Transcriptome-wide association study (TWAS) is a powerful approach for investigating the molecular mechanisms linking genetic loci to complex phenotypes. However, the complexity of the TWAS analytical pipeline, including the construction of gene expression reference panels, gene expression prediction, and association analysis using data from genome-wide association studies (GWASs), poses challenges for genetic studies in many species. In this study, we provide the Farm Animal Genotype-Tissue Expression (FarmGTEx) TWAS-server, an interactive and user-friendly multispecies platform designed to streamline the translation of genetic findings across tissues and species. The server incorporates gene expression data from 49 human tissues (838 individuals), 34 pig tissues (5457 individuals), and 23 cattle tissues (4889 individuals), providing prediction models for 38,180 human genes, 21,037 pig genes, and 17,942 cattle genes. It supports genotype-based gene expression prediction, GWAS summary statistics imputation, customizable TWAS analysis, functional annotation, and result visualization. Additionally, we provide 479,203, 1208, and 657 tissue–gene–trait associations for 1129 human traits, 41 cattle traits, and 11 pig traits, respectively. Utilizing the TWAS-server, we validated the association of the ABCD4 gene with pig teat number. Furthermore, we identified that pig backfat thickness may share genetic similarities with human diastolic blood pressure, sarcoidosis (Löfgren syndrome), and body mass index. The FarmGTEx TWAS-server offers a comprehensive and accessible platform for researchers to perform TWAS analyses across tissues and species. It is freely available at https://twas.farmgtex.org, with regular updates planned as the FarmGTEx project expands to include more species.

Background: Pigs are crucial sources of meat and protein, valuable animal models, and potential donors for xenotransplantation. However, the existing reference genome for pigs is incomplete, with thousands of segments and centromeres and telomeres missing, which limits our understanding of the important traits in these genomic regions. Findings: We present a near-complete genome assembly for the Jinhua pig (JH-T2T) and provide a set of diploid Jinhua reference genomes, constructed using PacBio HiFi, ONT long reads, and Hi-C reads. This assembly includes all 18 autosomes and the X and Y sex chromosomes, with only 6 gaps. It features annotations of 46.90% repetitive sequences, 33 telomeres, 17 centromeres, and 23,924 high-confident genes. Compared to the Sscrofa11.1, JH-T2T closes nearly all gaps, extends sequences by 177 Mb, predicts more intact telomeres and centromeres, and gains 799 more genes and loses 114 genes. Moreover, it enhances the mapping rate for both Western and Chinese local pigs, outperforming Sscrofa11.1 as a reference genome. Additionally, this comprehensive genome assembly will facilitate large-scale variant detection. Conclusions: This study produced a near-gapless assembly of the pig genome and provides a set of haploid Jinhua reference genomes. Our findings represent a significant advance in pig genomics, providing a robust resource that enhances genetic research, breeding programs, and biomedical applications.

Pigs are crucial sources of meat and protein, valuable animal models, and potential donors for xenotransplantation. However, the existing reference genome for pigs is incomplete, with thousands of segments and missing centromeres and telomeres, which limits our understanding of the important traits in these genomic regions. To address this issue, we present a near complete genome assembly for the Jinhua pig (JH-T2T), constructed using PacBio HiFi and ONT long reads. This assembly includes all 18 autosomes and the X and Y sex chromosomes, with only six gaps. It features annotations of 46.90% repetitive sequences, 35 telomeres, 17 centromeres, and 23,924 high-confident genes. Compared to the Sscrofa11.1, JH-T2T closes nearly all gaps, extends sequences by 177 Mb, predicts more intact telomeres and centromeres, and gains 799 more genes and loses 114 genes. Moreover, it enhances the mapping rate for both Western and Chinese local pigs, outperforming Sscrofa11.1 as a reference genome. Additionally, this comprehensive genome assembly will facilitate large-scale variant detection and enable the exploration of genes associated with pig domestication, such as GPAM , CYP2C18 , LY9 , ITLN2 , and CHIA . Our findings represent a significant advancement in pig genomics, providing a robust resource that enhances genetic research, breeding programs, and biomedical applications.

