Dataset Information

Construction of an ultrahigh-density genetic linkage map for Jatropha curcas L. and identification of QTL for fruit yield.

ABSTRACT: Background:As an important biofuel plant, the demand for higher yield Jatropha curcas L. is rapidly increasing. However, genetic analysis of Jatropha and molecular breeding for higher yield have been hampered by the limited number of molecular markers available. Results:An ultrahigh-density linkage map for a Jatropha mapping population of 153 individuals was constructed and covered 1380.58 cM of the Jatropha genome, with average marker density of 0.403 cM. The genetic linkage map consisted of 3422 SNP and indel markers, which clustered into 11 linkage groups. With this map, 13 repeatable QTLs (reQTLs) for fruit yield traits were identified. Ten reQTLs, qNF-1, qNF-2a, qNF-2b, qNF-2c, qNF-3, qNF-4, qNF-6, qNF-7a, qNF-7b and qNF-8, that control the number of fruits (NF) mapped to LGs 1, 2, 3, 4, 6, 7 and 8, whereas three reQTLs, qTWF-1, qTWF-2 and qTWF-3, that control the total weight of fruits (TWF) mapped to LGs 1, 2 and 3, respectively. It is interesting that there are two candidate critical genes, which may regulate Jatropha fruit yield. We also identified three pleiotropic reQTL pairs associated with both the NF and TWF traits. Conclusion:This study is the first to report an ultrahigh-density Jatropha genetic linkage map construction, and the markers used in this study showed great potential for QTL mapping. Thirteen fruit-yield reQTLs and two important candidate genes were identified based on this linkage map. This genetic linkage map will be a useful tool for the localization of other economically important QTLs and candidate genes for Jatropha.

SUBMITTER: Xia Z

PROVIDER: S-EPMC5759280 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

Construction of an ultrahigh-density genetic linkage map for <i>Jatropha curcas</i> L. and identification of QTL for fruit yield.

Xia Zhiqiang Z Zhang Shengkui S Wen Mingfu M Lu Cheng C Sun Yufang Y Zou Meiling M Wang Wenquan W

Biotechnology for biofuels 20180109

<h4>Background</h4>As an important biofuel plant, the demand for higher yield <i>Jatropha curcas</i> L. is rapidly increasing. However, genetic analysis of <i>Jatropha</i> and molecular breeding for higher yield have been hampered by the limited number of molecular markers available.<h4>Results</h4>An ultrahigh-density linkage map for a <i>Jatropha</i> mapping population of 153 individuals was constructed and covered 1380.58 cM of the <i>Jatropha</i> genome, with average marker density of 0.403 ...[more]

PMID: 29321812

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Project description:BACKGROUND:Improving fiber quality and yield are the primary research objectives in cotton breeding for enhancing the economic viability and sustainability of Upland cotton production. Identifying the quantitative trait loci (QTL) for fiber quality and yield traits using the high-density SNP-based genetic maps allows for bridging genomics with cotton breeding through marker assisted and genomic selection. In this study, a recombinant inbred line (RIL) population, derived from cross between two parental accessions, which represent broad allele diversity in Upland cotton, was used to construct high-density SNP-based linkage maps and to map the QTLs controlling important cotton traits. RESULTS:Molecular genetic mapping using RIL population produced a genetic map of 3129 SNPs, mapped at a density of 1.41?cM. Genetic maps of the individual chromosomes showed good collinearity with the sequence based physical map. A total of 106 QTLs were identified which included 59 QTLs for six fiber quality traits, 38 QTLs for four yield traits and 9 QTLs for two morphological traits. Sub-genome wide, 57 QTLs were mapped in A sub-genome and 49 were mapped in D sub-genome. More than 75% of the QTLs with favorable alleles were contributed by the parental accession NC05AZ06. Forty-six mapped QTLs each explained more than 10% of the phenotypic variation. Further, we identified 21 QTL clusters where 12 QTL clusters were mapped in the A sub-genome and 9 were mapped in the D sub-genome. Candidate gene analyses of the 11 stable QTL harboring genomic regions identified 19 putative genes which had functional role in cotton fiber development. CONCLUSION:We constructed a high-density genetic map of SNPs in Upland cotton. Collinearity between genetic and physical maps indicated no major structural changes in the genetic mapping populations. Most traits showed high broad-sense heritability. One hundred and six QTLs were identified for the fiber quality, yield and morphological traits. Majority of the QTLs with favorable alleles were contributed by improved parental accession. More than 70% of the mapped QTLs shared the similar map position with previously reported QTLs which suggest the genetic relatedness of Upland cotton germplasm. Identification of QTL clusters could explain the correlation among some fiber quality traits in cotton. Stable and major QTLs and QTL clusters of traits identified in the current study could be the targets for map-based cloning and marker assisted selection (MAS) in cotton breeding. The genomic region on D12 containing the major stable QTLs for micronaire, fiber strength and lint percentage could be potential targets for MAS and gene cloning of fiber quality traits in cotton.

Dataset Information

Construction of an ultrahigh-density genetic linkage map for Jatropha curcas L. and identification of QTL for fruit yield.

Publications

Construction of an ultrahigh-density genetic linkage map for <i>Jatropha curcas</i> L. and identification of QTL for fruit yield.

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