Ask about this productRelated genes to: ZNF385D antibody
- Gene:
- ZNF385D NIH gene
- Name:
- zinc finger protein 385D
- Previous symbol:
- ZNF659
- Synonyms:
- FLJ22419
- Chromosome:
- 3p24.3
- Locus Type:
- gene with protein product
- Date approved:
- 2005-01-24
- Date modifiied:
- 2014-11-18
Related products to: ZNF385D antibody
Related articles to: ZNF385D antibody
- The characterization of genetic architecture and the optimization of genomic prediction are pivotal for the genetic improvement of complex traits in poultry. In this study, we investigated the genetic basis of 15 growth and carcass traits in an F2 chicken population (n = 877) using high-depth whole-genome sequencing with an average coverage of 31.2 × . By implementing an ensemble strategy involving four independent callers, we identified 35,924 high-confidence structural variations (SVs), with deletions being the most prevalent type. Combining SNPs and SVs enhanced genomic heritability for 14 out of 15 traits compared to SNPs alone. SNP-based GWAS corroborated well-known genes, including the prominent QTL cluster on chromosome 1, the NCAPG-LCORL locus on chromosome 4, and IGF2BP1 on chromosome 27. Notably, SV-based analysis unveiled additional candidate genes, such as ZNF385D, MYH10, and MOB1B. To gain functional insights, eQTL-GWAS colocalization analysis integrating SNP-based GWAS signals with tissue-specific eQTL data identified significant colocalization signals for ITM2B in brain tissue, potentially implicating excitatory synaptic transmission, and TRIM13 in blood, potentially implicating inflammatory and immune regulation. To optimize genomic breeding value estimation through the effective utilization of multi-type markers, we developed GPDLBP, a hybrid deep learning framework that integrates locally connected networks to capture SV effects with the GBLUP model for SNP effects. Compared with the traditional SNP-only model, GPDLBP improved prediction accuracy for most traits, with gains exceeding 2% for BW21 (body weight at 21 days of age), BW49 (body weight at 49 days of age), EW (eviscerated weight), LMW (leg muscle weight), and AFW (abdominal fat weight); for example, prediction accuracy increased from 0.512 to 0.532 for BW49 and from 0.471 to 0.491 for EW. These findings show that SVs complement SNPs in both genetic dissection and genomic prediction of economically important traits in chickens. The integration of multiple variant types provides a practical strategy for accelerating precision breeding in high-depth sequencing-based poultry programs. - Source: PubMed
Publication date: 2026/08/03
Ye HaoqiangZhang SiyuQi LinLiu XiaoqiBello Semiu FolaniyiZhao ChangbinLuo WenNie Qinghua - Atherosclerosis (AS) is a complex cardiovascular disorder driven by endothelial cell dysfunction and immune microenvironment dysregulation. We identified novel endothelial-related diagnostic biomarkers through multi-omics integration and machine learning approaches. - Source: PubMed
Publication date: 2026/02/08
Xue FenlongShi YingZhang YuhuiZhu Rangfei - Single-cell and single-nuclei RNA-sequencing (scRNA-seq and snRNA-seq) analyze cell-specific transcriptomes. However, only snRNA-seq applies to frozen biobanked samples. For human pancreatic islets, marker genes and reference-based cell type annotation methods are mainly from scRNA-seq datasets and may not be suitable for snRNA-seq. We compared human islet scRNA-seq and snRNA-seq data from the same donors (N = 4) and evaluated annotation methods by studying cell type composition and gene detection, and identified novel marker genes. We compared cell type annotations: (1) manual annotation based on identified marker genes, (2) reference-based annotation using Azimuth's scRNA-seq pancreasref dataset, or (3) Seurat's label transfer from the Human Pancreas Analysis Program (HPAP) scRNA-seq dataset. ScRNA-seq and snRNA-seq identified the same cell types, but predicted cell type proportions differed. Cell type proportion-differences between annotation methods were larger for snRNA-seq. Reference-based annotations generated higher cell type prediction and mapping scores for scRNA-seq than snRNA-seq. Manual annotation identified the novel snRNA-seq markers DOCK10, KIRREL3 (beta cells), STK32B (alpha cells), MECOM, AC007368.1 (acinar cells), LAMC2 and SLC28A3 (ductal cells), which improve snRNA-seq-based annotation. We confirmed ZNF385D as a snRNA-seq beta cell marker and ZNF385D silencing reduced insulin secretion. In conclusion, this study discovered novel snRNA-seq cell type marker genes in human pancreatic islets, and highlights the need for tailored snRNA-seq annotation strategies. - Source: PubMed
