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PubMed2026

Development of a 10K breeder-friendly SNP chip for faba bean.

INTRODUCTION: Faba bean breeding and genomics have seen steady progress in recent years, supported by genome sequences and high-density genotyping platforms. These tools have been valuable for trait mapping, diversity assessment, and genomic research, but they have limited routine use in breeding programs due to their relatively high cost. Recent progress in establishing an optimized, cost-efficient genotyping-by-sequencing protocol tailored to the large and complex faba bean genome has created the foundation for a more accessible genotyping solution. METHODS: Using this approach, we explored the genetic diversity of faba bean germplasm from various panels, providing a comprehensive representation of the crop's genetic landscape. From this dataset, we identified and selected a high-quality set of informative SNP markers that are evenly distributed across the genome. Building on these resources, we designed a breeder-friendly 10K SNP chip. RESULTS: The 10K SNP chip delivers high accuracy, broad genomic coverage, and affordability. The chip was validated across diverse germplasm panels, demonstrating strong clustering performance, high reproducibility, and applicability to breeding-relevant germplasm. DISCUSSION: This platform offers a cost-effective alternative to higher-density arrays, enabling its integration into genomic selection, marker-assisted breeding, and diversity monitoring, ultimately supporting accelerated genetic gain and the delivery of improved varieties to farmers.

SNP chip↗

PubMed2026

Multi-omics analysis identifies key genes and functional loci affecting teat number in American Large White and Landrace pigs and their application in optimizing genomic selection models.

BACKGROUND: Teat number is a crucial economic trait in pigs. It directly affects the ability of sows to lactate, which in turn influences the survival and health of piglets. The teat number of French Large White pigs is close to 16, while the teat number of American Large White and Landrace pigs is about 14. In order to improve the teat number of American Landrace and Large White pigs through molecular approaches and precise breeding techniques, we genotyped 2,131 American Landrace and 4,564 American Large White with teat number phenotype using a 50 K SNP chip. Then, the SNP-chip data was imputed to the level of whole-genome sequencing (iWGS). Based on iWGS data, we conducted GWAS to identify novel, significant SNPs associated with teat number and to incorporate them into genomic selection. RESULTS: In Landrace pigs, significant SNPs for TTN mapped to SSC2, SSC7, SSC8, and SSC14; the SSC8 and SSC14 effects are novel. LTN mapped to SSC7, RTN to SSC7 and SSC8. The lead SSC7 SNP explained 2.60% of TTN phenotypic variance. In Large White pigs, significant SNPs were detected on SSC7 and SSC10 for TTN; SSC7, SSC10, and SSC12 for LTN; and SSC7 and SSC10 for RTN. The most significant locus on SSC7 accounted for 2.99% of the phenotypic variance in TTN. Additionally, a multi-population meta-analysis detected significant novel SNPs for LTN on SSC1 and SSC8. By utilizing Bayesian fine mapping, the most precise QTL confidence interval on SSC7 for both TTN and RTN in Large White pigs was reduced to 40 kb. By integrating functional gene annotation with RNA-seq and ATAC-seq data from Erhualian and Bamaxiang pigs mammary placodes at embryonic day 26, we prioritized PTPN13, TRPV3, ZDHHC13, and BRD2 as novel candidate genes for teat number. We then incorporated the significant SNPs to GBLUP and benchmarked genomic-selection accuracy. In both breeds, fitting the top SNP as fixed maximized prediction for TTN and RTN, whereas treating all significant loci as an additional random effect optimized LTN. CONCLUSIONS: Our findings provide a theoretical basis for dissecting new key genes affecting teat number and for advancing molecular breeding of teat number in pigs.

Animals↗

PubMed2025

Development and validation of a high-density 'Amahysnp' genotyping array in grain amaranth (Amaranthus hypochondriacus).

