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PubMed2026

Transcriptomic responses of Porphyrophora sophorae larvae during licorice root colonization reveal coordinated remodeling of translation, mitochondrial energy metabolism and defense-related genes.

BACKGROUND: Porphyrophora sophorae is a subterranean piercing-sucking scale insect that damages licorice (Glycyrrhiza uralensis) roots, but the molecular responses associated with larval root colonization remain insufficiently defined. METHODS: We compared non-parasitic larvae (NP) and root-colonizing larvae (RC) using six RNA-seq libraries, de novo transcriptome assembly, DESeq2-based differential expression analysis, GO/KEGG enrichment, annotation-based candidate gene screening, and RT-qPCR validation of selected genes. RESULTS: Sequencing yielded 260.91 million clean reads, and de novo assembly produced 60,794 non-redundant transcripts. DESeq2 identified 703 FDR-significant DEGs, including 49 upregulated and 654 downregulated genes in RC larvae. Upregulated genes were mainly associated with translation- and ribosome-related processes, whereas downregulated genes were enriched in mitochondrial, oxidation-reduction, energy metabolism, and oxidative phosphorylation-related functions. Annotation-based screening identified 75 FDR-significant candidate genes associated with chemosensation, defense-related responses, and energy metabolism, with mitochondrial energy metabolism-related genes forming the largest module. RT-qPCR validation based on the raw Ct data showed concordant expression directions for ten selected transcript targets. CONCLUSIONS: Root colonization in P. sophorae larvae was associated with coordinated transcriptional remodeling involving selective activation of translation-related processes, adjustment of mitochondrial energy metabolism, and changes in defense-related gene expression. These results provide candidate molecular targets for future functional studies of host contact, feeding establishment, and physiological adjustment in this subterranean scale insect.

Animals↗
PubMed2025

Bioinformatics analysis of miR-2861 and miR-5011-5p that function as potential tumor suppressors in colorectal carcinogenesis.

BACKGROUND: The study aimed to was to investigate the relationship between miR-2861, miR-5011-5p, and colorectal carcinogenesis. METHOD: In the present study, it was isolated RNA from both the tumor and non-tumor tissue of a total of 80 CRC patients and after synthesizing the cDNA, it was performed qRT-PCR to determine the expression levels of miR‑2861 and miR‑5011-5p. In addition, it was predicted that dysregulated miRNAs targets, pathways and functional gene annotations that may be important in colorectal carcinogenesis using KEGG pathway and GO analysis. RESULTS: The resulting data revealed that both expression levels of miR-2861 and miR-5011-5p were significantly decreased in tumor tissues compared with non-tumor tissues of CRC patients. The GO and KEGG pathway analysis showed that miR-2861 and miR-5011-5p may participate in multiple the biological process, cellular components, and molecular function subcategories such as mitotic cell cycle, regulation of small GTPase mediated signal transduction, cell death, and acid binding transcription factor activity. It was also revealed that target genes of miRNAs can be found in signaling pathways such as TGF-beta, Rap1, Ras, cAMP, Wnt, mTOR and, PI3K-Akt signaling pathways. CONCLUSION: These findings imply that miR-2861 and miR-5011-5p might function as tumor suppressors in the development of CRC.

MicroRNAs↗
PubMed2026

Structural genomics sheds light on protein functions and remote homologs across the insect tree of life.

Protein structure bridges the sequence-function relationship, enabling deep exploration of biological processes across diverse organisms. Insects, the most diverse animal lineage, accounting for over 50% of all described animal species, provide an exceptional system for exploring sequence-structure-function relationships. Here, we reconstructed a comprehensive and well-resolved phylogeny of 4854 insects, spanning all orders. Leveraging this framework, we created an atlas of 13.29 million predicted protein structures from 824 representative species, including 11.63 million newly predicted structures. Structural clustering revealed that proteins with divergent sequences but similar structures could be effectively grouped together. Structural similarity searches against proteins with well-characterized functions yielded annotations for 7.61 million insect proteins, including up to 14% of previously unannotated proteins. We further identified 750 million remote homologs between insect proteins, many of which trace back to ancient branches of the insect phylogeny. Remarkably, despite extensive sequence divergence, cGAS-like receptors (cGLRs) were structurally conserved across all 824 insects. Experimental assays demonstrated that these structurally identified cGLRs play a crucial role in antiviral defense in the yellow fever mosquito. Our findings highlight the significance of structural genomics for understanding protein function and evolution across the tree of life.

