Genome-wide association studies of 14 agronomic traits in rice landraces

Comprehensive mapping and modelling of the rice regulome landscape unveils the regulatory architecture underlying complex traits

Unraveling the regulatory mechanisms that govern complex traits is pivotal for advancing crop improvement. Here we present a comprehensive regulome atlas for rice (Oryza sativa), charting the chromatin accessibility across 23 distinct tissues from three representative varieties. Our study uncovers 117,176 unique open chromatin regions (OCRs), accounting for ~15% of the rice genome, a notably higher proportion compared to previous reports in plants. Integrating RNA-seq data from matched tissues, we confidently predict 59,075 OCR-to-gene links, with enhancers constituting 69.54% of these associations, including many known enhancer-to-gene links. Leveraging this resource, we re-evaluate genome-wide association study results and discover a previously unknown function of OsbZIP06 in seed germination, which we subsequently confirm through experimental validation. We optimize deep learning models to decode regulatory grammar, achieving robust modeling of tissue-specific chromatin accessibility. This approach allows to predict cross-variety regulatory dynamics from genomic sequences, shedding light on the genetic underpinnings of cis-regulatory divergence and morphological disparities between varieties. Overall, our study establishes a foundational resource for rice functional genomics and precision molecular breeding, providing valuable insights into regulatory mechanisms governing complex traits.

Understanding natural genetic variation for nutritional quality in grain and identification of superior haplotypes in deepwater rice genotypes of Assam, India

Rice grown under deepwater ecosystem is considered to be natural farming and hence they are considered to be input efficient. Thus, to identify gene responsible for nutritional content under natural conditions, a genome-wide association study (GWAS)was performed. GWAS identified single nucleotide polymorphisms (SNPs) significantly associated with various nutritional quality traits such as Zn (mg/kg), Fe (mg/kg), Protein (%), Oil (%), Amylose (%), Starch (%), Phytic acid (%), Phenol (%) and TDF (%) in 184 deepwater rice accessions evaluated over 2 consecutive years. A total of 278 SNPs distributed across 12 chromosomes were found to be significantly associated with Zn, Oil and Phenol content. Among them, eight high confidence SNPs were significant and identified on chr1 (AX-95933712), chr7 (AX-95957036), and chr8 (AX-95965181) for Zn content. Similarly, on chr2 (AX-95945186), chr8 (AX-95964718), and chr11 (AX-95961099) have been found to be associated with Oil content and for, on chr3 (AX-95922121) and chr4 (AX-95963889) for Phenol content. Genomic regions of ± 220 kb flanking the three consistent lowest p value containing SNPs for each trait were considered for finding superior haplotypes. These SNPs showed significant phenotypic variations with different identified haplotype blocks. The allelic variations with phenotypes were considered to be superior haplotypes i.e., Block 1: Hap 1 (ACCC) for high Zn content, Block 2: Hap 1 (CT) for high Oil content, and Block 2: Hap 1(CGGG) for low Phenol content. The discovered superior haplotype with high nutritional content could be important for understanding the mechanisms involving nutrient use efficiency. Thus, the present study demonstrated that developing rice varieties with appropriate nutritional quality traits will be possible through the incorporation of such superior haplotypes in breeding programs.

Effective population size in field pea

BACKGROUND

Effective population size (Ne) is a pivotal parameter in population genetics as it can provide information on the rate of inbreeding and the contemporary status of genetic diversity in breeding populations. The population with smaller Ne can lead to faster inbreeding, with little potential for genetic gain making selections ineffective. The importance of Ne has become increasingly recognized in plant breeding, which can help breeders monitor and enhance the genetic variability or redesign their selection protocols. Here, we present the first Ne estimates based on linkage disequilibrium (LD) in the pea genome.

RESULTS

We calculated and compared Ne using SNP markers from North Dakota State University (NDSU) modern breeding lines and United States Department of Agriculture (USDA) diversity panel. The extent of LD was highly variable not only between populations but also among different regions and chromosomes of the genome. Overall, NDSU had a higher and longer-range LD than the USDA that could extend up to 500 Kb, with a genome-wide average r2 of 0.57 (vs 0.34), likely due to its lower recombination rates and the selection background. The estimated Ne for the USDA was nearly three-fold higher (Ne = 174) than NDSU (Ne = 64), which can be confounded by a high degree of population structure due to the selfing nature of pea.

CONCLUSIONS

Our results provided insights into the genetic diversity of the germplasm studied, which can guide plant breeders to actively monitor Ne in successive cycles of breeding to sustain viability of the breeding efforts in the long term.