Growth and egg production are the two most economically important traits in goose production systems. However, negative genetic correlations between these traits make it difficult to achieve balanced genetic improvement through selection. In this study, we analyzed whole-genome resequencing data from 1033 Zhedong White Geese to identify genetic variants related to birth weight (BW), body weight at 90 days (BW90), and egg number at 66 weeks of age (EN66). Single-trait genome-wide association studies (GWASs) identified 6, 5, and 5 lead SNPs significantly associated with BW, BW90, and EN66, respectively. By integrating network analysis, PLACO, and multivariate linear mixed models (mvLMMs), we further identified KCNAB2 and KCND3 as potential pleiotropic candidate genes influencing both growth and egg production. Notably, the variant at CHR25: 6006715, located within an intronic region of KCND3, was associated with increased BW (ZscoreBW = 4.44) and decreased EN66 (ZscoreEN66 = −3.55), showing strong pleiotropic significance (P_PLACO = 4.88 × 10⁻⁸). Collectively, these findings provide new insights into the genetic architecture underlying the antagonistic relationship between growth and egg production in geese and offer valuable genetic targets for developing breeding strategies that jointly optimize growth performance and reproductive efficiency.

Intensively farmed animals such as pigs inevitably experience a certain degree of psychological stress, which leads to a reduction in production performance. Mental health traits are currently difficult to measure, resulting in a gap in understanding their genetic basis. To address this challenge, we propose a computational framework called mental health of animals (MeHA), capable of revealing genes related to animal mental health traits. Using MeHA, we identified 109 candidate genes associated with pig mental health and discovered their intricate connections with critical functions, such as memory, cognition, and neural development, which are essential components of mental health and cognitive performance. Importantly, our findings provide evidence of the potential impact of these genes on economically important traits, including meat quality and piglet survival. This research underscores the importance of genetic studies in enhancing our understanding of animal behavior and cognition, as well as promoting agricultural practices. By applying our approach to study the genetic basis of mental health in pigs as a case, we confirmed that our framework is an effective way to reveal genetic factors affecting animal mental health traits, which contributes to animal welfare and has potential implications for understanding human mental disorders.

Gut microbiota remodeling is a critical component of the domestication syndrome. However, the structural and functional consequences of domestication on gut microbiomes in ducks remain poorly understood. Understanding how domestication and associated ecological transitions influence gut microbial communities can shed light on host adaptation mechanisms. We performed integrated metagenomic and metabolomic analyses of the ileal and cecal microbiota from Mallards and Shaoxing ducks-two ecotypes of Anas platyrhynchos representing wild and domesticated lineages-to investigate microbial community structure, functional capacity, and host-microbe metabolic interactions. Principal coordinates analysis (PCoA) revealed distinct microbial stratification between intestinal compartments (ileum vs. cecum), with domestication-associated divergence observed primarily in the cecum. Metabolomic profiles were relatively stable across both segments and populations. Mallards harbored a more diverse and metabolically versatile gut microbiota, with significant enrichment in pathways related to carbohydrate, amino acid, and vitamin metabolism. The genus Gemmiger emerged as a key functional contributor, supporting branched-chain amino acid biosynthesis, coenzyme activation, and carbohydrate utilization, thus reflecting enhanced metabolic adaptability. In Shaoxing ducks, the gut microbiome was enriched in the glucagon signaling pathway and glucose-regulatory metabolites such as l-carnitine, myo-inositol, and quinate. Butyricicoccus sp017886875 was identified as a candidate taxon associated with glucose homeostasis. Additionally, immune-related pathways, including the NOD-like receptor signaling and antigen processing and presentation, were significantly enriched and linked to Anaerobiospirillum and Parabasalia, respectively. Co-enrichment of anti-inflammatory metabolites suggests the presence of a host-microbiota feedback mechanism that mitigates inflammation while maintaining immune readiness. These findings reveal that gut microbiota contribute to population-specific environmental adaptation in ducks, with distinct microbiome and functional traits associated with domestication history. The study highlights microbiota-mediated host adaptation as a key feature of domestication-related ecological transitions.