Quantitative Trait Locus Analysis for Rice Yield Traits under Two Nitrogen Levels

Yue, Feng; Zhai, Rongrong; Lin, Zhou; Zhang, Yingxin; Wei, Xinghua; Cheng, Shifeng

doi:10.1016/j.rsci.2015.05.014

Cited by 25 publications

(22 citation statements)

References 19 publications

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“…Rice (Oryza Sativa) is staple food for more than half of the world's population. [1]. About 90% of the global rice is produced as well as consumed in Asia [2].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Drought Tolerant Rice Cultivars Using Drought Tolerant Indices under Water Stress and Irrigated Condition

Adhikari¹,

Adhikari²,

Sharma³

et al. 2019

AJCC

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Drought is the most critical abiotic factor reducing rice yield in rainfed and drought prone areas. Majority of rice cultivated area in south Asia are under rainfed, where water stress at any of the critical growth stage causes sharp decline in yield. Research was conducted in western Nepal at farmers field around the close vicinity of Regional Agriculture Research Center (RARS) Nepalgunj. Ten different rice cultivars were evaluated under drought stress and non-stress condition during the year 2017 to identify superior stress tolerant cultivars. Different drought tolerance indices like stress tolerance (TOL), Stress tolerance index (STI), Stress susceptibility index (SSI), were tested in screening superior rice cultivars. Significant reduction in mean grain yield was observed under drought stress in all rice cultivars under the study. The rice cultivars with high STI values and low TOL and SSI were identified as superior drought tolerant cultivars. Based on results of different tolerance indices, Sukha series of rice, Sukha Dhan 1-6 and Radha-4 showed low TOL and SSI and high STI values and were identified as drought tolerant cultivars. The present study reveals that selection based on drought tolerance indices can be an efficient tool in identification of superior drought tolerant cultivars with higher yield and stability.

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“…Rice (Oryza Sativa) is staple food for more than half of the world's population. [1]. About 90% of the global rice is produced as well as consumed in Asia [2].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Drought Tolerant Rice Cultivars Using Drought Tolerant Indices under Water Stress and Irrigated Condition

Adhikari¹,

Adhikari²,

Sharma³

et al. 2019

AJCC

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“…for linkage mapping are well established (Yue et al, 2015). The common population types are F 2 , backcross populations, RILs, backcross inbred lines, and double haploids.…”

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confidence: 99%

Characterization of ThreeIndicaRice Multiparent Advanced Generation Intercross (MAGIC) Populations for Quantitative Trait Loci Identification

et al. 2016

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Three new rice (Oryza sativa L.) multiparent advanced generation intercross (MAGIC) populations were developed using eight elite indica rice varieties from different breeding programs. These three populations were two recombinant inbred line (RIL) populations derived from two 4-way crosses, DC1 and DC2, and one RIL population derived from an 8-way cross. These populations were genotyped using an Illumina Infinium rice 6K SNP chip. The potential of the three MAGIC populations in identifying marker-trait associations was demonstrated using the plant height (PH) and heading date (HD) measured in 2014. A population of 248 IRRI breeding lines and a population of 323 Chinese breeding lines were also included to compare genetic diversity and linkage disequilibrium (LD) pattern. Our study discovered that (i) the 8-way population had a higher gene diversity than the DC1, DC2, and IRRI populations; (ii) all three MAGIC populations showed no clear population structure; (iii) LD decayed to r 2 < 0.2 at about 2.5, 2.5, 1.25, 1.75, and 4.0 Mb for the DC1, DC2, 8-way, IRRI, and Chinese populations, respectively; and (iv) the 8-way population was more powerful than the DC1, DC2, and IRRI populations on QTL identification. The association analysis identified two and three QTL for PH and HD, respectively. Four of the five QTL had peak markers close to known genes. A novel QTL for PH was identified on chromosome 12 using the 8-way population. Therefore, our study suggests that the three new MAGIC populations are valuable resources for QTL identification. The identification of QTL is a critical step for dissecting the molecular basis of agronomy traits in crops, including rice. The detection of the associations between traits of interest and molecular markers is also the prerequisite for most of the marker-assisted selection methods. Linkage mapping and association mapping (AM) are the two most commonly used approaches for QTL mapping in crops. The methods using biparental populations Core Ideas• Three rice MAGIC populations were developed to better integrate QTL identification and breeding.• MAGIC populations are valuable for QTL identification, 8-way populations being more powerful.• QTL (2 and 3) were identified for heading date and plant height, respectively.• One novel QTL for PH was identified on chromosome 12 using the 8-way population.

