Screening and identification of soybean seed-specific genes by using integrated bioinformatics of digital differential display, microarray, and RNA-seq data

Guangjun Yin, Hongliang Xu, Jingyi Liu, Cong Gao, Jinyue Sun, Yueming Yan, Yingkao Hu

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Soybean is one of the most economically important crops in the world. Soybean seeds have abundant protein and lipid content and very high economic value. In this study, a total of 184 seed-specific genes were obtained using online microarray databases, DDD, and RNA-seq data. The reported seed-specific genes in soybean and the 184 seed-specific genes analyzed in this paper were compared. Of the screened genes, 26 were common to both previous reports and the current screening. Meanwhile, 90 of the 184 genes have homologous counterparts in Arabidopsis, among which 24 have seed-specific expression, as indicated by microarray data for Arabidopsis. Furthermore, promoter analysis showed that almost all seed-specific genes contain at least one seed specific-related element. Seed-specific element Skn-1 motif exists in most, if not all, of the seed-specific genes screened. Five genes were randomly selected from 184 soybean seed specific gene pool and their expressions were quantified using quantitative real time polymerase chain reaction (qRT-PCR) to further confirm the specificity of the screened genes. The results indicated that all five genes showed seed-specific expression. Moreover, the identification of genes with seed-specific expression screened in this study provides information valuable to the in-depth study of soybean.

Original languageEnglish (US)
Pages (from-to)177-186
Number of pages10
JournalGene
Volume546
Issue number2
DOIs
StatePublished - Aug 10 2014

Bibliographical note

Funding Information:
The authors would like to thank Dr. Wan Ping, College of Life Sciences, Capital Normal University, China, for bioinformatics analysis. We would like to thank the National Natural Science Foundation of China ( 30971783 ) and the Natural Science Foundation of Beijing, China ( 5132005 ) for their financial support.

Keywords

  • Digital differential display
  • Microarray
  • RNA-seq
  • Seed-specific genes
  • Soybean

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