Genome-Wide Analyses Reveal the Genetic Architecture and Candidate Genes of Indicine, Taurine, Synthetic Crossbreds, and Locally Adapted Cattle in Brazil

Abstract

Cattle population history, breeding systems, and geographic subdivision may be reflected in runs of homozygosity (ROH), effective population size (Ne), and linkage disequilibrium (LD) patterns. Thus, the assessment of this information has become essential to the implementation of genomic selection on purebred and crossbred cattle breeding programs. In this way, we assessed the genotype of 19 cattle breeds raised in Brazil belonging to taurine, indicine, synthetic crossbreds, and Iberian-derived locally adapted ancestries to evaluate the overall LD decay patterns, Ne, ROH, and breed composition. We were able to obtain a general overview of the genomic architecture of cattle breeds currently raised in Brazil and other tropical countries. We found that, among the evaluated breeds, different marker densities should be used to improve the genomic prediction accuracy and power of genome-wide association studies. Breeds showing low Ne values indicate a recent inbreeding, also reflected by the occurrence of longer ROH, which demand special attention in the matting schemes to avoid extensive inbreeding. Candidate genes (e.g., ABCA7, PENK, SPP1, IFNAR1, IFNAR2, SPEF2, PRLR, LRRTM1, and LRRTM4) located in the identified ROH islands were evaluated, highlighting biological processes involved with milk production, behavior, rusticity, and fertility. Furthermore, we were successful in obtaining the breed composition regarding the taurine and indicine composition using single-nucleotide polymorphism (SNP) data. Our results were able to observe in detail the genomic backgrounds that are present in each breed and allowed to better understand the various contributions of ancestor breeds to the modern breed composition to the Brazilian cattle.

Genome‐wide scan for signatures of selection in the Brangus cattle genome

“…Interestingly, a signature of selection in Brangus was previously reported by Goszczynski et al (2018) in this region. Some genes involved in dairy production traits, temperament and coat colour are also within candidate regions detected in both comparisons, such as HAL and CSF2RB and PPARGC1A, that influencing milk production (Kowalewska-Łuczak et al, 2010;Li et al, 2014;Lopdell et al, 2019;Wang et al, 2014), SNRPF (in BTA5) and PENK (in BTA14) previously reported to play a role in cattle temperament (Costilla et al, 2020;Verardo et al, 2021), and BLOC1S1, RAB5b, DCTN2 and MYO1A related to pigmentation (Gutiérrez-Gil et al, 2007). Finally, some heat shock proteins were found within the candidate regions, for example HSPA13, HSP90B1, HSPA6, HSPA4, HSPA5, HSPH1 and HSPBAP1 (Archana et al, 2017).…”

Association analysis of single-nucleotide polymorphism in prolactin and its receptor with productive and body conformation traits in Liaoning cashmere goats

“…Previous studies indicated that the prolactin receptor (PRLR) is an important candidate gene affecting the reproductive traits of livestock and poultry, including pig, sheep, chicken and geese (Liu et al, 2020). A high correlation between PRLR and lactation performance was revealed in dairy cows (Verardo et al, 2021;Leyva-Corona et al, 2018). At the molecular level, it has been demonstrated that oxytocin induced lactation through PRLR dimerization (Lü et al, 2010).…”

Genetic diversity analysis in dairy cows of Nariño, southwestern Colombia

“…Among livestock species, this technology has been successfully applied in cattle thanks to many factors such as evolutionary history, genetic structure, and economic conditions, which render cattle particularly suitable for the application of genome-assisted selection (Nicolazzi et al, 2014). Genome-wide comparison of populations from different geographical regions can also detect potential candidate genes associated with ecological adaptations (Edea et al, 2015;Zambrano et al, 2020;Verardo et al, 2021). In livestock populations, approximately half of the genetic diversity is shared across breeds, while the other half is observed within single breeds (Sponenberg & Bixby, 2007).…”