Animal genetics最新文献

The absence of horns (polled trait) in cattle is associated with better animal welfare by reducing the need for dehorning. In Brahman cattle, population size and the scarcity of phenotypic records challenge the accuracy of genomic predictions for this trait. This study aimed to evaluate the genetic architecture of this trait in Brahman cattle using single-breed and multi-breed genomic prediction models, including metafounders, and to assess the influence of phenotypic classifications on heritability, prediction accuracy, bias, and dispersion. Phenotypic and genotypic data from 14 333 Nelore and Brahman animals were analyzed using threshold and linear models implemented in the BLUPF90+ software suite. Single-breed models (n = 12) were considered phenotypes (polled, scab, scur, horned), while multi-breed models (n = 10) incorporated metafounders and breed effects. Variance components were estimated via threshold models with Gibbs sampling, and predictive ability was assessed using the LR method with datasets. Single-breed models showed heritability estimates (h²) ranging from 0.56 to 0.72, but with predictive ability reflecting the Brahman population size. Multi-breed models improved predictive performance. Results were obtained with Model 20, which included alternative phenotypes, metafounders, and breed effects, yielding accuracy (0.79), reduced bias (0.36), and dispersion close to 1. These findings demonstrate that the polled trait in Brahman cattle exhibits additive genetic variability amenable to selection. The use of multi-breed analyses and metafounders enhances predictive accuracy, providing a strategy for populations and traits, and enables the inclusion of traits as genomic selection criterion to increase allele frequency in Brahman cattle and improve animal welfare.

Pregnancy loss (PL) affects reproductive efficiency in beef cattle, yet its genetic architecture remains poorly understood in Bos indicus populations. Here, PL was defined as failure from pregnancy diagnosis to calving, capturing a window approximately 60 days after the breeding season. This study aimed to identify genomic regions and biological pathways associated with PL in early Nellore heifers using weighted single-step genome-wide association study (WssGWAS). Phenotypic records from 23 507 Nellore heifers were analyzed, including 17 052 genotyped animals (GGP Indicus panel, Neogen) and 44 233 SNPs. Genomic regions explaining more than 0.5% of additive genetic variance were used to identify putative candidate genes and perform functional enrichment analysis. The estimated heritability for PL was low (0.033), indicating strong environmental influence. WssGWAS identified 25 genomic regions across 16 chromosomes, explaining 31.16% of additive genetic variance for PL. The most relevant region was located on BTA16, explaining 6.51% of the variance, although no annotated protein-coding genes were found. Additional regions occurred on BTA6, BTA14, BTA22, BTA25, and BTA29. Putative candidate genes included IL4R, IL21R, LRRC4C, RBMS3, ZFPM2, PRSS23, and NDST4, involved in immune regulation, cell adhesion, extracellular matrix remodeling, and transcriptional regulation. Functional enrichment identified Gene Ontology terms and REACTOME pathways related to nucleosome assembly, epigenetic regulation, transmembrane transport, focal adhesion, calcium signaling, immune response, and WNT signaling. These findings inform the genetic architecture of PL in Nellore cattle and suggest roles for embryo-maternal communication, immune regulation, chromatin organization, and placental development in pregnancy maintenance, supporting future functional validation and genomic selection strategies.

Heterozygosity-rich regions (HRR) are genomic segments characterized by high heterozygosity that may arise from admixture, introgression, or balancing selection and may harbor loci associated with adaptation and fitness-related traits. This study aimed to characterize HRR patterns in five Kazakh sheep breeds using a publicly available OvineSNP50 genotyping dataset. After quality control, ~25 000 SNPs were retained for 1634 Akzhaiyk, 1089 Edilbay, 532 Kazakh Fine-Wool, 932 Kazakh Semi-Coarse, and 282 Saryarka sheep. HRR were detected separately in each breed using the sliding-window approach in detectRUNS R package, with a minimum segment length of 250 kb, at least 10 SNPs per window and segment, and a maximum of two opposing homozygous and one missing SNP per window. The average number of HRR per individual ranged from 40.75 ± 6.38 in Saryarka to 54.75 ± 7.34 in Kazakh Fine-Wool sheep. HRR lengths ranged from 259.07 kb to 3.26 Mb, with an average of 0.7 Mb across breeds. Seventeen HRR islands, defined as regions shared by HRR in at least 25% of individuals within a breed, were identified, including regions on chromosomes 8 and 17 shared across all breeds. Genes overlapping these islands were associated with cellular homeostasis, immunity, metabolism, growth, and stress response, while the HRR islands overlapped with QTL associated with health, wool characteristics, and reproduction. These findings highlight the potential of HRR analysis to identify candidate genomic regions relevant to adaptation and economically important traits, providing insights for the conservation and genetic improvement of Kazakh sheep populations.

