Detection of selection signatures in Piemontese and Marchigiana cattle, two breeds with similar production aptitudes but different selection histories

Abstract

Background: Domestication and selection are processes that alter the pattern of within- and between-population genetic variability. They can be investigated at the genomic level by tracing the so-called selection signatures. Recently, sequence polymorphisms at the genome-wide level have been investigated in a wide range of animals. A common approach to detect selection signatures is to compare breeds that have been selected for different breeding goals (i.e. dairy and beef cattle). However, genetic variations in different breeds with similar production aptitudes and similar phenotypes can be related to differences in their selection history.

Methods: In this study, we investigated selection signatures between two Italian beef cattle breeds, Piemontese and Marchigiana, using genotyping data that was obtained with the Illumina BovineSNP50 BeadChip. The comparison was based on the fixation index (Fst), combined with a locally weighted scatterplot smoothing (LOWESS) regression and a control chart approach. In addition, analyses of Fst were carried out to confirm candidate genes. In particular, data were processed using the varLD method, which compares the regional variation of linkage disequilibrium between populations.

Results: Genome scans confirmed the presence of selective sweeps in the genomic regions that harbour candidate genes that are known to affect productive traits in cattle such as DGAT1, ABCG2, CAPN3, MSTN and FTO. In addition, several new putative candidate genes (for example ALAS1, ABCB8, ACADS and SOD1) were detected.

Conclusions: This study provided evidence on the different selection histories of two cattle breeds and the usefulness of genomic scans to detect selective sweeps even in cattle breeds that are bred for similar production aptitudes.

Fig. 1

Comparison of average heterozygosity (H_obs) per chromosome (BTA) between the two breeds. Green = Piemontese and red = Marchigiana

Fig. 2

a Pattern of raw F_st data calculated for SNPs located on BTA 26. b Predicted F_st values for SNPs located on BTA 26 using the LOWESS regression with the smoothing parameter set at 0.022. c Control chart of predicted F_st values for BTA 26. Solid line = mean, dotted lines are upper (UCLI) and lower (LCLI) control limits. These control limits are three standard deviations apart from the mean value. The borderline peak is at about 7 Mb

Fig. 3

Comparison between genome-wide F_st and varLD analysis for the two breeds. Manhattan plots demonstrate the presence of significant signals in the same regions on several BTA chromosomes between genome-wide F_st and varLD analyses. Black dots represent significant signals with whole-genome significance thresholds set at three standard deviations apart from the mean value

Fig. 4

Protein network of bovine ALAS1 according to STRING 9.0 action view. Nodes are proteins; lines indicate interactions between proteins with: pink lines for post-translational, yellow lines for expression, black lines for reaction, blue lines for binding and light blue lines for phenotype. Protein interactions include direct (physical) and indirect (functional) associations derived from different sources (genomic context, high through-put experiments, conserved coexpression, previous knowledge). 0.91 and 0.89 are the confidence values for the products of NRF1 and SMARCD3, respectively