Fine‐scale estimation of inbreeding rates, runs of homozygosity and genome‐wide heterozygosity levels in the Mangalarga Marchador horse breed

Abstract

With the availability of high‐density SNP panels and the establishment of approaches for characterizing homozygosity and heterozygosity sites, it is possible to access fine‐scale information regarding genomes, providing more than just comparisons of different inbreeding coefficients. This is the first study that seeks to access such information for the Mangalarga Marchador (MM) horse breed on a genomic scale. To this end, we aimed to assess inbreeding levels using different coefficients, as well as to characterize homozygous and heterozygous runs in the population. Using Axiom ® Equine Genotyping Array—670k SNP (Thermo Fisher), 192 horses were genotyped. Our results showed different estimates: inbreeding from genomic coefficients (FROH) = 0.16; pedigree‐based (FPED) = 0.008; and a method based on excess homozygosity (FHOM) = 0.010. The correlations between the inbreeding coefficients were low to moderate, and some comparisons showed negative correlations, being practically null. In total, 85,295 runs of homozygosity (ROH) and 10,016 runs of heterozygosity (ROHet) were characterized for the 31 horse autosomal chromosomes. The class with the highest percentage of ROH was 0–2 Mbps, with 92.78% of the observations. In the ROHet results, only the 0–2 class presented observations, with chromosome 11 highlighted in a region with high genetic variability. Three regions from the ROHet analyses showed genes with known functions: tripartite motif‐containing 37 (TRIM37), protein phosphatase, Mg2+/Mn2+ dependent 1E (PPM1E) and carbonic anhydrase 10 (CA10). Therefore, our findings suggest moderate inbreeding, possibly attributed to breed formation, annulling possible recent inbreeding. Furthermore, regions with high variability in the MM genome were identified (ROHet), associated with the recent selection and important events in the development and performance of MM horses over generations.

Detection and Visualization of Heterozygosity-Rich Regions and Runs of Homozygosity in Worldwide Sheep Populations

“…Scenario 2 was chosen as the best scenario for the detection of HRR islands, for presenting a high number of HRRs and a satisfactory maximum HRR length, when compared with the other scenarios. The average number of HRRs detected per animal (139.59) was higher than that detected by other authors in turkey (57.80), cattle (9.87), and horse (52.17) populations [ 20 , 23 , 24 ], and similar to the number detected by Ferenčaković et al [ 22 ] in a cattle population (122.52). Most of these studies reported the detection of higher numbers of ROH than HRR; however, our results showed the opposite.…”

“…In this study, we set the minimum number of SNPs within an HRR at 5 or 10, which is lower than the number used for ROH (15) because HRRs are usually reported as being shorter than ROH [23]. The same difference in the parameters was observed in other studies [20,21,24]. We observed that changing the minimal number of SNPs and window size from 10 to 5 did not increase the number of HRRs detected; in fact, the number and length of HRRs detected decreased.…”

“…Few studies have been conducted with the aim of characterizing HRR in livestock, and only one has attempted to identify factors impacting HRR detection, using a low-density SNP chip [ 23 ]. Furthermore, most of the studies on HRRw used high-density SNP chips [ 21 , 22 , 24 ], which have been shown to require other parameters than low density SNP chips for ROH detection [ 17 , 41 ]. The same is most likely true for the identification of HRRs.…”

“…Runs of homozygosity have been extensively studied across many species for the quantification of inbreeding [ 2 , 3 , 9 , 10 , 11 , 12 ], detection of selection signatures [ 13 , 14 , 15 ], and comparison of statistical methods and identification parameters [ 4 , 16 , 17 , 18 , 19 ]. Runs of heterozygosity, most appropriately defined as heterozygosity-rich regions (HRRs) [ 20 ], represents a more recent concept [ 21 ], and is not as well described in the literature as ROH [ 20 , 22 , 23 , 24 ]. HRRs can also provide insights about population structure and demographic history [ 24 ], and these HRRs may harbor important loci for key functional traits such as immune response, survival rate, fertility, and other fitness traits [ 25 ].…”

“…Runs of heterozygosity, most appropriately defined as heterozygosity-rich regions (HRRs) [ 20 ], represents a more recent concept [ 21 ], and is not as well described in the literature as ROH [ 20 , 22 , 23 , 24 ]. HRRs can also provide insights about population structure and demographic history [ 24 ], and these HRRs may harbor important loci for key functional traits such as immune response, survival rate, fertility, and other fitness traits [ 25 ]. To the best of our knowledge, there are no reported studies characterizing HRRs in sheep populations.…”