Identification of selection signatures involved in performance traits in a paternal broiler line

Abstract

Background Natural and artificial selection leads to changes in certain regions of the genome resulting in selection signatures that can reveal genes associated with the selected traits. Selection signatures may be identified using different methodologies, of which some are based on detecting contiguous sequences of homozygous identical-by-descent haplotypes, called runs of homozygosity (ROH), or estimating fixation index (F ST ) of genomic windows that indicates genetic differentiation. This study aimed to identify selection signatures in a paternal broiler TT line at generations 7th and 16th of selection and to investigate the genes annotated in these regions as well as the biological pathways involved. For such purpose, ROH and F ST -based analysis were performed using whole genome sequence of twenty-eight chickens from two different generations. Results ROH analysis identified homozygous regions of short and moderate size. Analysis of ROH patterns revealed regions commonly shared among animals and changes in ROH abundance and size between the two generations. Results also suggest that whole genome sequencing (WGS) outperforms SNPchip data avoiding overestimation of ROH size and underestimation of ROH number; however, sequencing costs can limited the number of animals analyzed. F ST -based analysis revealed genetic differentiation in several genomic windows. Annotation of the consensus regions of ROH and F ST windows revealed new and previously identified genes associated with traits of economic interest, such as APOB, IGF1, IGFBP2, POMC, PPARG, and ZNF423 . Over-representation analysis of the genes resulted in biological terms of skeletal muscle, matrilin proteins, adipose tissue, hyperglycemia, diabetes, Salmonella infections and tyrosine. Conclusions Identification of ROH and F ST -based analyses revealed selection signatures in TT line and genes that have important role in traits of economic interest. Changes in the genome of the chickens were observed between the 7th and 16th generations showing that ancient and recent selection in TT line may have acted over genomic regions affecting diseases and performance traits. Electronic supplementary material The online version of this article (10.1186/s12864-019-5811-1) contains supplementary material, which is available to authorized users.

Runs of Homozygosity in Modern Chicken Revealed by Sequence Data

“…Studies have reported high correlation between F is and F ROH based on short ROH segments in cattle, suggesting ancestral inbreeding back up to 50 generations ago ( Ferenčaković et al 2013 ; Mastrangelo et al 2016 ; Limper 2018 ). The high correlation observed between two metrics of molecular inbreeding is consistent with the previous reports on chicken ( Bortoluzzi et al 2018 ; Marchesi et al 2018 ; Almeida et al 2019 ), cattle ( Ferenčaković et al 2013 ; Zhang et al 2015 ; Mastrangelo et al 2016 ; Peripolli et al 2018 ) and sheep ( Mastrangelo et al 2017 ; Purfield et al 2017 ; Mastrangelo et al 2018 ) as well as human model ( Clark et al 2019 ). These results confirm the usefulness of the ROH analysis in monitoring differentiation and inbreeding values for further exploitation in chicken breeding programs in the absence of pedigree records.…”

“…The average size of ROH tracts observed in Red Junglefowls is comparable to the African indigenous chicken populations from Rwanda and Uganda both genotyped with the chicken Affymetrix 600K Axiom Array ( Elbeltagy et al 2019 ). Our measure of ROH in broiler populations confirms the dimension reported in previous studies ( Marchesi et al 2018 ; Almeida et al 2019 ). Layers, especially WL carry the lengthy ROH tracts with 432.1 Mb (± 18.7 Mb; max.…”

“…The –homozyg module makes ROH calls using a pre-defined sliding window that scans along an individual’s SNP panel to detect homozygous stretches ( Howrigan et al 2011 ). The parameters and thresholds to define an ROH were set according to Almeida et al (2019) and Ceballos et al (2018b) . Accordingly, we applied (i) sliding windows of size 50 SNPs across the genome; (ii) the proportion of homozygous overlapping windows set to 0.05; (iii) the minimum number of consecutive SNPs included in a ROH set to 50; (iv) the minimum length of a ROH set to 300 kb; (v) the maximum gap size between consecutive homozygous SNPs set to 1000 kb; (vi) required minimum density to consider a ROH was 1 SNP in 50 Kb; and (vii) a maximum of five SNPs with missing genotypes and up to three heterozygous.…”

“…ROH islands are widely observed in populations and can be used as a useful tool to identify the phenomenon called “selective sweeps”, genome regions undergone selection pressure ( Szmatoła et al 2019 ). ROH islands have been used to localize selection signatures in the genome of farm animals including sheep ( Purfield et al 2017 ; Mastrangelo et al 2017 ; Mastrangelo et al 2018 ; Luigi-Sierra et al 2019 ; Signer-Hasler et al 2019 ), goat ( Bertolini et al 2018 ; Onzima et al 2018 ), horse ( Metzger et al 2015 ; Grilz-Seger et al 2018 ; Ablondi et al 2019 ; Grilz-Seger et al 2019 ), cattle ( Goszczynski et al 2018 ; Peripolli et al 2018 ; Nandolo et al 2018 ; Szmatoła et al 2019 ; Peripolli et al 2020 ), pig ( Wang et al 2019 ; Xu et al 2019 ; Xie et al 2019 ; Gorssen et al 2020 ) and in chicken ( Marchesi et al 2018 ; Almeida et al 2019 ; Strillacci et al 2018 ; Zhang et al 2018 ; Zhang et al 2020 ).…”

Genomic Tools for Effective Conservation of Livestock Breed Diversity

“…As selection is distinguished by local reductions in haplotype diversity, depending on the distribution of ROH patterns across the genome, results allow the identification of genomic regions that have been subjected to either recent and/or ancient selective pressure events [74,75]. These regions also allow, through gene ontology and enrichment analyses, identifying of candidate genes associated with selection for different traits, highlighting those of economic-interest in different livestock populations such as horses, cattle, sheep and poultry [76][77][78][79].…”