Whole-genome selective scans detect genes associated with important phenotypic traits in goat (Capra hircus)

Selection Signatures in Italian Goat Populations Sharing the "facciuto" Phenotype

Background: The presence of light-pigmented facial stripes, parallel on both sides of the cranial region, is a widespread characteristic in various goat breeds of European origin and beyond. In Italy, this phenotype is relatively common from the north to the south of the peninsula. The availability of genotypic data at single-nucleotide polymorphism (SNP) loci for breeds and populations characterized by such a pigmentation pattern enabled us to study the genomic regions potentially correlated with this phenotype, for simplicity referred to as "facciuto". Methods: We adopted an FST-outlier approach to detect signals of differential selection in 18 pairwise comparisons, each involving 6 genetic goat types with the "facciuto" phenotype (Facciuta Lucana, Facciuta della Valnerina, Valfortorina, Teramana, Capestrina, and Roccaverano) contrasted with each of 3 "non-facciuto" goat breeds selected as reference populations (Red Mediterranean, light brown; Saanen, white; Malagueña, mahogany solid). Results: The analysis of the region ±200 kbps upstream and downstream of the two significant signals on chromosome 13 and 15 allowed us to identify, among the annotated genes, ASIP, AHCY, ITCH, DYNLRB1, MAP1LC3A, PIGU, LOC102177263, and DTX4, whose functions could be related to several mechanisms underlying the phenotype under investigation. Conclusions: This study confirmed the fundamental role of ASIP in pigmentation, although additional pathways may concurrently contribute to the determinism of the considered "facciuto" phenotype in Italian goats.

Whole genome and transcriptome analyses in dairy goats identify genetic markers associated with high milk yield

Milk production is the most important economic trait of dairy goats and a key indicator for genetic improvement and breeding. However, milk yield is a complex phenotypic trait, and its genetic mechanisms are still not fully understood. This study focuses on dairy goats and non-dairy goats. By analyzing the population structure of these two groups, we found that there is a significant genetic distance between the populations of dairy goats and non-dairy goats. Using SNP and Indel analyses to identify selection signals, we identified several genes associated with milk production traits, including MPP7, PRPF6, DNAJC5, TPD52L2, HNF4G, LAMA3, FAM13A, and EPHA5. Through longitudinal GWAS of the milk production traits of 298 dairy goats, we discovered additional genes such as TRNAS-GGA-102, TTC39C, LAMA3, ANKRD29, NPC1, C24H18orf8, LOC108633789, RIOK3, TMEM241, CABLES1, LOC108633781, and RBBP8. Transcriptome sequencing of breast tissues at different lactation stages reveals dynamic LAMA3 expression changes. Three non-synonymous mutations in LAMA3 are identified, with the TT genotype at one site correlating significantly with average milk production in dairy goats. Our study discovered new genetic markers for improving dairy goat genetics and provided valuable insights into the genetic mechanisms underlying complex traits.

Characterization of runs of homozygosity islands in American mink using whole-genome sequencing data

The genome-wide analysis of runs of homozygosity (ROH) islands can be an effective strategy for identifying shared variants within a population and uncovering important genomic regions related to complex traits. The current study performed ROH analysis to characterize the genome-wide patterns of homozygosity, identify ROH islands and annotated genes within these candidate regions using whole-genome sequencing data from 100 American mink (Neogale vison). After sequence processing, variants were called using GATK and Samtools pipelines. Subsequent to quality control, 8,373,854 bi-allelic variants identified by both pipelines remained for further analysis. A total of 34,652 ROH segments were identified in all individuals, among which shorter segments (0.3-1 Mb) were abundant throughout the genome, approximately accounting for 84.39% of all ROH. Within these segments, we identified 63 ROH islands housing 156 annotated genes. The genes located in ROH islands were associated with fur quality (EDNRA, FGF2, FOXA2 and SLC24A4), body size/weight (MYLK4, PRIM2, FABP2, EYS and PHF3), immune capacity (IL2, IL21, PTP4A1, SEMA4C, JAK2, CCNA2 and TNIP3) and reproduction (ADAD1, KHDRBS2, INSL6, PGRMC2 and HSPA4L). Furthermore, Gene Ontology and KEGG pathway enrichment analyses revealed 56 and 9 significant terms (FDR-corrected p-value < 0.05), respectively, among which cGMP-PKG signalling pathway, regulation of actin cytoskeleton, and calcium signalling pathway were highlighted due to their functional roles in growth and fur characteristics. This is the first study to present ROH islands in American mink. The candidate genes from ROH islands and functional enrichment analysis suggest possible signatures of selection in response to the mink breeding targets, such as increased body length, reproductive performance and fur quality. These findings contribute to our understanding of genetic characteristics, and provide complementary information to assist with implementation of breeding strategies for genetic improvement in American mink.

Genetic Diversity, Population Structure and Selection Signature in Begait Goats Revealed by Whole-Genome Sequencing

Goats belong to a group of animals called small ruminants and are critical sources of livelihood for rural people. Genomic sequencing can provide information ranging from basic knowledge about goat diversity and evolutionary processes that shape genomes to functional information about genes/genomic regions. In this study, we exploited a whole-genome sequencing data set to analyze the genetic diversity, population structure and selection signatures of 44 individuals belonging to 5 Ethiopian goat populations: 12 Aberegalle (AB), 5 Afar (AF), 11 Begait (BG), 12 Central highlands (CH) and 5 Meafure (MR) goats. Our results revealed the highest genetic diversity in the BG goat population compared to the other goat populations. The pairwise genetic differentiation (FST) among the populations varied and ranged from 0.011 to 0.182, with the closest pairwise value (0.003) observed between the AB and CH goats and a distant correlation (FST = 0.182) between the BG and AB goats, indicating low to moderate genetic differentiation. Phylogenetic tree, ADMIXTURE and principal component analyses revealed a classification of the five Ethiopian goat breeds in accordance with their geographic distribution. We also found three top genomic regions that were detected under selection on chromosomes 2, 5 and 13. Moreover, this study identified different candidate genes related to milk characteristics (GLYCAM1 and SRC), carcass (ZNF385B, BMP-7, PDE1B, PPP1R1A, FTO and MYOT) and adaptive and immune response genes (MAPK13, MAPK14, SCN7A, IL12A, EST1 DEFB116 and DEFB119). In conclusion, this information could be helpful for understanding the genetic diversity and population structure and selection scanning of these important indigenous goats for future genetic improvement and/or as an intervention mechanism.

The RELT Family of Proteins: An Increasing Awareness of Their Importance for Cancer, the Immune System, and Development

This review highlights Receptor Expressed in Lymphoid Tissues (RELT), a Tumor Necrosis Factor Superfamily member, and its two paralogs, RELL1 and RELL2. Collectively, these three proteins are referred to as RELTfms and have gained much interest in recent years due to their association with cancer and other human diseases. A thorough knowledge of their physiological functions, including the ligand for RELT, is lacking, yet emerging evidence implicates RELTfms in a variety of processes including cytokine signaling and pathways that either promote cell death or survival. T cells from mice lacking RELT exhibit increased responses against tumors and increased inflammatory cytokine production, and multiple lines of evidence indicate that RELT may promote an immunosuppressive environment for tumors. The relationship of individual RELTfms in different cancers is not universal however, as evidence indicates that individual RELTfms may be risk factors in certain cancers yet appear to be protective in other cancers. RELTfms are important for a variety of additional processes related to human health including microbial pathogenesis, inflammation, behavior, reproduction, and development. All three proteins have been strongly conserved in all vertebrates, and this review aims to provide a clearer understanding of the current knowledge regarding these interesting proteins.