Genome-Wide Association Study for Plant Height and Grain Yield in Rice under Contrasting Moisture Regimes

Genome-Wide Association Study of Rice Diversity Panel Reveals New QTLs for Tolerance to Water Deficit Under the Egyptian Conditions

Drought has a significant impact on rice yield by restricting the crop's ability to grow and develop. Producing rice cultivars adapted to water deficit conditions is still the main interest of rice breeders and geneticists. To address this challenge, a set of 413 highly diverse rice populations were evaluated under normal and water deficit conditions for two growing seasons of 2021 and 2022. High genetic variation was found among genotypes for all studied traits. The heritability estimates ranged from 0.82 (panicle length) to 0.95 (plant height). Sterility percentage (SET%) was the most trait affected by water deficit in two growing seasons. 22 Rice genotypes were classified as drought tolerant in both years. Genome-wide association mapping was performed for all traits in the two growing seasons under both conditions using a total of 700,000 SNPs. The GWAS results revealed important and major SNPs associated with all traits. 26 Significant SNPs with stable allele effects were found to be associated with yield traits under water deficit conditions in both years. The results of this study provided rice genotypes that can be adapted under water deficit conditions and important stable SNP markers that can be used for marker-assisted selection after validation in different genetic backgrounds.

Genome-wide association study of drought tolerance in wheat (Triticum aestivum L.) identifies SNP markers and candidate genes

Drought stress poses a severe threat to global wheat production, necessitating an in-depth exploration of the genetic basis for drought tolerance associated traits. This study employed a 90 K SNP array to conduct a genome-wide association analysis, unravelling genetic determinants of key traits related to drought tolerance in wheat, namely plant height, root length, and root and shoot dry weight. Using the mixed linear model (MLM) method on 125 wheat accessions subjected to both well-watered and drought stress treatments, we identified 53 SNPs significantly associated with stress susceptibility (SSI) and tolerance indices (STI) for the targeted traits. Notably, chromosomes 2A and 3B stood out with ten and nine associated markers, respectively. Across 17 chromosomes, 44 unique candidate genes were pinpointed, predominantly located on the distal ends of 1A, 1B, 1D, 2A, 3A, 3B, 4A, 6A, 6B, 7A, 7B, and 7D chromosomes. These genes, implicated in diverse functions related to plant growth, development, and stress responses, offer a rich resource for future investigation. A clustering pattern emerged, notably with seven genes associated with SSI for plant height and four genes linked to both STI of plant height and shoot dry weight, converging on specific regions of chromosome arms of 2AS and 3BL. Additionally, shared genes encoding polygalacturonase, auxilin-related protein 1, peptide deformylase, and receptor-like kinase underscored the interconnectedness between plant height and shoot dry weight. In conclusion, our findings provide insights into the molecular mechanisms governing wheat drought tolerance, identifying promising genomic loci for further exploration and crop improvement strategies.

Uncovering the Genomic Regions Associated with Yield Maintenance in Rice Under Drought Stress Using an Integrated Meta-Analysis Approach

The complex trait of yield is controlled by several quantitative trait loci (QTLs). Given the global water deficit issue, the development of rice varieties suitable for non-flooded cultivation holds significant importance in breeding programs. The powerful approach of Meta-QTL (MQTL) analysis can be used for the genetic dissection of complicated quantitative traits. In the current study, a comprehensive MQTL analysis was conducted to identify consistent QTL regions associated with drought tolerance and yield-related traits under water deficit conditions in rice. In total, 1087 QTLs from 134 rice populations, published between 2000 to 2021, were utilized in the analysis. Distinct MQTL analysis of the relevant traits resulted in the identification of 213 stable MQTLs. The confidence interval (CI) for the detected MQTLs was between 0.12 and 19.7 cM. The average CI of the identified MQTLs (4.68 cM) was 2.74 times narrower compared to the average CI of the initial QTLs. Interestingly, 63 MQTLs coincided with SNP peak positions detected by genome-wide association studies for yield and drought tolerance-associated traits under water deficit conditions in rice. Considering the genes located both in the QTL-overview peaks and the SNP peak positions, 19 novel candidate genes were introduced, which are associated with drought response index, plant height, panicle number, biomass, and grain yield. Moreover, an inclusive MQTL analysis was performed on all the traits to obtain "Breeding MQTLs". This analysis resulted in the identification of 96 MQTLs with a CI ranging from 0.01 to 9.0 cM. The mean CI of the obtained MQTLs (2.33 cM) was 4.66 times less than the mean CI of the original QTLs. Thirteen MQTLs fulfilling the criteria of having more than 10 initial QTLs, CI < 1 cM, and an average phenotypic variance explained greater than 10%, were designated as "Breeding MQTLs". These findings hold promise for assisting breeders in enhancing rice yield under drought stress conditions.

Coordination of growth and drought responses by GA-ABA signaling in rice

The drought caused by global warming seriously affects the crop growth and agricultural production. Plants have evolved distinct strategies to cope with the drought environment. Under drought stress, energy and resources should be diverted from growth toward stress management. However, the molecular mechanism underlying coordination of growth and drought response remains largely elusive. Here, we discovered that most of the gibberellin (GA) metabolic genes were regulated by water scarcity in rice, leading to the lower GA contents and hence inhibited plant growth. Low GA contents resulted in the accumulation of more GA signaling negative regulator SLENDER RICE 1, which inhibited the degradation of abscisic acid (ABA) receptor PYL10 by competitively binding to the co-activator of anaphase-promoting complex TAD1, resulting in the enhanced ABA response and drought tolerance. These results elucidate the synergistic regulation of crop growth inhibition and promotion of drought tolerance and survival, and provide useful genetic resource in breeding improvement of crop drought resistance.

Data-driven approaches to improve water-use efficiency and drought resistance in crop plants

With the increasing population, there lies a pressing demand for food, feed and fibre, while the changing climatic conditions pose severe challenges for agricultural production worldwide. Water is the lifeline for crop production; thus, enhancing crop water-use efficiency (WUE) and improving drought resistance in crop varieties are crucial for overcoming these challenges. Genetically-driven improvements in yield, WUE and drought tolerance traits can buffer the worst effects of climate change on crop production in dry areas. While traditional crop breeding approaches have delivered impressive results in increasing yield, the methods remain time-consuming and are often limited by the existing allelic variation present in the germplasm. Significant advances in breeding and high-throughput omics technologies in parallel with smart agriculture practices have created avenues to dramatically speed up the process of trait improvement by leveraging the vast volumes of genomic and phenotypic data. For example, individual genome and pan-genome assemblies, along with transcriptomic, metabolomic and proteomic data from germplasm collections, characterised at phenotypic levels, could be utilised to identify marker-trait associations and superior haplotypes for crop genetic improvement. In addition, these omics approaches enable the identification of genes involved in pathways leading to the expression of a trait, thereby providing an understanding of the genetic, physiological and biochemical basis of trait variation. These data-driven gene discoveries and validation approaches are essential for crop improvement pipelines, including genomic breeding, speed breeding and gene editing. Herein, we provide an overview of prospects presented using big data-driven approaches (including artificial intelligence and machine learning) to harness new genetic gains for breeding programs and develop drought-tolerant crop varieties with favourable WUE and high-yield potential traits.