Animals↗
PubMed2025

Chromosome-level genome assembly and annotation of Pterygoplichthys pardalis.

Suckermouth catfishes, with their evolved powerful features, have become notorious invasive species, causing significant damage to aquatic ecosystems. However, the lack of high-quality genomes severely restricts research on this group within the field. In this study, we de novo assembled the chromosome-level genome assembly of Pterygoplichthys pardalis using multiple platforms of sequencing data, including Illumina short reads, Nanopore long reads, and Hi-C sequencing reads, resulting in a 1.51 Gb genome assembly. Multiple evaluations, including read mapping ratio (98.52%), transcript mapping ratio (99.61%), conserved BUSCO gene set (98.8%), and N50 score (49.47 Mb), indicated the high continuity and accuracy of the genome assembly we generated. Genome annotation found that 0.97 Gb of genome sequences are repetitive sequences, accounting for 64.47% of the genome assembly. Further, 23,859 protein-coding genes were successfully predicted, 92.92% of which could be annotated in functional databases. This high-quality genome assembly of P. pardalis provides a valuable resource for understanding the genetic underpinnings of P. pardalis's invasive success and offers critical data for future fisheries research and management.

Animals↗
PubMed2025

PICRUSt2-SC: an update to the reference database used for functional prediction within PICRUSt2.

SUMMARY: PICRUSt2 is a bioinformatic tool that predicts microbial functions in amplicon sequencing data using a database of annotated reference genomes. We have constructed an updated database for PICRUSt2 that has substantially increased the number of bacterial (19,493 to 26,868) and archaeal (406 to 1,002) genomes as well as the number of functional annotations present. The previous PICRUSt2 database relied on many timely and computationally intensive manual processes that made it difficult to update. We constructed a new streamlined process to allow regular upgrades to the PICRUSt2 database on an ongoing basis, and used this process to create a new database, PICRUSt2-SC (Sugar-Coated). Additionally, we have shown that this updated database contains genomes that more closely match study sequences from a range of different environments. The genomes contained in the database therefore better represent these environments and this leads to an improvement in the predicted functional annotations obtained from PICRUSt2. AVAILABILITY AND IMPLEMENTATION: PICRUSt2 source code is freely available at https://github.com/picrust/picrust2 and at https://anaconda.org/bioconda/picrust2. The latest version of PICRUSt2 at the time of writing is also archived: https://doi.org/10.5281/zenodo.15119781. The PICRUSt2-SC database comes pre-installed with PICRUSt2 from version 2.6.0 onwards. Step-by-step instructions for making the updated database are at https://github.com/picrust/picrust2/wiki/Updating-the-PICRUSt2-database. All code used for the analyses and figures in this manuscript is at https://github.com/R-Wright-1/PICRUSt2-SC_application_note and https://doi.org/10.5281/zenodo.15119770.

Software↗
PubMed2025

Assessment of genomic prediction capabilities of transcriptome data in a barley multi-parent RIL population.

