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qCT7, a novel QTL for increasing seedling cold tolerance in rice, was fine-mapped to a 70.9-kb region on chromosome 7, and key OsWRKY115 was identified in transgenic plants. Cold stress caused by underground cold-water irrigation seriously limits rice productivity. We systemically measured the cold-responsive traits of 2,570 F2 individuals derived from two widely cultivated rice cultivars, Kong-Yu-131 and Dong-Nong-422, to identify the major genomic regions associated with cold tolerance. A novel major QTL, qCT7, was mapped on chromosome 7 associated with the cold tolerance and survival, using whole-genome re-sequencing with bulked segregant analysis. Local QTL linkage analysis with F

As one of the most important part of the ideal plant type of japonica rice, leaf shape affects the photosynthesis and carbohydrate accumulation directly. Mining and using new leaf shape related genes/QTLs can further enrich the theory of molecular breeding and accelerate the breeding process of japonica rice. In the present study, 2 RILs and a natural population with 295 japonica rice varieties were used to map QTLs for flag leaf length (FL), flag leaf width (FW) and flag leaf area (FLA) by linkage analysis and genome-wide association study (GWAS) through 2 years. A total of 64 QTLs were detected by 2 ways, and pleiotropic QTLs qFL2 (Chr2_33,332,579) and qFL10 (Chr10_10,107,835; Chr10_10,230,100) consisted of overlapping QTLs mapped by linkage analysis and GWAS through 2 years were identified. The candidate genes LOC_Os02g54254, LOC_Os02g54550, LOC_Os10g20160, LOC_Os10g20240, LOC_Os10g20260 were obtained, filtered by linkage disequilibrium (LD), and haplotype analysis. LOC_Os10g20160 (SD-RLK-45) showed outstanding characteristics in quantitative real-time PCR (qRT-PCR) analysis in leaf development period, belongs to S-domain receptor-like protein kinases gene and probably to be a main gene regulating flag leaf width of japonica rice. The results of this study provide valuable resources for mining the main genes/QTLs of japonica rice leaf development and molecular breeding of japonica rice ideal leaf shape.

The C (Cys) 2H (His) 2-type transcription factor is one of the most important transcription factors in plants and plays a regulatory role in the physiological responses of rice to abiotic stresses. A novel rice C2H2-type zinc finger protein, abscisic acid (ABA)-drought-reactive oxygen species (ROS) 3 (OsADR3), was found to confer drought stress tolerance by enhancing antioxidant defense and regulating OsGPX1. Overexpression of OsADR3 in rice increased tolerance to drought stress by increasing ROS scavenging ability and ABA sensitivity. In contrast, CRISPR/Cas9-mediated knockout of osadr3 increased the sensitivity of rice to drought and oxidative stress. An exogenous ROS-scavenging reagent restored the drought-stress tolerance of osadr3-CRISPR plants. Global transcriptome analysis suggested that OsADR3 increased the expression of OsGPX1 under drought stress. Electrophoretic mobility shift, yeast one-hybrid, and dual-luciferase reporter assays revealed that OsADR3 modified the expression of OsGPX1 by directly binding to its promoter. Knockdown of OsGPX1 repressed ROS scavenging ability under drought stress in OsADR3-overexpression plants. These findings suggest that OsADR3 plays a positive regulatory role in drought-stress tolerance by inducing antioxidant defense and associated with the ABA signaling pathway in rice.

β-ketoacyl-CoA synthase is a key enzyme in the biosynthesis of over-long-chain fattty acids; thus, it plays a crucial role in plant resistance to stress. Herein, 33 OsKCSs were classified into five subfamilies based on phylogenetic analysis and domain structure in rice. Nonsynonymous to synonymous substitution ratio (Ka/Ks) analysis showed that duplicated genes were possibly under strong purifying selection pressure. Cis-element analysis revealed that OsKCSs may be regulated by different transcription factors. SNP distribution of OsKCSs in 295 germplasm accessions seemed associated with functional disparity under environmental stress. Additionally, 10 of the 33 OsKCSs were not expressed in different rice tissues. RNA-Seq and qRT-PCR analysis demonstrated that seven OsKCSs (OsKCS5, OsKCS6, OsKCS14, OsKCS15, OsKCS4, OsKCS30, and OsKCS21) had significantly different expression levels under 0.5% NaCl, 0.5% Na2CO3, and a 10-day incubation at 17 °C. Our results provide a solid foundation for understanding the roles of OsKCS genes and the mechanism by which they regulate stress resistance.

