Mapping QTL controlling maize deep-seeding tolerance-related traits and confirmation of a major QTL for mesocotyl length

Deep-seeding tolerant seeds can emerge from deep soil where the moisture is suitable for seed germination. Breeding deep-seeding tolerant cultivars is becoming increasingly important in arid and semi-arid regions. To dissect the quantitative trait loci (QTL) controlling deep-seeding tolerance traits, we selected a tolerant maize inbred line 3681-4 and crossed it with the elite inbred line-X178 to generate an F₂ population and the derivative F_2:3 families. A molecular linkage map composed of 179 molecular markers was constructed, and 25 QTL were detected including 10 QTL for sowing at 10 cm depth and 15 QTL for sowing at 20 cm depth. The QTL analysis results confirmed that deep-seeding tolerance was mainly caused by mesocotyl elongation and also revealed considerable overlap among QTL for different traits. To confirm a major QTL on chromosome 10 for mesocotyl length measured at 20 cm depth, we selected and self-pollinated a BC₃F₂ plant that was heterozygous at the markers around the target QTL and homozygous at other QTL to generate a BC₃F₃ population. We found that this QTL explained more phenotypic variance in the BC₃F₃ population than that in the F₂ population, which laid the foundation for fine mapping and NIL (near-isogenic line) construction.     

Mapping QTLs for submergence tolerance in rice using a population fixed for <Emphasis Type="Italic">SUB1A</Emphasis> tolerant allele

Submergence is a widespread problem of rice production, especially in low-lying areas in South and Southeast Asia. Despite the success of Sub1 mega varieties, repeated instances of prolonged and severe flooding in stress-prone areas suggests that the SUB1 gene is no longer sufficient in those regions and requires improved varieties with increased tolerance. A study was conducted to identify quantitative trait loci (QTLs) associated with submergence tolerance using 115 F₇ recombinant inbred lines (RILs) derived from the cross of Ciherang-Sub1, a popular Indonesian cultivar carrying the SUB1 gene that has relatively higher tolerance to submergence compared to the performance of most other Sub1 lines and the submergence and stagnant flooding tolerant IR10F365. As the tolerant allele at SUB1A on chromosome 9 was fixed in this mapping population, additional QTLs responsible for submergence tolerance were expected to be revealed. Genotyping with an Infinium 6K SNP chip resulted in 469 polymorphic markers that were then used for QTL mapping. Phenotyping was performed under complete submergence with two replicates. A major QTL for submergence derived from Ciherang-Sub1, named qSUB8.1, was detected on chromosome 8 with a LOD score of 10.3 and phenotypic variance of 27.5%. Additionally, a smaller QTL, also derived from Ciherang-Sub1, was detected on chromosome 2 with a LOD score of 3.5 and phenotypic variance of 12.7%. There was no digenic interaction detected between these QTLs suggesting their independent action. The QTLs detected in this study can be used in marker-assisted selection to further improve the tolerance of other Sub1 varieties.     

Identifying novel QTLs for submergence tolerance in rice cultivars IR72 and Madabaru

Short-term submergence is a recurring problem in many rice production areas. The SUB1 gene, derived from the tolerant variety FR13A, has been transferred to a number of widely grown varieties, allowing them to withstand complete submergence for up to 2 weeks. However, in areas where longer-term submergence occurs, improved varieties having higher tolerance levels are needed. To search for novel quantitative trait loci (QTLs) from other donors, an F_2:3 population between IR72 and Madabaru, both moderately tolerant varieties, was investigated. After a repeated phenotyping of 466 families under submergence stress, a subset of 80 families selected from the two extreme phenotypic tails was used for the QTL analysis. Phenotypic data showed transgressive segregation, with several families having an even higher survival rate than the FR13A-derived tolerant check (IR40931). Four QTLs were identified on chromosomes 1, 2, 9, and 12; the largest QTL on chromosome 1 had a LOD score of 11.2 and R ² of 52.3%. A QTL mapping to the SUB1 region on chromosome 9, with a LOD score of 3.6 and R ² of 18.6%, had the tolerant allele from Madabaru, while the other three QTLs had tolerant alleles from IR72. The identification of three non-SUB1 QTLs from IR72 suggests that an alternative pathway may be present in this variety that is independent of the ethylene-dependent pathway mediated by the SUB1A gene. These novel QTLs can be combined with SUB1 using marker assisted backcrossing in an effort to enhance the level of submergence tolerance for flood-prone areas.     