BACKGROUND: Grain amaranth has recently gained global attention as a promising crop alternative to traditional cereals due to its nutritional value and adaptability to various growing conditions. Although gene banks conserve extensive collections of amaranth germplasm, the genomic and phenotypic characterization of these resources is limited, which hinders their full utilization in breeding programs. A major challenge is the lack of high-throughput genotyping assays essential for comprehensive genomic characterization and trait mapping. High-density SNP arrays have become standard tools for genome-wide analysis across multiple loci, enabling molecular breeding across a range of crop species. RESULTS: In this study, we developed a 64 K high-throughput SNP genotyping array named "AmahySNP", using Affymetrix® Axiom® technology. The array contains 64,069 high-density SNPs distributed across both genic (55.17%) and non-genic (44.83%) regions of the Amaranthus hypochondriacus genome. The genic region includes 8,879 genes, which consist of 4,830 single-copy genes and 4,049 multi-copy genes distributed across 16 scaffolds. These genes cover various functional regions, including exons (10.5%), introns (40.1%), 5'UTRs (1.6%), and 3'UTRs (2.9%), respectively. The AmahySNP array was effectively utilized for population structure analysis, genetic diversity studies, core development, and genome wide association studies (GWAS) in amaranth germplasm. A representative core set of 112 accessions was identified, which includes two released varieties (Annapurna and Suvarna) and 100 diverse accessions from 12 different regions, representing 12% of the total 917 accessions evaluated. Phylogenetic analysis revealed three major genetic clusters, independent of their geographical origins. GWAS conducted using 22,763 polymorphic SNPs from 540 genotypes identified 13 novel loci associated days to flowering (DTF) trait, seven of which were located within annotated genes. CONCLUSIONS: The AmahySNP 64 K SNP chip a valuable genomic tool for amaranth research and breeding with a strong potential to accelerate its genetic improvement. It enables high-throughput genotyping for a wide range of applications, including GWAS and other genomic studies, and will significantly advance the exploration of natural genetic variations. Ultimately, this resource will empower amaranth breeders to develop improved amaranth cultivars with enhanced crop yield, resilience, and nutritional quality, contributing to global food security and sustainable agriculture.

Amaranthus↗

PubMed2026

Estimation Model of Pig Weight Based on Body Measurements and Analysis of Its Genetic Basis.

Body weight and body measurements are key indicators of growth and economic efficiency in pigs, but conventional weighing is labor-intensive and stressful, increasing disease risk and necessitating non-contact estimation. We measured five dimensions (body length, chest circumference, abdominal circumference, body width, and body height) in 811 Suzi black pigs and constructed six multiple linear regression models using different combinations. All models had R2 > 0.91, with adjusted R2 also exceeding 0.91, and the model combining length, chest, and abdominal circumference gave the lowest RMSE, balancing accuracy and practicality. Separately, we performed GWAS on 165 genotyped individuals (100 K SNP chip and GBS) for age (as a growth rate proxy), body weight, and the five measurements. No SNP reached genome-wide significance (p < 1.86 × 10-6), but three suggestive loci (p < 1.39 × 10-5) were detected: SNP 4_12 319 200 for age (35.55% variance), a pleiotropic SNP 1_60 912 826 associated with length, chest, and abdominal circumference (42.10%, 53.06%, and 45.97% variance), and SNP 1_60 638 159 for abdominal circumference. Positional mapping identified EPHA7 as the nearest candidate gene. Enrichment analyses revealed focal adhesion, receptor tyrosine kinase, IgSF-CAM, integrin, and PI3K-Akt pathways, with EPHA7 and FYN as key regulators. Notably, the three traits in the best model mapped to the same pleiotropic locus, suggesting a shared genetic basis. This study provides a practical estimation tool and suggestive markers, supporting non-contact weighing systems and molecular breeding.

Animals↗

PubMed2026

Towards a Standard Threshold for Genome Wide Significance in Dogs.