Composite cattle breeds are developed to combine favorable traits from parental populations and to exploit heterosis across diverse production environments. However, their genomic structure becomes progressively more complex across generations, and it remains unclear to what extent patterns of local ancestry and heterozygosity are conserved across breeds. The objective of this study was to characterize genomic breed composition in Argentine Brangus and Braford at both global and local levels, and to identify shared genomic segments with extreme values of indicine ancestry and heterozygosity. A total of 783 animals from six breeds were analyzed using SNP data. Global ancestry proportions were estimated using STRUCTURE, whereas local ancestry was inferred through haplotype phasing (Shapeit5) and local ancestry inference using LOTER. Deviations between observed and expected breed composition and heterozygosity were evaluated at the SNP level using chi-square tests with multiple testing correction. Shared genomic segments were defined as contiguous genomic intervals composed of SNPs showing significant deviations in both breeds. Brangus and Braford showed lower indicine proportions than the expected 37.5%, with reductions of 1.2% and 7.1%, respectively. Local ancestry analysis revealed heterogeneous genomic patterns, with shared segments enriched for indicine ancestry on chromosomes 3, 6, 20, and 28. In contrast, segments with reduced indicine ancestry were more broadly distributed. No SNP exceeded the expected heterozygosity; however, multiple regions showed significant reductions, particularly on chromosome 18. These results demonstrate that Brangus and Braford exhibit complex and heterogeneous genomic architectures, with shared genomic regions showing extreme patterns of ancestry and heterozygosity.

The order Passeriformes, the most speciose avian order, includes over 6000 species (~60% of all birds). The Amazon Basin alone hosts > 900 bird species, with Passeriformes representing > 500 of them. The family Thamnophilidae comprises ~200 insectivorous species, accounting for 15% of Neotropical passerine richness. Within Thamnophilinae, Isleria is the least speciose genus, containing only two species. It was erected after phylogenetic analyses revealed Myrmotherula as non-monophyletic. To advance knowledge of chromosomal evolution in Passeriformes, we analyzed the karyotype of Isleria hauxwelli using molecular cytogenetics. We found a diploid number of 2n = 84 and a fundamental number (FN) of 92. The BOE-7 probe, corresponding to the ancestral fusion of GGA-9 with two microchromosomes, maintained that configuration without undergoing fission to produce IHA-5. The BOE-14 probe, typically fragmented in all cytogenomically characterized Passeriformes, corresponded to two distinct GGA segments: the R3 portion and a region of unknown homology. This is the first documentation of such chromosomal organization in passerines. The absence of these fissions suggests a possible autapomorphic chromosomal condition within Thamnophilidae. Additionally, a potential fission involving microchromosomes homeologous to probes BOE-15 and BOE-16 is suggested: while these probes mark three microchromosome pairs in GGA, they mark four pairs in I. hauxwelli-a feature not yet observed in other passerines. As most Thamnophilidae remain cytogenetically uncharacterized, systematic study of this family is essential to determine whether these rearrangements represent synapomorphies, autapomorphies, or convergent events.

Meat quality is a vital economic trait in geese and is largely determined by embryonic muscle development. Building on previously reported whole-genome resequencing and breast muscle transcriptome data from Xianghai Flying (XHF) Goose and Zi Goose, two breeds with divergent meat quality, fibulin-1 (FBLN1) was identified as a candidate gene showing both strong selection signals and significant differential expression. FBLN1 was overexpressed and knocked down in primary goose embryonic myoblasts. Because no goose-specific antibody is commercially available, all readouts were obtained at the mRNA level. FBLN1 was found to promote myoblast proliferation and to accelerate the G1/S cell cycle transition, with increased expression of CCND1 and CDK2. Apoptosis was concurrently suppressed, accompanied by downregulation of Bax and upregulation of Bcl-2, whereas transcript levels of Caspase-3 and Caspase-9 remained unaltered. The mRNA levels of the myogenic differentiation markers Myomaker, MYOD1, and MYF5 were correspondingly affected. Bioinformatic analyses predicted FBLN1 to be an extracellular matrix protein that interacts with proteins implicated in muscle elasticity, tenderness, and juiciness. These findings suggest that FBLN1 plays an important role in embryonic myoblast development and represents a valuable candidate gene for improving goose meat quality, thereby offering new perspectives for poultry molecular breeding.

