Human concern about the status of genetic diversity in livestock breeds and their conservation has increased, as intense selection and reduced population sizes in many breeds has caused losses on the global livestock genetic biodiversity. Traditionally, pedigree data provided by the breeders were used to estimate genetic diversity parameters, but over the past decades, technology has made possible the development of genomic markers. The result has been new opportunities to estimate genetic diversity in more detail, and to improve selection as well as prioritizing animals for conservation of genetic resources. The aim of the review is to summarize the evolution of livestock genomic markers and to explore the potential of the newest high-throughput technologies for estimation and conservation of livestock genetic diversity. More accurate diversity parameters are observed when genomic information is used for selection decisions instead of the traditional estimates using pedigree data. It is also possible to estimate additional parameters such as linkage disequilibrium to calculate effective population size or to minimize the genetic relatedness among the selected individuals based on runs of homozygosity. For long-term perspectives, new methods on genome editing are considered as new perspectives to reach a genetic diversity balance.

The identification of genomic regions including signatures of selection produced by domestication and its subsequent artificial selection processes allows the understanding of the evolution of bovine breeds. Although several studies describe the genomic variability among meat or milk production cattle breeds, there are limited studies orientated towards bovine behavioural features. This study is focused on mapping genomic signatures of selection which may provide insights of differentiation between neutral and selected polymorphisms. Their effects are studied in the Lidia cattle traditionally selected for agonistic behaviour compared with Spanish breeds showing tamed behaviour. Two different approaches, BayeScan and SelEstim, were applied using genotypic 50K SNP BeadChip data. Both procedures detected two genomic regions bearing genes previously related to behavioural traits. The frequencies of the selected allele in these two regions in Lidia breed were opposite to those found in the tamed breeds. In these genomic regions, several putative genes associated with enriched metabolic pathways related to the behavioural development were identified, as neurochondrin gene (NCDN) or glutamate ionotropic receptor kainate type subunit 3 (GRIK3) both located at BTA3 or leucine-rich repeat and Ig domain containing 2 (LINGO2) and phospholipase A2-activating protein (PLAA) at BTA8.

SummaryMolecular mechanisms underlying aggressive behavior are primitive and similar among the subphylum Vertebrata. In humans, a primary goal in the study of aggression is to determine the neurobehavioral molecular factors triggering violence. Although several species have been used to study agonistic responses, researchers are limited by the difficulty of artificially inducing aggression in animals not selected for it. Conversely, the Lidia cattle breed has been selected since the eighteenth century to display agonistic responses based on traits such as aggressiveness, ferocity and mobility, all of them showing significant heritability values. This intensive selection may have driven shifts in specific allele frequencies. In a previous analysis across the autosomes, we revealed long‐term selection regions including genes involved in behavioral development. In the present study, we focus on mapping recent signatures of selection associated with aggressiveness at chromosome X, by comparing Lidia cattle samples with two non‐specialized Spanish breeds showing tamed behavior. The most significant markers peaked around the monoamine oxidase A (MAOA) gene, and thus the associations of three functionally important regions located near the promoter of this gene were further investigated. A polymorphism consisting of a variable number of tandem repeats of the nucleotide ‘C’ (BTX:105,462,494) and displaying lower number of repetitions in the Lidia breed when compared with the tamed breeds was detected. In silico analyses predicted that the g.105,462,494delsinsC variant may code for the Sp1 binding motif, one of the major transcription factors controlling the core promoter and expression of the MAOA gene in humans.

The Lidia bovine breed is distinguished for its low genetic exchangeability given its selection on aggressive behavior, its management uniqueness and its subdivided structure. In this study, we present a comprehensive genome-wide analysis of genetic diversity, population structure and admixture of 468 animals from Mexican and Spanish Lidia breed populations and 64 samples belonging to 10 Spanish native and American-creole breeds using 37 148 single nucleotide polymorphisms. We found similar average inbreeding values in the Lidia breed, with different distributions within groups; variability of inbreeding values among Spanish lineages was significant and no differences were found among the Mexican sub-populations. Together, the high F of the lineages and the behavior of the runs of homozygosity are consequences of the lineage's small effective population sizes, contributing to their inbreeding increase. Population admixture analysis discarded any influence on the genetic structure of the Lidia populations from the Spanish native and American-creole breeds. In addition, both Lidia populations depicted different genetic origins, with the exception of some Mexican individuals whose origins traced back to recent Spanish importations.

We performed a genome-wide association study to map the genetic determinants of carcass traits in 350 Duroc pigs typed with the Porcine SNP60 BeadChip. Association analyses were carried out using the gemma software. The proportion of phenotypic variance explained by the SNPs ranged between negligible to moderate (hSNP2= 0.01-0.30) depending on the trait under consideration. At the genome-wide level, we detected one significant association between backfat thickness between the 3 and 4 ribs and six SNPs mapping to SSC12 (37-40 Mb). We also identified several chromosome-wide significant associations for ham weight (SSC11: 51-53 Mb, three SNPs; 67-68 Mb, two SNPs), carcass weight (SSC11: 66-68 Mb, two SNPs), backfat thickness between the 3 and 4 ribs (SSC12: 21 Mb, one SNP; 33-40 Mb, 17 SNPs; 51-58 Mb, two SNPs), backfat thickness in the last rib (SSC12: 37 Mb, one SNP; 40-41 Mb, nine SNPs) and lean meat content (SSC13: 34 Mb, three SNPs and SSC16: 45.1 Mb, one SNP; 62-63 Mb, 10 SNPs; 71-75 Mb, nine SNPs). The ham weight trait-associated region on SSC11 contains two genes (UCHL3 and LMO7) related to muscle development. In addition, the ACACA gene, which encodes an enzyme for the catalysis of fatty acid synthesis, maps to the SSC12 (37-41 Mb) region harbouring trait-associated regions for backfat thickness traits. Sequencing of these candidate genes may help to uncover the causal mutations responsible for the associations found in the present study.