Low-cost and high-throughput RNA sequencing data for barley RILs achieved GP performance comparable to or better than traditional SNP array datasets when combined with parental whole-genome sequencing SNP data. The field of genomic selection (GS) is advancing rapidly on many fronts including the utilization of multi-omics datasets with the goal of increasing prediction ability and becoming an integral part of an increasing number of breeding programs ensuring future food security. In this study, we used RNA sequencing (RNA-Seq) data to perform genomic prediction (GP) on three related barley RIL populations. We investigated the potential of increasing prediction ability by combining genomic and transcriptomic datasets, adding whole-genome sequencing (WGS) SNP data, functional annotation-based filtering, and empirical quality filtering. Our RNA-Seq data were generated cost-efficiently using small-footprint plant cultivation, high-throughput RNA extraction, and Library preparation miniaturization. We also examined sequencing depth reduction as an additional cost-saving measure. We used fivefold cross-validation to evaluate the prediction ability of the gene expression dataset, the RNA-Seq SNP dataset, and the consensus SNP dataset between the RNA-Seq and parental WGS data, resulting in prediction abilities between 0.73 and 0.78. The consensus SNP dataset performed best, with five out of eight traits performing significantly better compared to a 50K SNP array, which served as a benchmark. The advantage of the consensus SNP dataset was most prominent in the inter-population predictions, in which the training and validation sets originated from different RIL sub-populations. We were therefore able to not only show that RNA-Seq data alone are able to predict various complex traits in barley using RILs, but also that the performance can be further increased with WGS data for which the public availability will steadily increase.

Hordeum↗
PubMed2026

A multi-model genome-wide association study identifies genetic variants underlying resistance to Largemouth Bass Ranavirus (LMBV) in Micropterus salmoides.

Largemouth bass (Micropterus salmoides) is an economically important freshwater aquaculture species, yet recurrent outbreaks of Largemouth Bass Ranavirus (LMBV) continue to impair production and cause substantial losses. The genetic basis of host variation in LMBV resistance remains insufficiently characterized. Here, we applied a multi-model genome-wide association study (GWAS) to identify loci associated with resistance following a controlled challenge with the LMBV-23PY strain. Whole-genome resequencing was performed for 146 phenotyped fish, including 72 susceptible and 74 resistant individuals. After stringent quality control, 877,262 high-quality variants were retained and tested using six GWAS models. Across binary survival status and survival time phenotypes, 32 shared suggestive variants were consistently detected across models, representing suggestive loci for LMBV-23PY resistance. Genes within ±50 kb of these loci were annotated, and functional enrichment highlighted immune- and redox-related biological processes. Three prioritized candidates-GSTT3L (glutathione S-transferase theta-3-like), CGRP2 (calcitonin gene-related peptide 2), and NPPC (natriuretic peptide C)-were associated with pathways involved in oxidative stress responses and immune regulation. Collectively, these results provide insight into the genetic architecture of LMBV-23PY resistance in largemouth bass and identify suggestive variants and associated candidate genes for downstream validation, functional interrogation, and the development of marker-assisted and genome-enabled breeding strategies.

Animals↗
PubMed2025

Cholesterol Metabolism-related Characteristics Predict Therapeutic Response and Survival in Esophageal Cancer.

INTRODUCTION: Cholesterol homeostasis has been identified as an essential downstream pathway of mutations in TP53. Esophageal cancer is one of the most prevalent malignancies exhibiting the mutation. OBJECTIVES: To explore the significance of cholesterol metabolism-related characteristics in tumor phenotype and treatment outcomes of esophageal cancer. METHODS: We established a cholesterol metabolism-related gene set (CMGs) and performed Lasso-Cox analysis to identify prognostic signatures. Nomogram-based risk scores and clinical stages afterwards were constructed and evaluated. We simultaneously identified two metabolic subtypes based on the distinct features of the CMGs. We annotated the functional and pathway characteristics of differentially expressed genes between the clusters and compared the differences in clinical and immune characteristics. Finally, we assessed the prognostic value of signatures in the GSE53625 and two clinical cohorts using whole-exon sequencing and multiplex immunofluorescence. RESULTS: Our study identified five cholesterol prognosis-related genes (CRGs) that demonstrated superior prognostic efficacy in the training set compared to clinical staging, validated in independent public databases and two clinical cohorts. According to the different expression patterns of the signatures, patients were divided into two subtypes. The C1 group demonstrated poorer overall survival, response to immunotherapy, and downregulation of the p53 pathway. In the immune correlation analysis, we found that the risk score based on 5-signature model was significantly positively correlated with the abundance of suppressive immune cells and the immune checkpoints. Finally, we explored the impact of expression and genomic polymorphism of the signatures on the prognosis at the pan-cancer level. CONCLUSIONS: Our findings underscore the distinct expression patterns of CRGs in esophageal cancer. These signatures are efficient to serve as prognostic indicators and assess the effectiveness of immunotherapy. They may also represent promising targets in other TP53 mutant malignancies.

