Although we did not directly measure selection in this study, we used the large body of work on drought adaptation to infer the adaptive value of specific trait combinations. We predicted that due to the drought escape strategy conferred by derived loss of function mutations at FRI, accessions with these alleles would inhabit environments with consistently wetter growing seasons, relative to accessions with functional FRI alleles. To confirm the allelic association with drought, we generated a climate envelope for both FRI allele classes . Functional alleles tend to be present in areas with lower growing season precipitation than non-functional alleles. We have demonstrated that lines that diverged only at FRI exhibit altered positions along an adaptive phenotypic correlation. Scarcelli et al. found antagonism between the floral morphology traits affected by FRI, and we cannot rule out that a portion of FRI’s pleiotropic gene action is maladaptive. However, analyses presented here demonstrate a strong adaptive role of the physiological and phenological phenotypic correlations conferred by FRI. Given our results, it is not surprising that FRI is associated with strong population genetic signatures of diversifying selection. Studies demonstrating historical selection on FRI invoke the timing of flowering as the phenotype under selection. Our results indicate that the observed signature of selection is not only an effect of FT variation, but may also be due to upstream physiological effects.Stress caused by salinity is one of the most serious environmental factors, which inhibits plant growth and decreases crop productivity worldwide. Primary effects occurring at the beginning of salt stress include retarded cell division and expansion, stomata closure and photosynthesis reduction. During long-term exposure to salt stress, accumulation of salt ions in plant aerial parts via the transpiration stream leads to ionic stress. To adaptively respond and survive under salinity, plants require changes of various cellular, physiological and metabolic mechanisms, which are controlled by the regulated expression of specific stress-related genes through cascades of complex regulatory networks. Rice , one of the world’s most important cereal crops, is classified as a salinity sensitive crop. An electrical conductivity of ~ 6 dS m− 1 would result in more than 50% reduction in yield of many rice varieties. Therefore, plant breeders are continuously improving salt tolerant rice cultivars to increase yield productivity. However, salt tolerance is a multi-genic trait, which underlying mechanisms are controlled by many genes and affected by the environment. Breeding efforts for developing salt tolerant rice have been limited because the salt tolerance mechanisms and the genes that control them are not completely understood.
To fill the knowledge gap between genotypes and phenotypes of the salt stress response in rice,vertical planters for vegetables forward and reverse genetics have been performed to identify salt-responsive loci/genes such as genetic mapping of quantitative trait loci using cross population; screening of mutants generated by chemical- or irradiation-induced mutagenesis; and transgenic approach. To identify salt-responsive genes using cross population, a number of mapping studies have identified QTLs of physiological traits related to salinity tolerance in economic crops such as soybean, barley and rice. Although QTL mapping is a powerful and popular method to tag the salt tolerance region in plants, the examination of the variation is one of the limitation because QTL mapping can identify only allelic diversity that segregates between the parents of a particular F2 cross or within recombinant inbred lines and the mapping resolution is limited by the amount of the genetic recombination event occurring in the mapping populations. Moreover, the genotyping by SSR markers, which is usually based on polymerase chain reaction , is limiting to examining the kinds of variations, and laborious and time-consuming when high-density genotyping is needed for a large number of individuals. Over the past several years, next generation sequencing has been used to rapidly generate a large amount of accurate genomic data, providing a powerful approach for functional genomics and molecular breeding studies, including the genome-wide association study. GWAS, which is the analysis of the statistical association between genetic variants and traits on the whole genome scale in a large number of individuals within an organism, has been employed to identify causal genetic variability for target traits, including those in Arabidopsis and crop species. Compared with the QTL linkage mapping method, GWAS provides high resolution mapping using single nucleotide polymorphisms as genetic markers. GWAS in rice was performed for agronomic traits such as tiller number, grain width, grain length and spikelet number in the indica subspecies based on SNPs identified by whole-genome sequencing. In another report, the genetic architecture of rice chlorophyll content at the heading stage was revealed by GWAS.
Forty-six significant loci were identified and Ghd7 was highlighted as a major locus for the natural variation of the chlorophyll content. GWAS also revealed three QTLs located on chromosomes 3, 6 and 12 associated with the responsiveness of yield-determination traits under field condition. Application of GWAS for causative gene identification has been reported in rice responding to abiotic stresses such as aluminum, boron, cold, drought and salt stresses. On salt stress, there are several GWA studies in rice with different growing stages and traits. Shi et al.studies GWAS on germination stage of salt-treated rice using ~ 6000,000 SNPs, 11 loci containing 22 significant SNPs responsible for stress-susceptibility indices of the vigor index and germination time were identified. The strongest association region for germination time was detected on chromosome 1, near salt-tolerance QTL controlling Na+ uptake and K+ concentration. At tillering stage, GWAS was performed on rice exposed to short- , medium- and longterm salt stress based on ~ 200,000 SNPs. Around 1200 candidate genes associated with growth parameters, and Na+ and K+ content were identified.For salt treated rice at reproductive stage, only a study of Kumar et al. were reported. Based on 6000 SNPs, it was shown that 20 loci were associated with the Na+ /K+ ratio, and 44 loci were associated with other traits. Twelve association mappings with Na+ /K+ were located on chromosome 1 where Saltol, a major QTL that controls shoot Na+ /K+ homeostasis in rice at the seedling stage, is located. However, GWAS has not been applied for the analysis of photosynthetic and yield-related traits in rice exposed to salt stress at the flowering stage, which is a highly salt-sensitive stage. Additionally, no rice accession from Thailand where a large collection of diverse rice germplasms can provide new allelic diversity for salt tolerance, were analyzed by GWAS. The objectives of this research were to investigate and cluster Thai and Asian rice accessions based on physiological responses and yield-related traits under the salt-stress condition at the flowering stage and to perform GWAS for these traits to identify regions/genes responsible for salt tolerance.
