Mapping and validation of QTLs for cold tolerance at seedling stage in rice from an indica cultivar Habiganj Boro VI (Hbj.BVI)

Progress in the study of functional genes related to direct seeding of rice

Rice is a major food crop in the world. Owing to the shortage of rural labor and the development of agricultural mechanization, direct seeding has become the main method of rice cultivation. At present, the main problems faced by direct seeding of rice are low whole seedling rate, serious weeds, and easy lodging of rice in the middle and late stages of growth. Along with the rapid development of functional genomics, the functions of a large number of genes have been confirmed, including seed vigor, low-temperature tolerance germination, low oxygen tolerance growth, early seedling vigor, early root vigor, resistance to lodging, and other functional genes related to the direct seeding of rice. A review of the related functional genes has not yet been reported. In this study, the genes related to direct seeding of rice are summarized to comprehensively understand the genetic basis and mechanism of action in direct seeding of rice and to lay the foundation for further basic theoretical research and breeding application research in direct seeding of rice.

Comparative transcriptomics and co-expression networks reveal cultivar-specific molecular signatures associated with reproductive-stage cold stress in rice

The resistance of Huaidao5 results from the high constitutive expression of tolerance genes, while that of Huaidao9 is due to the cold-induced resistance in flag leaves and panicles. The regulation mechanism of rice seedlings' cold tolerance is relatively clear, and knowledge of its underlying mechanisms at the reproductive stage is limited. We performed differential expression and co-expression network analyses to transcriptomes from panicle and flag leaf tissues of a cold-tolerant cultivar (Huaidao5), and a sensitive cultivar (Huaidao9), under reproductive-stage cold stress. The results revealed that the expression levels of genes in stress-related pathways such as MAPK signaling pathway, diterpenoid biosynthesis, glutathione metabolism, plant-pathogen interaction and plant hormone signal transduction were constitutively highly expressed in Huaidao5, especially in panicles. Moreover, the Hudaidao5's panicle sample-specific (under cold) module contained some genes related to rice yield, such as GW5L, GGC2, SG1 and CTPS1. However, the resistance of Huaidao9 was derived from the induced resistance to cold in flag leaves and panicles. In the flag leaves, the responses included a series of stress response and signal transduction, while in the panicles nitrogen metabolism was severely affected, especially 66 endosperm-specific genes. Through integrating differential expression with co-expression networks, we predicted 161 candidate genes (79 cold-responsive genes common to both cultivars and 82 cold-tolerance genes associated with differences in cold tolerance between cultivars) potentially affecting cold response/tolerance, among which 85 (52.80%) were known to be cold-related genes. Moreover, 52 (65.82%) cold-responsive genes (e.g., TIFY11C, LSK1 and LPA) could be confirmed by previous transcriptome studies and 72 (87.80%) cold-tolerance genes (e.g., APX5, OsFbox17 and OsSTA109) were located within QTLs associated with cold tolerance. This study provides an efficient strategy for further discovery of mechanisms of cold tolerance in rice.

QTL and Candidate Genes: Techniques and Advancement in Abiotic Stress Resistance Breeding of Major Cereals

At least 75% of the world's grain production comes from the three most important cereal crops: rice (Oryza sativa), wheat (Triticum aestivum), and maize (Zea mays). However, abiotic stressors such as heavy metal toxicity, salinity, low temperatures, and drought are all significant hazards to the growth and development of these grains. Quantitative trait locus (QTL) discovery and mapping have enhanced agricultural production and output by enabling plant breeders to better comprehend abiotic stress tolerance processes in cereals. Molecular markers and stable QTL are important for molecular breeding and candidate gene discovery, which may be utilized in transgenic or molecular introgression. Researchers can now study synteny between rice, maize, and wheat to gain a better understanding of the relationships between the QTL or genes that are important for a particular stress adaptation and phenotypic improvement in these cereals from analyzing reports on QTL and candidate genes. An overview of constitutive QTL, adaptive QTL, and significant stable multi-environment and multi-trait QTL is provided in this article as a solid framework for use and knowledge in genetic enhancement. Several QTL, such as DRO1 and Saltol, and other significant success cases are discussed in this review. We have highlighted techniques and advancements for abiotic stress tolerance breeding programs in cereals, the challenges encountered in introgressing beneficial QTL using traditional breeding techniques such as mutation breeding and marker-assisted selection (MAS), and the in roads made by new breeding methods such as genome-wide association studies (GWASs), the clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 system, and meta-QTL (MQTL) analysis. A combination of these conventional and modern breeding approaches can be used to apply the QTL and candidate gene information in genetic improvement of cereals against abiotic stresses.

