Dataset Information

Identification of rice landraces with promising yield and the associated genomic regions under low nitrogen.

ABSTRACT: With the priority of the low input sustainable rice cultivation for environment friendly agriculture, NUE of rice becomes the need of the hour. A set of 472 rice genotypes comprising landraces and breeding lines were evaluated for two seasons under field conditions with low and recommended nitrogen and >100 landraces were identified with relative higher yield under low nitrogen. Donors were identified for higher N uptake, N translocation into grains and grain yield under low N. Grains on secondary branches, N content in grain and yield appears to be the selection criterion under low N. Through association mapping, using minimum marker set of 50 rice SSR markers, 12 genomic regions were identified for yield and yield associated traits under low nitrogen. Four associated genomic regions on chromosomes 5, 7 and 10 were fine mapped and QTL for yield under low N were identified from the marker delimited regions. Three candidate genes viz., 2-oxoglutarate /malate translocator (Os05g0208000), alanine aminotransferase (Os07g0617800) and pyridoxal phosphate-dependent transferase (Os10g0189600) from QTL regions showed enhanced expression in the genotypes with promising yield under low N. Marker assisted selection using SSR markers associated with three candidate genes identified two stable breeding lines confirmed through multi-location evaluation.

SUBMITTER: Rao IS

PROVIDER: S-EPMC6003918 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Identification of rice landraces with promising yield and the associated genomic regions under low nitrogen.

Rao I Subhakara IS Neeraja C N CN Srikanth B B Subrahmanyam D D Swamy K N KN Rajesh K K Vijayalakshmi P P Kiran T Vishnu TV Sailaja N N Revathi P P Rao P Raghuveer PR Rao L V Subba LVS Surekha K K Babu V Ravindra VR Voleti S R SR

Scientific reports 20180615 1

With the priority of the low input sustainable rice cultivation for environment friendly agriculture, NUE of rice becomes the need of the hour. A set of 472 rice genotypes comprising landraces and breeding lines were evaluated for two seasons under field conditions with low and recommended nitrogen and >100 landraces were identified with relative higher yield under low nitrogen. Donors were identified for higher N uptake, N translocation into grains and grain yield under low N. Grains on seconda ...[more]

PMID: 29907833

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Project description:The complex trait of yield is controlled by several quantitative trait loci (QTLs). Given the global water deficit issue, the development of rice varieties suitable for non-flooded cultivation holds significant importance in breeding programs. The powerful approach of Meta-QTL (MQTL) analysis can be used for the genetic dissection of complicated quantitative traits. In the current study, a comprehensive MQTL analysis was conducted to identify consistent QTL regions associated with drought tolerance and yield-related traits under water deficit conditions in rice. In total, 1087 QTLs from 134 rice populations, published between 2000 to 2021, were utilized in the analysis. Distinct MQTL analysis of the relevant traits resulted in the identification of 213 stable MQTLs. The confidence interval (CI) for the detected MQTLs was between 0.12 and 19.7 cM. The average CI of the identified MQTLs (4.68 cM) was 2.74 times narrower compared to the average CI of the initial QTLs. Interestingly, 63 MQTLs coincided with SNP peak positions detected by genome-wide association studies for yield and drought tolerance-associated traits under water deficit conditions in rice. Considering the genes located both in the QTL-overview peaks and the SNP peak positions, 19 novel candidate genes were introduced, which are associated with drought response index, plant height, panicle number, biomass, and grain yield. Moreover, an inclusive MQTL analysis was performed on all the traits to obtain "Breeding MQTLs". This analysis resulted in the identification of 96 MQTLs with a CI ranging from 0.01 to 9.0 cM. The mean CI of the obtained MQTLs (2.33 cM) was 4.66 times less than the mean CI of the original QTLs. Thirteen MQTLs fulfilling the criteria of having more than 10 initial QTLs, CI < 1 cM, and an average phenotypic variance explained greater than 10%, were designated as "Breeding MQTLs". These findings hold promise for assisting breeders in enhancing rice yield under drought stress conditions.

Project description:Higher grain yield in high-yielding rice varieties is mostly driven by nitrogen (N) fertilizer applied in abundant amounts leading to increased production cost and environmental pollution. This has fueled the studies on nitrogen use efficiency (NUE) to decrease the N fertilizer application in rice to the possible extent. NUE is a complex physiological trait controlled by multiple genes, but yet to be completely deciphered in rice. With an objective of identifying the promising physiological traits associated with NUE in rice, the performance of 14 rice genotypes was assessed at N0, N50, N100, and N150 for four (two wet and two dry) seasons using agro-morphological, grain yield, flag leaf traits, photosynthetic pigment content, flag leaf gas exchange traits, and chlorophyll fluorescence traits. Furthermore, the data were used to derive various NUE indices to identify the most appropriate indices useful to screen rice genotypes at N50. Results indicate that with the increase in N application, cumulative grain yield increased significantly up to N100 (5.02 t ha-1); however, the increment in grain yield was marginal at N150 (5.09 t ha-1). The mean reduction of grain yield was only 26.66% at N50 ranging from 15.0% to 34.2%. The significant finding of the study is the identification of flag leaf chlorophyll fluorescence traits (Fv/Fm, ΦPSII, ETR, and qP) and Ci associated with grain yield under N50, which can be used to screen N use efficient genotypes in rice under reduced N application. Out of nine NUE indices assessed, NUpE, NUtE, and NUEyield were able to delineate the high-yielding genotypes at N50 and were useful to screen rice under reduced N conditions. Birupa emerged as one of the high yielders under N50, even though it is a moderate yielder at N100 and infers the possibility of cultivating some of the released rice varieties under reduced N inputs. The study indicates the possibility of the existence of promising genetic variability for grain yield under reduced N, the potential of flag leaf chlorophyll fluorescence, and gas exchange traits as physiological markers and best suitable NUE indices to be deployed in rice breeding programs.

Dataset Information

Identification of rice landraces with promising yield and the associated genomic regions under low nitrogen.

Publications

Identification of rice landraces with promising yield and the associated genomic regions under low nitrogen.

Similar Datasets

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