Zebu cattle (Bos indicus) represent a critical livestock resource in the arid and semi-arid regions, known for their disease resistance, heat tolerance and physiological hardiness. Despite their agricultural importance, the precise matrilineal evolutionary history, genetic diversity and demographic trajectory remain incompletely resolved within the broader context of South Asian cattle domestication. This study explores the phylogeographic patterns and maternal lineage diversity of zebu cattle through complete mitochondrial genomes (mtDNA), the D-loop, and hypervariable regions from 50 individuals of 10 indigenous Pakistani breeds. These breeds were classified into three regions: North Pakistan, Central Pakistan/Punjab (Indus Valley region) and South Pakistan (the site of Mohenjo-Daro). Our data include 183 newly generated sequences and are supplemented with comparative datasets from 19 countries. Analysis reveals South Pakistan, especially the Mehrgarh area, as a key potential domestication epicentre, exhibiting highest nucleotide diversity (π = 0.01480) across Asian zebu populations, accompanied by ancient maternal lineages estimated to date back approximately 2.17 million years. Highest haplotype diversity was observed in Punjab (0.901 ± 0.014) followed by Southern Pakistan (0.893 ± 0.026). Phylogenetic and demographic analyses (mismatch distribution, Fu's Fs) further support an early dispersal scenario (I1 haplogroup) originating in Mehrgarh and radiating through the Indus Valley into broader Asian lineages. These findings enhance our understanding of the domestication origins of Bos indicus, its implications for breed conservation and sustainable livestock management.

In this study, we conducted a population genomic survey of two local pig breeds in Jilin Province, Dongliao Black (DLB) and Jilin Spotted (JLS) pigs, and evaluated their genetic relationships with 23 Northeastern Asian pig breeds, comprising 46 wild boars, 211 Chinese local pigs, 69 Russian pigs, 13 Korean pigs, and 107 commercial pigs. The results will be helpful for the conservation and utilization of these rare germplasm resources. The minor allele frequency of DLB and JLS pigs was 0.24 and 0.22, respectively. Both DLB and JLS pigs exhibited higher observed heterozygosity than expected values. Moreover, JLS pigs displayed the lowest excess of homozygosity inbreeding coefficient (-0.12 ± 0.07) among all studied populations. Additionally, population structure analyses indicated that DLB and JLS pigs possess admixed ancestries intermediate between Chinese and Western pigs, with DLB being closely related to Min pigs and both breeds showing admixture signals with neighboring Northeastern Chinese breeds, reflecting their distinct hybrid histories. Furthermore, 16 and 19 genes were identified as putative candidate genes in DLB and JLS pigs using Fst analyses, respectively. All these findings are consistent with a history of crossbreeding and with low levels of inbreeding in DLB and JLS pig populations. Additionally, it is hypothesized that DLB and JLS pig breeds may carry putative candidate genes during their breeding programs, which are associated with meat quality, reproduction, production, immunity, and environmental adaptation. Therefore, strengthening conservation and promotion efforts for DLB and JLS pigs is of great significance.

Feature reduction of genetic markers and its impact on genomic selection has been studied extensively. Prior information borrowed from genome-wide association studies (GWAS) can improve genomic selection accuracy. However, the effect of integration of posterior inclusion probability (PIP) information from fine mapping algorithm and linkage disequilibrium (LD) on genomic selection remains less studied. Here, three marker prioritization strategies-genome-wide fine-mapping (GWFM), LD pruning (LDFM), and GWAS-informed LD pruning ((GWAS + LD)FM)-were evaluated, using Bayesian fine-mapping integrated with linear and nonlinear genomic selection frameworks, across 12 traits for three species. A consistent ranking of prediction performance (GWFM < LDFM < (GWAS + LD)FM) was observed across species and statistical models. Moreover, (GWAS + LD)FM achieved prediction accuracy (96% of maximal accuracy) with markedly minimal number of marker subsets. Gene ontology enrichment analysis showed that prioritized loci could converge on functional modules of biological importance. Independent validation using another fine mapping algorithm (FINEMAP) replicated the identical performance ordering. Genetic variants prioritized by LD and fine mapping reduced dimensional complexity and only were minimal number of marker subsets required for improved genomic selection accuracy. Fine mapping-informed dimension reduction provides novel insights and avenue for the enhancement of genomic selection performance.