Screening of Candidate Pathogenic Genes for Spontaneous Abortion using Whole Exome Sequencing

Author:

Zhu Qingwen1,Zhou Yiwen2,Ding Jiayi3,Chen Li3,Liu Jia2,Zhou Tao3,Bian Wenjun4,Ding Guohui2,Li Guang2

Affiliation:

1. Nantong Municipal Maternal and Child Health Hospital, Nantong, 226010, China

2. Shanghai Biological Information Research Center, Zhangjiang Hi-tech Park, Shanghai, 201203, China

3. Reproductive Medicine Center, Nantong Municipal Maternal and Child Health Hospital, Nantong, 226010, China

4. Prenatal Screening and Diagnosis Center, Nantong Municipal Maternal and Child Health Hospital, Nantong, 226010, China

Abstract

Background: Spontaneous abortion is a common disease in obstetrics and reproduction. Objective: This study aimed to screen candidate pathogenic genes for spontaneous abortion using whole-exome sequencing. Methods: Genomic DNA was extracted from abortion tissues of spontaneous abortion patients and sequenced using the Illumina HiSeq2500 high-throughput sequencing platform. Whole exome sequencing was performed to select harmful mutations, including SNP and insertion and deletion sites, associated with spontaneous abortion. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and gene fusion analyses were performed. MUC3A and PDE4DIP were two novel mutation genes that were screened and verified by PCR in abortion tissues of patients. Results: A total of 83,633 SNPs and 13,635 Indel mutations were detected, of which 29172 SNPs and 3093 Indels were screened as harmful mutations. The 7 GO-BP, 4 GO-CC, 9 GO-MF progress, and 3 KEGG pathways were enriched in GO and KEGG pathway analyses. A total of 746 gene fusion mutations were obtained, involving 492 genes. MUC3A and PDE4DIP were used for PCR verification because of their high number of mutation sites in all samples. Conclusion: There are extensive SNPs and Indel mutations in the genome of spontaneous abortion tissues, and the effect of these gene mutations on spontaneous abortion needs further experimental verification.

Publisher

Bentham Science Publishers Ltd.

Subject

Organic Chemistry,Computer Science Applications,Drug Discovery,General Medicine

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