Linkage disequilibrium, persistence of phase, and effective population size in Spanish local beef cattle breeds assessed through a high-density single nucleotide polymorphism chip1

Abstract

Linkage disequilibrium (LD) and persistence of phase are fundamental approaches for exploring the genetic basis of economically important traits in cattle, including the identification of QTL for genomic selection and the estimation of effective population size () to determine the size of the training populations. In this study, we have used the Illumina BovineHD chip in 168 trios of 7 Spanish beef cattle breeds to obtain an overview of the magnitude of LD and the persistence of LD phase through the physical distance between markers. Also, we estimated the time of divergence based on the persistence of the LD phase and calculated past from LD estimates using different alternatives to define the recombination rate. Estimates of average (as a measure of LD) for adjacent markers were close to 0.52 in the 7 breeds and decreased with the distance between markers, although in long distances, some LD still remained (0.07 and 0.05 for markers 200 kb and 1 Mb apart, respectively). A panel with a lower boundary of 38,000 SNP would be necessary to launch a successful within-breed genomic selection program. Persistence of phase, measured as the pairwise correlations between estimates of in 2 breeds at short distances (10 kb), was in the 0.89 to 0.94 range and decreased from 0.33 to 0.52 to a range of 0.01 to 0.08 when marker distance increased from 200 kb to 1 Mb, respectively. The magnitude of the persistence of phase between the Spanish beef breeds was similar to those found in dairy breeds. For across-breed genomic selection, the size of the SNP panels must be in the range of 50,000 to 83,000 SNP. Estimates of past showed values ranging from 26 to 31 for 1 generation ago in all breeds. The divergence among breeds occurred between 129 and 207 generations ago. The results of this study are relevant for the future implementation of within- and across-breed genomic selection programs in the Spanish beef cattle populations. Our results suggest that a reduced subset of the SNP panel would be enough to achieve an adequate precision of the genomic predictions.

Performance of genomic selection under a single‐step approach in autochthonous Spanish beef cattle populations

“…This result confirms the postulates of Cañas‐Álvarez et al. () who suggested that the Spanish autochthonous beef cattle populations need at least 38,000 segregating SNP markers. Thus, the potential increase that can be obtained from higher densities can be considered negligible, as it was also suggested by Solberg, Sonesson, Woolliams, and Meuwissen (), even for unrelated individuals (Meuwissen, ).…”

“…Thus, doubling or halving the effective size implies that double or half of the markers are needed to achieve the same accuracy. The Ne of the Spanish autochthonous populations was estimated between 26 and 47 (Cañas‐Álvarez et al., ) and, as a consequence, the results of the base simulation study presented earlier can be considered as a conservative estimation of the potential gain in accuracy.…”

The Bos taurus–Bos indicus balance in fertility and milk related genes

“…Genotype data from high-density single nucleotide polymorphism (SNP) arrays serves as a starting point for many genomic analyses as they can reflect a wide range of processes [ 1 – 3 ]. SNP data have been used to characterize linkage disequilibrium and estimate effective population size [ 4 , 5 ], to perform genome-wide association studies [ 6 – 8 ], to compress genomes and highlight regions of evolutionary interest in humans and livestock species [ 9 – 11 ], to study the genetic variants of common diseases [ 12 – 14 ], and to identify population structure and signatures of selection [ 5 , 15 – 18 ]. These numerical approaches are employed independently to address specific questions.…”

Estimation of Linkage Disequilibrium and Effective Population Size in Three Italian Autochthonous Beef Breeds

“…Information of LD has been utilized in genomic breeding programs, such as marker-assisted selection and whole genome predictions [15]. The cost reduction and the efficient implementation of genotyping in animal breeding have made LD a common analysis in various species, such as pigs [16,17], poultry [18], sheep [19], goats [20], and cattle [21][22][23]. The most common LD measures are the squared genetic correlation coefficient (r 2 ) described by Hill and Robertson [24] and D' reported by Lewontin [10].…”