QTL mapping and analysis for drought tolerance in rice by genome-wide association study

Rice drought resistance is a complicated quantitative feature involving a range of biological and agronomic variables, but little is known about the underlying genetics and regulatory mechanisms that regulate drought tolerance. This study used 120 recombinant inbred lines (RILs), derived from a cross between drought tolerant Lvhan 1 and susceptible Aixian 1. The RILs were subjected to drought stress at the first ear stage, and phenotypic data of 16 agronomic and physiological traits under varying conditions were investigated. Genome-wide association study (GWAS) on the drought resistance index of traits was carried out. A total of 9 quantitative trait loci (QTLs) associated with drought-related traits were identified on chromosomes 2, 6, 7, 8, 9, and 10, which includes QTLs for plant height (PH) qPH10.1, effective panicles number (EPN) qEPN6.1, panicle length (PL) qPL9.1, thousand-grain weight (TGW) qTGW2.1, qTGW6.1, qTGW8.1, leaf length (LL) qLL7.1, leaf width (LW) qLW7.1, and leaf area (LA) qLA7.1. The fraction of phenotypic variation explained by individual QTL varied from 10.6% to 13.9%. Except for days to flowering (DTF), the mean values of all traits under normal water management conditions were considerably higher than those under drought conditions. Except for the DTF, the drought resistance index of all rice traits was less than 1, indicating that drought treatment reduced the EPN, FGPP, SSR, PH, and LA, which affected the growth and development of rice. The drought resistance index of DTF was 1.02, indicating that drought prolonged the heading time of rice and diminish the yield parameters. Along with identifying QTLs, the results also predicted ten candidate genes, which are directly or indirectly involved in various metabolic functioning related to drought stress. The identification of these genomic sites or QTLs that effectively respond to water scarcity will aid in the quest of understanding the drought tolerance mechanisms. This study will facilitate the marker-assisted rice breeding and handy in the breeding of drought-tolerant rice varieties.

Genome-Wide Association Study Identifies a Plant-Height-Associated Gene OsPG3 in a Population of Commercial Rice Varieties

Plant height is one of the most crucial components of plant structure. However, due to its complexity, the genetic architecture of rice plant height has not been fully elucidated. In this study, we performed a genome-wide association study (GWAS) to determine rice plant height using 178 commercial rice varieties and identified 37 loci associated with rice plant height (LAPH). Among these loci, in LAPH2, we identified a polygalacturonase gene, OsPG3, which was genetically and functionally associated with rice plant height. The rice plant exhibits a super dwarf phenotype when the knockout of the OsPG3 gene occurs via CRISPR-Cas9 gene-editing technology. RNA-Seq analysis indicated that OsPG3 modulates the expression of genes involved in phytohormone metabolism and cell-wall-biosynthesis pathways. Our findings suggest that OsPG3 plays a vital role in controlling rice plant height by regulating cell wall biosynthesis. Given that rice architecture is one of the most critical phenotypes in rice breeding, OsPG3 has potential in rice's molecular design breeding toward an ideal plant height.

Novel Salinity-Tolerant Third-Generation Hybrid Rice Developed via CRISPR/Cas9-Mediated Gene Editing

Climate change has caused high salinity in many fields, particularly in the mud flats in coastal regions. The resulting salinity has become one of the most significant abiotic stresses affecting the world's rice crop productivity. Developing elite cultivars with novel salinity-tolerance traits is regarded as the most cost-effective and environmentally friendly approach for utilizing saline-alkali land. To develop a highly efficient green strategy and create novel rice germplasms for salt-tolerant rice breeding, this study aimed to improve rice salinity tolerance by combining targeted CRISPR/Cas9-mediated editing of the OsRR22 gene with heterosis utilization. The novel alleles of the genic male-sterility (GMS) and elite restorer line (733S^rr22-T1447-1 and HZ^rr22-T1349-3) produced 110 and 1 bp deletions at the third exon of OsRR22 and conferred a high level of salinity tolerance. Homozygous transgene-free progeny were identified via segregation in the T2 generation, with osrr22 showing similar agronomic performance to wild-type (733S and HZ). Furthermore, these two osrr22 lines were used to develop a new promising third-generation hybrid rice line with novel salinity tolerance. Overall, the results demonstrate that combining CRISPR/Cas9 targeted gene editing with the "third-generation hybrid rice system" approach allows for the efficient development of novel hybrid rice varieties that exhibit a high level of salinity tolerance, thereby ensuring improved cultivar stability and enhanced rice productivity.

Combined genome-wide association study and epistasis analysis reveal multifaceted genetic architectures of plant height in Asian cultivated rice

Plant height (PH) in rice (Oryza sativa) is an important trait for its adaptation and agricultural performance. Discovery of the semi-dwarf1 (SD1) mutation initiated the Green Revolution, boosting rice yield and fitness, but the underlying genetic regulation of PH in rice remains largely unknown. Here, we performed genome-wide association study (GWAS) and identified 12 non-repetitive QTL/genes regulating PH variation in 619 Asian cultivated rice accessions. One of these was an SD1 structural variant, not normally detected in standard GWAS analyses. Given the strong effect of SD1 on PH, we also divided 619 accessions into subgroups harbouring distinct SD1 haplotypes, and found a further 85 QTL/genes for PH, revealing genetic heterogeneity that may be missed by analysing a broad, diverse population. Moreover, we uncovered two epistatic interaction networks of PH-associated QTL/genes in the japonica (Geng)-dominant SD1^NIP subgroup. In one of them, the hub QTL/gene qphSN1.4/GAMYB interacted with qphSN3.1/OsINO80, qphSN3.4/HD16/EL1, qphSN6.2/LOC_Os06g11130, and qphSN10.2/MADS56. Sequence variations in GAMYB and MADS56 were associated with their expression levels and PH variations, and MADS56 was shown to physically interact with MADS57 to coregulate expression of gibberellin (GA) metabolic genes OsGA2ox3 and Elongated Uppermost Internode1 (EUI1). Our study uncovered the multifaceted genetic architectures of rice PH, and provided novel and abundant genetic resources for breeding semi-dwarf rice and new candidates for further mechanistic studies on regulation of PH in rice.

GWAS analysis to elucidate genetic composition underlying a photoperiod-insensitive rice population, North Korea

Heading date (Hd) is one of the main factors determining rice production and regional adaptation. To identify the genetic factors involved in the wide regional adaptability of rice, we conducted a genome-wide association study (GWAS) with 190 North Korean rice accessions selected for non-precocious flowering in the Philippines, a low-latitude region. Using both linear mixed models (LMM) and fixed and random model circulating probability unification (FarmCPU), we identified five significant loci for Hd in trials in 2018 and 2019. Among the five lead single nucleotide polymorphisms (SNPs), three were located adjacent to the known Hd genes, Heading date 3a (Hd3a), Heading date 5 (Hd5), and GF14-c. In contrast, three SNPs were located in novel loci with minor effects on heading. Further GWAS analysis for photoperiod insensitivity (PS) revealed no significant genes associated with PS, supporting that this North Korean (NK) population is largely photoperiod-insensitive. Haplotyping analysis showed that more than 80% of the NK varieties harbored nonfunctional alleles of major Hd genes investigated, of which a nonfunctional allele of Heading date 1 (Hd1) was observed in 66% of the varieties. Geographical distribution analysis of Hd allele combination types showed that nonfunctional alleles of floral repressor Hd genes enabled rice cultivation in high-latitude regions. In contrast, Hd1 alleles largely contributed to the wide regional adaptation of rice varieties. In conclusion, an allelic combination of Hd genes is critical for rice cultivation across wide areas.

