Literature DB >> 24929124

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

Guangjun Yin1, Hongliang Xu2, Jingyi Liu3, Cong Gao4, Jinyue Sun5, Yueming Yan6, Yingkao Hu7.   

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.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Digital differential display; Microarray; RNA-seq; Seed-specific genes; Soybean

Mesh:

Year:  2014        PMID: 24929124     DOI: 10.1016/j.gene.2014.06.021

Source DB:  PubMed          Journal:  Gene        ISSN: 0378-1119            Impact factor:   3.688


  5 in total

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Authors:  Mahbod Sahebi; Mohamed M Hanafi; Parisa Azizi; Abdul Hakim; Sadegh Ashkani; Rambod Abiri
Journal:  Mol Biotechnol       Date:  2015-10       Impact factor: 2.695

2.  Cloning and functional verification of a porcine adipose tissue-specific promoter.

Authors:  Dawei Zhang; Liangcai Shen; Wenjing Wu; Keke Liu; Jin Zhang
Journal:  BMC Genomics       Date:  2022-05-24       Impact factor: 4.547

3.  Dynamic transcriptome profiles of skeletal muscle tissue across 11 developmental stages for both Tongcheng and Yorkshire pigs.

Authors:  Yuqiang Zhao; Ji Li; Huijing Liu; Yu Xi; Ming Xue; Wanghong Liu; Zhenhua Zhuang; Minggang Lei
Journal:  BMC Genomics       Date:  2015-05-12       Impact factor: 3.969

4.  A reverse transcription-cross-priming amplification method with lateral flow dipstick assay for the rapid detection of Bean pod mottle virus.

Authors:  Qian-Qian Yang; Xing-Xing Zhao; Dao Wang; Peng-Jun Zhang; Xue-Nan Hu; Shuang Wei; Jing-Yuan Liu; Zi-Hong Ye; Xiao-Ping Yu
Journal:  Sci Rep       Date:  2022-01-13       Impact factor: 4.996

Review 5.  Expanding Omics Resources for Improvement of Soybean Seed Composition Traits.

Authors:  Juhi Chaudhary; Gunvant B Patil; Humira Sonah; Rupesh K Deshmukh; Tri D Vuong; Babu Valliyodan; Henry T Nguyen
Journal:  Front Plant Sci       Date:  2015-11-24       Impact factor: 5.753

  5 in total

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