Humans↗
PubMed2026

Unraveling the genomic blueprint of the Indian black soldier fly: From genome assembly to evolutionary insights.

The black soldier fly (BSF) (Hermetia illucens) has been renowned for its sustainable bioconversion capabilities, resulting in smart protein production with wide applications in animal feed, bioenergy, and biofertilizer. However, the genetic mechanisms underlying efficient bioconversion and productivity remain poorly understood. To advance strain-specific applications and strengthen genetic resource availability, we present the whole genome sequencing (WGS) data for an Indian isolate of black soldier fly. The assembled genome was 1.46 Gb with a scaffold N50 of 172.7 Mb, and a GC content of 42.6%. Furthermore, 64.17% of genomic sequences were masked as repeated, and 14,317 protein-coding sequences were identified. Variant analysis against the reference genome identified 34.44 million variants (∼33.25 million SNPs and ∼ 1.18 million INDELs), with the majority (99.3%) classified as MODIFIER, 0.54% as LOW impact, 0.14% as MODERATE, and only 0.003% as HIGH impact. Comparative genomic analysis with other related species revealed expansions of gene families in BSF associated with Immune effector (Antimicrobial peptides (AMPs), Lysozymes, and Peptidoglycan Recognition Protein (PGRP) and Detoxification (cytochrome P450 enzymes). Notably, AMPs in the Indian isolate showed enhanced copy number variation in defensin (27) and PGRP (40) compared to reference BSF, suggesting potential regional adaptations to pathogen exposure. Collectively, this genomic data provides an improved resource for evolutionary studies, functional genomics, and targeted genetic improvement of BSF for sustainable bioconversion applications.

Comparative genomics↗
PubMed1998

Selection system for genes encoding nuclear-targeted proteins.

Nuclear proteins have essential roles in cell proliferation and differentiation. We have developed a yeast selection system-the nuclear transportation trap (NTT)-to identify genes encoding nuclear transport signals. Both unknown and previously identified nuclear localization signals were identified from a human fetal brain cDNA library. The majority (75%) of the unknown proteins examined were exclusively localized to the nucleus in COS-7 cells. We propose that NTT is an efficient method for isolating cDNAs that encode nuclear targeted proteins that can be applied to the retrieval of novel nuclear proteins and to annotate gene function.

Amino Acid Sequence↗
PubMed2025

OpTiles: an R package for adaptive tiling and methylation variability profiling.

SUMMARY: OpTiles is an R package that dynamically defines tiling windows based on the distribution of sequenced CpGs, addressing the limitations of traditional fixed-tiling approaches in targeted methylation datasets. By integrating CpG density with intra-region methylation variability, it provides a reliability metric and extended functionality for annotating, prioritizing, and interpreting complex methylation data. AVAILABILITY AND IMPLEMENTATION: OpTiles is implemented in R and source code is freely available at https://github.com/fhaive/OpTiles. Data are available on Zenodo at https://doi.org/10.5281/zenodo.16961292.

DNA Methylation↗
PubMed2000

The SBASE protein domain library, release 7.0: a collection of annotated protein sequence segments.

SBASE 7.0 is the seventh release of the SBASE protein domain library sequences that contains 237 937 annotated structural, functional, ligand-binding and topogenic segments of proteins, cross-referenced to all major sequence databases and sequence pattern collections. The entries are clustered into over 1811 groups and are provided with two WWW-based search facilities for on-line use. SBASE 7.0 is freely available by anonymous 'ftp' file transfer from ftp.icgeb. trieste.it. Automated searching of SBASE with BLAST can be carried out with the WWW servers http://www.icgeb.trieste.it/sbase/and http://sbase.abc.hu/sbase/

Amino Acid Sequence↗
PubMed2001

The InterPro database, an integrated documentation resource for protein families, domains and functional sites.

