The distribution of runs of homozygosity in the genome of river and swamp buffaloes reveals a history of adaptation, migration and crossbred events

Abstract

Background Water buffalo is one of the most important livestock species in the world. Two types of water buffalo exist: river buffalo (Bubalus bubalis bubalis) and swamp buffalo (Bubalus bubalis carabanensis). The buffalo genome has been recently sequenced, and thus a new 90 K single nucleotide polymorphism (SNP) bead chip has been developed. In this study, we investigated the genomic population structure and the level of inbreeding of 185 river and 153 swamp buffaloes using runs of homozygosity (ROH). Analyses were carried out jointly and separately for the two buffalo types. Results The SNP bead chip detected in swamp about one-third of the SNPs identified in the river type. In total, 18,116 ROH were detected in the combined data set (17,784 SNPs), and 16,251 of these were unique. ROH were present in both buffalo types mostly detected (~ 59%) in swamp buffalo. The number of ROH per animal was larger and genomic inbreeding was higher in swamp than river buffalo. In the separated datasets (46,891 and 17,690 SNPs for river and swamp type, respectively), 19,760 and 10,581 ROH were found in river and swamp, respectively. The genes that map to the ROH islands are associated with the adaptation to the environment, fitness traits and reproduction. Conclusions Analysis of ROH features in the genome of the two water buffalo types allowed their genomic characterization and highlighted differences between buffalo types and between breeds. A large ROH island on chromosome 2 was shared between river and swamp buffaloes and contained genes that are involved in environmental adaptation and reproduction.

Characterization of Runs of Homozygosity, Heterozygosity-Enriched Regions, and Population Structure in Cattle Populations Selected for Different Breeding Goals

“…As mentioned by Biscarini et al [16], few studies aimed to evaluate the impact of different parameters on ROH detection, with such parameters still not well established. This de nition is of crucial importance, as it has a direct effect on the results obtained [23]; not only in ROH detection, but also in the secondary analyses (e.g., inbreeding coe cient based on ROH).…”

Runs of homozygosity in the Italian goat breeds: impact of management practices in low-input systems

“…We performed two linear mixed models to evaluate the statistical significance of the difference between the ROH parameters identified for each population group [ 23 ] using the statistical software JMP 16 [ 24 ]. We modelized two variables ( ): (i) a standardized ratio between the length of single ROH in each individual and the length of the corresponding chromosome , and (ii) a standardized ratio between the number of ROH on each chromosome of each individual and the length of the chromosome ; both of these models included the same factors: where is the mean, is the fixed effect of the autosome (chromosomes 1 to 29), is the fixed effect of the population group (CSD vs NRD), is the fixed effect of the breed nested within the population groups (n = 20 in CSD and n = 10 in NRD), is the interaction between population group and autosome, is the random effect of the animal, and is the random residual.…”

Inbreeding Calculated with Runs of Homozygosity Suggests Chromosome-Specific Inbreeding Depression Regions in Line 1 Hereford

“…In a population with high inbreeding levels for a long time, such as Line 1 Hereford, the effects of inbreeding depression could be moderate because of selection against deleterious alleles in the population [ 31 ]. As an illustration of that in a bubaline population, Macciota et al [ 32 ] used ROH islands to identify genes associated with environmental adaptation, fitness, and reproduction. In this sense, positive and negative inbreeding may counterbalance, leading to small or no inbreeding depression, as found by Sumreddee [ 7 ] for reproduction traits.…”

“…Studies with ROH in dairy cattle have shown that chromosomal ROH vary widely [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ]. Similarly, in beef cattle the contributions of different chromosomes also fluctuate [ 7 , 34 , 35 ].…”