Mapping of yield influencing QTL in Brassica juncea: implications for breeding of a major oilseed crop of dryland areas View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2007-10

AUTHORS

N. Ramchiary, K. L. Padmaja, S. Sharma, V. Gupta, Y. S. Sodhi, A. Mukhopadhyay, N. Arumugam, D. Pental, A. K. Pradhan

ABSTRACT

Quantitative trait loci (QTL) analysis of yield influencing traits was carried out in Brassica juncea (AABB) using a doubled haploid (DH) mapping population of 123 lines derived from a cross between Varuna (a line representing the Indian gene pool) and Heera (representing the east European gene pool) to identify potentially useful alleles from both the parents. The existing AFLP based map of B. juncea was further saturated with RFLP and SSR markers which led to the identification of the linkage groups belonging to the A (B. rapa) and B (B. nigra) genome components of B. juncea. For QTL dissection, the DH lines were evaluated at three different environments and phenotyped for 12 quantitative traits. A total of 65 QTL spread over 13 linkage groups (LG) were identified from the three environments. QTL analysis showed that the A genome has contributed more than the B genome to productivity (68% of the total QTL detected) suggesting a more prominent role of the A genome towards domestication of this crop. The east European line, Heera, carried favorable alleles for 42% of the detected QTL and the remaining 58% were in the Indian gene pool line, Varuna. We observed clustering of major QTL in a few linkage groups, particularly in J7 and J10 of the A genome, with QTL of different traits having agronomically antagonistic allelic effects co-mapping to the same genetic interval. QTL analysis also identified some well-separated QTL which could be readily transferred between the two pools. Based on the QTL analysis, we propose that improvement in yield could be achieved more readily by heterosis breeding rather than by pure line breeding. More... »

PAGES

807-817

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00122-007-0610-5

DOI

http://dx.doi.org/10.1007/s00122-007-0610-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1000587413

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/17646960


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