Whole-genome single nucleotide variant distribution on genomic regions and its relationship to major depression

Chenglong Yu, Bernhard Baune, Julio Licinio, Ma-Li Wong

    Research output: Contribution to journalArticlepeer-review

    11 Citations (Scopus)


    Recent advances in DNA technologies have provided unprecedented opportunities for biological and medical research. In contrast to current popular genotyping platforms which identify specific variations, whole-genome sequencing (WGS) allows for the detection of all private mutations within an individual. Major depressive disorder (MDD) is a chronic condition with enormous medical, social and economic impacts. Genetic analysis, by identifying risk variants and thereby increasing our understanding of how MDD arises, could lead to improved prevention and the development of new and more effective treatments. Here we investigated the distributions of whole-genome single nucleotide variants (SNVs) on 12 different genomic regions for 25 human subjects using the symmetrised Kullback-Leibler divergence to measure the similarity between their SNV distributions. We performed cluster analysis for MDD patients and ethnically matched healthy controls. The results showed that Mexican-American controls grouped closer; in contrast depressed Mexican-American participants grouped away from their ethnically matched controls. This implies that whole-genome SNV distribution on the genomic regions may be related to major depression.

    Original languageEnglish
    Pages (from-to)75-79
    Number of pages5
    JournalPsychiatry Research
    Publication statusPublished - 1 Jun 2017


    • Cluster analysis
    • Kullback-Leibler divergence
    • Major depressive disorder
    • Mexican-American
    • Whole-genome sequencing


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