Drought stress at jointing–booting directly affects plant growth and productivity in rice. Limited by natural factors, the jointing and booting stages of short-growth-period rice varieties are highly overlapped in high-latitude areas, which are more sensitive to water deficit. However, little is known about the dry matter translocation in rice and the strategies of starch synthesis and filling of superior and inferior grains under different drought stress was unclear. In this study, the rice plants were subjected to three degrees of drought stress (−10 kPa, −25 kPa, −40 kPa) for 15 days during the jointing–booting stage; we investigated dry matter accumulation and translocation, grain filling and enzyme activities to starch synthesis of superior and inferior grains in rice with overlapping growth stages from 2016 to 2017. The results showed that drought stress significantly reduced dry matter accumulation in the stems and leaves. Mild and moderate drought increased dry matter translocation efficiency. However, severe drought stress largely limited the dry matter accumulation and translocation. A large amount of dry matter remains in vegetative organs under severe drought stress. The high content in NSC in stem and sheath plays a key role in resisting drought stress. The drought stress at jointing–booting directly caused a change in the grain filling strategy. Under moderate and severe drought, the grain-filling active period of the superior grains was shortened to complete the necessary reproductive growth. The grain-filling active period of the inferior grains was significantly prolonged to avoid a decrease in grain yield. The significant decrease in the grain-filling rate of the superior and inferior grains caused a reduction in the thousand-grain weight. In particular, the influence of the grain-filling rate of inferior grains on the thousand-grain weight was more significant. Drought stress changed the starch synthesis strategies of the superior and inferior grains. Soluble starch synthase and starch branching enzyme activities of inferior grains increased significantly under drought stress. GBSS activity was not sensitive to drought stress. Therefore, amylose content was decreased and amylopectin synthesis was enhanced under drought stress, especially in inferior grains.

Caffeic acid O-methyltransferase (COMT) is one of the core enzymes involved in lignin synthesis. However, there is no systematic study on the rice COMT gene family. We identified 33 COMT genes containing the methyltransferase-2 domain in the rice genome using bioinformatic methods and divided them into Group I (a and b) and Group II. Motifs, conserved domains, gene structure and SNPs density are related to the classification of

Nitrogen-based nutrients are the main factors affecting rice growth and development. As the nitrogen (N) application rate increased, the nitrogen use efficiency (NUE) of rice decreased. Therefore, it is important to understand the molecular mechanism of rice plant morphological, physiological, and yield formation under low N conditions to improve NUE. In this study, changes in the rice morphological, physiological, and yield-related traits under low N (13.33 ppm) and control N (40.00 ppm) conditions were performed. These results show that, compared with control N conditions, photosynthesis and growth were inhibited and the carbon (C)/N and photosynthetic nitrogen use efficiency (PNUE) were enhanced under low N conditions. To understand the post-translational modification mechanism underlying the rice response to low N conditions, comparative phosphoproteomic analysis was performed, and differentially modified proteins (DMPs) were further characterized. Compared with control N conditions, a total of 258 DMPs were identified under low N conditions. The modification of proteins involved in chloroplast development, chlorophyll synthesis, photosynthesis, carbon metabolism, phytohormones, and morphology-related proteins were differentially altered, which was an important reason for changes in rice morphological, physiological, and yield-related traits. Additionally, inconsistent changes in level of transcription and protein modification, indicates that the study of phosphoproteomics under low N conditions is also important for us to better understand the adaptation mechanism of rice to low N stress. These results provide insights into global changes in the response of rice to low N stress and may facilitate the development of rice cultivars with high NUE by regulating the phosphorylation level of carbon metabolism and rice morphology-related proteins.