Genome-wide association studies (GWAS) are a foundational step in tying phenotype to genotype, relying on statistical significance thresholds to distinguish true- from false-positive signals of association. Dog genomics has long relied on per-study Bonferroni thresholds of significance, basing these on SNP chip levels of markers (~100 k to > 14 M variable sites). However, as the field progresses into whole genome imputation analyses and more powerful meta-analyses, there is a clear need to develop a standard significance threshold for common-variant GWAS. Using 1591 dogs from the broad-ancestry Dog10K dataset, we performed permutation analysis and developed GWAS thresholds for datasets using either 1% or 5% minor allele frequencies. The resultant p-values, 4.2 × 10-7 and 5.0 × 10-7 respectively, are similar to previous Bonferroni levels (p-value ~6 × 10-7), but less restrictive than the standard human p-value, 5 × 10-8, which is sometimes used in dog studies. Given the diverse haplotypes from the > 320 breeds in the Dog10K input dataset, we suggest a p-value of 4 × 10-7 as a standard significance threshold that could be applied to any dog GWAS.

Animals↗

PubMed2025

Genomic diversity and selection signatures in Asian Zebu Cattle: insights into adaptation and genetic erosion.

Indigenous cattle breeds in Asia are highly adapted to their local environments providing essential commodities such as meat, milk and draught power while also playing a key role in traditional ceremonies, and sports. Despite ongoing efforts to characterize and conserve these breeds, the increasing trend of indiscriminate crossbreeding of Zebu cattle with high-yielding taurine breeds, threatens their genetic diversity. This study investigates the population structure, inbreeding levels, effective population size, gene flow and identification of selection footprints of Asian Zebu (Bos indicus) cattle. Using an Axiom 60 K SNP chip, we analyzed genotypes from 1303 cattle across 36 populations in nine countries, including seven taurine outgroups and 29 Zebu populations from Bangladesh, Cambodia, India, Myanmar, Pakistan, and Sri Lanka. Zebu populations demonstrated moderate genetic diversity, with heterozygosity levels averaging 0.356, inbreeding coefficients ranging from 0.026 to 0.074 and genetic differentiation (FST) varied between 0.01 and 0.11. Breed clusters aligned closely with their geographic locations except for Achai (Pakistan) and Baru Harak (Sri Lanka) breeds that appeared in both Zebu and taurine clusters indicating evidence of taurine admixture. Genomic analyses identified regions under selection using extended haplotype homozygosity (EHH) and fixation index (FST) methods. Candidate genes associated with key biological functions related to environmental responsiveness, including heat tolerance (HSP90AA1), immunity (RIPK3), metabolism and fertility (REC8, CLIC4, TSSK4), were identified, reflecting adaptive traits critical for Zebu survival and utility across diverse environments. These findings provide valuable insights for conservation and management strategies aimed at preserving the unique genetic diversity of Asian Bos indicus breeds.

Animals↗

PubMed2025

Genomic study for pregnancy loss in Brahman cattle.

Reproduction has major influence on productivity of beef cattle operations. Maintaining an animal in the herd for an extended period without producing a marketable product can result in significant economic losses, compromising the efficiency of the production system. Understanding genetic variation's role in pregnancy loss (PL) is crucial for improving reproductive success in cattle. Identifying genomic regions that influence embryo and fetal survival, as well as pinpointing candidate genes associated with PL, can enhance breeding strategies. The objective of this study was to estimate variance components and investigate genetic factors associated with PL in Brahman cattle. Phenotypic records consisted of 29,905 pregnancy (28,691) and abortion (1,214) records from nulliparous, primiparous, and multiparous cows. A total of 921 animals were genotyped using a medium-density SNP chip (∼52K markers). Variance components were estimated using a threshold model to assess the binary response to PL through a single-step genomic BLUP procedure. The heritability estimate for PL was low (0.11), but the presence of genetic variance suggests that selection for improved reproductive performance is feasible. Genome-wide association analyses identified 17 candidate regions containing 92 genes. Regions on BTA4, 7, 8, 9, 11, 12, 16, 18, 19, 21, 22, and 29 harbored genes associated with embryonic development and implantation, fertilization, G protein-coupled receptors, embryonic brain development, olfactory receptor activity, and calcium signaling. Orthologous genes were also identified in humans (Homo sapiens), rats (Rattus norvegicus), and mice (Mus musculus). The candidate regions reported in this study provide insights for identifying and selecting animals with improved reproductive performance, ultimately enhancing the productivity of Brahman cattle. Moreover, our findings contribute to a better understanding of the genetic and physiological mechanisms underlying pregnancy retention in beef cattle.

