Dataset Information

High-Density Mapping and Candidate Gene Analysis of Pl₁₈ and Pl₂₀ in Sunflower by Whole-Genome Resequencing.

ABSTRACT: Downy mildew (DM) is one of the severe biotic threats to sunflower production worldwide. The inciting pathogen, Plasmopara halstedii, could overwinter in the field for years, creating a persistent threat to sunflower. The dominant genes Pl₁₈ and Pl₂₀ conferring resistance to known DM races have been previously mapped to 1.5 and 1.8 cM intervals on sunflower chromosomes 2 and 8, respectively. Utilizing a whole-genome resequencing strategy combined with reference sequence-based chromosome walking and high-density mapping in the present study, Pl₁₈ was placed in a 0.7 cM interval on chromosome 2. A candidate gene HanXRQChr02g0048181 for Pl₁₈ was identified from the XRQ reference genome and predicted to encode a protein with typical NLR domains for disease resistance. The Pl₂₀ gene was placed in a 0.2 cM interval on chromosome 8. The putative gene with the NLR domain for Pl₂₀, HanXRQChr08g0210051, was identified within the Pl₂₀ interval. SNP markers closely linked to Pl₁₈ and Pl₂₀ were evaluated with 96 diverse sunflower lines, and a total of 13 diagnostic markers for Pl₁₈ and four for Pl₂₀ were identified. These markers will facilitate to transfer these new genes to elite sunflower lines and to pyramid these genes with broad-spectrum DM resistance in sunflower breeding.

SUBMITTER: Ma G

PROVIDER: S-EPMC7765508 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Publications

High-Density Mapping and Candidate Gene Analysis of Pl18 and Pl20 in Sunflower by Whole-Genome Resequencing.

Ma Guojia G Song Qijian Q Li Xuehui X Qi Lili L

International journal of molecular sciences 20201216 24

Downy mildew (DM) is one of the severe biotic threats to sunflower production worldwide. The inciting pathogen, Plasmopara halstedii, could overwinter in the field for years, creating a persistent threat to sunflower. The dominant genes Pl18 and Pl20 conferring resistance to known DM races have been previously mapped to 1.5 and 1.8 cM intervals on sunflower chromosomes 2 and 8, respectively. Utilizing a whole-genome resequencing strategy combined with r ...[more]

PMID: 33339111

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Project description: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.

Dataset Information

High-Density Mapping and Candidate Gene Analysis of Pl₁₈ and Pl₂₀ in Sunflower by Whole-Genome Resequencing.

Publications

High-Density Mapping and Candidate Gene Analysis of <i>Pl</i><sub>18</sub> and <i>Pl</i><sub>20</sub> in Sunflower by Whole-Genome Resequencing.

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