Natural variation of Alfin-like family affects seed size and drought tolerance in rice

The Alfin-like (AL) family is a group of small plant-specific transcriptional factors involved in abiotic stresses in dicotyledon. In an early study, we found an AL gene in rice that was associated with grain yield under drought stress. However, little information is known about the AL family in rice. In this study, AL genes in the rice genome were identified, and the OsAL proteins were found to locate in the nucleus and have no transcriptional self-activation activity. The expression of the OsALs was regulated by different environmental stimulations and plant hormones. Association and domestication analysis revealed that natural variation of most OsALs was significantly associated with yield traits, drought resistance and divergence in grain size in indica and japonica rice varieties. Hap1 of OsAL7.1 and Hap7 of OsAL11 were favorable haplotypes of seed weight and germination under osmotic stress. Furthermore, osal7.1 and osal11 mutants have larger seeds and are more sensitive to abscisic acid and mannitol during germination stage. Overexpressing of OsAL7.1 and OsAL11 in rice weakened the tolerance to drought in the adult stage. Thus, our work provides informative knowledge for exploring and harnessing haplotype diversity of OsALs to improve yield stability under drought stress.

CRISPR/Cas-mediated editing of cis-regulatory elements for crop improvement

To improve future agricultural production, major technological advances are required to increase crop production and yield. Targeting the coding region of genes via the Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated Protein (CRISPR/Cas) system has been well established and has enabled the rapid generation of transgene-free plants, which can lead to crop improvement. The emergence of the CRISPR/Cas system has also enabled scientists to achieve cis-regulatory element (CRE) editing and, consequently, engineering endogenous critical CREs to modulate the expression of target genes. Recent genome-wide association studies have identified the domestication of natural CRE variants to regulate complex agronomic quantitative traits and have allowed for their engineering via the CRISPR/Cas system. Although engineering plant CREs can be advantageous to drive gene expression, there are still many limitations to its practical application. Here, we review the current progress in CRE editing and propose future strategies to effectively target CREs for transcriptional regulation for crop improvement.

Biotechnological Advances to Improve Abiotic Stress Tolerance in Crops

The major challenges that agriculture is facing in the twenty-first century are increasing droughts, water scarcity, flooding, poorer soils, and extreme temperatures due to climate change. However, most crops are not tolerant to extreme climatic environments. The aim in the near future, in a world with hunger and an increasing population, is to breed and/or engineer crops to tolerate abiotic stress with a higher yield. Some crop varieties display a certain degree of tolerance, which has been exploited by plant breeders to develop varieties that thrive under stress conditions. Moreover, a long list of genes involved in abiotic stress tolerance have been identified and characterized by molecular techniques and overexpressed individually in plant transformation experiments. Nevertheless, stress tolerance phenotypes are polygenetic traits, which current genomic tools are dissecting to exploit their use by accelerating genetic introgression using molecular markers or site-directed mutagenesis such as CRISPR-Cas9. In this review, we describe plant mechanisms to sense and tolerate adverse climate conditions and examine and discuss classic and new molecular tools to select and improve abiotic stress tolerance in major crops.

Linkage mapping and association analysis to identify a reliable QTL for stigma exsertion rate in rice

The commercialization of hybrid rice has greatly contributed to the increase in rice yield, with the improvement of its seed production capacity having played an important role. The stigma exsertion rate (SER) is a key factor for improving the outcrossing of the sterile line and the hybrid rice seed production. We used the Zhenshan 97B × IRAT109 recombinant inbred population comprising 163 lines and a natural population of 138 accessions to decipher the genetic foundation of SER over 2 years in three environments. Additionally, we detected eight QTLs for SER on chromosomes 1, 2, and 8 via linkage mapping. We also identified seven and 19 significant associations for SER using genome-wide association study in 2016 and 2017, respectively. Interestingly, we located two lead SNPs (sf0803343504 and sf083344610) on chromosome 8 in the qTSE8 QTL region that were significantly associated with total SER. After transcriptomic analysis, quantitative real-time PCR, and haplotype analysis, we found 13 genes within this reliable region as important candidate genes. Our study results will be beneficial to molecular marker-assisted selection of rice lines with high outcrossing rate, thereby improving the efficiency of hybrid seed production.

Genetic Diversity and Selection Signatures in Synthetic-Derived Wheats and Modern Spring Wheat

Synthetic hexaploid wheats and their derived advanced lines were subject to empirical selection in developing genetically superior cultivars. To investigate genetic diversity, patterns of nucleotide diversity, population structure, and selection signatures during wheat breeding, we tested 422 wheat accessions, including 145 synthetic-derived wheats, 128 spring wheat cultivars, and 149 advanced breeding lines from Pakistan. A total of 18,589 high-quality GBS-SNPs were identified that were distributed across the A (40%), B (49%), and D (11%) genomes. Values of population diversity parameters were estimated across chromosomes and genomes. Genome-wide average values of genetic diversity and polymorphic information content were estimated to be 0.30 and 0.25, respectively. Neighbor-joining (NJ) tree, principal component analysis (PCA), and kinship analyses revealed that synthetic-derived wheats and advanced breeding lines were genetically diverse. The 422 accessions were not separated into distinct groups by NJ analysis and confirmed using the PCA. This conclusion was validated with both relative kinship and Rogers' genetic distance analyses. EigenGWAS analysis revealed that 32 unique genome regions had undergone selection. We found that 50% of the selected regions were located in the B-genome, 29% in the D-genome, and 21% in the A-genome. Previously known functional genes or QTL were found within the selection regions associated with phenology-related traits such as vernalization, adaptability, disease resistance, and yield-related traits. The selection signatures identified in the present investigation will be useful for understanding the targets of modern wheat breeding in Pakistan.

Autophagy and Programmed Cell Death Are Critical Pathways in Jasmonic Acid Mediated Saline Stress Tolerance in Oryza sativa

Saline stress is the most limiting condition impacting the plant growth, development, and productivity. In this present study, jasmonic acid (JA) was used as a foliar spray on the rice seedlings grown under saline stress. Increase in photosynthetic pigments, anthocyanin, and total protein content was observed with JA treatment while NaCl showed reduction in biochemical constituents and enhanced antioxidant enzyme activity. The leaf cells of NaCl-treated seedlings accumulated more ROS and had more fragmented nuclei, whereas JA decreased the accumulation and fragmentation during saline stress. In NaCl treatment, gene expression analysis showed many fold upregulation in comparison with other treatments. The results suggest that JA acts as a promoter for growth, physiological, biochemical, and cellular contents, as well as ameliorate the effects of saline stress. The expression of genes demonstrated that saline stress may promote autophagy, which leads to autophagic cell death, and improve tolerance to saline stress in rice seedlings via the jasmonic acid signaling pathway. However, the mechanism by which jasmonate signaling induces autophagy and cell death is unknown and requires further exploration.

Combined GWAS and Transcriptome Analyses Provide New Insights Into the Response Mechanisms of Sunflower Against Drought Stress

Sunflower is one of the most important oil crops in the world, and drought stress can severely limit its production and quality. To understand the underlying mechanism of drought tolerance, and identify candidate genes for drought tolerance breeding, we conducted a combined genome-wide association studies (GWAS) and RNA-seq analysis. A total of 226 sunflower inbred lines were collected from different regions of China and other countries. Eight phenotypic traits were evaluated under control and drought stress conditions. Genotyping was performed using a Specific-Locus Amplified Fragment Sequencing (SLAF-seq) approach. A total of 934.08 M paired-end reads were generated, with an average Q30 of 91.97%. Based on the 243,291 polymorphic SLAF tags, a total of 94,162 high-quality SNPs were identified. Subsequent analysis of linkage disequilibrium (LD) and population structure in the 226 accessions was carried out based on the 94,162 high-quality SNPs. The average LD decay across the genome was 20 kb. Admixture analysis indicated that the entire population most likely originated from 11 ancestors. GWAS was performed using three methods (MLM, FarmCPU, and BLINK) simultaneously. A total of 80 SNPs showed significant associations with the 8 traits (p < 1.062 × 10-6). Next, a total of 118 candidate genes were found. To obtain more reliable candidate genes, RNA-seq analysis was subsequently performed. An inbred line with the highest drought tolerance was selected according to phenotypic traits. RNA was extracted from leaves at 0, 7, and 14 days of drought treatment. A total of 18,922 differentially expressed genes were obtained. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed up-regulated genes were mainly enriched in the branched-chain amino acid catabolic process, while the down-regulated genes were mainly enriched in the photosynthesis-related process. Six DEGs were randomly selected from all DEGs for validation; these genes showed similar patterns in RNA-seq and RT-qPCR analysis, with a correlation coefficient of 0.8167. Through the integration of the genome-wide association study and the RNA-sequencing, 14 candidate genes were identified. Four of them (LOC110885273, LOC110872899, LOC110891369, LOC110920644) were abscisic acid related protein kinases and transcription factors. These genes may play an important role in sunflower drought response and will be used for further study. Our findings provide new insights into the response mechanisms of sunflowers against drought stress and contribute to further genetic breeding.

