical difficulties (Geibel et al, 2022;Yan et al, 2021).…”