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
- 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 - Recurrent acute and chronic pancreatitis (RAP, CP) are complex, progressive inflammatory diseases with variable pain experiences impacting patient function and quality of life. The genetic variants and pain pathways in patients contributing to most severe pain experiences are unknown. We used previously genotyped individuals with RAP/CP from the North American Pancreatitis Study II (NAPS2) of European Ancestry for nested genome-wide associated study (GWAS) for pain-severity, chronicity, or both. Lead variants from GWAS were determined using FUMA. Loci with p<1e-5 were identified for post-hoc candidate identification. Transcriptome-wide association studies (TWAS) identified loci in cis and trans to the lead variants. Serum from phenotyped individuals with CP from the PROspective Evaluation of Chronic Pancreatitis for EpidEmiologic and Translational StuDies (PROCEED) was assessed for BDNF levels using Meso Scale Discovery Immunoassay. We identified four pain systems defined by candidate genes: 1) Pancreas-associated injury/stress mitigation genes include: REG gene cluster, CTRC, NEURL3 and HSF22. 2) Neural development and axon guidance tracing genes include: SNPO, RGMA, MAML1 and DOK6 (part of the RET complex). 3) Genes linked to psychiatric stress disorders include TMEM65, RBFOX1, and ZNF385D. 4) Genes in the dorsal horn pain-modulating BDNF/neuropathic pathway included SYNPR, NTF3 and RBFOX1. In an independent cohort BDNF was significantly elevated in patients with constant-severe pain. Extension and expansion of this exploratory study may identify pathway- and mechanism-dependent targets for individualized pain treatments in CP patients. PERSPECTIVE: Pain is the most distressing and debilitating feature of chronic pancreatitis. Yet many patients with chronic pancreatitis have little or no pain. The North American Pancreatitis Study II (NAPS2) includes over 1250 pancreatitis patients of all progressive stages with all clinical and phenotypic characteristics carefully recorded. Pain did not correlate well with disease stage, inflammation, fibrosis or other features. Here we spit the patients into groups with the most severe pain and/or chronic pain syndromes and compared them genetically with patients reporting mild or minimal pain. Although some genetic variants associated with pain were expressed in cells (1) of the pancreas, most genetic variants were linked to genes expressed in the nervous system cells associated with (2) neural development and axon guidance (as needed for the descending inhibition pathway), (3) psychiatric stress disorders, and (4) cells regulating sensory nerves associated with BDNF and neuropathic pain. Similar and overlapping genetic variants in systems 2 -4 are also seen in pain syndromes form other organs. The implications for treating pancreatic pain are great in that we can no longer focus on just the pancreas. Furthermore, new treatments designed for pain disorders in other tissues may be effective in some patient with pain syndromes from the pancreas. Further research is needed to replicate and extend these observations so that new, genetics-guided rational treatments can be developed and delivered. - Source: PubMed
Publication date: 2024/12/12
Dunbar Ellyn KGreer Phil JSaloman Jami LAlbers Kathryn MYadav DhirajWhitcomb David C