Genetic linkage mapping and QTL identification for salinity tolerance in Indian mustard (Brassica juncea L. Czern and Coss.) using SSR markers

Soil salinity is one of the major environmental constraints that limits crop yield and nearly 7% of the total area worldwide is affected by salinity. Salinity-induced oxidative stress causes membrane damage during germination and seedling growth. Indian mustard is a major oilseed crop in India and i...

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Veröffentlicht in:Oil Crop Science 2023-07, Vol.8 (3), p.191-205
Hauptverfasser: Patel, Rekha, Jangra, Sumit, Avtar, Ram, Yadav, Neelam R., Yadav, Ram C.
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Sprache:eng
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Zusammenfassung:Soil salinity is one of the major environmental constraints that limits crop yield and nearly 7% of the total area worldwide is affected by salinity. Salinity-induced oxidative stress causes membrane damage during germination and seedling growth. Indian mustard is a major oilseed crop in India and its production and productivity are severely affected by salt stress. Breeding Brassica cultivars for salinity tolerance by conventional means is very difficult and time-consuming. Therefore, understanding the molecular components associated with salt tolerance is needed to facilitate breeding for salt tolerance in Brassica. In this investigation, quantitative trait loci (QTLs) associated with salt tolerance were identified using F2:3 developed from a cross between CS52 (salinity tolerant) and RH30 (salinity sensitive). Parents and F2:3 were evaluated under controlled and salinity stress conditions for 14 morpho-physiological traits for two consecutive generations (F2 and F2:3), explaining proportion of the phenotypic variance under control condition. Simple sequence repeat (SSR) markers were used for mapping studies. A genetic linkage map based on 42 simple sequence repeats (SSRs) markers was constructed covering 2298.5 cM (Haldane) to identify the loci associated with salt tolerance in Brassica juncea. Forty-one SSRs that showed polymorphism in the parents (CS52 and RH30) mapped on 8 linkage groups (C1–C8). One marker (nga 129) did not map to any of the linkage groups and was excluded from mapping. Linkage group 5 (C5; 317.9 cM) was longest and linkage group 1 (C1, 255.0 cM) was shortest. Further, we identified 15 QTLs controlling 8 traits using F2:3 population. These QTLs explained 12.44–60.63% of the phenotypic variation with a LOD score range of 3.62–5.97. Out of these QTLs, QMI4.1 related to membrane injury showed 51.28% phenotypic variance with a LOD score of 3.34. QTL QBYP8.1 related to biological yield per plant showed 60.63% phenotypic variance at a LOD score of 3.62. The highest LOD score of 5.97 was recorded for QTL related to seed yield per plant (QSYP4.1). Major QTL were biological yield per plant (QBYP8.1), QTL for siliquae per plant (QSP4.1), QTL for primary branches (QPB4.1), QTLs for seed per siliqua (QSS4.1, QSS4.2), QTL for seed yield per plant (QSYP4.1), and QTL for membrane injury (QMI8.1) which showed more than 50% phenotypic variance. These QTLs identified in our study need to be confirmed in other populations as well so that these can be
ISSN:2096-2428
DOI:10.1016/j.ocsci.2023.09.003