Development and validation of a novel core set of KASP markers for the traits improving grain yield and adaptability of rice under direct-seeded cultivation conditions

The development and utilization of molecular-markers play an important role in genomics-assisted breeding during pyramiding of valuable genes. The aim of present study was to develop and validate a novel core-set of KASP (Kompetitive Allele-Specific PCR) markers associated with traits improving rice grain yield and adaptability under direct-seeded cultivation conditions. The 110 phenotypically validated KASP assays out of 171 designed KASP, include assays for biotic-resistance genes, anaerobic germination, root-traits, grain yield, lodging resistance and early-uniform emergence. The KASP assays were validated for their robustness and reliability at five different levels using diverse germplasm, segregating and advanced population, comparison with SSR markers and on F_1s. The present research work will provide (i) breeding material in form of anticipated pre-direct-seeded adapted rice varieties (ii) single improved breeding line with many useful genes and (iii) KASP assay information for the useful QTL/genes providing grain yield and adaptability to rice under direct-seeded cultivation conditions.     

Identification of a major QTL allele from wild soybean (Glycine soja Sieb. & Zucc.) for increasing alkaline salt tolerance in soybean

Salt-affected soils are generally classified into two main categories, sodic (alkaline) and saline. Our previous studies showed that the wild soybean accession JWS156-1 (Glycine soja) from the Kinki area of Japan was tolerant to NaCl salt, and the quantitative trait locus (QTL) for NaCl salt tolerance was located on soybean linkage group N (chromosome 3). Further investigation revealed that the wild soybean accession JWS156-1 also had a higher tolerance to alkaline salt stress. In the present study, an F₆ recombinant inbred line mapping population (n = 112) and an F₂ population (n = 149) derived from crosses between a cultivated soybean cultivar Jackson and JWS156-1 were used to identify QTL for alkaline salt tolerance in soybean. Evaluation of soybean alkaline salt tolerance was carried out based on salt tolerance rating (STR) and leaf chlorophyll content (SPAD value) after treatment with 180 mM NaHCO₃ for about 3 weeks under greenhouse conditions. In both populations, a significant QTL for alkaline salt tolerance was detected on the molecular linkage group D2 (chromosome 17), which accounted for 50.2 and 13.0% of the total variation for STR in the F₆ and the F₂ populations, respectively. The wild soybean contributed to the tolerance allele in the progenies. Our results suggest that QTL for alkaline salt tolerance is different from the QTL for NaCl salt tolerance found previously in this wild soybean genotype. The DNA markers closely associated with the QTLs might be useful for marker-assisted selection to pyramid tolerance genes in soybean for both alkaline and saline stresses.     

Dynamic QTL analysis of the Na+ content,K+ content,and Na+/K+ ratio in rice roots during the field growth under salt stress

Rice (Oryza sativa L.) is seriously impacted by global soil salinization. To determine the quantitative trait loci (QTLs) related to salt tolerance in rice roots, F_2:3 and BC₁F_2:3 populations derived from a cross between the cv. Dongnong 425 of high quality and yield and the salt-tolerant cv. Changbai 10, were studied at different development stages. Two genetic linkage maps of F_2:3 and BC1F_2:3 populations were constructed. A 66 mM NaCl solution was used to irrigate the field and to analyze the dynamic QTL of some rice root traits. Using unconditional and conditional QTL mapping methods, 30 unconditional QTLs and 16 conditional QTLs related to the 6 root traits were detected on the 9 rice chromosomes during different developmental stages. Fourteen pairs of unconditional and conditional QTLs were detected at the identical developmental stage in the identical population. A number of QTLs were detected at different developmental stages, however, many did not appear at the last stage. Remarkably, qRKC1 appeared continuously at multiple stages in both the populations suggesting its key role in regulating the salt tolerance of rice roots.     

Molecular Dissection of a Genomic Region Governing Root Traits Associated with Drought Tolerance Employing a Combinatorial Approach of QTL Mapping and RNA-seq in Rice

Drought is considered as one of the major obstacles for progressive yield enhancement and stability in rice, especially in rain-fed conditions. Being a complex trait, drought is regulated by numerous quantitative trait loci (QTL), of which, however, very few underlying genes have been cloned. In the present investigation, we made an attempt to uncover the candidate gene(s) behind a major QTL, rdw8.1 governing drought tolerance traits viz., root dry weight and root length. The targeted QTL has been delimited to 366.75 kb from 10.17 Mb by QTL mapping in BC₁F₂ population. Further, the targeted region was delineated employing next-generation sequencing based RNA-seq. Based on the QTL mapping and RNA-seq approaches, the plausible candidate gene underlying the QTL region was identified as a wound inducible protein (LOC_Os08g08090). This gene can be of potential value to enhance the drought tolerance of the elite rice varieties through molecular breeding.     

