Martijn F. L. Derks

As one of the earliest domesticated and most globally ubiquitous livestock, pigs (Sus scrofa) have undergone profound environmental adaptation while following human expansion across diverse bioclimatic zones. Despite their evolutionary significance, the genomic mechanisms enabling pigs to thrive in disparate ecological settings remain poorly understood. Here, we present a comprehensive global analysis using a dataset of 1,151 pig genome sequences representing 146 distinct populations. By integrating three complementary genotype–environment association (GEA) frameworks including redundancy analysis (RDA), BayPass, and latent factor mixed models (LFMM), we identified genomic regions and candidate genes associated with environmental variation. Our analysis detected several candidate genes associated with high-altitude adaptation, particularly those involved in ultraviolet radiation response. By integrating lung single-cell RNA sequencing analysis (scRNA) from high-altitude and commercial breeds, we identified ASXL1 as a candidate gene potentially involved in high-altitude adaptation. Meanwhile, scRNA revealed candidate regulatory pathways, including the NOTCH signaling pathway, that were overlooked by traditional GEA methods, suggesting the complex regulatory landscape of physiological adaptation. Together, this study integrates large-scale population genomics and scRNA to provide insights into the genetic associations and regulatory landscapes potentially contributing to environmental adaptation in domestic pigs, advancing our understanding of livestock evolutionary responses to diverse ecological conditions.

Variant intolerance methods score the essentiality of genes based on large datasets of genetic variants and have been used in population genomics of humans and model organisms. In this paper, we estimated Residual Variation Intolerance Scores for protein-coding genes and predicted protein domains in cattle. In agreement with results from other species, the most variant-tolerant genes and domains included genes related to olfaction and adaptive immunity, whereas the least-variant tolerant genes and domains included genes involved in fundamental cellular processes. There was a moderate positive correlation with estimates from orthologous human genes. We provide estimates of variant intolerance for cattle may be useful for genomic analyses of deleterious variants and population genomics in cattle.

In this study, we provide a comprehensive genomic analysis of population structure, genetic diversity, and load across the four Asian elephant (Elephas maximus) subspecies using whole-genome sequencing data of 81 wild-born individuals, with most of them currently living under human care. Our results reveal striking contrast in inbreeding: the Bornean subspecies (E.m. borneensis) exhibits the highest level of inbreeding, with ∼65% of its genome in runs of homozygosity (ROH), and the lowest genome-wide heterozygosity (∼46 heterozygous sites per 100 kb). The Sumatran subspecies (E.m. sumatranus) shows intermediate levels of inbreeding (35% ROH) and heterozygosity (∼101 sites per 100 kb), while the mainland and Sri Lankan subspecies (E.m indicus and E.m. maximus) display similarly low inbreeding (∼10% to 11% ROH) and high heterozygosity (∼130 to 134 sites per 100 kb). Notably, when correcting for ROH coverage, heterozygosity levels are comparable across all four subspecies (∼136 to 155 sites per 100 kb), indicating that differences in genetic diversity are primarily driven by loss of heterozygosity within ROHs due to inbreeding. Genetic load remains relatively low in all subspecies, especially in highly conserved genomic regions. The high genetic diversity observed in the island-dwelling E.m. maximus subspecies likely reflects historical gene flow linked to intensive human-mediated elephant trade, raising questions about its taxonomic status. Given its high inbreeding, E.m. borneensis represents the highest conservation priority, with genetic rescue as a potential management strategy. This study highlights the urgent need for focused conservation efforts and further genomic research to safeguard the unique genetic diversity and long-term viability of Asian elephants.

Unmapped sequencing reads in livestock often contain valuable information about pathogens but are typically discarded. We analyzed blood‐derived DNA and RNA from chickens and pigs kept under high‐ and low‐biosecurity conditions, focusing on unmapped reads. In chickens, low‐biosecurity farms harbored substantially more viral sequences, primarily plant viruses, indicating environmental contamination. In pigs, Mycoplasmoides pneumoniae and several pig‐specific viruses were detected. Our bioinformatics pipeline, involving host read removal, assembly, BLAST, and taxonomic filtering, efficiently identified candidate pathogens and contaminants. This approach demonstrates the potential of sequencing‐based environmental DNA monitoring to track microbial and viral presence, assess farm biosecurity, and support animal health surveillance.

Cattle are integral to global food security, yet the molecular architecture of their complex traits remains poorly understood. Here, we present the Cattle Genotype–Tissue Expression (CattleG-TEx) Phase 1 resource (https://cattlegtex.farmgtex.org/), a substantial expansion of the pilot study. By leveraging 12,422 RNA-seq profiles across 43 tissues and 82 breeds, we characterized 433,972 primary and 161,428 non-primary regulatory effects spanning seven molecular phenotypes. This high-resolution atlas resolves 75% of GWAS signals for 44 complex traits, significantly addressing the "missing regulation" in livestock. We propose a genetic regulatory model demonstrating how variants across multiple biological layers interact with specific biological contexts to shape pheno-typic variation. Furthermore, CattleGTEx elucidates mechanisms underlying adaptive evolution between Bos taurus and Bos indicus, as well as artificial selection in dairy and beef breeds. Finally, by mapping evolutionary constraints on these regulatory effects, we demonstrate the translational value of this resource for prioritizing causal variants in human complex diseases. Together, Phase 1 of CattleGTEx provides a transformative framework for functional genomics, precision breeding, and comparative genetics.

