A meta-analysis of potential candidate genes associated with salinity stress tolerance in rice

Q1 Agricultural and Biological Sciences
Sukhdeep Kaur , M.A. Iquebal , Sarika Jaiswal , Gitanjali Tandon , R.M. Sundaram , R.K. Gautam , K.P. Suresh , Anil Rai , Dinesh Kumar
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引用次数: 6

Abstract

Even though cultivated rice is highly sensitive to salinity, significant variability exists in the primary and secondary gene-pool of rice with respect to traits of salinity tolerance. Breeding salinity tolerance rice varieties is imperative due to climate change and increasing rice demand for global population. A meta-analysis of plethora of genomic data and published literature available on various genes/factors associated with response to rice salinity and tolerance can be used to enlist selected candidates genes affecting salinity. Such genes can be utilized to identify potential candidate salinity resistance genes from donor rice genotypes and facilitate their transfer to high yielding varieties of rice through marker-assisted breeding. This approach has tremendous advantage over transgenic approach as no bio-safety or regulatory issues are involved in exploiting the variability.

Meta-analyses were performed on three datasets viz., rice microarray data of 166 series comprising of 2586 samples, 1228 published research literature in the last one and half decades and RNA-Seq data of 454 and Illumina from Sequence Retrieval Archive (SRA) at NCBI. Among microarray dataset, six salinity related series were finally selected and multi experiment analysis revealed 2289 differentially expressed genes belonging to 44 gene families. Out of these, 13 families viz., AP2-EREBP, AUX/IAA, bZIP, C2H2, bHLH, C3H, HB, HSF, MYB, MYB-related, NAC, Tify and WRKY were selected. Applying various parameters on the published literature data, 13 genes were selected, of which five were common to the different microarray datasets. From RNA-Seq data, total of 751 differentially expressed genes were obtained from 21 gene families, out of which 11 genes were common with those obtained from microarray data and five genes, viz., AP2-EREBP/DREB, MYB, HSF, bZIP and NAC were common to all the three data sets. Based on the results obtained, a total of 31 meta-analyzed genes have been selected and recommended for use in genetic improvement programs aimed at salinity resistance in rice.

The meta-analysis of microarray, RNA-Seq and published literature has been successfully used to select 31 best salinity tolerance associated genes which can be exploited by candidate gene approach for targeted introgression through marker assisted breeding. This approach has multi-fold advantages, as it obviates statutory and ecological issues. Such endeavors are more warranted for combating the key abiotic stresses like salinity, whose effects are increasing due to a changing climate.

水稻耐盐胁迫相关潜在候选基因荟萃分析
尽管栽培水稻对盐分高度敏感,但在水稻耐盐性状方面,主要基因库和次要基因库存在显著差异。由于气候变化和全球人口对水稻需求的增加,培育耐盐水稻品种势在必行。通过对大量基因组数据和已发表文献的荟萃分析,可获得与水稻对盐度和耐受性的反应相关的各种基因/因素,从而筛选出影响盐度的候选基因。这些基因可用于从供体水稻基因型中鉴定潜在的候选耐盐基因,并通过标记辅助育种促进其转移到高产水稻品种。这种方法与转基因方法相比具有巨大的优势,因为利用这种可变性不涉及生物安全或监管问题。对166个系列2586个样本的水稻微阵列数据、近15年来发表的1228篇研究文献和NCBI序列检索档案(SRA)中454篇和Illumina的RNA-Seq数据进行meta分析。在微阵列数据集中,最终选择了6个盐度相关序列,通过多实验分析,发现了44个基因家族的2289个差异表达基因。从中筛选出AP2-EREBP、AUX/IAA、bZIP、C2H2、bHLH、C3H、HB、HSF、MYB、MYB相关、NAC、Tify、WRKY等13个家族。通过对已发表文献数据的各种参数分析,共筛选出13个基因,其中5个基因为不同微阵列数据集共有。RNA-Seq数据共获得21个基因家族的751个差异表达基因,其中11个基因与微阵列数据共有,AP2-EREBP/DREB、MYB、HSF、bZIP和NAC 5个基因与3个数据集共有。根据所获得的结果,共选择了31个荟萃分析基因,并推荐用于旨在提高水稻耐盐性的遗传改良计划。通过对微阵列、RNA-Seq和已发表文献的荟萃分析,成功筛选了31个最佳耐盐相关基因,这些基因可以通过候选基因方法通过标记辅助育种进行靶向渗入。这种方法有多重优点,因为它避免了法定和生态问题。这样的努力更有理由对抗关键的非生物压力,如盐度,其影响由于气候变化而增加。
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来源期刊
Agri Gene
Agri Gene Agricultural and Biological Sciences-Agricultural and Biological Sciences (miscellaneous)
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期刊介绍: Agri Gene publishes papers that focus on the regulation, expression, function and evolution of genes in crop plants, farm animals, and agriculturally important insects and microorganisms. Agri Gene strives to be a diverse journal and topics in multiple fields will be considered for publication so long as their main focus is on agriculturally important organisms (plants, animals, insects, or microorganisms). Although not limited to the following, some examples of potential topics include: Gene discovery and characterization. Genetic markers to guide traditional breeding. Genetic effects of transposable elements. Evolutionary genetics, molecular evolution, population genetics, and phylogenetics. Profiling of gene expression and genetic variation. Biotechnology and crop or livestock improvement. Genetic improvement of biological control microorganisms. Genetic control of secondary metabolic pathways and metabolic enzymes of crop pathogens. Transcription analysis of beneficial or pest insect developmental stages Agri Gene encourages submission of novel manuscripts that present a reasonable level of analysis, functional relevance and/or mechanistic insight. Agri Gene also welcomes papers that have predominantly a descriptive component but improve the essential basis of knowledge for subsequent functional studies, or which provide important confirmation of recently published discoveries provided that the information is new.
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