水稻粒长QTL定位与主效基因的遗传分析

该研究利用短粒普通野生稻矮杆突变体和长粒栽培稻品种KJ01组配杂交组合F_1,构建分离群体F_2;并对该群体粒长进行性状遗传分析,利用平均分布于水稻的12条染色体上的132对多态分子标记对该群体进行QTL定位及主效QTLs遗传分析,为进一步克隆新的主效粒长基因奠定基础,并为水稻粒形育种提供理论依据。结果表明:(1)所构建的水稻杂交组合分离群体F_2的粒长性状为多基因控制的数量性状。(2)对543株F_2分离群体进行QTL连锁分析,构建了控制水稻粒长的连锁遗传图谱,总长为1 713.94 cM,共检测出24个QTLs,只有3个表现为加性遗传效应,其余位点均表现为遗传负效应。(3)检测到的3个主效QTLs分别位于3号染色体的分子标记PSM379～RID24455、RID24455～RM15689和RM571～RM16238之间,且三者对表型的贡献率分别为54.85%、31.02%和7.62%。(4)在标记PSM379～RID24455之间已克隆到的粒长基因为该研究新发现的主效QTL位点。     

QTLs for Tolerance of Drought and Breeding for Tolerance of Abiotic and Biotic Stress: An Integrated Approach

Background

The coupling of biotic and abiotic stresses leads to high yield losses in rainfed rice (Oryza sativa L.) growing areas. While several studies target these stresses independently, breeding strategies to combat multiple stresses seldom exist. This study reports an integrated strategy that combines QTL mapping and phenotypic selection to develop rice lines with high grain yield (GY) under drought stress and non-stress conditions, and tolerance of rice blast.

Methodology

A blast-tolerant BC₂F₃-derived population was developed from the cross of tropical japonica cultivar Moroberekan (blast- and drought-tolerant) and high-yielding indica variety Swarna (blast- and drought-susceptible) through phenotypic selection for blast tolerance at the BC₂F₂ generation. The population was studied for segregation distortion patterns and QTLs for GY under drought were identified along with study of epistatic interactions for the trait.

Results

Segregation distortion, in favour of Moroberekan, was observed at 50 of the 59 loci. Majority of these marker loci co-localized with known QTLs for blast tolerance or NBS-LRR disease resistance genes. Despite the presence of segregation distortion, high variation for DTF, PH and GY was observed and several QTLs were identified under drought stress and non-stress conditions for the three traits. Epistatic interactions were also detected for GY which explained a large proportion of phenotypic variance observed in the population.

Conclusions

This strategy allowed us to identify QTLs for GY along with rapid development of high-yielding purelines tolerant to blast and drought with considerably reduced efforts. Apart from this, it also allowed us to study the effects of the selection cycle for blast tolerance. The developed lines were screened at IRRI and in the target environment, and drought and blast tolerant lines with high yield were identified. With tolerance to two major stresses and high yield potential, these lines may provide yield stability in rainfed rice areas.     

水稻萌发耐淹性的遗传分析

水稻(Oryza sativa)萌发耐淹性受到复杂的网络调控, 其分子机制不同于苗期耐淹性的相关机制, 萌发耐淹性的强弱影响着直播稻的成苗率。通过对256份水稻核心种质的萌发耐淹性评估, 发现粳稻和籼稻之间的萌发耐淹性差异并不显著, 都存在广泛的遗传变异。利用以粳稻R0380为供体亲本, 籼稻RP2334为轮回亲本的170个高代回交自交系构建含146个分子标记的连锁图谱, 以低氧胚芽鞘长度为性状指标, 通过复合区间作图法检测到影响萌发耐淹性的4个QTLs(quantitative trait loci), 分别定位于第2(2个)、3(1个)和8号(1个)染色体。贡献率最大的QTL为qGS2.2, 其值为17.34%, 增效等位基因来自轮回亲本籼稻RP2334; 其余3个QTLs的增效等位基因均来自供体亲本粳稻R0380, 贡献率分别为12.86%、9.37%和14.60%。     

Mapping of the quantitative trait locus (QTL) conferring partial resistance to rice leaf blast disease