The association panel consisted of a diverse collection of 190 rice cultivars including both standard salt-tolerant and salt-sensitive varieties. The rice accessions in this study were kindly provided by the Pathum Thani Rice Research Center . The experiment was designed with a randomized complete block design with four replications. According to the limitation of the time-consuming process of data collection, the experiment was performed in three separate sets of experiments. The standard salt tolerant and salt-sensitive cultivars were included in every experimental set. Twenty-one day old seedlings were cultivated using a hydroponic system with WP No. 2 nutrient solution and transplanted into pots containing soil and maintained until harvest. At heading stage in the flowering phase of each accession, water on the soil surface was drained before salt stress treatment. Rice plants were then watered with 900 mL of 150 mM NaCl solution to reach the desired final soil electrical conductivity of 8–9 dS m− 1 and treated for 9 days. For the control condition, rice plants were treated by tap water for the same period. To recover,vertical farming technology tap water was used to wash out salt ions in the soil every day until the soil EC was lower than 2 dS m− 1 ; this condition was maintained until harvest to collect yield-related traits. These experiments were conducted in the greenhouse facility at the Nakhon Ratchasima Rice Research Center, Rice Department, Ministry of Agriculture and Cooperatives. The air temperature was maximum at 32 °C with natural light and minimum at 21.1 °C during the night.
The average relative humidity was 72.5%. The short-sequence reads from the Illumina Genome Analyzer were grouped into the correct categories using the pipeline created by Missirian et al.. The rice reference genome was downloaded from the database , and indexed by SAMtools. Raw reads were aligned against the reference genome using the Burrow-Wheeler Aligner. Variants were called using genome analysis toolkit. Variants were filtered if they fitted the following criteria: to be called heterozygous, minimum coverage and minimum percentage of each of the two observed major base calls were 5 and 20, respectively and minimum total coverage was 10; for a position to be called homozygous, minimum coverage was 6 or 3 if positions with the minimum coverage of 6 were present in at least 10 accessions. SNP density was visualized using R ‘CMplot’ .We evaluated photosynthetic parameters and cell membrane stability on 104 rice accessions individually at the flowering stage after salt stress for 3, 6 and 9 days and analyzed yield-related traits at harvesting time. The mean values and frequency distributions of all parameters of each accession are shown in Additional file 2: Table S2 and Additional file 3: Figure S1. The highest reduction of phenotypic traits was observed at day 9 after salt stress: photosynthetic rate, PN ; stomatal conductance, gs ; transpiration rate, E , and cell membrane stability, CMS when compared with the control condition . However, we found that the mean values of intercellular CO2 concentration, Ci increased about 6% at day 9 after salt stress treatment. For yield-related traits, on average, number of tillers per plant, TIL; number of panicles per plant, PAN; number of filled grains per plant, FG decreased by 19, 11 and 26%, respectively, whereas number of unfilled grains per plant, UFG increased by 10% . To determine substantial genotypic variation in salt-stress responses, relative phenotypic values were calculated by the salt stability index of each rice accession [ × 100] . These parameters tended to decrease when plants were exposed to salt stress, except Ci , which tended to increase under salt stress. The variations of phenotypic traits were found in all parameters and were pronounced, particularly in the case of PN, FG and UFG . The relationships of the salt stability index of all parameters were determined by Pearson’s correlation r . We found a strong positive correlation between PN and gs, or E . PN also had a positive correlation with CMS, though weaker, at days 6 and 9 after salt treatment. Conversely, a strong negative correlation between PN and Ci was found. As expected for yield-related traits, the strongest positive correlation was observed between TIL, PAN and UFG. In addition, the relationship between photosynthetic performance and yield-related traits were observed. TIL was negatively correlated with gs at days 3 and 6; and with E at day 3. Similarly, PAN was negatively correlated with gs at day 3 as well as PN. Following the same trend, UFG was negatively correlated with gs or E at days 3 after salt treatment, and with Ci both at days 3 and 6. . In an opposite trend, a positive correlation was found between FG and gs at day 6. At day 9, no correlation was observed between photosynthetic parameters and yield-related traits.The list of rice accessions used for exome sequencing is shown in Additional file 1: Table S1. In total, 190 rice accessions were used for exome-sequencing, with the capture probes designed to cover about 50 Mb of the nucleotide target covering all 12 chromosomes of rice. SNPs that showed a minor allele frequency of < 5% of our population were removed to decrease overestimation of the effect of low-MAF SNPs. Therefore, the resultant number of 112,565 SNPs , which were high-quality SNPs genotyped across this population, was subsequently used for GWAS.EINGENSOFT was implemented for population structure analysis, which was based on PCA. Using SNPs identified by exome sequencing, two main sub-populations were delineated , consisting of five accessions in the first group and 185 accessions in the second group, respectively. The rice accessions in the first group included ‘Ai Tai’, ‘Jao Haw’, ‘Beu Saw Mi’, ‘E-Puang’ and ‘Leung Tah Young’ rice, which were grouped as upland rice .