Animals↗

PubMed2026

Deep soil layers show the most pronounced genetic variation in wheat root length.

Wheat is one of the most important cereals worldwide, yet significant gaps remain in our understanding of genetic variability in root traits, especially those associated with deeper rooting that support resource acquisition in challenging environments. Root traits are typically controlled by many genes with small effects and often display low heritability. Our aim was to develop a statistical approach to analyse root variation across soil depth and to determine where genetic differences in root intensity are most detectable. An experiment was conducted at the RadiMax semi-field facility, which is designed to measure deep root systems. Five years of phenotypic data recorded each June produced observations from 1500 rows. Each row captured root intensity across the soil profile from 0.6 m to 2.6 m, enabling detailed analysis of vertical root distribution. Across the five years, 513 winter wheat cultivars were grown in the facility, and among those 409 were genotyped with SNP chips. Depth-resolved regression models with random coefficients were used to quantify genetic and non-genetic variation in root intensity across soil depths, while accounting for spatial variation between rows. Random variation within rows was found to be constant across depths. The models showed that genetic variance for cumulative root intensity increased substantially below 1.1 m, with the deepest layers exhibiting the largest differences between wheat lines. Narrow-sense heritability of point measurements peaked at approximately 1.5 m ([Formula: see text]).

Genetic variability↗

PubMed2024

Copy number variant scan in more than four thousand Holstein cows bred in Lombardy, Italy.

Copy Number Variants (CNV) are modifications affecting the genome sequence of DNA, for instance, they can be duplications or deletions of a considerable number of base pairs (i.e., greater than 1000 bp and up to millions of bp). Their impact on the variation of the phenotypic traits has been widely demonstrated. In addition, CNVs are a class of markers useful to identify the genetic biodiversity among populations related to adaptation to the environment. The aim of this study was to detect CNVs in more than four thousand Holstein cows, using information derived by a genotyping done with the GGP (GeneSeek Genomic Profiler) bovine 100K SNP chip. To detect CNV the SVS 8.9 software was used, then CNV regions (CNVRs) were detected. A total of 123,814 CNVs (4,150 non redundant) were called and aggregated into 1,397 CNVRs. The PCA results obtained using the CNVs information, showed that there is some variability among animals. For many genes annotated within the CNVRs, the role in immune response is well known, as well as their association with important and economic traits object of selection in Holstein, such as milk production and quality, udder conformation and body morphology. Comparison with reference revealed unique CNVRs of the Holstein breed, and others in common with Jersey and Brown. The information regarding CNVs represents a valuable resource to understand how this class of markers may improve the accuracy in prediction of genomic value, nowadays solely based on SNPs markers.

Cattle↗

PubMed2026

Systematic Approach for Compound Angus Populations Revealing Positional Candidate Genes and Improving Prediction Accuracy in Carcass Traits.