Malaysian rice, Pongsu Seribu 2, has wide-spectrum resistance against blast disease. Chromosomal locations conferring quantitative resistance were detected by linkage mapping with SSRs and quantitative trait locus (QTL) analysis. For the mapping population, 188 F₃ families were derived from a cross between the susceptible cultivar, Mahsuri, and a resistant variety, Pongsu Seribu 2. Partial resistance to leaf blast in the mapping population was assessed. A linkage map covering ten chromosomes and consisting of 63 SSR markers was constructed. 13 QTLs, including 6 putative and 7 putative QTLs, were detected on chromosomes 1, 2, 3, 5, 6, 10, 11 and 12. The resulting phenotypic variation due to a single QTL ranged from 2 to 13 %. These QTLs accounted for approx. 80 % of the total phenotypic variation within the F₃ population. Therefore, partial resistance to blast in Pongsu Seribu 2 is due to combined effects of multiple loci with major and minor effects.     

水稻资源芽期和苗期耐盐碱性综合评价及耐盐基因分析

培育耐盐碱水稻品种是应对全球人口日益增长的重要途径之一。文中以21份耐盐碱性不同的水稻品种(系)为材料,在芽期和苗期设置6个不同盐碱浓度处理,测定了发芽势、发芽率、芽长、根长、根数、芽鲜重和苗鲜总重等指标,以各指标盐害率的平均值作为耐盐碱性的综合评价标准。结果表明随着盐碱浓度的提升,对种子萌发和生长的抑制越明显。在1%NaCl加0.25%NaHCO3溶液处理下,发芽率盐害率变异最大,为0%–89.80%。在所有浓度处理下,各性状指标的盐害率都具有相似的变化趋势。筛选到4份综合耐盐碱能力强(大酒谷、日本晴、魔王谷和02428)和7份弱的种质资源。比较了4份耐盐碱强和3份耐盐碱弱的资源耐盐基因序列:OsHAL3和OsRR22基因在7份材料中没有差异,SKC1和DST基因在耐盐碱强和耐盐碱弱的品种之间有明显的变异。研究结果为进一步挖掘水稻耐盐碱基因和培育耐盐碱水稻新品种提供了种质资源和理论基础。     

Identification and Validation of Quantitative Trait Loci for Agronomic Traits in Advanced Backcross Breeding Lines Derived from Oryza rufipogon × Oryza sativa Cultivar MR219

A backcross breeding strategy was used to identify quantitative trait loci (QTLs) associated with 14 traits in a BC₂F₂ population derived from a cross between MR219, an indica rice cultivar and an accession of Oryza rufipogon (IRGC 105491). A total of 261 lines were genotyped with 96 microsatellite markers and evaluated for plant morphology, yield components and growth period. The genetic linkage map generated for this population with an average interval size of 16.2?cM, spanning 1,553.4?cM (Kosambi) of the rice genome. Thirty-eight QTLs were identified with composite interval mapping (CIM), whereas simple interval mapping (SIM) resulted in 47 QTLs (LOD >3.0). The O. rufipogon allele was favourable for 59% of QTLs detected through CIM. Of 261 BC₂F₂ families, 26 advanced backcross breeding lines (BC₂F₅) were used for QTL validation. These lines were selected on the basis of the yield traits potentiality in BC₂F₃ and BC₂F₄ generations. The field trial was conducted at three different locations in Malaysia using randomized complete block design with three replications. Trait based marker analysis was done for QTL determination. Twenty-five QTLs were detected in BC₂F₅ generation whereas 29 QTLs were detected in BC₂F₂ generation of the same population. Two QTLs (qPL-1 and qSPL-7) were not considered for validation due to their low R ² values and two QTLs (qPSS-3-2 and qGW-3-2) were not detected in the BC₂F₅ population. Fifteen QTLs showed the beneficial effect to enhance the trait value of the breeding lines. QTL validation aided to select the promising lines for further utilization.     

Mapping quantitative trait loci associated with yield and yield components under reproductive stage salinity stress in rice (Oryza sativa L.)

