Admixed populations have not been examined in detail in cancer genetic studies. Here, we inferred the local ancestry of cancer-associated single nucleotide polymorphisms (SNPs) and haplotypes of a highly admixed Brazilian population. SNP array was used to genotype 73 unrelated individuals aged 80-102 years. Local ancestry inference was performed by merging genotyped regions with phase three data from the 1000 Genomes Project Consortium using RFmix. The average ancestry tract length was 9.12-81.71 megabases. Strong linkage disequilibrium was detected in 48 haplotypes containing 35 SNPs in 10 cancer driver genes. All together, 19 risk and eight protective alleles were identified in 23 out of 48 haplotypes. Homozygous individuals were mainly of European ancestry, whereas heterozygotes had at least one Native American and one African ancestry tract. Native-American ancestry for homozygous individuals with risk alleles for HNF1B, CDH1, and BRCA1 was inferred for the first time. Results indicated that analysis of SNP polymorphism in the present admixed population has a high potential to identify new ancestry-associated alleles and haplotypes that modify cancer susceptibility differentially in distinct human populations. Future case-control studies with populations with a complex history of admixture could help elucidate ancestry-associated biological differences in cancer incidence and therapeutic outcomes.
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http://dx.doi.org/10.1590/1678-4685-GMB-2021-0172 | DOI Listing |
Biology (Basel)
December 2024
Hunan Institute of Animal and Veterinary Science, Changsha 410131, China.
Exploring the genetic landscape of native cattle is an exciting avenue for elucidating nuanced patterns of genetic variation and adaptive dynamics. Xiangnan cattle, a native Chinese cattle breed mainly produced in Hunan Province, are well adapted to the high temperature and humidity of the local environment and exhibit strong disease resistance. Herein, we employed whole-genome sequences of 16 Xiangnan cattle complemented by published genome data from 81 cattle.
View Article and Find Full Text PDFStructural variants (SVs) drive gene expression in the human brain and are causative of many neurological conditions. However, most existing genetic studies have been based on short-read sequencing methods, which capture fewer than half of the SVs present in any one individual. Long-read sequencing (LRS) enhances our ability to detect disease-associated and functionally relevant structural variants (SVs); however, its application in large-scale genomic studies has been limited by challenges in sample preparation and high costs.
View Article and Find Full Text PDFmedRxiv
December 2024
Department of Medicine, Harvard Medical School, Boston, MA, USA.
Polygenic risk scores (PRSs) depend on genetic ancestry due to differences in allele frequencies between ancestral populations. This leads to implementation challenges in diverse populations. We propose a framework to calibrate PRS based on ancestral makeup.
View Article and Find Full Text PDFBMC Immunol
January 2025
Laboratoire Génomique, Bioinformatique, et Chimie Moléculaire, Conservatoire National des Arts et Métiers, 2 rue Conté 75003, Paris, EA7528, France.
Introduction: We have reanalyzed the genomic data from the International Collaboration for the Genomics of HIV (ICGH), focusing on HIV-1 Elite Controllers (EC).
Methods: A genome-wide association study (GWAS) was performed, comparing 543 HIV-1 EC individuals with 3,272 uninfected controls (CTR) of European ancestry. 8 million single nucleotide polymorphisms (SNPs) and HLA class I and class II gene alleles were imputed to compare EC and CTR.
Am J Hum Genet
December 2024
Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; The Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX 77030, USA. Electronic address:
In recent years, significant efforts have been made to improve methods for genomic studies of admixed populations using local ancestry inference (LAI). Accurate LAI is crucial to ensure that downstream analyses accurately reflect the genetic ancestry of research participants. Here, we test analytic strategies for LAI to provide guidelines for optimal accuracy, focusing on admixed populations reflective of Latin America's primary continental ancestries-African (AFR), Amerindigenous (AMR), and European (EUR).
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