Misidentification of runs of homozygosity islands in cattle caused by interference with copy number variation or large intermarker distances

Abstract

BackgroundRuns of homozygosity (ROH) islands are stretches of homozygous sequence in the genome of a large proportion of individuals in a population. Algorithms for the detection of ROH depend on the similarity of haplotypes. Coverage gaps and copy number variants (CNV) may result in incorrect identification of such similarity, leading to the detection of ROH islands where none exists. Misidentified hemizygous regions will also appear as homozygous based on sequence variation alone. Our aim was to identify ROH islands influenced by marker coverage gaps or CNV, using Illumina BovineHD BeadChip (777 K) single nucleotide polymorphism (SNP) data for Austrian Brown Swiss, Tyrol Grey and Pinzgauer cattle.MethodsROH were detected using clustering, and ROH islands were determined from population inbreeding levels for each marker. CNV were detected using a multivariate copy number analysis method and a hidden Markov model. SNP coverage gaps were defined as genomic regions with intermarker distances on average longer than 9.24 kb. ROH islands that overlapped CNV regions (CNVR) or SNP coverage gaps were considered as potential artefacts. Permutation tests were used to determine if overlaps between CNVR with copy losses and ROH islands were due to chance. Diversity of the haplotypes in the ROH islands was assessed by haplotype analyses.ResultsIn Brown Swiss, Tyrol Grey and Pinzgauer, we identified 13, 22, and 24 ROH islands covering 26.6, 389.0 and 35.8 Mb, respectively, and we detected 30, 50 and 71 CNVR derived from CNV by using both algorithms, respectively. Overlaps between ROH islands, CNVR or coverage gaps occurred for 7, 14 and 16 ROH islands, respectively. About 37, 44 and 52% of the ROH islands coverage in Brown Swiss, Tyrol Grey and Pinzgauer, respectively, were affected by copy loss. Intersections between ROH islands and CNVR were small, but significantly larger compared to ROH islands at random locations across the genome, implying an association between ROH islands and CNVR. Haplotype diversity for reliable ROH islands was lower than for ROH islands that intersected with copy loss CNVR.ConclusionsOur findings show that a significant proportion of the ROH islands in the bovine genome are artefacts due to CNV or SNP coverage gaps.Electronic supplementary materialThe online version of this article (10.1186/s12711-018-0414-x) contains supplementary material, which is available to authorized users.

Functional and population genetic features of copy number variations in two dairy cattle populations

“…The chromosome-wide coverage varies between 1% on BTA24 and 10% on BTA12 (Additional file 2: Table S4 and Additional file 1: Figure S2). Compared to other cattle CNV studies conducted using the same SNP array and the genome assembly UMD3.1 [22,24,[29][30][31][32], our CNV discovery results are in a similar range (Additional file 2: Table S5).…”

“…We further inspected BTA12:70-77 MB region where a large change between UMD3.1 and ARS-UCD1.2 was observed. This region was reported to have a large number deletion and duplication calls by other cattle CNV studies based on UMD3.1, regardless of the studied breeds [24,[29][30][31][32][33]. In our CNV discovery, we identified 7 CNVRs (total length of~6.2 Mb) in this region based on UMD3.1, whereas ARS-UCD1.2 based results revealed 9 CNVRs that cov-ered~1 Mb.…”

Functional and population genetic features of copy number variations in two dairy cattle populations

“…The chromosome-wide coverage varies between 1% on BTA24 and 10% on BTA12 (Table S4 and Figure S2). Compared to other cattle CNV studies conducted using the same SNP array and the genome assembly UMD3.1 [22,24,[29][30][31][32], our CNV discovery results are in a similar range (Table S5).…”

Low genome‐wide homozygosity in 11 Spanish ovine breeds

“…Moreover, a recent study demonstrated that a significant proportion of ROH islands or hotspots detected in the bovine genome are artifacts due to gaps in SNP coverage as well as to structural variations such as deletions (Nandolo et al . ).…”