Salinity tolerance in rice is critical at reproductive stage because it ultimately determines grain yield. An F₂ mapping population derived from a Sadri/FL478 cross was exposed to saline field conditions (6–8 dS m^???1) after the active tillering stage to identify reproductive stage specific QTLs for salinity tolerance. Genetic linkage map was constructed using 123 microsatellite markers on 232 F₂ progenies. Totally 35 QTLs for 11 traits under salinity stress were detected with LOD > 3, out of which 28 QTLs that explained from 5.9 to 30.0% phenotypic variation were found to be significant based on permutation test. Three major QTL clusters were found on chromosomes 2 (RM423–RM174), 4 (RM551–RM518) and 6 (RM20224–RM528) for multiple traits under salinity stress. Both parental lines contributed additively for QTLs identified for the yield components. A majority of the QTLs detected in our study are reported for the first time for reproductive stage salinity stress. Fine-mapping of selected putative QTLs will be the next step to facilitate marker-assisted backcrossing and to detect useful genes for salinity tolerance at the reproductive stage in rice.     

Mapping of Quantitative Trait Loci Underlying Cold Tolerance in Rice Seedlings via High-Throughput Sequencing of Pooled Extremes

Low temperature is a major limiting factor in rice growth and development. Mapping of quantitative trait loci (QTLs) controlling cold tolerance is important for rice breeding. Recent studies have suggested that bulked segregant analysis (BSA) combined with next-generation sequencing (NGS) can be an efficient and cost-effective way for QTL mapping. In this study, we employed NGS-assisted BSA to map QTLs conferring cold tolerance at the seedling stage in rice. By deep sequencing of a pair of large DNA pools acquired from a very large F₃ population (10,800 individuals), we obtained ∼450,000 single nucleotide polymorphisms (SNPs) after strict screening. We employed two statistical methods for QTL analysis based on these SNPs, which yielded consistent results. Six QTLs were mapped on chromosomes 1, 2, 5, 8 and 10. The three most significant QTLs on chromosomes 1, 2 and 8 were validated by comparison with previous studies. Two QTLs on chromosomes 2 and 5 were also identified previously, but at the booting stage rather than the seedling stage, suggesting that some QTLs may function at different developmental stages, which would be useful for cold tolerance breeding in rice. Compared with previously reported QTL mapping studies for cold tolerance in rice based on the traditional approaches, the results of this study demonstrated the advantages of NGS-assisted BSA in both efficiency and statistical power.     

Introgression of dual abiotic stress tolerance QTLs (Saltol QTL and Sub1 gene) into Rice (Oryza sativa L.) variety Aiswarya through marker assisted backcross breeding

Salinity and submergence are two very prominent abiotic stress conditions affecting rice yield adversely in the coastal agro ecosystem. Marker Assisted Backcross Breeding (MABB) is an efficient and fast track molecular tool to incorporate a desired stress tolerant QTL/gene into an improved cultivar. The present study was carried out for the introgression of Saltol QTL responsible for salinity tolerance and Sub1 gene responsible for submergence tolerance into the high yielding rice variety Aiswarya independently through MABB. Final objective of the study is to develop dual stress tolerant (tolerance to salinity and submergence) Aiswarya rice variety by pyramiding the both target QTLs introgressed BC₂F₂ progenies having maximum background homozygosity. The donors of Saltol QTL and Sub1 gene used in the present study were FL478 and Swarna Sub1, respectively. Based on the background genome analysis of the introgressed plants, the plants with > 85–90% background similarity were selected for pyramiding of Saltol QTL and Sub1 gene into the elite background of rice variety Aiswarya. Those selected introgressed lines with Saltol QTL and Sub1 gene will be again crossed to pyramid both Saltol QTL and Sub1 gene into the rice variety Aiswarya. Such a mega rice variety pyramided with dual stress tolerant QTLs is the expected outcome of this study and can be recommended for cultivation in the flood prone saline coastal agroecosystem.     

Identification of QTLs with Additive,Epistatic, and QTL × Seed Maturity Interaction Effects for Seed Vigor in Rice

Seed maturity is a critical process of seed vigor establishment. In this study, one rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed vigor, including the germination potential (GP), germination rate (GR), germination index (GI), and time for 50 % of germination (T₅₀), at 4, 5, and 6 weeks after heading in 2 years. Significant differences of seed vigor were observed among two parents and RIL population; the heritability of four traits was more than 90 % at three maturity stages. A total of 19 additive and 2 epistatic quantitative trait loci (QTL) for seed vigor were identified using QTL Cartographer and QTLNetwork program, respectively, in 2012, while 16 simple sequence repeat (SSR) markers associated with seed vigor were detected using bulked segregant analysis (BSA) in 2013. The phenotypic variation explained by each additive, epistatic QTL, and QTL × seed maturity interaction ranged from 9.19 to 22.94 %, 7.23 to 7.75 %, and 0.05 to 0.63 %, respectively. Ten additive QTLs were stably expressed in 2 years which might play important roles in establishment of seed vigor in different environments. By comparing chromosomal positions of ten stably expressed additive QTLs with those previously identified, they might be true QTLs for seed vigor; the regions of QTLs for seed vigor are likely to coincide with QTLs for seed dormancy, seed reserve mobilization, low-temperature germinability, and seedling growth. Using four selected RILs, three cross-combinations were predicted to improve seed vigor; 9 to 10 elite alleles could be pyramided by each combination. The selected RILs and the identified QTLs might be applicable for the improvement of seed vigor by marker-assisted selection (MAS) in rice.     