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“…Twenty SSRs were having association with more than one traits and have been reported in the gramene-database (http://www.gramene.org/) by earlier studies (Table 6) [28,29,49,89]. These were significantly associated with yield controlling complex traits viz., PH, DFF, SLBR, TL, PL, FLL, FLW, FG, TG, TGW and YLD and supposed to have played a significant role in yield enhancement (Table 5, Table 6, Fig 8).…”

Section: Discussionmentioning

confidence: 72%

Identification of QTLs for high grain yield and component traits in New Plant Types of rice

Donde

Mohapatra

Baksh

et al. 2020

Preprint

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16A panel of 60 genotypes consisting of New Plant Types (NPTs) along with indica, tropical and 17 temperate japonica genotypes were phenotypically evaluated for four seasons in irrigated situation 18 for grain yield per se and component traits. Twenty NPT genotypes were found to be promising with 19 an average grain yield of 5.45 to 8.8 t/ha. A total of 85 SSR markers were used in the study to 20 identify QTLs associated with grain yield per se and related traits. Sixty-six (77.65%) markers were 21 found to be polymorphic. The PIC values varied from 0.516 to 0.92 with an average of 0.704. A 22 moderate level of genetic diversity (0.39) was detected among genotypes. Variation to the tune of 23 8% within genotypes, 68% among the genotypes within the population and 24% among the 24 populations were observed (AMOVA). The association analysis using GLM and MLM models led to 25 the identification of 30 and 10 SSR markers were associated with 70 and 16 QTLs, respectively. 26 Thirty novel QTLs linked with 16 SSRs were identified to be associated with eleven traits, namely, 27 tiller number (qTL-6. 29 total no. of grains (qTG-2.2, qTG-a7.1), thousand-grain weight 30 qTGW-8.1 ), fertile grains (qFG-7.1), seed length-breadth ratio (qSlb-3.1), plant height (qPHT-6.1, 31 qPHT-9.1), days to 50% flowering (qFD-1.1) and grain yield per se 11.1). This information could be useful for identification of highly potential parents for development 33 of transgressive segregants. Moreover, super rice genotypes could be developed through pyramiding 34 of these QTLS for important yield traits for prospective increment in yield potentiality and breaking 35 yield ceiling. 36 Introduction 39Rice (Oryza sativa L.) is a staple crop for more than 3.5 billion people in the globe. In current 40 scenario, rice productivity is increasing rate at 1% per year which is less than the 2.4% per year rate 41 required to double the global production by 2050 [1]. Considering a glimpse of the history, a 42 quantum jump in productivity was achieved due to the green revolution in mid-sixties, which 43 drastically enhanced the rice production of the world. However, a ceiling of productivity potentiality 44 is reported by and large in semi-dwarf inbred indica genotypes since release of , in spite of 45 substantial improvement in yield stability, per day productivity and grain quality [3]. A 46 breakthrough in productivity barrier is necessitated because of increasing competition for natural 47 resources viz., land, water and others given population explosion coupled with expanding 48 industrialization, urbanization and diversion of agricultural land [1,4,5]. This is still aggravated with 49 the abnormal change in weather and climate with significant influence on crop productivity and 50 quality [6,7]. 51Rice scientists are facing many challenges for doubling rice production by 2050. Irrigated 52 rice has a share of 75% of total rice production in the world, although it has a share of about 55% of 53 the total rice area [2]. Therefore, improveme...

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Quantitative Trait Locus Analysis for Rice Yield Traits under Two Nitrogen Levels

Cited by 25 publications

References 19 publications

Evaluation of Drought Tolerant Rice Cultivars Using Drought Tolerant Indices under Water Stress and Irrigated Condition

Evaluation of Drought Tolerant Rice Cultivars Using Drought Tolerant Indices under Water Stress and Irrigated Condition

Characterization of ThreeIndicaRice Multiparent Advanced Generation Intercross (MAGIC) Populations for Quantitative Trait Loci Identification

Identification of QTLs for high grain yield and component traits in New Plant Types of rice

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