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Updated: Mar 1, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing
Published on: February 17, 2017
Investigation of copy number variation in subjects with major depression based on whole-genome sequencing data
Chenglong Yu1, Bernhard T Baune2, Ma-Li Wong1
1Mind and Brain Theme, South Australian Health and Medical Research Institute, North Terrace, Adelaide, SA 5000, Australia; School of Medicine, Flinders University, Bedford Park, SA 5042, Australia.
Background:
Despite recent intensive research using genome-wide association studies, the underlying biological basis of major depressive disorder (MDD) still remains unknown. In contrast to genotyping platforms which identify specific variations, whole-genome sequencing (WGS) allows us to detect all private genetic variations within an individual. So far there have been no studies investigating copy number variations (CNVs) in subjects with MDD using WGS data.
Methods:
We obtained complete WGS paired-end reads data of 15 MDD patients and 10 ethnically matched healthy controls. We performed alignments for the sequencing reads and used GASV package to call CNVs including deletion, inversion, translocation and divergence for those subjects.
Results:
Our results show that, in the Mexican-American sample, deletion CNVs were significantly richer in MDD cases than healthy controls on each of 23 chromosomes. However, other types of CNVs failed to reach any significance. In the Australian sample, there was no statistically significant difference of CNVs between MDD cases and controls. Furthermore, we found that the Australian group had significantly more deletion CNVs than the Mexican-American group.
Limitations:
High quality WGS costs limited obtaining larger datasets. The GASV package does not currently support duplication or insertion CNVs.
Conclusions:
To our knowledge this is the first time that CNVs detected by WGS data are used to study major depression. The conclusion that deletion CNVs are significantly richer in MDD cases than healthy controls is consistent with the previous finding about recurrent depressive disorder by genome-wide association analysis of CNVs on a large genotyping microarray data.
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