Fine mapping a major QTL <Emphasis Type="Italic">qFCC7</Emphasis><Subscript><Emphasis Type="Italic">L</Emphasis></Subscript> for chlorophyll content in rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) cv. PA64s

Chlorophyll (Chl) content is an important agronomic trait directly affecting the photosynthetic rate. Using a high-density genetic map of 132 recombinant inbred lines (RILs) derived from the cross between 93-11 and PA64s, we detected the quantitative trait loci (QTLs) for Chl content of the top three leaves under two nitrogen (N) conditions at two developmental stages. A total of 32 main-effect QTLs located on chromosomes 1, 4, 5, 6, 7, 8, and 12 were identified, and these QTLs individually accounted for 6.0–20.8?% of the total phenotypic variation. A major QTL qFCC7 _L affecting the Chl content under low N condition was identified, and its positive allele came from PA64s. This QTL might be associated with the ability to tolerate low-N stress in rice. The chromosomal segment substitution line (CSSL) with the corresponding segment from PA64s had a higher SPAD value and photosynthetic rate than 93-11 and showed a lower specific leaf area (SLA). We performed a fine-mapping using a BC₄F₂ population via marker-assisted backcross and finally mapped this QTL to a 124.5 kb interval on the long arm of chromosome 7. Candidate gene analysis showed that there were sequence variations and expression differences in the predicted candidate gene between the two parents. These results suggest that the QTL qFCC7 _L may be useful for breeding the rice varieties with higher photosynthetic rate and grain yield.     

Locating QTLs controlling overwintering seedling rate in perennial glutinous rice 89-1 (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.)

A new cold tolerant germplasm resource named glutinous rice 89-1 (Gr89-1, Oryza sativa L.) can overwinter using axillary buds, with these buds being ratooned the following year. The overwintering seedling rate (OSR) is an important factor for evaluating cold tolerance. Many quantitative trait loci (QTLs) controlling cold tolerance at different growth stages in rice have been identified, with some of these QTLs being successfully cloned. However, no QTLs conferring to the OSR trait have been located in the perennial O. sativa L. To identify QTLs associated with OSR and to evaluate cold tolerance. 286 F₁₂ recombinant inbred lines (RILs) derived from a cross between the cold tolerant variety Gr89-1 and cold sensitive variety Shuhui527 (SH527) were used. A total of 198 polymorphic simple sequence repeat (SSR) markers that were distributed uniformly on 12 chromosomes were used to construct the linkage map. The gene ontology (GO) annotation of the major QTL was performed through the rice genome annotation project system. Three main-effect QTLs (qOSR2, qOSR3, and qOSR8) were detected and mapped on chromosomes 2, 3, and 8, respectively. These QTLs were located in the interval of RM14208 (35,160,202 base pairs (bp))–RM208 (35,520,147 bp), RM218 (8,375,236 bp)–RM232 (9,755,778 bp), and RM5891 (24,626,930 bp)–RM23608 (25,355,519 bp), and explained 19.6%, 9.3%, and 11.8% of the phenotypic variations, respectively. The qOSR2 QTL displayed the largest effect, with a logarithm of odds score (LOD) of 5.5. A total of 47 candidate genes on the qOSR2 locus were associated with 219 GO terms. Among these candidate genes, 11 were related to cell membrane, 7 were associated with cold stress, and 3 were involved in response to stress and biotic stimulus. OsPIP1;3 was the only one candidate gene related to stress, biotic stimulus, cold stress, and encoding a cell membrane protein. After QTL mapping, a total of three main-effect QTLs—qOSR2, qOSR3, and qOSR8—were detected on chromosomes 2, 3, and 8, respectively. Among these, qOSR2 explained the highest phenotypic variance. All the QTLs elite traits come from the cold resistance parent Gr89-1. OsPIP1;3 might be a candidate gene of qOSR2.