Phenotypic and Molecular Characterization of Rice Genotypes’ Tolerance to Cold Stress at the Seedling Stage

Rice plants are affected by low-temperature stress during germination, vegetative growth, and reproductive stages. Thirty-nine rice genotypes including 36 near-isogenic lines (NILs) of BRRI dhan29 were evaluated to investigate the level of cold tolerance under artificially induced low temperature at the seedling stage. Three cold-related traits, leaf discolouration (LD), survivability, and recovery rate, were measured to determine the level of cold tolerance. Highly significant variation among the genotypes was observed for LD, survivability, and recovery rate. Three NILs, IR90688-74-1-1-1-1-1, IR90688-81-1-1-1-1-1, and IR90688-103-1-1-1-1-1, showed tolerance in all three traits, while IR90688-118-1-1-1-1-1 showed cold tolerance with LD and recovery rate. IR90688-92-1-1-1-1-1, IR90688-125-1-1-1-1-1, IR90688-104-1-1-1-1-1, IR90688-124-1-1-1-1-P2, IR90688-15-1-1-1-1-1, and IR90688-27-1-1-1-1-1 showed significantly higher yield coupled with short growth duration and good grain quality. Genetic analysis with SSRs markers revealed that the high-yielding NILs were genetically 67% similar to BRRI dhan28 and possessed cold tolerance at the seedling stage. These cold-tolerant NILs could be used as potential resources to broaden the genetic base of the breeding germplasm to develop high-yielding cold-tolerant rice varieties.

Mapping of QTLs for Yield Traits Using F2:3:4 Populations Derived From Two Alien Introgression Lines Reveals qTGW8.1 as a Consistent QTL for Grain Weight From Oryza nivara

Wild introgressions play a crucial role in crop improvement by transferring important novel alleles and broadening allelic diversity of cultivated germplasm. In this study, two stable backcross alien introgression lines 166s and 14s derived from Swarn/Oryza nivara IRGC81848 were used as parents to generate populations to map quantitative trait loci (QTLs) for yield-related traits. Field evaluation of yield-related traits in F₂, F₃, and F₄ population was carried out in normal irrigated conditions during the wet season of 2015 and dry seasons of 2016 and 2018, respectively. Plant height, tiller number, productive tiller number, total dry matter, and harvest index showed a highly significant association to single plant yield in F₂, F₃, and F₄. In all, 21, 30, and 17 QTLs were identified in F₂, F_2:3, and F_2:4, respectively, for yield-related traits. QTLs qPH6.1 with 12.54% phenotypic variance (PV) in F₂, qPH1.1 with 13.01% PV, qTN6.1 with 10.08% PV in F_2:3, and qTGW6.1 with 15.19% PV in F_2:4 were identified as major effect QTLs. QTLs qSPY4.1 and qSPY6.1 were detected for grain yield in F₂ and F_2:3 with PV 8.5 and 6.7%, respectively. The trait enhancing alleles of QTLs qSPY4.1, qSPY6.1, qPH1.1, qTGW6.1, qTGW8.1, qGN4.1, and qTDM5.1 were from O. nivara. QTLs of the yield contributing traits were found clustered in the same chromosomal region. qTGW8.1 was identified in a 2.6 Mb region between RM3480 and RM3452 in all three generations with PV 6.1 to 9.8%. This stable and consistent qTGW8.1 allele from O. nivara can be fine mapped for identification of causal genes. From this population, lines C₂12, C₂124, C₂128, and C₂143 were identified with significantly higher SPY and C₂103, C₂116, and C₂117 had consistently higher thousand-grain weight values than both the parents and Swarna across the generations and are useful in gene discovery for target traits and further crop improvement.

Chilling tolerance in rice: Past and present

Rice is generally sensitive to chilling stress, which seriously affects growth and yield. Since early in the last century, considerable efforts have been made to understand the physiological and molecular mechanisms underlying the response to chilling stress and improve rice chilling tolerance. Here, we review the research trends and advances in this field. The phenotypic and biochemical changes caused by cold stress and the physiological explanations are briefly summarized. Using published data from the past 20 years, we reviewed the past progress and important techniques in the identification of quantitative trait loci (QTL), novel genes, and cellular pathways involved in rice chilling tolerance. The advent of novel technologies has significantly advanced studies of cold tolerance, and the characterization of QTLs, key genes, and molecular modules have sped up molecular design breeding for cold tolerance in rice varieties. In addition to gene function studies based on overexpression or artificially generated mutants, elucidating natural allelic variation in specific backgrounds is emerging as a novel approach for the study of cold tolerance in rice, and the superior alleles identified using this approach can directly facilitate breeding.

Locating QTLs controlling overwintering seedling rate in perennial glutinous rice 89-1 (Oryza sativa 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.