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. 2022 Jun;49(6):4293-4306.
doi: 10.1007/s11033-022-07264-w. Epub 2022 Mar 3.

Genotyping by sequencing-based linkage map construction and identification of quantitative trait loci for yield-related traits and oil content in Jatropha (Jatropha curcas L.)

Vijay Yepuri  1 , Saakshi Jalali  1 , Vishwnadharaju Mudunuri  2 , Sai Pothakani  2 , Nagesh Kancharla  1 , S Arockiasamy  3
Affiliations

Genotyping by sequencing-based linkage map construction and identification of quantitative trait loci for yield-related traits and oil content in Jatropha (Jatropha curcas L.)

Vijay Yepuri et al. Mol Biol Rep. 2022 Jun.

Abstract

Background: Jatropha (Jatropha curcas L.) has been considered as a potential bioenergy crop and its genetic improvement is essential for higher seed yield and oil content which has been hampered due to lack of desirable molecular markers.

Methods and results: An F2 population was created using an intraspecific cross involving a Central American line RJCA9 and an Asiatic species RJCS-9 to develop a dense genetic map and for Quantitative trait loci (QTL) identification. The genotyping-by-sequencing (GBS) approach was used to genotype the mapping population of 136 F2 individuals along with the two parental lines for classification of the genotypes based on single nucleotide polymorphism (SNPs). NextSeq 2500 sequencing technology provided a total of 517.23 million clean reads, with an average of ~ 3.8 million reads per sample. We analysed 411 SNP markers and developed 11 linkage groups. The total length of the genetic map was 4092.3 cM with an average marker interval of 10.04 cM. We have identified a total of 83 QTLs for various yield and oil content governing traits. The percentage of phenotypic variation (PV) was found to be in the range of 8.81 to 65.31%, and a QTL showed the maximum PV of 65.3% for a total seed number on the 6th linkage group (LG).

Conclusions: The QTLs detected in this study for various phenotypic traits will lay down the path for marker-assisted breeding in the future and cloning of genes that are responsible for phenotypic variation.

Keywords: GBS; Jatropha; Linkage map; Markers; QTL; SNP.

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