Whole-Genome Sequencing and RNA-Seq Reveal Differences in Genetic Mechanism for Flowering Response between Weedy Rice and Cultivated Rice

Flowering is a key agronomic trait that influences adaptation and productivity. Previous studies have indicated the genetic complexity associated with the flowering response in a photoinsensitive weedy rice accession PSRR-1 despite the presence of a photosensitive allele of a key flowering gene Hd1. In this study, we used whole-genome and RNA sequencing data from both cultivated and weedy rice to add further insights. The de novo assembly of unaligned sequences predicted 225 genes, in which 45 were specific to PSRR-1, including two genes associated with flowering. Comparison of the variants in PSRR-1 with the 3K rice genome (RG) dataset identified unique variants within the heading date QTLs. Analyses of the RNA-Seq result under both short-day (SD) and long-day (LD) conditions revealed that many differentially expressed genes (DEGs) colocalized with the flowering QTLs, and some DEGs such as Hd1, OsMADS56, Hd3a, and RFT1 had unique variants in PSRR-1. Ehd1, Hd1, OsMADS15, and OsMADS56 showed different alternate splicing (AS) events between genotypes and day length conditions. OsMADS56 was expressed in PSRR-1 but not in Cypress under both LD and SD conditions. Based on variations in both sequence and expression, the unique flowering response in PSRR-1 may be due to the high-impact variants of flowering genes, and OsMADS56 is proposed as a key regulator for its day-neutral flowering response.

Genome-Wide Association Analyses to Identify SNPs Related to Drought Tolerance

Drought stress is a serious agronomic problem resulting in significant yield losses globally. Breeding cultivars with drought tolerance is an important strategy that can be used to address this problem. Drought tolerance, however, is a complex multigenic trait, making advancements with conventional breeding approaches very challenging. This emphasizes the importance of dissecting the genetics of this trait and the identification and cloning of genes responsible for drought tolerance. With the rapid development of sequencing technologies and analytic methodologies, genome-wide association study (GWAS) has become an important tool for detecting natural variations underlying complex traits in crops. Identified loci can serve as targets for genomic selection or precise editing that enables the molecular design of new cultivars. This chapter describes the pipeline of statistical methods used in GWAS analysis, and covers field design, quality control, population structure control, association tests, and visualization of data. GWAS methodology used to dissect the genetic basis of drought tolerance is presented, and perspectives for optimizing the design and analysis of GWAS are discussed. The provided information serves as a valuable resource for researchers interested in GWAS technology.

Potato biofortification: an effective way to fight global hidden hunger

Hidden hunger is leading to extensive health problems in the developing world. Several strategies could be used to reduce the micronutrient deficiencies by increasing the dietary uptake of essential micronutrients. These include diet diversification, pharmaceutical supplementation, food fortification and crop biofortification. Among all, crop biofortification is the most sustainable and acceptable strategy to overcome the global issue of hidden hunger. Since most of the people suffering from micronutrient deficiencies, have monetary issues and are dependent on staple crops to fulfil their recommended daily requirements of various essential micronutrients. Therefore, increasing the micronutrient concentrations in cost effective staple crops seems to be an effective solution. Potato being the world's most consumed non-grain staple crop with enormous industrial demand appears to be an ideal candidate for biofortification. It can be grown in different climatic conditions, provide high yield, nutrition and dry matter in lesser time. In addition, huge potato germplasm have natural variations related to micronutrient concentrations, which can be utilized for its biofortification. This review discuss the current scenario of micronutrient malnutrition and various strategies that could be used to overcome it. The review also shed a light on the genetic variations present in potato germplasm and suggest effective ways to incorporate them into modern high yielding potato varieties.

EigenGWAS: An online visualizing and interactive application for detecting genomic signatures of natural selection

Detecting genetic regions under selection in structured populations is of great importance in ecology, evolutionary biology and breeding programmes. We recently proposed EigenGWAS, an unsupervised genomic scanning approach that is similar to F ST but does not require grouping information of the population, for detection of genomic regions under selection. The original EigenGWAS is designed for the random mating population, and here we extend its use to inbred populations. We also show in theory and simulation that eigenvalues, the previous corrector for genetic drift in EigenGWAS, are overcorrected for genetic drift, and the genomic inflation factor is a better option for this adjustment. Applying the updated algorithm, we introduce the new EigenGWAS online platform with highly efficient core implementation. Our online computational tool accepts plink data in a standard binary format that can be easily converted from the original sequencing data, provides the users with graphical results via the R-Shiny user-friendly interface. We applied the proposed method and tool to various data sets, and biologically interpretable results as well as caveats that may lead to an unsatisfactory outcome are given. The EigenGWAS online platform is available at www.eigengwas.com, and can be localized and scaled up via R (recommended) or docker.

Omics and CRISPR-Cas9 Approaches for Molecular Insight, Functional Gene Analysis, and Stress Tolerance Development in Crops

Plants are regularly exposed to biotic and abiotic stresses that adversely affect agricultural production. Omics has gained momentum in the last two decades, fueled by statistical methodologies, computational capabilities, mass spectrometry, nucleic-acid sequencing, and peptide-sequencing platforms. Functional genomics—especially metabolomics, transcriptomics, and proteomics—have contributed substantially to plant molecular responses to stress. Recent progress in reverse and forward genetics approaches have mediated high-throughput techniques for identifying stress-related genes. Furthermore, web-based genetic databases have mediated bioinformatics techniques for detecting families of stress-tolerant genes. Gene ontology (GO) databases provide information on the gene product’s functional features and help with the computational estimation of gene function. Functional omics data from multiple platforms are useful for positional cloning. Stress-tolerant plants have been engineered using stress response genes, regulatory networks, and pathways. The genome-editing tool, CRISPR-Cas9, reveals the functional features of several parts of the plant genome. Current developments in CRISPR, such as de novo meristem induction genome-engineering in dicots and temperature-tolerant LbCas12a/CRISPR, enable greater DNA insertion precision. This review discusses functional omics for molecular insight and CRISPR-Cas9-based validation of gene function in crop plants. Omics and CRISPR-Cas9 are expected to garner knowledge on molecular systems and gene function and stress-tolerant crop production.

Association Mapping and Transcriptome Analysis Reveal the Genetic Architecture of Maize Kernel Size

Kernel length, kernel width, and kernel thickness are important traits affecting grain yield and product quality. Here, the genetic architecture of the three kernel size traits was dissected in an association panel of 309 maize inbred lines using four statistical methods. Forty-two significant single nucleotide polymorphisms (SNPs; p < 1.72E-05) and 70 genes for the three traits were identified under five environments. One and eight SNPs were co-detected in two environments and by at least two methods, respectively, and they explained 5.87-9.59% of the phenotypic variation. Comparing the transcriptomes of two inbred lines with contrasting seed size, three and eight genes identified in the association panel showed significantly differential expression between the two genotypes at 15 and 39 days after pollination, respectively. Ten and 17 genes identified by a genome-wide association study were significantly differentially expressed between the two development stages in the two genotypes. Combining environment-/method-stable SNPs and differential expression analysis, ribosomal protein L7, jasmonate-regulated gene 21, serine/threonine-protein kinase RUNKEL, AP2-EREBP-transcription factor 16, and Zm00001d035222 (cell wall protein IFF6-like) were important candidate genes for maize kernel size and development.

