Within- and between-Breed Selection Signatures in the Original and Improved Valachian Sheep

Integration of selective sweeps across the sheep genome: understanding the relationship between production and adaptation traits

BACKGROUND

Livestock populations are under constant selective pressure for higher productivity levels for different selective purposes. This pressure results in the selection of animals with unique adaptive and production traits. The study of genomic regions associated with these unique characteristics has the potential to improve biological knowledge regarding the adaptive process and how it is connected to production levels and resilience, which is the ability of an animal to adapt to stress or an imbalance in homeostasis. Sheep is a species that has been subjected to several natural and artificial selective pressures during its history, resulting in a highly specialized species for production and adaptation to challenging environments. Here, the data from multiple studies that aim at mapping selective sweeps across the sheep genome associated with production and adaptation traits were integrated to identify confirmed selective sweeps (CSS).

RESULTS

In total, 37 studies were used to identify 518 CSS across the sheep genome, which were classified as production (147 prodCSS) and adaptation (219 adapCSS) CSS based on the frequency of each type of associated study. The genes within the CSS were associated with relevant biological processes for adaptation and production. For example, for adapCSS, the associated genes were related to the control of seasonality, circadian rhythm, and thermoregulation. On the other hand, genes associated with prodCSS were related to the control of feeding behaviour, reproduction, and cellular differentiation. In addition, genes harbouring both prodCSS and adapCSS showed an interesting association with lipid metabolism, suggesting a potential role of this process in the regulation of pleiotropic effects between these classes of traits.

CONCLUSIONS

The findings of this study contribute to a deeper understanding of the genetic link between productivity and adaptability in sheep breeds. This information may provide insights into the genetic mechanisms that underlie undesirable genetic correlations between these two groups of traits and pave the way for a better understanding of resilience as a positive ability to respond to environmental stressors, where the negative effects on production level are minimized.

Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations

South Africa boasts a diverse range of pig populations, encompassing intensively raised commercial breeds, as well as indigenous and village pigs reared under low-input production systems. The aim of this study was to investigate how natural and artificial selection have shaped the genomic landscape of South African pig populations sampled from different genetic backgrounds and production systems. For this purpose, the integrated haplotype score (iHS), as well as cross population extended haplotype homozygosity (XP-EHH) and Lewontin and Krakauer's extension of the Fst statistic based on haplotype information (HapFLK) were utilised. Our results revealed several population-specific signatures of selection associated with the different production systems. The importance of natural selection in village populations was highlighted, as the majority of genomic regions under selection were identified in these populations. Regions under natural and artificial selection causing the distinct genetic footprints of these populations also allow for the identification of genes and pathways that may influence production and adaptation. In the context of intensively raised commercial pig breeds (Large White, Kolbroek, and Windsnyer), the identified regions included quantitative loci (QTLs) associated with economically important traits. For example, meat and carcass QTLs were prevalent in all the populations, showing the potential of village and indigenous populations' ability to be managed and improved for such traits. Results of this study therefore increase our understanding of the intricate interplay between selection pressures, genomic adaptations, and desirable traits within South African pig populations.

Assessing Genomic Diversity and Signatures of Selection in Chinese Red Steppe Cattle Using High-Density SNP Array

Chinese Red Steppe Cattle (CRS), a composite cattle breed, is well known for its milk production, high slaughter rate, carcass traits, and meat quality. Nowadays, it is widely bred in Jilin and Hebei Province and the Inner Mongolia Autonomous region. However, the population structure and the genetic basis of prominent characteristics of CRS are still unknown. In this study, we systematically describe their population structure, genetic diversity, and selection signature based on genotyping data from 61 CRS individuals with GGP Bovine 100 K chip. The results showed that CRS cattle had low inbreeding levels and had formed a unique genetic structure feature. Using two complementary methods (including comprehensive haplotype score and complex likelihood ratio), we identified 1291 and 1285 potentially selected genes, respectively. There were 141 genes annotated in common 106 overlapping genomic regions covered 5.62 Mb, including PLAG1, PRKG2, DGAT1, PARP10, TONSL, ADCK5, and BMP3, most of which were enriched in pathways related to muscle growth and differentiation, milk production, and lipid metabolism. This study will contribute to understanding the genetic mechanism behind artificial selection and give an extensive reference for subsequent breeding.