Identification of Prostate Cancer Predisposition Genes on the Y Chromosome

Abstract

We used various methods to perform a test for an excess of prostate cancer among males sharing the same Y chromosome. Methodology is being refined by comparing 2 competing methods and selecting the preferred model. This analysis identified a ranked list of Y chromosomes from the UPDB resource. A set of 20 samples representing the top 10 high risk and 10 low-risk Y chromosomes for genotyping with a set of 16,000 Y SNPs, and Y chromosome full genome sequencing was submitted. We used available Utah data for ~1,000 Y chromosome SNPs on 80 high risk Y chromosomes and 150 low risk Y chromosomes with some Y chromosome genotype data available. The set of ~1,000 SNPs was used to perform a phylogenetic analysis of the high vs low risk Y chromosomes; some clustering of high risk Y chromosomes was noted. Analysis of 10 high risk Y sequence data compared to 10 low risk Y sequence data, identified 3 coding and 3 non -coding candidate genes/variants seen in excess in high-risk Y chromosomes and not observed in the low risk set. We used the ranked list of Y chromosomes from our initial analysis to select a set of 100 YIDs to submit for complete Y chromosome sequencing for analysis as cases. Complete Genomics and provided us with Y chromosome sequence data for 1,800 control men.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2017
Accession Number
AD1048411

Entities

People

  • Alun Thomas
  • Craig Teerlink
  • Lisa Cannon-Albright

Organizations

  • University of Utah

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Chromosomes
  • Computational Biology
  • Computer Programming
  • Computer Programs
  • Data Sets
  • Genes
  • Genetic Phenomena
  • Genetic Structures
  • Genetics
  • Genome
  • Genotypes
  • Identification
  • Neoplasms
  • Prostate
  • Prostate Cancer
  • Quality Control
  • Sequences

Fields of Study

  • Biology

Readers

  • Molecular and genetic basis of cancer.
  • Regression Analysis.