Identification of QTLs for high grain yield and component traits in new plant types of rice

A panel of 60 genotypes comprising New Plant Types (NPTs) along with indica, tropical and temperate japonica genotypes was phenotypically evaluated for four seasons in irrigated situation for grain yield per se and component traits. Twenty NPT genotypes were found promising with an average grain yield varying from 5.45 to 8.8 t/ha. A total of 85 SSR markers were used in the study to identify QTLs associated with grain yield per se and related traits. Sixty-six (77.65%) markers were found to be polymorphic. The PIC values varied from 0.516 to 0.92 with an average of 0.704. A moderate level of genetic diversity (0.39) was detected among genotypes. Variation to the tune of 8% within genotypes, 68% among the genotypes within the population and 24% among the populations were observed (AMOVA). This information may help in identification of potential parents for development of transgressive segregants with very high yield. The association analysis using GLM and MLM models led to the identification of 30 and 10 SSR markers associated with 70 and 16 QTLs, respectively. Thirty novel QTLs linked with 16 SSRs were identified to be associated with eleven traits, namely tiller number (qTL-6.1, qTL-11.1, qTL-4.1), panicle length (qPL-1.1, qPL-5.1, qPL-7.1, qPL-8.1), flag leaf length (qFLL-8.1, qFLL-9.1), flag leaf width (qFLW-6.2, qFLW-5.1, qFLW-8.1, qFLW-7.1), total no. of grains (qTG-2.2, qTG-a7.1), thousand-grain weight (qTGW-a1.1, qTGW-a9.2, qTGW-5.1, qTGW-8.1), fertile grains (qFG-7.1), seed length-breadth ratio (qSlb-3.1), plant height (qPHT-6.1, qPHT-9.1), days to 50% flowering (qFD-1.1) and grain yield per se (qYLD-5.1, qYLD-6.1a, qYLD-11.1).Some of the SSRs were co-localized with more than two traits. The highest co-localization was identified with RM5709 linked to nine traits, followed by RM297 with five traits. Similarly, RM5575, RM204, RM168, RM112, RM26499 and RM22899 were also recorded to be co-localized with more than one trait and could be rated as important for marker-assisted backcross breeding programs, for pyramiding of these QTLs for important yield traits, to produce new-generation rice for prospective increment in yield potentiality and breaking yield ceiling.

Discovery of selection-driven genetic differences of Duroc, Landrace, and Yorkshire pig breeds by EigenGWAS and Fst analyses

Pigs are one of the earliest domesticated animals and multiple breeds have been developed to meet the various demands of consumers. EigenGWAS is a novel strategy to identify candidate genes that underlying population genetic differences and to infer candidate regions under selection as well. In this study, EigenGWAS and F_st analyses were performed using the public re-sequencing data of three typical commercial pig breeds, Duroc, Landrace and Yorkshire. The intersection of genome-wide significant SNPs detected by EigenGWAS and top-ranked 1% SNPs of F_st results were treated as signals under selection. Using the data of all three breeds, 3062 signals under selection were detected and the nearby genomic regions within 300 kb upstream and downstream covered 6.54% of whole genome. Pairs of breeds were analysed along with the pathway analysis. The gene function enrichment results indicated that many candidate genes located in the genomic regions of the signals under selection were associated with biological processes related to growth, metabolism, reproduction, sensory perception, etc. Among the candidate genes, the FSHB, AHR, PTHLH, KDR and FST genes were reported to be associated with reproductive performance; the KIT, KITLG, MITF, MC1R and EDNRB genes were previously identified to affect coat colour; the RETREG1, TXNIP, BMP5, PPARD and RBP4 genes were reported to be associated with lipid metabolism and growth traits. The identified genetic differences across the three commercial breeds will advance understanding of the artificial selection history of pigs and the signals under selection will suggest potential uses in pig genomic breeding programmes.

Pleiotropic changes revealed by in situ recovery of the semi-dwarf gene sd1 in rice

The "Green Revolution" that dramatically reduced cultivar heights and sharply boosted rice production mid-century was achieved in large part through introgression of defective alleles of Semi-Dwarf 1 (SD1), which encodes a GA20ox oxidase involved in the final steps of the synthesis of bioactive gibberellin in rice. Here, we ask whether converting the defective sd1 version in a modern semi-dwarf cultivar back to wild-type SD1 in situ recovers ancestral plant traits, and more broadly, what it reveals about pleiotropic effects of this gene. We assess these effects of SD1 restoration in three independent recombinant lines recovered from F₂ progeny of a cross between 93-11 and PA64s. We then used RNA-seq to dissect gene network changes that accompanied SD1 restoration. We report that this in situ restoration of wild-type SD1 nearly doubles plant height, increases total grain yield per panicle, and elongates the second-leaf length. Comparison of expression profiles reveals changes in key nodes of the gibberellin pathway, such as OsKO1 and OsGA2ox3, and more broadly in genes related to metabolic networks, defense response, and catabolic processes. Two JA-induced genes, RIR1b and OsPR1b, are extremely down-regulated after SD1 restoration, suggesting that SD1 restoration alters the balance between GA and JA to plant growth, at the cost of degrading the defense response. This in situ approach at the SD1 locus also provides a model example that is applicable to other systems and will further understanding of gene networks underlying high-yield traits in crops.

Genome-Wide Association Study Reveals Novel Marker-Trait Associations (MTAs) Governing the Localization of Fe and Zn in the Rice Grain

Micronutrient malnutrition due to Fe and Zn, affects around two billion people globally particularly in the developing countries. More than 90% of the Asian population is dependent on rice-based diets, which is low in these micronutrients. In the present study, a set of 192 Indian rice germplasm accessions, grown at two locations, were evaluated for Fe and Zn in brown rice (BR) and milled rice (MR). A significant variation was observed in the rice germplasm for these micronutrients. The grain Fe concentration was in the range of 6.2–23.1 ppm in BR and 0.8–12.3 ppm in MR, while grain Zn concentration was found to be in the range of 11.0–47.0 ppm and 8.2–40.8 ppm in the BR and MR, respectively. Grain Fe exhibited maximum loss upon milling with a mean retention of 24.9% in MR, while Zn showed a greater mean retention of 74.2% in MR. A genome-wide association study (GWAS) was carried out implementing the FarmCPU model to control the population structure and kinship, and resulted in the identification of 29 marker-trait associations (MTAs) with significant associations for traits viz. FeBR (6 MTAs), FeMR (7 MTAs), ZnBR (11 MTAs), and ZnMR (5 MTAs), which could explain the phenotypic variance from 2.1 to as high as 53.3%. The MTAs governing the correlated traits showed co-localization, signifying the possibility of their simultaneous improvement. The robust MTAs identified in the study could be valuable resource for enhancing Fe and Zn concentration in the rice grain and addressing the problem of Fe and Zn malnutrition among rice consumers.

Integrating a genome-wide association study with transcriptomic analysis to detect genes controlling grain drying rate in maize (Zea may, L.)

