Prostate cancer is a complex disease with a substantial genetic contribution involved in the disease risk. Several genomewide linkage studies conducted so far have demonstrated a strong heterogeneity of susceptibility. In order to assess candidate regions that are particularly relevant for the German population, we performed a genomewide linkage search on 139 prostate cancer families. A nonparametric method (Zlr scores), using GENEHUNTERPLUS, was applied at 500 markers (panel P1400, deCODE), with an average spacing of 7.25 cM. In the entire family collection, linkage was most evident at 8p22 (Zlr=2.47, P=0.0068), close to the previously identified susceptibility gene MSR1. Further local maxima with Zlr>2 (P<0.025) were observed at 1q, 5q and 15q. In a subgroup of 47 families, which matched the Johns Hopkins criteria of hereditary prostate cancer, suggestive linkage was found on 1p31 (Zlr=3.37, P=0.00038), a previously not described candidate region. The remaining 92 pedigrees, with no strong disease history, revealed a maximum Zlr=3.15 (P=0.00082) at 8q13, possibly indicating a gene with reduced penetrance or recessive inheritance. Our results suggest pronounced locus heterogeneity of prostate cancer susceptibility in Germany. In the present study population, the MSR1 gene could play a significant role. Other conspicuous loci, like 1p31 and 8q13, need further investigation in order to verify their relevance and to identify candidate genes.
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http://dx.doi.org/10.1038/sj.ejhg.5201333 | DOI Listing |
Gigascience
January 2025
State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China.
Background: Plumage coloration is a distinctive trait in ducks, and the Liancheng duck, characterized by its white plumage and black beak and webbed feet, serves as an excellent subject for such studies. However, academic comprehension of the genetic mechanisms underlying duck plumage coloration remains limited. To this end, the Liancheng duck genome (GCA_039998735.
View Article and Find Full Text PDFHortic Res
January 2025
College of Horticulture, Sichuan Agricultural University, Chengdu 611130, China.
Cherries are one of the economically important fruit crops in the Rosaceae family, genus. As the first fruits of the spring season in the northern hemisphere, their attractive appearance, intensely desirable tastes, high nutrients content, and consumer-friendly size captivate consumers worldwide. In the past 30 years, although cherry geneticists and breeders have greatly progressed in understanding the genetic and molecular basis underlying fruit quality, adaptation to climate change, and biotic and abiotic stress resistance, the utilization of cherry genomic data in genetics and molecular breeding has remained limited to date.
View Article and Find Full Text PDFAm J Hum Genet
January 2025
Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, MN, USA. Electronic address:
Alzheimer disease (AD) is a complex and progressive neurodegenerative disorder that accounts for the majority of individuals with dementia. Here, we aim to identify causal plasma proteins for AD, shedding light on the etiology of AD. We utilized the latest large-scale plasma proteomic data from the UK Biobank Pharma Proteomics Project (UKB-PPP) and AD genome-wide association study (GWAS) summary data from the International Genomics of Alzheimer's Project (IGAP).
View Article and Find Full Text PDFMol Breed
January 2025
College of Agronomy, Northwest A&F University, Yangling, 712100 Shaanxi China.
Unlabelled: Pre-harvest sprouting (PHS) of wheat ( L.) is one of the complex traits that result in rainfall-dependent reductions in grain production and quality worldwide. Breeding new varieties and germplasm with PHS resistance is of great importance to reduce this problem.
View Article and Find Full Text PDFJ Cell Mol Med
January 2025
Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
This study aims to elucidate the potential genetic commonalities between metabolic syndrome (MetS) and rheumatic diseases through a disease interactome network, according to publicly available large-scale genome-wide association studies (GWAS). The analysis included linkage disequilibrium score regression analysis, cross trait meta-analysis and colocalisation analysis to identify common genetic overlap. Using modular partitioning, the network-based association between the two disease proteins in the protein-protein interaction set was divided and quantified.
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