Carcass traits, which reflect growth performance and muscle development, are economically important in beef cattle, yet their genetic determinants remain poorly characterized. Both single-population Genome-wide association studies (GWAS) methods, such as BLINK, and cross-population meta-analysis approaches are widely used to identify genetic variants, yet their comparative performance in genomic prediction for complex traits in structured populations remains underexplored. Few studies have directly compared these methods in genomic prediction. To address this gap, this study aims to (i) identify positional candidate genes associated with carcass traits and (ii) evaluate the context-dependent advantages of Covariate Adjustment (CA) and meta in genomic prediction. In this study, we analyzed carcass weight (CW), live weight (LW), and dressing percentage (DP) in 279 crossbred Angus cattle genotyped with the PHR0105_Bt140K_v1.0 SNP chip. GWAS was performed on the full population using BLINK, and results from three subpopulations were combined via meta-analysis, with significance thresholds for both approaches determined by a shuffle-based method. Candidate genes located within ±10 kb of significant SNPs were associated with different carcass traits, including STRIT1, SEL1L3, NOC4L and ANK1 for DP; SNCA and DNAH5 for CW; and GYPC, GPR158, and GUCY1A1 for LW. Prediction accuracy under MAS and MABLUP showed meta slightly outperformed BLINK in MAS, while BLINK was better with covariate adjustment; after incorporating kinship in MABLUP, meta achieved higher accuracy and population partitioning was negligible. Overall, MABLUP yielded the highest accuracy (0.52-0.79) versus MAS (0.37-0.54) in all traits. These findings provide a methodological basis for selecting appropriate GWAS strategies in structured populations and highlight candidate genes.

GS↗

PubMed2026

Genomic Regions Associated with Resistance to Soybean Cyst Nematode (Heterodera glycines Ichinohe) Population HG Type 1.2.5.7 in Dry Beans (Phaseolus vulgaris L.).

North Dakota, the largest dry bean (Phaseolus vulgaris L.) producing state in the U.S., faces an emerging production threat caused by the soybean cyst nematode (SCN; Heterodera glycines Ichinohe, 1952). Host resistance is an effective management strategy, yet resistance to the virulent SCN population HG type 1.2.5.7 has not been genetically characterized in dry beans. In this study, 170 dry bean genotypes (113 breeding lines/cultivars and 57 germplasm accessions) were evaluated for response to HG type 1.2.5.7 under controlled conditions using female index (FI) as the resistance phenotype. FI values ranged from 4.1% to 78.1%, with one genotype (PI 313733) classified as resistant, 35 moderately resistant, 104 moderately susceptible, and 30 susceptible. Genome-wide association analysis using 2,044 single-nucleotide polymorphism (SNP) markers from the 3.8K Bean Panel chip and the BLINK model identified four significant marker-trait associations on chromosomes Pv02, Pv05, Pv07, and Pv11. Linkage disequilibrium-defined candidate intervals spanned 108 kb (Pv02), 1.50 Mb (Pv05), 798 kb (Pv07), and 1.45 Mb (Pv11), collectively containing 126 annotated genes: 20 on Pv02, 39 on Pv05, 35 on Pv07, and 32 on Pv11. The intervals contained putative genes annotated for signaling and transcriptional regulation, cell wall and carbohydrate metabolism, transport, and secondary metabolism. Together, these findings indicate that the response to HG type 1.2.5.7 in dry bean is quantitative and associated with multiple genomic regions. The identified intervals provide candidate targets for independent validation, fine mapping, functional analysis, and future marker development to support breeding for SCN resistance.

Disease Resistance↗

PubMed2026

Influence of FAM13A gene polymorphism and serum matrix metalloproteinases 9 and 12 on the phenotypes of chronic obstructive pulmonary disease.