Nitrogen is an important nutrient for plant growth and essential metabolic processes. Roots integrally obtain nutrients from soil and are closely related to the growth and development of plants. In this study, the morphological analysis of rice root tissues collected at different time points under low-nitrogen and normal nitrogen conditions demonstrated that, compared with normal nitrogen treatment, the root growth and nitrogen use efficiency (NUE) of rice under low-nitrogen treatment were significantly improved. To better understand the molecular mechanisms of the rice root system’s response to low-nitrogen conditions, a comprehensive transcriptome analysis of rice seedling roots under low-nitrogen and control conditions was conducted in this study. As a result, 3171 differentially expressed genes (DEGs) were identified. Rice seedling roots enhance NUE and promote root development by regulating the genes related to nitrogen absorption and utilization, carbon metabolism, root growth and development, and phytohormones, thereby adapting to low-nitrogen conditions. A total of 25,377 genes were divided into 14 modules using weighted gene co-expression network analysis (WGCNA). Two modules were significantly associated with nitrogen absorption and utilization. A total of 8 core genes and 43 co-expression candidates related to nitrogen absorption and utilization were obtained in these two modules. Further studies on these genes will contribute to the understanding of low-nitrogen adaptation and nitrogen utilization mechanisms in rice.

Background Plant height is a key factor in the determination of rice yield since excessive height can easily cause lodging and reduce yield. Therefore, the identification and analysis of plant height-related genes to elucidate their physiological, biochemical, and molecular mechanisms have significant implications for rice breeding and production. Results High-throughput quantitative trait locus (QTL) sequencing analysis of a 638-individual F2:3 mapping population resulted in the identification of a novel height-related QTL (qPH9), which was mapped to a 2.02-Mb region of Chromosome 9. Local QTL mapping, which was conducted using 13 single nucleotide polymorphism (SNP)-based Kompetitive allele-specific PCR (KASP) markers for the qPH9 region, and traditional linkage analysis, facilitated the localization of qPH9 to a 126-kb region that contained 15 genes. Subsequent haplotype and sequence analyses indicated that OsPH9 was the most probable candidate gene for plant height at this locus, and functional analysis of osph9 CRISPR/Cas9-generated OsPH9 knockout mutants supported this conclusion. Conclusion OsPH9 was identified as a novel regulatory gene associated with plant height in rice, along with a height-reducing allele in ‘Dongfu-114’ rice, thereby representing an important molecular target for rice improvement. The findings of the present study are expected to spur the investigation of genetic mechanisms underlying rice plant height and further the improvement of rice plant height through marker-assisted selection.

Salinity tolerance plays an important role in direct seeding cultivation since tolerance to salinity at the bud burst stage of rice directly affects seedling formation and yield. However, information on the quantitative trait loci (QTL) associated with salinity tolerance at the bud burst stage is limited. Here, a recombinant inbred line (RIL) population, derived from a cross between Kongyu131 (salinity-sensitive) and Xiaobaijingzi (salinity-tolerant), was used to identify QTLs for salinity tolerance at the bud burst stage using a high-density genetic map. Four QTLs were identified. The threshold LOD score for QTL identification was 3.0. Among the four QTLs detected, two QTLs namely qRSL3 (PVE, 22.59%) and qRRL3 (PVE, 21.21%) were considered to be one QTL, named qST3, which was the major QTL related to salinity tolerance on chromosome 3. This major QTL was located within an interval of 2.55 Mb and contained 253 candidate genes. Using RNA-seq data, 51 differentially expressed genes (DEGs) were detected among the candidate region. According to Rice Annotation Project and quantitative real-time PCR (qRT-PCR) analysis, Os03g0664800 was accepted as the most likely candidate gene for qST3. These results will be useful for improving salinity tolerance of rice and for developing rice cultivars suitable for direct seeding in salinized soil.