Genetic Analysis of Soybean Flower Size Phenotypes Based on Computer Vision and Genome-Wide Association Studies

The dimensions of organs such as flowers, leaves, and seeds are governed by processes of cellular proliferation and expansion. In soybeans, the dimensions of these organs exhibit a strong correlation with crop yield, quality, and other phenotypic traits. Nevertheless, there exists a scarcity of research concerning the regulatory genes influencing flower size, particularly within the soybean species. In this study, 309 samples of 3 soybean types (123 cultivar, 90 landrace, and 96 wild) were re-sequenced. The microscopic phenotype of soybean flower organs was photographed using a three-eye microscope, and the phenotypic data were extracted by means of computer vision. Pearson correlation analysis was employed to assess the relationship between petal and seed phenotypes, revealing a strong correlation between the sizes of these two organs. Through GWASs, SNP loci significantly associated with flower organ size were identified. Subsequently, haplotype analysis was conducted to screen for upstream and downstream genes of these loci, thereby identifying potential candidate genes. In total, 77 significant SNPs associated with vexil petals, 562 significant SNPs associated with wing petals, and 34 significant SNPs associated with keel petals were found. Candidate genes were screened by candidate sites, and haplotype analysis was performed on the candidate genes. Finally, the present investigation yielded 25 and 10 genes of notable significance through haplotype analysis in the vexil and wing regions, respectively. Notably, Glyma.07G234200, previously documented for its high expression across various plant organs, including flowers, pods, leaves, roots, and seeds, was among these identified genes. The research contributes novel insights to soybean breeding endeavors, particularly in the exploration of genes governing organ development, the selection of field materials, and the enhancement of crop yield. It played a role in the process of material selection during the growth period and further accelerated the process of soybean breeding material selection.

GWAS unravels acid phosphatase ACP2 as a photosynthesis regulator under phosphate starvation conditions through modulating serine metabolism in rice

Inorganic phosphorus (Pi) deficiency significantly impacts plant growth, development, and photosynthetic efficiency. This study evaluated 206 rice accessions from a MiniCore population under both Pi-sufficient (Pi+) and Pi-starvation (Pi-) conditions in the field to assess photosynthetic phosphorus use efficiency (PPUE), defined as the ratio of AsatPi- to AsatPi+. A genome-wide association study and differential gene expression analyses identified an acid phosphatase gene (ACP2) that responds strongly to phosphate availability. Overexpression and knockout of ACP2 led to a 67% increase and 32% decrease in PPUE, respectively, compared with wild type. Introduction of an elite allele A, by substituting the v5 SNP G with A, resulted in an 18% increase in PPUE in gene-edited ACP2 rice lines. The phosphate-responsive gene PHR2 was found to transcriptionally activate ACP2 in parallel with PHR2 overexpression, resulting in an 11% increase in PPUE. Biochemical assays indicated that ACP2 primarily catalyzes the hydrolysis of phosphoethanolamine and phospho-L-serine. In addition, serine levels increased significantly in the ACP2v8G-overexpression line, along with a concomitant decrease in the expression of all nine genes involved in the photorespiratory pathway. Application of serine enhanced PPUE and reduced photorespiration rates in ACP2 mutants under Pi-starvation conditions. We deduce that ACP2 plays a crucial role in promoting photosynthesis adaptation to Pi starvation by regulating serine metabolism in rice.

Grain Protein Content Phenotyping in Rice via Hyperspectral Imaging Technology and a Genome-Wide Association Study

Efficient and accurate acquisition of the rice grain protein content (GPC) is important for selecting high-quality rice varieties, and remote sensing technology is an attractive potential method for this task. However, the majority of multispectral sensors are poor predictors of GPC due to their broad spectral bands. Hyperspectral technology provides a new analytical technology for bridging the gap between phenomics and genomics. However, the small size of typical datasets is a constraint for model construction for estimating GPC, limiting their accuracy and reducing their ability to generalize to a wide range of varieties. In this study, we used hyperspectral data of rice grains from 515 japonica varieties and deep convolution generative adversarial networks (DCGANs) to generate simulated data to improve the model accuracy. Features sensitive to GPC were extracted after applying a continuous wavelet transform (CWT), and the estimated GPC model was constructed by partial least squares regression (PLSR). Finally, a genome-wide association study (GWAS) was applied to the measured and generated datasets to detect GPC loci. The results demonstrated that the simulated GPC values generated after 8,000 epochs were closest to the measured values. The wavelet feature (WF1743, 2), obtained from the data with the addition of 200 simulated samples, exhibited the highest GPC estimation accuracy (R 2 = 0.58 and RRMSE = 6.70%). The GWAS analysis showed that the estimated values based on the simulated data detected the same loci as the measured values, including the OsmtSSB1L gene related to grain storage protein. This study provides a new technique for the efficient genetic study of phenotypic traits in rice based on hyperspectral technology.

