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Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
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Prioritizing genes for X-linked diseases using population exome data.

Xiaoyan Ge1, Pui-Yan Kwok2, Joseph T C Shieh3

  • 1Division of Medical Genetics, Department of Pediatrics, University of California San Francisco, San Francisco, CA 94143, USA Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA.

Human Molecular Genetics
|September 14, 2014
PubMed
Summary
This summary is machine-generated.

We developed a method using human exome data to predict gene pathogenicity by analyzing non-synonymous variation. A low ratio of non-synonymous to synonymous substitutions (dN/dS) indicates genes linked to childhood diseases, aiding in identifying new disease genes.

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Area of Science:

  • Genomics
  • Human Genetics
  • Computational Biology

Background:

  • High-throughput sequencing generates vast genomic data, but interpreting variants of uncertain significance and unannotated genes is challenging.
  • Identifying disease-causing genes is crucial for genetic diagnostics and understanding disease mechanisms.
  • Clinically significant genes may be under negative selection, influencing their variation patterns.

Purpose of the Study:

  • To develop and test a prediction method for inferring gene-based pathogenicity using population-level variation data.
  • To assess the utility of the non-synonymous to synonymous substitution rate ratio (dN/dS) for identifying disease-associated genes, particularly on the X-chromosome.
  • To identify novel candidate disease genes and potential pathogenic hotspots.

Main Methods:

  • Integrated exome data from over 6000 individuals from the NHLBI Exome Sequencing Project.
  • Developed a prediction method based on the ratio of non-synonymous to synonymous substitution rates (dN/dS) to measure the paucity of non-synonymous variation.
  • Applied the dN/dS analysis to X-chromosome genes to infer pathogenicity.

Main Results:

  • A low dN/dS ratio was found to characterize genes associated with childhood disease and outcome.
  • The method successfully identified new candidate genes for diseases associated with early mortality.
  • Intragenic patterns of variants suggested the presence of pathogenic hotspots within genes.

Conclusions:

  • Intrahuman substitution analysis, particularly the dN/dS ratio, is a valuable tool for prioritizing novel disease genes.
  • This approach aids in the interpretation of large-scale genomic data, improving diagnostic capabilities.
  • The findings highlight the role of negative selection in shaping human genetic variation and its utility in disease gene discovery.