Background Rice (Oryza sativa L.) is one of the most widely grown food crops, and its yield and quality are particularly important for a warm-saturated diet. Cold stress restricts rice growth, development, and yield; however, the specific mechanism of cold tolerance in rice remains unknown. Results The analysis of leaf physiological and photosynthetic characteristics showed that the two rice varieties were significantly affected by cold stress, but the cold-tolerant variety KY131 had more stable physiological characteristics, maintaining relatively good photosynthetic capacity. To better explore the transcriptional regulation mechanism and biological basis of rice response to cold stress, a comprehensive analysis of the rice transcriptome and lipidome under low temperature and control temperature conditions was carried out. The transcriptomic analysis revealed that lipid metabolism, including membrane lipid and fatty acid metabolism, may be an important factor in rice cold tolerance, and 397 lipid metabolism related genes have been identified. Lipidomics data confirmed the importance of membrane lipid remodeling and fatty acid unsaturation for rice adaptation to cold stress. This indicates that the changes in the fluidity and integrity of the photosynthetic membrane under cold stress lead to the reduction of photosynthetic capacity, which could be relieved by increased levels of monogalactosyldiacylglycerol that mainly caused by markedly increased expression of levels of 1,2-diacylglycerol 3-beta-galactosyltransferase (MGD). The upregulation of phosphatidate phosphatase (PAP2) inhibited the excessive accumulation of phosphatidate (PA) to produce more phosphatidylcholine (PC), phosphatidylethanolamine (PE), and phosphatidylglycerol (PG), thereby preventing of membrane phase transition under cold stress. In addition, fatty acid β-oxidation is worth further study in rice cold tolerance. Finally, we constructed a metabolic model for the regulatory mechanism of cold tolerance in rice, in which the advanced lipid metabolism system plays a central role. Conclusions Lipidome analysis showed that membrane lipid composition and unsaturation were significantly affected, especially phospholipids and galactolipids. Our study provides new information to further understand the response of rice to cold stress.

Over-application of nitrogen (N) fertilizer in fields has had a negative impact on both environment and human health. Domesticated rice varieties with high N use efficiency (NUE) reduce fertilizer requirements, enabling sustainable agriculture. Genome-wide association study (GWAS) analysis of N absorption and utilization traits under low and high N conditions was performed to obtain 12 quantitative trait loci (QTLs) based on genotypic data including 151,202 single-nucleotide polymorphisms (SNPs) developed by re-sequencing 267 japonica rice varieties. Eighteen candidate genes were obtained by integrating GWAS and transcriptome analyses; among them, the functions of OsNRT2.4, OsAMT1.2, and OsAlaAT genes in N transport and assimilation have been identified, and OsJAZ12 and OsJAZ13 also play important roles in rice adaptation to abiotic stresses. A NUE-related candidate gene, OsNAC68, was identified by quantitative real-time PCR (qRT-PCR) analyses. OsNAC68 encodes a NAC transcription factor and has been shown to be a positive regulator of the drought stress response in rice. Overexpression of OsNAC68 significantly increased rice NUE and grain yield under deficient N conditions, but the difference was not significant under sufficient N conditions. NUE and grain yield significantly decreased under both N supply conditions in the osbnac68 mutant. This study provides crucial insights into the genetic basis of N absorption and utilization in rice, and a NUE-related gene, OsNAC68, was cloned to provide important resources for rice breeding with high NUE and grain yield.

Low-temperature tolerance during the bud-bursting stage is an important characteristic of direct-seeded rice. The identification of cold-tolerance quantitative trait loci (QTL) in species that can stably tolerate cold environments is crucial for the molecular breeding of rice with such traits. In our study, high-throughput QTL-sequencing analyses were performed in a 460-individual F2:3 mapping population to identify the major QTL genomic regions governing cold tolerance at the bud-bursting (CTBB) stage in rice. A novel major QTL, qCTBB9, which controls seed survival rate (SR) under low-temperature conditions of 5°C/9 days, was mapped on the 5.40-Mb interval on chromosome 9. Twenty-six non-synonymous single-nucleotide polymorphism (nSNP) markers were designed for the qCTBB9 region based on re-sequencing data and local QTL mapping conducted using traditional linkage analysis. We mapped qCTBB9 to a 483.87-kb region containing 58 annotated genes, among which six predicted genes contained nine nSNP loci. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis revealed that only Os09g0444200 was strongly induced by cold stress. Haplotype analysis further confirmed that the SNP 1,654,225 bp in the Os09g0444200 coding region plays a key role in regulating the cold tolerance of rice. These results suggest that Os09g0444200 is a potential candidate for qCTBB9. Our results are of great significance to explore the genetic mechanism of rice CTBB and to improve the cold tolerance of rice varieties by marker-assisted selection.