PURPOSE: FAM13A as a susceptibility gene for chronic obstructive pulmonary disease(COPD).Many studies verified that FAM13A involved epithelial‒mesenchymal transition (EMT) via the TGF-β1 pathway, some accompanied by an increase in MMP levels. The present study aimed to explore the disease susceptibility of the FAM13A gene, with clinical phenotypes, and investigate the relationships between FAM13A SNP loci and the serum levels of MMP-9 and MMP-12. PATIENTS AND METHODS: We recurited 497 patients with stable COPD patients and 303 healthy controls. Data on blood tests, pulmonary function, and HRCT imaging were collected. Serum MMP-9 and MMP-12 levels were measured by ELISA. Genomic DNA was extracted, and SNPs in the FAM13A gene were detected using targeted region genotyping chips. Logistic regression analysis was performed to assess the associations between SNP loci and COPD susceptibility. Differences in pulmonary function, haematological indicators, bronchial wall thickness, and emphysema parameters among different genotypes were evaluated. Multiple linear regression analysis was used to explore the relationship between genotypes and serum MMP-12 level. RESULTS: We screened a total of 476 SNPs and identified the rs2869947 polymorphism in the FAM13A gene as significantly associated with an increased risk of COPD,Stratified analyses further revealed that this association was particularly in males and individual with BMI ≥ 24.Serum levels of MMP-9 and MMP-12 were significantly higher in COPD patients compared with healthy controls. Genotype(AA vs.GG) showed no significant association with pulmonary function severity,bronchial wall indices,hematological marker,and serum MMP-9 levels in COPD patients(P > 0.05).Compared with GG genotype, AA genotype presented significantly higher LAA-950% and serum MMP-12 levels (P = 0.049 and P = 0.023). CONCLUSION: Our findings suggest that the FAM13A SNP rs2869947 may be associated with COPD susceptibility in the Han Chinese population. The FAM13A AA genotype increased serum MMP-12 levels and correlated with emphysema phenotype.

Humans↗

PubMed2026

Enhancer-promoter interaction maps in pig implantation tissue identify candidate cis-regulatory elements and regulatory variants.

Due to the polygenic nature of pig reproductive traits, most variants accounting for the phenotypic variation remain poorly characterized. It is well established that trait-associated variants are often enriched in regulatory elements of relevant tissues, and coordinated endometrial-conceptus crosstalk is critical for implantation success. Accordingly, this study aimed to investigate the chromatin landscape in pig endometrium-conceptus tissues and identify regulatory variants associated with reproductive traits. Combining RNA-seq and ChIP-seq, we uncovered cis-regulatory elements whose histone modification patterns correlate with gene expression. H3K27ac-based chromatin interaction profiling further resolved 2137 cis-regulatory elements involved in enhancer-promoter (E-P) interactions. Subsequent analyses identified candidate variants within these regulatory regions that associate with reproductive traits, in which the enhancer SNP rs346038249 likely affects transcriptional activity through allele-dependent transcription factor binding. Collectively, our findings provide mechanistic insights into pig embryo implantation and nominate candidate regulatory variants that merit further functional validation for their potential role in pig genetic improvement.

Embryo implantation↗

PubMed2026

Interrogation of functional variants in COPD GWAS loci by massively parallel reporter assays.

RATIONALE: Genome-wide association study (GWAS) loci often contain many linked variants, making it difficult to determine which variant is functionally relevant. Massively parallel reporter assays (MPRA) allow experimental testing of candidate variants to identify those with regulatory activity. Prior chronic obstructive pulmonary disease (COPD) MPRA studies have largely focused on individual loci, whereas broader multi-locus, multi-cell-type interrogation remains limited. OBJECTIVES: We aim to identify functional variants in five COPD GWAS loci across three lung-relevant cell types. METHODS: We screened 1120 variants using MPRA in epithelial (16HBE), fibroblast (MRC5), and endothelial (HUVEC) cells followed by reporter assay validation. Public Hi-C, ChIP-seq and ATAC-seq datasets were analyzed to evaluate chromatin context near candidate variants. We further performed CRISPR interference (CRISPRi) targeting variant-containing regions and measured gene expression by RT-qPCR in primary normal human bronchial epithelial (NHBE) cells using two gRNAs per variant. Co-immunoprecipitation was performed to test interaction between selected candidate genes. MEASUREMENTS AND MAIN RESULTS: In MPRA, we identified 25 variants with allele-specific effects (∼2% of tested variants). Enrichment of H3K27Ac and open chromatin near rs35421223 was detected in 16HBE cells. CRISPRi identified two SNP-gene pairs, RUVBL1 and RAB7A regulated by rs35421223 in both the 16HBE cell line and primary NHBE cells. We detected interaction between RUVBL1 and the known COPD gene product FAM13A. CONCLUSIONS: Screening COPD loci across three cell types identified functional regulatory variants and linked them to candidate target genes for future mechanistic studies.

Journal Article↗