Signature databases are vital tools for identifying distant relationships in novel sequences and hence for inferring protein function. InterPro is an integrated documentation resource for protein families, domains and functional sites, which amalgamates the efforts of the PROSITE, PRINTS, Pfam and ProDom database projects. Each InterPro entry includes a functional description, annotation, literature references and links back to the relevant member database(s). Release 2.0 of InterPro (October 2000) contains over 3000 entries, representing families, domains, repeats and sites of post-translational modification encoded by a total of 6804 different regular expressions, profiles, fingerprints and Hidden Markov Models. Each InterPro entry lists all the matches against SWISS-PROT and TrEMBL (more than 1,000,000 hits from 462,500 proteins in SWISS-PROT and TrEMBL). The database is accessible for text- and sequence-based searches at http://www.ebi.ac.uk/interpro/. Questions can be emailed to interhelp@ebi.ac.uk.

Databases, Factual↗
PubMed2001

The SBASE protein domain library, release 8.0: a collection of annotated protein sequence segments.

SBASE 8.0 is the eighth release of the SBASE library of protein domain sequences that contains 294 898 annotated structural, functional, ligand-binding and topogenic segments of proteins, cross-referenced to most major sequence databases and sequence pattern collections. The entries are clustered into over 2005 statistically validated domain groups (SBASE-A) and 595 non-validated groups (SBASE-B), provided with several WWW-based search and browsing facilities for online use. A domain-search facility was developed, based on non-parametric pattern recognition methods, including artificial neural networks. SBASE 8.0 is freely available by anonymous 'ftp' file transfer from ftp.icgeb.trieste.it. Automated searching of SBASE can be carried out with the WWW servers http://www.icgeb.trieste.it/sbase/ and http://sbase.abc. hu/sbase/.

Binding Sites↗
PubMed2026

VicMAG, an open-source tool for visualizing circular metagenome-assembled genomes highlighting bacterial virulence and antimicrobial resistance.

Bacterial pathogens spread in clinical and environmental settings, and mobile genetic elements (MGEs), such as plasmids and phages, mediate the transfer of virulence factor genes (VFGs) and antimicrobial resistance genes (ARGs) among bacterial communities. Metagenomic analysis of environmental and wastewater samples using highly accurate long-read sequencing technologies, such as Pacific Biosciences (PacBio) HiFi sequencing, provides valuable insights into monitoring the regional spread of VFGs and ARGs, including dissemination mediated by MGEs. No visualization tool is currently available for the comprehensive display of numerous resulting circular metagenome-assembled genomes (cMAGs) with functional gene annotations. Here, we developed visualization of circular metagenome-assembled genome (VicMAG), a visualization tool for highly complex cMAGs derived from long-read metagenome assemblies annotated using updated databases of VFGs, ARGs, and MGEs. Using 353 cMAGs from PacBio HiFi sequencing of a wastewater sample, we demonstrated the utility of VicMAG for metagenome visualization. VicMAG provides comprehensive, size-aware visualization of cMAGs representing bacterial chromosomes and plasmids, annotated with VFGs, ARGs, and phages. By simultaneously visualizing all cMAGs in a framework, VicMAG facilitates a holistic understanding of the distribution and genomic context of VFGs and ARGs across complex microbial communities. This tool supports integrated surveillance of bacteria associated with virulence and antimicrobial resistance across clinical, environmental, and One Health contexts.

Metagenome↗
PubMed2025

Gene and pathway analysis of genome-wide genetic associations of bladder cancer.