Rice is highly susceptible to drought and cold. The goal of this study was to identify the QTLs affecting the rice heading date (HD), leaf area (LA) and chlorophyll content (CC) under cold and drought stress. A total of twenty‐nine and thirty‐eight additive QTLs were detected from two crosses of ‘Dongnong422’/‘Kongyu131’ and ‘Xiaobaijingzi’/‘Kongyu131’, respectively. qHD1‐7‐1, qHD1‐7‐2, qHD1‐2‐1, qLA1‐7‐1, qLA1‐6‐3 and qCC1‐7‐1 show adaptive effects under cold treatment, while qHD2‐2‐3, qHD2‐2‐2, qLA2‐7‐3 and qCC2‐5‐1 were important for explaining the genetic mechanism during drought tolerance. Additionally, nine and five additive × environment interaction QTLs were detected for two RILs, respectively. RIL26 and RIL73 were two lines that are associated with cold and drought for HD. 339 QTLs related to HD, CC and LA of rice from database and our research were projected onto the genetic map. Nine cloned genes and nineteen homologous candidate genes related to HD, CC, cold tolerance and drought tolerance were mapped by meta‐analysis. These results lay the foundation for the fine mapping of QTLs related to HD, LA and CC for marker‐assisted selection.

Soil alkalinity greatly affects plant growth and crop productivity. Although RNA-Seq analyses have been conducted to investigate genome-wide gene expression in response to alkaline stress in many plants, the expressions of alkali-responsive genes in rice have not been previously investigated. In this study, the transcriptomic data between an alkaline-tolerant (WD20342) and an alkaline-sensitive (Caidao) rice cultivar were compared under alkaline stress conditions. A total of 962 important alkali-responsive (IAR) genes from highly differentially expressed genes (DEGs) were identified, including 28 alkaline-resistant cultivar-related genes, 771 alkaline-sensitive cultivar-related genes and 163 cultivar-non-specific genes. Gene ontology (GO) analysis indicated the enrichment of IAR genes involved in various stimulus or stress responses. According to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, the IAR genes were related primarily to plant hormone signal transduction and biosynthesis of secondary metabolites. Additionally, among these 962 IAR genes, 74 were transcription factors and 15 occurred with differential alternative splicing between the different samples after alkaline treatment. Our results provide a valuable resource on alkali-responsive genes and should benefit the improvement of alkaline stress tolerance in rice.

Alkaline stress causes injuries to rice seedlings in many parts of the world and is therefore an important factor affecting rice production in such areas. In this study, we preliminarily located quantitative trait loci (QTLs) for survival days of seedlings (SDS) and the concentrations of Na+ and K+ in shoots (SNC and SKC) and roots (RNC and RKC) under alkaline stress using an F2:3 population, which was derived from a cross between Caidao and WD20342 with 151 simple sequence repeat (SSR) markers. A total of seven QTLs were detected. Of these QTLs, qSNC3 had the largest effect, which explained 21.24% of the total phenotypic and is a major QTL. Next, a mapping population consisting of 190 BC2F2 plants was constructed using WD20342 as a donor parent to verify qSNC3. As a result, qSNC3 was delimited to an 81.7-kb region between markers RM1221 and RM4404. In this region, LOC_Os03 g62500 and LOC_Os03 g62620 exhibited different expression between Caidao and WD20342 under alkaline stress. These results provide a basis for identifying genes related to alkaline tolerance in rice.

We projected meta-QTL (MQTL) for drought, salinity, cold state, and high metal ion tolerance in rice using a meta-analysis based on high-density consensus maps. In addition, a genome-wide association analysis was used to validate the results of the meta-analysis, and four new chromosome intervals for mining abiotic stress candidate genes were obtained. Drought, severe cold, high salinity, and high metallic ion concentrations severely restrict rice production. Consequently, the breeding of abiotic stress-tolerant variety is being paid increasingly more attention. This study aimed to identify meta-quantitative trait loci (MQTL) for abiotic stress tolerance in rice, as well as the molecular markers and potential candidate genes of the MQTL regions. We summarized 2785 rice QTL and conducted a meta-analysis of 159 studies. We found 82 drought tolerance (DT), 70 cold tolerance (CT), 70 salt tolerance (ST), and 51 heavy metal ion tolerance (IT) meta-QTL, as well as 20 DT, 11 CT, 22 ST, and 5 IT candidate genes in the MQTL interval. Thirty-one multiple-tolerance related MQTL regions, which were highly enriched, were also detected, and 13 candidate genes related to multiple-tolerance were obtained. In addition, the correlation between DT, CT, and ST was significant in the rice genome. Four candidate genes and four MM-QTL regions were detected simultaneously by GWAS and meta-analysis. The four candidate genes showed distinct genetic differentiation and substantial genetic distance between indica and japonica rice, and the four MM-QTL are potential intervals for mining abiotic stress-related candidate genes. The candidate genes identified in this study will not only be useful for marker-assisted selection and pyramiding but will also accelerate the fine mapping and cloning of the candidate genes associated with abiotic stress-tolerance mechanisms in rice.

