» Articles » PMID: 24684805

Identification of Candidate Genes for Drought Tolerance by Whole-genome Resequencing in Maize

Overview
Journal BMC Plant Biol
Publisher Biomed Central
Specialty Biology
Date 2014 Apr 2
PMID 24684805
Citations 49
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Drought stress is one of the major limiting factors for maize production. With the availability of maize B73 reference genome and whole-genome resequencing of 15 maize inbreds, common variants (CV) and clustering analyses were applied to identify non-synonymous SNPs (nsSNPs) and corresponding candidate genes for drought tolerance.

Results: A total of 524 nsSNPs that were associated with 271 candidate genes involved in plant hormone regulation, carbohydrate and sugar metabolism, signaling molecules regulation, redox reaction and acclimation of photosynthesis to environment were detected by CV and cluster analyses. Most of the nsSNPs identified were clustered in bin 1.07 region that harbored six previously reported QTL with relatively high phenotypic variation explained for drought tolerance. Genes Ontology (GO) analysis of candidate genes revealed that there were 35 GO terms related to biotic stimulus and membrane-bounded organelle, showing significant differences between the candidate genes and the reference B73 background. Changes of expression level in these candidate genes for drought tolerance were detected using RNA sequencing for fertilized ovary, basal leaf meristem tissue and roots collected under drought stressed and well-watered conditions. The results indicated that 70% of candidate genes showed significantly expression changes under two water treatments and our strategies for mining candidate genes are feasible and relatively efficient.

Conclusions: Our results successfully revealed candidate nsSNPs and associated genes for drought tolerance by comparative sequence analysis of 16 maize inbred lines. Both methods we applied were proved to be efficient for identifying candidate genes for complex traits through the next-generation sequencing technologies (NGS). These selected genes will not only facilitate understanding of genetic basis of drought stress response, but also accelerate genetic improvement through marker-assisted selection in maize.

Citing Articles

Identification of alkali-tolerant candidate genes using the NGS-assisted BSA strategy in rice.

Sun J, Wang J, Guo W, Yin T, Zhang S, Wang L Mol Breed. 2023; 41(7):44.

PMID: 37309384 PMC: 10236117. DOI: 10.1007/s11032-021-01228-x.


Effects of drought stress on photosynthetic physiological characteristics, leaf microstructure, and related gene expression of yellow horn.

Hu F, Zhang Y, Guo J Plant Signal Behav. 2023; 18(1):2215025.

PMID: 37243677 PMC: 10228403. DOI: 10.1080/15592324.2023.2215025.


MicroRNA162 regulates stomatal conductance in response to low night temperature stress abscisic acid signaling pathway in tomato.

Li Y, Liu Y, Gao Z, Wang F, Xu T, Qi M Front Plant Sci. 2023; 14:1045112.

PMID: 36938045 PMC: 10019595. DOI: 10.3389/fpls.2023.1045112.


Identification of QTN-by-environment interactions for yield related traits in maize under multiple abiotic stresses.

Wen Y, Wu X, Wang S, Han L, Shen B, Wang Y Front Plant Sci. 2023; 14:1050313.

PMID: 36875585 PMC: 9975332. DOI: 10.3389/fpls.2023.1050313.


Identification of Heat-Tolerant Genes in Non-Reference Sequences in Rice by Integrating Pan-Genome, Transcriptomics, and QTLs.

Tareke Woldegiorgis S, Wu T, Gao L, Huang Y, Zheng Y, Qiu F Genes (Basel). 2022; 13(8).

PMID: 36011264 PMC: 9407402. DOI: 10.3390/genes13081353.


References
1.
Kakumanu A, Ambavaram M, Klumas C, Krishnan A, Batlang U, Myers E . Effects of drought on gene expression in maize reproductive and leaf meristem tissue revealed by RNA-Seq. Plant Physiol. 2012; 160(2):846-67. PMC: 3461560. DOI: 10.1104/pp.112.200444. View

2.
Reumers J, Conde L, Medina I, Maurer-Stroh S, Van Durme J, Dopazo J . Joint annotation of coding and non-coding single nucleotide polymorphisms and mutations in the SNPeffect and PupaSuite databases. Nucleic Acids Res. 2007; 36(Database issue):D825-9. PMC: 2238831. DOI: 10.1093/nar/gkm979. View

3.
Hesse M, Zimek A, Weber K, Magin T . Comprehensive analysis of keratin gene clusters in humans and rodents. Eur J Cell Biol. 2004; 83(1):19-26. DOI: 10.1078/0171-9335-00354. View

4.
Chia J, Song C, Bradbury P, Costich D, de Leon N, Doebley J . Maize HapMap2 identifies extant variation from a genome in flux. Nat Genet. 2012; 44(7):803-7. DOI: 10.1038/ng.2313. View

5.
Zhuang Y, Ren G, Yue G, Li Z, Qu X, Hou G . Effects of water-deficit stress on the transcriptomes of developing immature ear and tassel in maize. Plant Cell Rep. 2007; 26(12):2137-47. DOI: 10.1007/s00299-007-0419-3. View