Candidate genes on grain drying rate (GDR) were identified, and drying molecular mechanism of grain was explored by integrating genome-wide association with transcriptomic analysis in maize. Grain drying rate (GDR) is a key determinant of grain moisture at harvest. Here, a genome-wide association study (GWAS) of 309 inbred maize lines was used to identify single-nucleotide polymorphisms (SNPs) associated with drying rates of grain, cob and bract. Out of 217,933 SNPs, seven significant SNPs were repeatedly identified in four environments (P < 10^-4). Based on genomic position of significant SNPs, six candidate genes were identified, one of which (Zm00001d047468) was verified by transcriptomic data between inbred lines with high and low GDR, indicating stable and reliable correlation with GDR. To further detect more genes correlated with GDR and explore drying molecular mechanism of grain, expression profile of all GWAS-identified genes (4941) detected from different environments, tissues and developmental stage was evaluated by transcriptomic data of six inbred lines with high or low GDR. Results revealed 162 genes exhibit up-regulated expression and another 123 down-regulated in three higher-GDR inbred lines. Based on GO enrichment, 162 up-regulated genes were significantly enriched into grain primary metabolic process, nitrogen compound metabolic process and macromolecule metabolic process (P < 0.05), which indicated grain filling imposes notable influence on GDR before and after physiological maturity. Our results lay foundation in accelerating development of higher-GDR maize germplasm through marker-assisted selection and clarifying genetic mechanism of GDR in maize.

Effect of moisture gradient on rice yields and greenhouse gas emissions from rice paddies

Fluxes of methane (CH₄) and nitrous oxide (N₂O) from two rice varieties, Huayou 14 and Hanyou 8, were monitored using closed chamber/gas chromatography method. Huayou 14 is a commonly grown variety of rice whereas Hanyou 8 is a water-saving and drought-resistant rice (WDR) variety. Low soil volumetric water content (VWC) existed in the treatments on the slope (W5 < W4 < W3 < W2). On the slope, rice yields of Hanyou 8 decreased by 12-39%, and Huayou 14 by 11-46% as compared to the plots on the flat. The total compatible solutes in Hanyou 8 had a greater variational range than Huayou 14. Compared to W1, CH₄ emissions from W2-W5 decreased by 58-86% in Hanyou 8 and 38-86% in Huayou 14, whereas those of N₂O increased by 26-121% in Hanyou 8 and 49-189% in Huayou 14 across both two seasons, which was mainly because the VWC varied in W2-W5 treatment. Under the treatments in the slope (W2, W3, W4, and W5), the global warming potential (GWP) was dominated by N₂O emissions, which accounted for 69-90% of the GWP. Hanyou 8 had greater tolerance for water stress than Huayou 14 did, as evident from the smaller reductions in rice yield and greater variational range of total compatible solutes content. Water stress could reduce CH₄ emissions but decrease N₂O emissions for both rice varieties. This results suggest that planting WDR varieties under water shortage irrigation (such as W4, W5) will be able to maintain rice yields and reduce the GWP with less water.

Genome-Wide Population Structure Analyses of Three Minor Millets: Kodo Millet, Little Millet, and Proso Millet

Developed genome-wide SNP marker data for kodo, proso, and little millet Marker data used to analyze genetic diversity Heritability results of various traits used to validate genetic data Millets are a diverse group of small-seeded grains that are rich in nutrients but have received relatively little advanced plant breeding research. Millets are important to smallholder farmers in Africa and Asia because of their short growing season, good stress tolerance, and high nutritional content. To advance the study and use of these species, we present genome-wide marker datasets and population structure analyses for three minor millets: kodo millet (Paspalum scrobiculatum L.), little millet (Panicum sumatrense Roth), and proso millet (Panicum miliaceum L.).We generated genome-wide marker data sets for 190 accessions of each species with genotyping-by-sequencing (GBS). After filtering, we retained between 161 and 165 accessions of each species, with 3461, 2245, and 1882 single-nucleotide polymorphisms (SNPs) for kodo, little, and proso millet, respectively. Population genetic analysis revealed seven putative subpopulations of kodo millet and eight each of proso millet and little millet. To confirm the accuracy of this genetic data, we used public phenotype data on a subset of these accessions to estimate the heritability of various agronomically relevant phenotypes. Heritability values largely agree with the prior expectation for each phenotype, indicating that these SNPs provide an accurate genome-wide sample of genetic variation. These data represent one of first genome-wide population genetics analyses-and the most extensive-in these species and the first genomic analyses of any sort for little millet and kodo millet. These data will be a valuable resource for researchers and breeders trying to improve these crops for smallholder farmers.

Black rice (Oryza sativa L.): A review of its historical aspects, chemical composition, nutritional and functional properties, and applications and processing technologies

Black rice is a variety of pigmented rice. It contains numerous nutritional and bioactive components, including essential amino acids, functional lipids, dietary fibre, vitamins, minerals, anthocyanins, phenolic compounds, γ-oryzanols, tocopherols, tocotrienols, phytosterols and phytic acid. There have been several studies of black rice due to its alleged beneficial health effects when consumed regularly. This review focuses on the historical aspects, chemical composition, and nutritional and functional properties of black rice. Furthermore, a discussion of the development of new foods and beverages with applications and processing technologies designed to improve their quality attributes. The nutritional value of black rice means that it has the potential to be used in the production of healthy foods and beverages, such as functional products and gluten-free cereals, thereby providing extra health benefits to consumers.

A novel rice grain size gene OsSNB was identified by genome-wide association study in natural population

Increasing agricultural productivity is one of the most important goals of plant science research and imperative to meet the needs of a rapidly growing population. Rice (Oryza sativa L.) is one of the most important staple crops worldwide. Grain size is both a major determinant of grain yield in rice and a target trait for domestication and artificial breeding. Here, a genome-wide association study of grain length and grain width was performed using 996,722 SNP markers in 270 rice accessions. Five and four quantitative trait loci were identified for grain length and grain width, respectively. In particular, the novel grain size gene OsSNB was identified from qGW7, and further results showed that OsSNB negatively regulated grain size. Most notably, knockout mutant plants by CRISPR/Cas9 technology showed increased grain length, width, and weight, while overexpression of OsSNB yielded the opposite. Sequencing of this gene from the promoter to the 3’-untranslated region in 168 rice accessions from a wide geographic range identified eight haplotypes. Furthermore, Hap 3 has the highest grain width discovered in japonica subspecies. Compared to other haplotypes, Hap 3 has a 225 bp insertion in the promoter. Based on the difference between Hap 3 and other haplotypes, OsSNB_Indel2 was designed as a functional marker for the improvement of rice grain width. This could be directly used to assist selection toward an improvement of grain width. These findings suggest OsSNB as useful for further improvements in yield characteristics in most cultivars.

Grain weight, including grain length and grain width, is a complex trait, and hundreds of quantitative trait loci (QTLs) were detected in different genetic rice populations. However, only about 10 genes have been isolated and characterized until now. Nine QTLs for grain size were identified by genome-wide association study in a natural rice population. The novel grain size gene OsSNB was identified from qGW7 based on the difference of expression levels between two different varieties with significantly different grain width. OsSNB is an AP2 transcription factor that is negatively regulated grain size. However, OsSNB was found to regulate the transition from the spikelet meristem to the floral meristem and the floral organ development in previous study. Compared to other haplotypes, Hap 3 has a 225 bp insertion in the promoter. Based on the difference between Hap 3 and other haplotypes, OsSNB_Indel2 was designed as a functional marker for the improvement of rice grain width. This can be directly used to assist selection for grain width improvement.

Genome-wide association study and candidate gene analysis of alkalinity tolerance in japonica rice germplasm at the seedling stage

BACKGROUND

Salinity-alkalinity stress is one of the major factors limiting rice production. The damage caused by alkaline salt stress to rice growth is more severe than that caused by neutral salt stress. At present, the genetic resources (quantitative trait loci (QTLs) and genes) that can be used by rice breeders to improve alkalinity tolerance are limited. Here, we assessed the alkalinity tolerance of rice at the seedling stage and performed a genome-wide association study (GWAS) based on genotypic data including 788,396 single-nucleotide polymorphisms (SNPs) developed by re-sequencing 295 japonica rice varieties.