Low temperature at the booting stage is a major abiotic stress-limiting rice production. In this study, Cold stress tolerance index of panicle traits of a recombinant inbred line was used to identify cold tolerance at booting stage for three consecutive years. The purpose was to locate the stable QTL linked to cold tolerance at booting stage. Combined with meta-analysis model, candidate genes for cold tolerance were mined. The results showed that a total of 17 cold resistant QTLs were detected, of which 5 were pleiotropic interval (CTB2-1, CTB6-2, CTB7-1, CTB7-2 and CTB7-4). However, only three traits obtained the same QTLs in different years, which indicated that cold tolerant QTL at the booting stage was greatly affected by environment. The six selected progenys with cold tolerance alleles can be used in cross combinations. A total of 47 cold tolerance meta-QTLs (MCqtl) were obtained from the meta-analysis, of which 8 reported cold response genes were found in 7 MCqtl regions, and 18 candidate genes conferring cold tolerance were identified, of which 10 candidate genes showed hits to ESTs expressed in the reproductive tissue. These results would lay a foundation for fine mapping of QTLs/genes related to cold tolerance in booting stage and marker-assisted selection for breeding in rice.

Tiller number per plant (TN) and plant height (PH) are important agronomic traits related to grain yield (GY) in rice (Oryza sativa L.). A total of 30 additive quantitative trait loci (A-QTL) and 9 significant additive × environment interaction QTLs (AE-QTL) were detected, while the phenotypic and QTL correlations confirmed the intrinsic relationship of the three traits. These QTLs were integrated with 986 QTLs from previous studies by metaanalysis. Consensus maps contained 7156 markers for a total map length of 1112.71 cM, onto which 863 QTLs were projected; 78 meta-QTLs (MQTLs) covering 11 of the 30 QTLs were detected from the cross between Dongnong422 and Kongyu131 in this study. A total of 705 predicted genes were distributed over the 21 MQTL intervals with physical length

Rice blast is one of the major fungal diseases that badly reduce rice production in China and worldwide. Molecular markers tightly linked to resistant genes can be used for marker-assisted and/or genomic selection. In this study, linkage mapping and association mapping were used to identify the QTLs for the disease index of 7 and 14 days after inoculation (DI7 and DI14) conferring resistance against two highly pathogenic and locally predominant isolates (DB22 and DB77) in japonica rice at the seedling stage. The recombinant inbred line (RIL) population with 114 SSR markers derived from Dongnong 415 (resistant to rice blast) as the male parent and Lijiangxintuanheigu (LTH, susceptible to rice blast) as the female parent was used for linkage mapping. A total of 10 QTLs were identified by the inclusive composite interval mapping method (ICIM), explaining 7.89–33.75 % of the total phenotypic variance. This study was supplemented with association mapping, which was conducted using a panel of 227 japonica rice cultivars released in Northeastern China during the past 50 years with 118 selected SSR markers. A total of 13 significant marker-trait associations (P ≤ 0.01) involving 10 markers were identified using the MLM (Q + K) models in TASSEL 3.0. Among them, 8 of the SSR markers confirmed or narrowed the genomic regions for blast resistance that were reported in linkage studies, including five QTLs identified during the present study. Phenotypic effects of each allele of the 8 stable markers were compared, and 12 resistant alleles were identified. These resistant alleles could be used to design parental combinations and the expected results would be obtained by pyramiding or substituting the resistant alleles per QTL (apart from possible epistatic effects). The results should increase our understanding of the genetic basis of blast resistance and facilitate future resistant breeding in rice.

