Combined, the strong signature of selection, high levels of population structure and lack of within-population variation observed at FRI suggests an adaptive role of this pleiotropy.Previous studies have found that the early flowering, low WUE phenotypes associated with drought escape are adaptive in sites without consistent low soil moisture. 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 corre lation. 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,strawberry grow pots but may also be due to upstream physiological effects.In order to reveal the evolution of StnA, the phylogenetic tree of StnA and these homologues structures was constructed and shown in Fig. 10.

The results show that StnA is clustered in a distinct clade and is closest to succinate hydrolase from Mesorhizobium loti 22 and human mono-glyceride lipase 23. The binding pockets of both 3KXP and 3JWE are located between the interfaces of α/β hydrolase domain and cap domain. 3JWE is a membrane-interacting protein and its inhibitor binding site is located between the two domains. However the binding pocket in StnA is mainly composed of the cap domain, with only the catalytic triad and oxyanion hole are from the α/β fold domain . As a broad type of α/β-fold hydrolases, lipolytic enzymes can hydrolyze water-insoluble ester substrates at binding pockets near the water/lipid interface. The active sites of most lipolytic enzymes are buried under secondary structure elements, including a narrow tunnel, or a flap as a flexible lid for the entrance of the substrate and the release of the product16. An eukaryotic thioesterase 24 has a bend tunnel formed by two domains as entry and exit routes for the substrate and product. Another human lipase 25 has a movable lid, formed by α4 and part of the loop connecting to α5, which acts as a highly dynamic open and close conformations during ligand binding and release. The cap domain may participate in the process of product release. However, StnA is significantly different from the lipolytic enzymes without open and close conformations or long tunnel. Based on the analysis of sequence, structure, and phylogenetic tree, we propose that StnA be classified as a new subfamily of lipolytic enzymes.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 re quire 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 multigenic trait, which underlying mechanisms are con trolled 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, 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,rolling bench 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 map ping can identify only allelic diversity that segregates be tween 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 long term 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 chromo some 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 .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. Water level was kept at 2 cm above the soil surface throughout the experimental period. To recover, 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%.Salt-tolerance of rice is a dynamic trait affected by grow ing stage and genotype. This study is the first large-scale tolerance evaluation and GWAS focusing on salt stress at the reproductive stage of rice. In this study, we applied salt stress to flowering rice and evaluated five parameters of photosynthetic performance , cell membrane stability, CMS and four parameters of yield-related traits . On average, the stability indices of photosynthesis performance and CMS decreased under salt stress, while increases of Ci were found, which were similar to the yield parameter, UFG . For PN, E and gs, these findings agreed with previous studies describing salt-induced photosyn thesis reduction in rice seedlings. Consistently, during the reproductive stage, Moradi and Ismail found that PN, E and gs were inhibited in the flag leaf under salinity. Additionally, the salt-sensitive rice cultivar IR29 displayed higher Ci than others when exposed to salt stress during both seedling and reproductive stages. As indicated by Burghardt et al., GWAS would have power to discover genes affecting the trait of interest in large of phenotypic variation greater than small of phenotypic variation. In this study, large variation was observed in PN in photosynthesis performance; and PAN, FG and UFG in yield-related traits under salt stress . Correspondingly we found high detection power of association mapping in these parameters, whereas GWAS for the other parameters that exhibited lower variation was not successful .Using efficient, high precision exome capture and sequencing, we have identified 112,565 SNPs. Previous studies used SNP array to identify SNP markers for GWAS in rice and yielded fewer SNP markers when compared with our study. The present study, however, focused on exonic regions, which are specific sequences in the genome while accounting for only one-sixth of the rice genome, resulted in more than 100,000 SNPs. Although several statistically robust models have been developed for GWAS, population structure can limit its effectiveness.