Cattle are integral to global food security, yet the molecular architecture of their complex traits remains poorly understood. Here, we present the Cattle Genotype–Tissue Expression (CattleGTEx) Phase 1 resource ( https://cattlegtex.farmgtex.org/ ), a substantial expansion of the pilot study. By leveraging 12,422 RNA-seq profiles across 43 tissues and 82 breeds, we characterized 433,972 primary and 161,428 non-primary regulatory effects spanning seven molecular phenotypes. This high-resolution atlas resolves 75% of GWAS signals for 44 complex traits, significantly addressing the “missing regulation” in livestock. We propose a genetic regulatory model demonstrating how variants across multiple biological layers interact with specific biological contexts to shape phenotypic variation. Furthermore, CattleGTEx elucidates mechanisms underlying adaptive evolution between Bos taurus and Bos indicus , as well as artificial selection in dairy and beef breeds. Finally, by mapping evolutionary constraints on these regulatory effects, we demonstrate the translational value of this resource for prioritizing causal variants in human complex diseases. Together, Phase 1 of CattleGTEx provides a transformative framework for functional genomics, precision breeding, and comparative genetics.

Pigs are not only a key source of animal protein worldwide, but also serve as important models in biological research. With the rapid development of short- and long-read sequencing technologies, genetic studies in pigs have advanced considerably. Although extensive research has been conducted on single-nucleotide polymorphisms (SNPs) and small insertions/deletions (indels), which has provided important insights into pig domestication, evolution, and trait formation, structural variants (SVs) remain underexplored due to technical limitations in sequencing resolution, challenges in variant detection, and insufficient population-scale sampling. In this study, we constructed the Pig Structural Variant Reference Panel (PSVRP) by integrating 21 long-read and 1,193 short-read whole-genome resequencing datasets from globally diverse pig populations. A total of 319,058 high-confidence SVs were identified, comprising 196,620 insertions and 122,438 deletions. Phylogenetic and ADMIXTURE analyses revealed clear divergence between Asian and European pigs, consistent with results derived from SNPs and indels data. Selection scans highlighted candidate genes associated with key traits, such as EPAS1 and NOVA1 for high-altitude adaptation, and PLAG1 and MIB1 for body size regulation. The PSVRP provides a high-resolution, population-scale pig SVs genotyping resource. This comprehensive panel deepens our understanding of genetic variation, facilitates the discovery of functional variants underlying adaptive and economic traits, and offers new insights for precision pig breeding.

Combined Annotation Dependent Depletion (CADD) is a machine learning approach used to predict the deleteriousness of genetic variants across a genome. By integrating diverse genomic features, CADD assigns a PHRED-like rank score to each potential variant. Unlike other methods, CADD does not rely on limited datasets of known pathogenic or benign variants but uses larger and less biased training sets. The rapid increase in high-quality genomes and functional annotations across species highlights the need for an automated, non-species-specific pipeline to generate CADD scores. Here, we introduce such a pipeline, facilitating the generation of CADD scores for various species using only a high-quality genome with gene annotation and a multi-species alignment. Additionally, we present updated chickenCADD scores and newly generated turkeyCADD scores, both generated with the pipeline.

Single nucleotide polymorphisms (SNPs) can serve as genetic markers to identify genetic differences between individuals. The primary objective of this study was to use SNP chip data and the concept of Mendelian mismatches to locate genomic regions that contain deletions. The dataset comprises 298 850 Fleckvieh cattle, primarily from Austria and Germany. Animal genotyping was conducted using the Illumina 50K Bead Chip and data from 40 144 autosomal SNPs were utilized. Among the 298 850 animals, sire genotypes were available for 267 393, and dam genotypes were available for 56 546 individuals. Data analysis was performed using plink and SAS. A large number (567 996) of Mendelian mismatches caused by deletions were detected, and the inheritance of the deletions could be traced back to a few ancestors. This study has shown that the detection of hemizygous deletions based on Mendelian mismatches in parent–offspring pairs is a promising approach due to the low cost and wide availability of SNP chip data for cattle. The exact positions and sizes of the deletions may be explored with whole‐genome sequence data of animals carrying these deletions.

In Friesian horses, withers height is an important trait as a minimum has been set to be eligible to the studbook. Several loci for withers height have been identified in horses. However, withers height has not been studied in the Friesian horse. Therefore, our aim was to identify loci associated with withers height in the Friesian horse population. We performed a genome‐wide association study using 70 K SNP data of 2192 Friesian horses. We found ECA1 and ECA9 to be significantly associated with withers height, explaining 19.6% and 3.5% of the phenotypic variance, respectively. In other horse breeds, the LCORL/NCPAG locus on ECA3 showed the strongest association with withers height, but here we found that the best‐associated SNP for that locus is nearly fixed in Friesian horses for the allele associated with small size. Moreover, we observed a clear decline followed by a marked increase in average withers height of the Friesian horse over time, probably owing to shifts in its primary use over the course of the years. Additionally, the frequency of the best‐associated SNP on ECA1 has increased over time. Together, our study showed that ECA1 and ECA9 are associated with withers height in Friesian horses. Further studies should be performed to confirm candidate causal mutations.