Figure S1. Distributions of coverage depth on chromosomes of the sequencing samples. X-axe indicates the 12 chromosomes of rice. Y-axe indicates the log2 value of coverage depth corresponding to chromosome location. (DOC 1130 kb)

Both low-temperature germinability (LTG) and cold tolerance at the seedling stage (CTS) are important traits for rice. In this study, a rice population of recombinant inbred lines (RILs), derived from the backcross population of a cross between Dongnong422 and Kongyu131, was developed to detect quantitative trait loci (QTL) affecting LTG and CTS by using seed of different storage times. Correlation analysis indicated that there was no significant relationship between LTG and CTS, suggesting that cold tolerance might be genetic differences for LTG and CTS. In total, Twelve and twenty-three major QTLs were detected for LTG and CTS, respectively, which could explain greater than 10% of the phenotypical variation. Eight (qCG12-1, qGI12-1, qGV9-1, qMLIT12-1, qPV6-1, qMDG12-1, qLDWcold10-1, qLFWcold10-1) significant QTLs were mapped for different storage time, it concluded that such QTLs were not affected by environment (storage time) and were closely related QTLs to cold tolerance. One or more QTLs were identified for each trait with some of these QTLs co-locating, qMLIT7-1, qCG7-1, and qGI7-1 for LTG, qLFWcold10-1, and qLDWcold10-1 for CTS with contributions over 15% were mapped common marker interval, respectively, co-location of QTLs for different traits can be an indication that a locus has pleiotropic effects on multiple traits due to a common mechanistic basis. Two lines, RIL128 and RIL73, might be valuable to improve the LTG and CTS through a combination of crosses. The identified QTLs might be applicable to improve the rice cold tolerance by the marker-assisted selection approach.

The author H.L. Chang is affiliated with “Innovation Center, Suihua Branch of Heilongjiang Academy of Agricultural Sciences, Suihua 152052, People’s Republic of China” in addition to the institution listed in the original publication.

Anthocyanins and proanthocyanidins are the primary pigments of red rice and are also important functional nutrients for human health. To identify novel quantitative trait loci (QTLs) underlying anthocyanins and proanthocyanidins (ANC and PAC) in rice, a recombinant inbred line (RIL) derived from a cross of red rice ‘Hong Xiang 1’ (‘HX1’) and white rice ‘Song 98-131’ (‘S98-131’) was cultivated in six environments. A genetic map containing 126 markers covering 1833.4 cM with an average of 14.55 cM between markers was constructed. A total of 21 additive QTLs (A-QTLs) for ANC and PAC were identified from six environments using the IciMapping v3.3 software. Two new QTLs, qANC3 and qPAC12-4, were detected in several environments, and explained significant phenotypic variance. Nine QTLs of ANC and PAC were detected with additive × environmental interaction effects (AE effects) by QTLNetwork 2.1 software, but no epistatic and epistatic × environmental interaction effects (AA and AAE effects) were detected. The information obtained in this study could be useful for fine mapping and molecular marker-assisted selection of ANC and PAC in rice.

Low temperatures dramatically influence spikelets at the booting stage, which is an important factor that greatly reduces grain yield. Mining the genes for grain yield under low temperatures and elucidating the genetic mechanism is a key approach to breeding improved-yield crops. In this study, we generated 190 recombinant inbred lines with 155 SSR markers from a cross between Dongnong422 (a low-temperature-sensitive variety) and Kongyu131 (a low-temperature-tolerant variety). These lines were employed for linkage mapping for yield-component traits under low water temperature and control conditions in two consecutive years. As a result, 18 addition QTLs (A-QTLs) were detected using ICIM, other two analytical methods, CIM (22 A-QTLs) and MICM (8 A-QTLs) were used to demonstrate QTLs ICIM has detected, which showed that all three analytical methods gave a consistency in result. Among these QTLs, 17 QTLs (35.4%) were detected simultaneously under both cold-water-irrigated and control conditions, and these QTLs were most influential (adaptive effect) under the cold-water treatment. Five pleiotropic genomic regions controlling yield were mapped on chromosomes 6, 7, 8 and 11. Among these regions, one of the major regions located, the marker interval RM1306–RM70, was repeatedly detected for panicle length, grains per panicle, primary branch number, secondary branch number and grain density under low-water temperature and control conditions based on three analysis models. Multiple-environment joint analysis showed that nine A-QTLs were detected for seven traits. Thirteen pairs of epistatic QTLs (E-QTLs) were detected for seven traits, but for yield per plant, only seven pairs had significant environmental specificity. The QTLs detected using three analytical models under different environments showed that it is possible to use molecular breeding for cold tolerance, and the markers linked to the QTLs of stable expression could be applied to rice yield improvement in low temperatures.