RESULTS

We used the score of alkalinity tolerance (SAT), the concentrations of Na⁺ and K⁺ in the shoots (SNC and SKC, respectively) and the Na⁺/K⁺ ratio of shoots (SNK) as indices to assess alkalinity tolerance at the seedling stage in rice. Based on population structure analysis, the japonica rice panel was divided into three subgroups. Linkage disequilibrium (LD) analysis showed that LD decay occurred at 109.77 kb for the whole genome and varied between 13.79 kb and 415.77 kb across the 12 chromosomes, at which point the pairwise squared correlation coefficient (r²) decreased to half of its maximum value. A total of eight QTLs significantly associated with the SAT, SNC and SNK were identified by genome-wide association mapping. A common QTL associated with the SAT, SNC and SNK on chromosome 3 at the position of 15.0 Mb, which explaining 13.36~13.64% of phenotypic variation, was selected for further analysis. The candidate genes were filtered based on LD decay, Gene Ontology (GO) enrichment, RNA sequencing data, and quantitative real-time PCR (qRT-PCR) analysis. Moreover, sequence analysis revealed one 7-bp insertion/deletion (indel) difference in LOC_Os03g26210 (OsIRO3) between the alkalinity-tolerant and alkalinity-sensitive rice varieties. OsIRO3 encodes a bHLH-type transcription factor and has been shown to be a negative regulator of the Fe-deficiency response in rice.

CONCLUSION

Based on these results, OsIRO3 maybe a novel functional gene associated with alkalinity tolerance in japonica rice. This study provides resources for improving alkalinity tolerance in rice, and the functional molecular marker could be verified to breed new rice varieties with alkalinity tolerance via marker-assisted selection (MAS).

Genome-Wide Association Study of Major Agronomic Traits in Foxtail Millet (Setaria italica L.) Using ddRAD Sequencing

Foxtail millet (Setaria italica), the second largest cultivated millet crop after pearl millet, is utilized for food and forage globally. Further, it is also considered as a model crop for studying agronomic, nutritional and biofuel traits. In the present study, a genome-wide association study (GWAS) was performed for ten important agronomic traits in 142 foxtail millet core eco-geographically diverse genotypes using 10 K SNPs developed through GBS-ddRAD approach. Number of SNPs on individual chromosome ranged from 844 (chromosome 5) to 2153 (chromosome 8) with an average SNP frequency of 25.9 per Mb. The pairwise linkage disequilibrium (LD) estimated using the squared-allele frequency correlations was found to decay rapidly with the genetic distance of 177 Kb. However, for individual chromosome, LD decay distance ranged from 76 Kb (chromosome 6) to 357 Kb (chromosome 4). GWAS identified 81 MTAs (marker-trait associations) for ten traits across the genome. High confidence MTAs for three important agronomic traits including FLW (flag leaf width), GY (grain yield) and TGW (thousand-grain weight) were identified. Significant pyramiding effect of identified MTAs further supplemented its importance in breeding programs. Desirable alleles and superior genotypes identified in the present study may prove valuable for foxtail millet improvement through marker-assisted selection.

Bi-directional Selection in Upland Rice Leads to Its Adaptive Differentiation from Lowland Rice in Drought Resistance and Productivity

Drought resistance is required in rice breeding to address the challenge of frequent droughts. However, the evolutionary mechanism of rice drought resistance is not fully understood. We investigated the genetic differentiation between upland and lowland rice domesticated in agro-ecosystems with contrasting water-soil conditions using genome-wide SNPs. We estimated morphological differences among upland and lowland rice in drought resistance and productivity through common garden experiments. Upland rice had better drought resistance but poorer productivity. The negative correlations between traits of drought resistance and productivity are attributed to the underlying genetic trade-offs through tight linkages (e.g., DCA1 and OsCesA7) or pleiotropic effects (e.g., LAX1). The genetic trade-offs are common and greatly shape the evolution of drought resistance in upland rice. In genomic regions associated with both productivity and drought resistance, signs of balancing selection were detected in upland rice, while signs of directional selection were detected in lowland rice, potentially contributing to their adaptive differentiation. Signs of balancing selection in upland rice resulted from bi-directional selection during its domestication in drought-prone upland agro-ecosystems. Using genome-wide association analysis, we identified several valuable quantitative trait loci associated with drought resistance, for which highly differentiated genes should be considered candidates. Bi-directional selection breaking tight linkages by accumulating recombination events would be applicable in breeding water-saving and drought-resistance rice.

A Genome-Wide Association Study Reveals Candidate Genes Related to Salt Tolerance in Rice (Oryza sativa) at the Germination Stage

Salt toxicity is the major factor limiting crop productivity in saline soils. In this paper, 295 accessions including a heuristic core set (137 accessions) and 158 bred varieties were re-sequenced and ~1.65 million SNPs/indels were used to perform a genome-wide association study (GWAS) of salt-tolerance-related phenotypes in rice during the germination stage. A total of 12 associated peaks distributed on seven chromosomes using a compressed mixed linear model were detected. Determined by linkage disequilibrium (LD) blocks analysis, we finally obtained a total of 79 candidate genes. By detecting the highly associated variations located inside the genic region that overlapped with the results of LD block analysis, we characterized 17 genes that may contribute to salt tolerance during the seed germination stage. At the same time, we conducted a haplotype analysis of the genes with functional variations together with phenotypic correlation and orthologous sequence analyses. Among these genes, OsMADS31, which is a MADS-box family transcription factor, had a down-regulated expression under the salt condition and it was predicted to be involved in the salt tolerance at the rice germination stage. Our study revealed some novel candidate genes and their substantial natural variations in the rice genome at the germination stage. The GWAS in rice at the germination stage would provide important resources for molecular breeding and functional analysis of the salt tolerance during rice germination.

Reducing the interval of a growth QTL on chromosome 4 in laying hens

In our previous research, we identified a QTL with an interval of 3.4 Mb for growth on chicken chromosome (GGA) 4 in an advanced intercross population of an initial cross between the New Hampshire inbred line (NHI) and the White Leghorn inbred line (WL77). In the current study, an association analysis was performed in a population of purebred white layers (WLA) with White Leghorn origin. Genotypic data of 130 SNPs within the previously identified 3.4-Mb region were obtained using a 60K SNP chip. In total, 24 significant SNPs (LOD ≥ 4.44) on GGA4 were detected for daily weigh gain from 8 to 14 weeks and two SNPs (LOD ≥ 4.80) for body weight at 14 weeks. The QTL interval was reduced by 1.9 Mb to an interval of 1.5 Mb (74.6-76.1 Mb) that harbors 15 genes. Furthermore, to identify additional loci for chicken growth, a genome-wide association study (GWAS) was carried out in a WLA population. The GWAS identified an additional QTL on GGA6 for body weight at six weeks (19.8-21.2 Mb). Our findings showed that by using a WLA population we were able to further reduce the QTL confidence interval previously detected using a NHI × WL77 advanced intercross population.

