Mapping Quantitative Trait Loci (QTLs) for Reproductive Stage Salinity Tolerance in Rice

Salinity is one of the major abiotic stresses that abate the yield of several crop species including rice. Several studies were conducted to identify quantitative trait loci (QTLs) for traits associated with salinity tolerance, mostly at the seedling stage of crop growth. However, the reproductive stage of development is highly sensitive to salt stress, and hence, better QTLs must be developed. QTLs have been identified in the present study for salt tolerance of the reproductive stage in rice using recombinant inbred lines (RILs). Thirty-day-old rice seedlings of 184 RILs derived from a cross between a salt sensitive RP Bio226 (indica), and a salt-tolerant Jarava (indica), were used to identify QTLs linked to salinity tolerance in moderate (field) and severe (pot) stress conditions. One hundred polymorphic simple sequence repeat (SSR) markers were used to construct a genetic linkage map that covered a 1349.4 cm genome with an average distance of 13.5 cm between loci. Eighteen new QTLs [logarithm of odds (LOD) 2.5 and above] were identified on chromosomes 1, 2, 6, 10, 11, and 12 using composite interval mapping with the phenotypic variation explained by QTL (PVE) as high as >42% with an LOD value of 5.2. qYLSt-12 with an LOD of 2.8 and a phenotypic variance (PV) of 6.4%, flanked by RM27940-RM27971, was identified for yield in moderate stress conditions. The qSTR-2 detected for salinity tolerance on chromosome 2 with 8.9% of the PV is the most significant finding of the present research. No QTL for salinity component traits has been reported in the region of RM110-RM423. The other salinity trait QTLs identified are qSN-11, qSN-12 for Na+ concentration with a total PVE% of 13.9 and qSNK-12.1, qSNK-12.2 for the Na+/K+ ratio showing a total of 26.7% of the PV. The QTLs for yield component traits viz. plant height, panicle number, panicle length, and biomass were also identified in the present study. Previous studies reported QTLs for salinity tolerance in rice on chromosome 1 but none of the QTLs in our study were on qSaltol or nearby position; therefore, Jarava conferred salinity tolerance in RILs due to novel QTLs. Fine mapping of these novel QTLs is suggested and could be helpful to enhance the level of tolerance through marker-assisted selection for the pyramiding of different QTLs in one background.

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Crops
Published
2024-12-11
DOI
https://doi.org/10.3390/crops4040047
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3
Primary Topic
Genetic Mapping and Diversity in Plants and Animals
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article
Field-Weighted Citation Impact
1.65

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article

Mapping Quantitative Trait Loci (QTLs) for Reproductive Stage Salinity Tolerance in Rice

Brajendra Parmar, Jyothi Badri, Polavarapu B. Kavi Kishor, Manish K. Pandey et al.
3 citations
Crops
Genetic Mapping and Diversity in Plants and Animals
1.65
article

Mapping Quantitative Trait Loci (QTLs) for Reproductive Stage Salinity Tolerance in Rice

Brajendra Parmar, Jyothi Badri, Polavarapu B. Kavi Kishor, Manish K. Pandey, Arun Kumar Singh, Akanksha Srivastava, Yamini Deepthi Sugasi, Ram Tilatoo
article en
3 citations

Abstract

Salinity is one of the major abiotic stresses that abate the yield of several crop species including rice. Several studies were conducted to identify quantitative trait loci (QTLs) for traits associated with salinity tolerance, mostly at the seedling stage of crop growth. However, the reproductive stage of development is highly sensitive to salt stress, and hence, better QTLs must be developed. QTLs have been identified in the present study for salt tolerance of the reproductive stage in rice using recombinant inbred lines (RILs). Thirty-day-old rice seedlings of 184 RILs derived from a cross between a salt sensitive RP Bio226 (indica), and a salt-tolerant Jarava (indica), were used to identify QTLs linked to salinity tolerance in moderate (field) and severe (pot) stress conditions. One hundred polymorphic simple sequence repeat (SSR) markers were used to construct a genetic linkage map that covered a 1349.4 cm genome with an average distance of 13.5 cm between loci. Eighteen new QTLs [logarithm of odds (LOD) 2.5 and above] were identified on chromosomes 1, 2, 6, 10, 11, and 12 using composite interval mapping with the phenotypic variation explained by QTL (PVE) as high as >42% with an LOD value of 5.2. qYLSt-12 with an LOD of 2.8 and a phenotypic variance (PV) of 6.4%, flanked by RM27940-RM27971, was identified for yield in moderate stress conditions. The qSTR-2 detected for salinity tolerance on chromosome 2 with 8.9% of the PV is the most significant finding of the present research. No QTL for salinity component traits has been reported in the region of RM110-RM423. The other salinity trait QTLs identified are qSN-11, qSN-12 for Na+ concentration with a total PVE% of 13.9 and qSNK-12.1, qSNK-12.2 for the Na+/K+ ratio showing a total of 26.7% of the PV. The QTLs for yield component traits viz. plant height, panicle number, panicle length, and biomass were also identified in the present study. Previous studies reported QTLs for salinity tolerance in rice on chromosome 1 but none of the QTLs in our study were on qSaltol or nearby position; therefore, Jarava conferred salinity tolerance in RILs due to novel QTLs. Fine mapping of these novel QTLs is suggested and could be helpful to enhance the level of tolerance through marker-assisted selection for the pyramiding of different QTLs in one background.

CropsVol. 4(4)
Indian Institute of Rice Research (IN), International Crops Research Institute for the Semi-Arid Tropics (IN), Osmania University (IN)
Indian Council of Agricultural Research
Life in Land
Openalex Percentile: Top 14%
Genetic Mapping and Diversity in Plants and Animals
1.65
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