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

Abstract

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.Electronic supplementary materialThe online version of this article (10.1186/s12863-019-0713-4) contains supplementary material, which is available to authorized users.

A Comparison between Hi-C and 10X Genomics Linked Read Sequencing for Whole Genome Phasing in Hanwoo Cattle

“…Future studies must benchmark the ability of the sequencing platforms assessed in this study for identifying and phasing other variants such as short insertion-deletion polymorphisms (indels) and structural variations such as larger insertion, deletions, duplications, and copy number variants (CNVs) which may play important roles in many diseases. Moreover, haplotype-based genome-wide association studies are gaining popularity for identifying trait associated genes [34]. Therefore, the ability to phase diploid genomes using long, highly accurate sequence data along with low-cost computation will push haplotype-based genome analysis to higher levels within livestock genomics.…”

A Genome-Wide Association Study for Calving Interval in Holstein Dairy Cows Using Weighted Single-Step Genomic BLUP Approach

“…Fragomeni, et al [42] also reported that small window sizes are accompanied with large noises. Furthermore, it has been shown that single-SNP GWAS cannot be effective enough, because single-SNPs provide limited information about the content of flanking genomic regions [43][44][45]. In the present study, 50-adjacent SNP windows (with an average of 165 Kb widow size) that explained equal to or more than 0.20% of the genetic variance was considered as the threshold for significance.…”

Single‐marker and haplotype‐based association analysis of anthracnose (Colletotrichum dematium)resistance in spinach (Spinacia oleracea)

“…We also performed single‐marker SNP tests to offer a comparison of their sensitivity to that of haplotype‐based markers in the same population. Differences in power and sensitivity of single SNPs compared to haplotypes and how these are calculated have been shown by other studies using simulated and empirical data in pigs and cattle, in humans and in barley (Braz et al, ; Clark, ; Gabriel et al, ; Hamon et al, ; Karimi et al, ; Lorenz et al, ; Meuwissen et al, ; Morris Rw, ; Wu et al, ). In the present study, we therefore concentrated on applying those principles with the aim of exploiting the advantages of single‐SNP and haplotype methods to enhance the detection of polymorphisms with potential roles in spinach–anthracnose interactions.…”

“…A number of studies have rationalized grouping SNPs into haplotype blocks because of the ability to improve power, robustness and accuracy of association mapping in humans (Gabriel et al, ), animals (pigs and cattle) (Karimi, Sargolzaei, JaB, & Schenkel, ; Meuwissen, Odegard, Andersen‐Ranberg, & Grindflek, ) and plants (barley) (Lorenz, Hamblin, & Jannink, ). Using haplotypes may also capture more LD between haplotypes and causal variants (Braz et al, ; Wu et al, ); provide more power than single SNPs when an allelic series exists at a locus (Morris Rw, ); potentially capture epistatic interactions between variants within a haplotyped locus (Clark, ; Hamon et al, ); and even allow informed testing between two alleles showing IBD and clades of haplotype alleles by capturing information from evolutionary history (Calus et al, ; Zhao, ).…”