BACKGROUND: Although genetic variants associated with bladder cancer (BCa) risk have been identified through hypothesis-driven and genome-wide association studies, a systematic understanding of BCa genetic susceptibility at the gene and pathway levels remains to be achieved. MATERIALS AND METHODS: In this 2-stage functional genomics study, we used 5 independent tools for genome-wide gene mapping and ranking based on BCa genome-wide association studies summary statistics, followed by a meta-analysis of gene-level significance p values, to obtain a consensus gene ranking in terms of association with BCa. Subsequently, we performed preranked gene-set enrichment analysis to identify the functional pathways involved in BCa genetic susceptibility. Joint analysis with gene-set enrichment analysis, based on somatic alteration frequency, was performed to explore the pathway-level relationships between genetic susceptibility and somatic alterations in BCa. RESULTS: Other than the well-known BCa genes (such as FGFR3, MYC, TERT, CCNE1, and TP63), we additionally prioritized a set of novel genes likely to be genetically implicated in BCa development, including SETD2, a possible tumor suppressor gene involved in chromatin remodeling. We further demonstrated convergence between genetic associations and somatic alterations at both the gene (eg, FGFR3 and TERT) and pathway levels (eg, cell cycle and chromatin modification), as well as functional ontologies specifically implicated in germline predisposition to BCa (eg, CD8/TCR signaling, immune checkpoints, and cytokine signaling). CONCLUSIONS: We identified several novel genes associated with BCa and demonstrated that genetic variants contribute to the development of BCa by affecting antitumor immunity, response to toxic exposure, and RNA and protein homeostasis and synergizing with somatic alterations in various cancer-related pathways.

Bladder cancer↗
PubMed2026

Moderate expression and activity of flocculins underlie the characteristic flocculation phenotype of Saccharomyces pastorianus.

Flocculation is a key technological trait in lager brewing, governing fermentation performance, yeast recovery, and beer quality. In the allo-aneuploid hybrid yeast Saccharomyces pastorianus, the genetic basis of flocculation remains poorly resolved due to its complex dual sub-genome architecture. Here, we systematically re-annotated and functionally characterized the complete FLO gene repertoire of the Group II strain CBS 1483. Thirteen FLO genes were identified, including allelic variants and a previously uncharacterized adhesin, Flo12, containing a Hyphal_reg_CWP domain instead of the canonical PA14 lectin-binding domain. Structural modeling revealed strong conservation of Ca²+-binding residues in PA14 domains, alongside repeat-region diversification likely contributing to functional variability. Using optogenetic expression in a FLO-null background, we demonstrated that SpcI-FLO9-1 and SpcI-FLO9-2_1 are the strongest drivers of flocculation, exhibiting NewFlo-like sugar sensitivity. Transcriptomic analysis during 17°P wort fermentation showed dynamic induction of these genes coinciding with flocculation onset. Surprisingly, deletion of both loci in CBS 1483 did not abolish but only delayed sedimentation in wort, accompanied by improved maltose utilization and attenuation. These findings reveal functional redundancy and compensatory mechanisms within the FLO network of lager yeast, highlighting the genetic complexity underlying flocculation, and providing a molecular framework to inform yeast selection, strain development, and optimization of the lager fermentation processes.IMPORTANCEFlocculation, the process by which yeast cells aggregate and settle, is essential for producing clear, high-quality lager beer, and for efficient yeast recovery during brewing. However, the genetic basis of this trait in lager yeast has remained poorly understood because these strains possess unusually complex hybrid genomes. In this study, we systematically identified and characterized the complete set of flocculation genes in the industrial lager yeast Saccharomyces pastorianus CBS 1483. We demonstrated that lager yeast flocculation is not controlled by a single dominant gene, but instead emerges from the combined action of several moderately active adhesion proteins that are expressed at low levels during fermentation. Surprisingly, deleting the two strongest candidate genes only delayed, rather than eliminated, sedimentation, revealing a robust compensatory network that preserves brewing performance. These findings refine the current understanding of yeast flocculation and provide a molecular framework for developing brewing strains with improved fermentation efficiency, product consistency, and flavor quality.

Saccharomyces pastorianus↗
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↗