Genome-wide association reveals novel genomic loci controlling rice grain yield and its component traits under water-deficit stress during the reproductive stage

A diversity panel comprising of 296 indica rice genotypes was phenotyped under non-stress and water-deficit stress conditions during the reproductive stage in the 2013 and 2014 dry seasons (DSs) at IRRI, Philippines. We investigated the genotypic variability for grain yield, yield components, and related traits, and conducted genome-wide association studies (GWAS) using high-density 45K single nucleotide polymorphisms. We detected 38 loci in 2013 and 64 loci in 2014 for non-stress conditions and 69 loci in 2013 and 55 loci in 2014 for water-deficit stress. Desynchronized flowering time confounded grain yield and its components under water-deficit stress in the 2013 experiment. Statistically corrected grain yield and yield component values using days to flowering helped to detect 31 additional genetic loci for grain yield, its components, and the harvest index in 2013. There were few overlaps in the detected loci between years and treatments, and when compared with previous studies using the same panel, indicating the complexity of yield formation under stress. Nevertheless, our analyses provided important insights into the potential links between grain yield with seed set and assimilate partitioning. Our findings demonstrate the complex genetic architecture of yield formation and we propose exploring the genetic basis of less complex component traits as an alternative route for further yield enhancement.

Genotyping of Soybean Cultivars With Medium-Density Array Reveals the Population Structure and QTNs Underlying Maturity and Seed Traits

Soybean was domesticated about 5,000 to 6,000 years ago in China. Although genotyping technologies such as genotyping by sequencing (GBS) and high-density array are available, it is convenient and economical to genotype cultivars or populations using medium-density SNP array in genetic study as well as in molecular breeding. In this study, 235 cultivars, collected from China, Japan, USA, Canada and some other countries, were genotyped using SoySNP8k iSelect BeadChip with 7,189 single nucleotide polymorphisms (SNPs). In total, 4,471 polymorphic SNP markers were used to analyze population structure and perform genome-wide association study (GWAS). The most likely K value was 7, indicating this population can be divided into 7 subpopulations, which is well in accordance with the geographic origins of cultivars or accession studied. The LD decay rate was estimated at 184 kb, where r2 dropped to half of its maximum value (0.205). GWAS using FarmCPU detected a stable quantitative trait nucleotide (QTN) for hilum color and seed color, which is consistent with the known loci or genes. Although no universal QTNs for flowering time and maturity were identified across all environments, a total of 30 consistent QTNs were detected for flowering time (R1) or maturity (R7 and R8) on 16 chromosomes, most of them were corresponding to known E1 to E4 genes or QTL region reported in SoyBase (soybase.org). Of 16 consistent QTNs for protein and oil contents, 11 QTNs were detected having antagonistic effects on protein and oil content, while 4 QTNs soly for oil content, and one QTN soly for protein content. The information gained in this study demonstrated that the usefulness of the medium-density SNP array in genotyping for genetic study and molecular breeding.

Identification of QTNs Controlling Seed Protein Content in Soybean Using Multi-Locus Genome-Wide Association Studies

Protein content (PC), an important trait in soybean (Glycine max) breeding, is controlled by multiple genes with relatively small effects. To identify the quantitative trait nucleotides (QTNs) controlling PC, we conducted a multi-locus genome-wide association study (GWAS) for PC in 144 four-way recombinant inbred lines (FW-RILs). All the FW-RILs were phenotyped for PC in 20 environments, including four locations over 4 years with different experimental treatments. Meanwhile, all the FW-RILs were genotyped using SoySNP660k BeadChip, producing genotype data for 109,676 non-redundant single-nucleotide polymorphisms. A total of 129 significant QTNs were identified by five multi-locus GWAS methods. Based on the 22 common QTNs detected by multiple GWAS methods or in multiple environments, pathway analysis identified 8 potential candidate genes that are likely to be involved in protein synthesis and metabolism in soybean seeds. Using superior allele information for 22 common QTNs in 22 elite and 7 inferior lines, we found higher superior allele percentages in the elite lines and lower percentages in the inferior lines. These findings will contribute to the discovery of the polygenic networks controlling PC in soybean, increase our understanding of the genetic foundation and regulation of PC, and be useful for molecular breeding of high-protein soybean varieties.

Genetic Diversity and Genome-Wide Association Study of Major Ear Quantitative Traits Using High-Density SNPs in Maize

Kernel and ear traits are key components of grain yield in maize (Zea mays L.). Investigation of these traits would help to develop high-yield varieties in maize. Genome-wide association study (GWAS) uses the linkage disequilibrium (LD) in the whole genome to determine the genes affecting certain phenotype. In this study, five ear traits (kernel length and width, ear length and diameter, cob diameter) were investigated across multi-environments for 2 years. Combining with the genotype obtained from Maize SNP50 chip, genetic diversity and association mapping in a set of 292 inbred lines were performed. Results showed that maize lines were clustered into seven subgroups and a total of 20 SNPs were found to be associated with ear traits significantly (P < 3.95E-05). The candidate genes identified by GWAS mainly encoded ubiquitin-activation enzymes (GRMZM2G015287), carotenoid cleavage dioxygenase (GRMZM2G446858), MYB-CC type transfactor, and phosphate starvation response protein 3, and they were associated with kernel length (KL) and ear diameter (ED), respectively. Moreover, two novel genes corresponding to RNA processing and fructose metabolism were found. Further, the SNPs detected by GWAS were confirmed by meta-QTL analysis. These genes and SNPs identified in the study would offer essential information for yield-related genes clone and breeding program in maize.

Genome-wide association study and gene set analysis for understanding candidate genes involved in salt tolerance at the rice seedling stage

Salt is the major factor limiting crop productivity in saline soils and is controlled by various genes. The development of salt-tolerant rice through molecular breeding methods is important to meet the needs of rice breeding. We used 295 accessions to perform a genome-wide association study (GWAS) of salt tolerance-related phenotypes in rice at the seedling stage and obtained 93 candidate genes with high association peaks across six phenotypes. We constructed a protein interaction network using the candidate genes identified here, and 33 genes were associated. Based on the expression patterns, we found that most of these genes showed a different expression level under control and salt stress conditions. In addition, haplotype network and sequence analysis of one 'key' gene, a transcription factor (Os12g0176700) encoding a SWIRM domain-containing protein, in the interaction network was investigated to explore its possible role in the network. Our study revealed candidate salt tolerance-related genes in rice at the seedling stage, and demonstrated the feasibility of using GWAS to identify genetic architecture underlying salt tolerance. The data generated here may provide resources for molecular breeding and functional analysis of salt tolerance in rice seedlings.

Genome-wide association study and gene set analysis for understanding candidate genes involved in salt tolerance at the rice seedling stage

Salt is the major factor limiting crop productivity in saline soils and is controlled by various genes. The development of salt-tolerant rice through molecular breeding methods is important to meet the needs of rice breeding. We used 295 accessions to perform a genome-wide association study (GWAS) of salt tolerance-related phenotypes in rice at the seedling stage and obtained 93 candidate genes with high association peaks across six phenotypes. We constructed a protein interaction network using the candidate genes identified here, and 33 genes were associated. Based on the expression patterns, we found that most of these genes showed a different expression level under control and salt stress conditions. In addition, haplotype network and sequence analysis of one 'key' gene, a transcription factor (Os12g0176700) encoding a SWIRM domain-containing protein, in the interaction network was investigated to explore its possible role in the network. Our study revealed candidate salt tolerance-related genes in rice at the seedling stage, and demonstrated the feasibility of using GWAS to identify genetic architecture underlying salt tolerance. The data generated here may provide resources for molecular breeding and functional analysis of salt tolerance in rice seedlings.

CRISPR/Cas9-Based Genome Editing in Plants

Recently, genome editing technologies have shown great potential in plants. The newly developed clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system is a new generation of genome editing tool rapidly replacing the earlier zinc finger nucleases and transcription activator-like effector nucleases systems. Indeed, due to its advantages of simplicity and high efficiency, the CRISPR/Cas9-based genome editing system is becoming a powerful tool in plant science research. Here, we introduce the technical features of the plant CRISPR/Cas9-based genome editing system and its applications in plant functional genomics studies and genetic improvement.