Publication date: 2025/10/16
Engström KarinNilsson ÅsaOfori Jones KWierup NilsBacos KarlLing Charlotte - Under the combined effects of long-term natural selection and artificial domestication, Tibetan sheep on the Qinghai-Tibet Plateau have evolved distinct ecotypes to survive extreme high-altitude conditions, including hypoxia, cold, and low oxygen levels. These ecotypic variations not only serve as an ideal model for studying plateau livestock adaptation but also harbor valuable genetic diversity. However, the lack of comprehensive genetic analyses on their adaptive and phenotypic traits has hindered the effective conservation and utilization of these resources. Using whole-genome resequencing, we systematically studied seven Tibetan sheep breeds, uncovering their genetic structure and diversity. Population analyses, including NJ and maximum likelihood trees, revealed clear genetic differentiation and migration patterns. Selective sweep analyses (Fst and θπ) identified hypoxia-related genes (DOCK8, IGF1R, JAK1, SLC47, TMTC2, and VPS13A) and wool color genes (TCF25, MITF, and MC1R). GWAS further detected candidate genes for body size traits (height, length, weight), enriched in cGMP-PKG, cAMP, and Hedgehog signaling pathways. Integrating GWAS and transcriptomics, we pinpointed key wool trait genes, including WNT16 (non-synonymous mutations), PRKCA, MAP3K8, MMP7, OVOL2 (intergenic SNPs), and COL7A1, KDM8, ZNF385D (intronic SNPs). Notably, HOX family transcription factors were found to critically regulate hair follicle development. These genetic markers offer promising targets for molecular breeding to enhance wool quality and adaptive traits. Our findings provide a genetic basis for understanding Tibetan sheep's unique adaptations and production traits, supporting future breeding strategies and sustainable utilization of their genetic resources. - Source: PubMed
Publication date: 2025/07/02
Tian DehongHan BuyingLi XuePei QuanbangZhou BaichengZhao Kai - Low-coverage whole-genome sequencing (LcWGS), a cost-effective genotyping method, offers greater flexibility in variant detection than SNP chips. However, to our knowledge, no studies have explored the application of LcWGS in sheep. This study aimed to evaluate the feasibility of implementing LcWGS and genotype imputation and assess their applicability in genomic studies of body weight and milk yield in sheep. A total of 45,787 birth weight (BiW), 31,135 weaning daily gain (WDG), 8,928 milk yield (MY), and 4,918 milk yield per unit of metabolic body weight (MWMY) data records were analyzed. Among these, 2,366 sheep had imputed high-density genotypes. Simulated sequencing depths from 0.1× to 3× were imputed using reference panels of 100 to 600 individuals. Genotype concordance with true data improved from 0.8875 to 0.9852 as the sequencing depth and panel size increased. The single-step GBLUP method applied to the imputed data yielded higher accuracy for BiW, WDG, MY, and MWMY than the classical pedigree-based BLUP, and notably increased MY accuracy from 0.61 to 0.66. Furthermore, a weighted single-step genome-wide association study identified key genes associated with BiW (ANKS1B, OPRM1, CSMD1), WDG (TKDP5, GRP, RAX, IGFBP7), MY (CCSER1, FGGY, HOOK1), and MWMY (NDUFA10, ZNF385D, NWD1), revealing the importance of multiple pathways in sheep growth and milk production. This is the first study to assess the feasibility of combining LcWGS with genotype imputation for sheep genomic selection, balancing economic costs and imputation efficiency. Furthermore, we demonstrate an effective approach for identifying genetic variants linked to body weight and milk production, offering a cost-effective strategy for dairy sheep breeding. - Source: PubMed
Publication date: 2025/01/06
Li DXiao YChen XChen ZZhao XXu XLi RJiang YAn XZhang LSong Y