Genomic investigation of 18,421 lines reveals the genetic architecture of rice

Understanding how numerous quantitative trait loci (QTL) shape phenotypic variation is an important question in genetics. To address this, we established a permanent population of 18,421 (18K) rice lines with reduced population structure. We generated reference-level genome assemblies of the founders and genotyped all 18K-rice lines through whole-genome sequencing. Through high-resolution mapping, 96 high-quality candidate genes contributing to variation in 16 traits were identified, including OsMADS22 and OsFTL1 verified as causal genes for panicle number and heading date, respectively. We identified epistatic QTL pairs and constructed a genetic interaction network with 19 genes serving as hubs. Overall, 170 masking epistasis pairs were characterized, serving as an important factor contributing to genetic background effects across diverse varieties. The work provides a basis to guide grain yield and quality improvements in rice.

Deepening genomic sequences of 1081 Gossypium hirsutum accessions reveals novel SNPs and haplotypes relevant for practical breeding utility

Fiber quality is a major breeding goal in cotton, but phenotypically direct selection is often hindered. In this study, we identified fiber quality and yield related loci using GWAS based on 2.97 million SNPs obtained from 10.65× resequencing data of 1081 accessions. The results showed that 585 novel fiber loci, including two novel stable SNP peaks associated with fiber length on chromosomes At12 and Dt05 and one novel genome regions linked with fiber strength on chromosome Dt12 were identified. Furthermore, by means of gene expression analysis, GhM_A12G0090, GhM_D05G1692, GhM_D12G3135 were identified and GhM_D11G2208 function was identified in Arabidopsis. Additionally, 14 consistent and stable superior haplotypes were identified, and 25 accessions were detected as possessing these 14 superior haplotype in breeding. This study providing fundamental insight relevant to identification of genes associated with fiber quality and yield will enhance future efforts toward improvement of upland cotton.

Dual-trait genomic analysis in highly stratified Arabidopsis thaliana populations using genome-wide association summary statistics

Genome-wide association study (GWAS) is a powerful tool to identify genomic loci underlying complex traits. However, the application in natural populations comes with challenges, especially power loss due to population stratification. Here, we introduce a bivariate analysis approach to a GWAS dataset of Arabidopsis thaliana. We demonstrate the efficiency of dual-phenotype analysis to uncover hidden genetic loci masked by population structure via a series of simulations. In real data analysis, a common allele, strongly confounded with population structure, is discovered to be associated with late flowering and slow maturation of the plant. The discovered genetic effect on flowering time is further replicated in independent datasets. Using Mendelian randomization analysis based on summary statistics from our GWAS and expression QTL scans, we predicted and replicated a candidate gene AT1G11560 that potentially causes this association. Further analysis indicates that this locus is co-selected with flowering-time-related genes. The discovered pleiotropic genotype-phenotype map provides new insights into understanding the genetic correlation of complex traits.

Genome wide association studies on seven yield-related traits of 183 rice varieties in Bangladesh

Rice genetic diversity is regulated by multiple genes and is largely dependent on various environmental factors. Uncovering the genetic variations associated with the diversity in rice populations is the key to breed stable and high yielding rice varieties. We performed genome wide association studies (GWASs) on seven rice yielding traits (grain length, grain width, grain weight, panicle length, leaf length, leaf width, and leaf angle) based on a population of 183 rice landraces of Bangladesh. Our GWASs reveal various chromosomal regions and candidate genes that are associated with different traits in Bangladeshi rice varieties. Noteworthy was the recurrent implication of chromosome 10 in all three grain-shape-related traits (grain length, grain width, and grain weight), indicating its pivotal role in shaping rice grain morphology. Our study also underscores the involvement of transposon gene families across these three traits. For leaf related traits, chromosome 10 was found to harbor regions that are significantly associated with leaf length and leaf width. The results of these association studies support previous findings as well as provide additional insights into the genetic diversity of rice. This is the first known GWAS study on various yield-related traits in the varieties of Oryza sativa available in Bangladesh-the fourth largest rice-producing country. We believe this study will accelerate rice genetics research and breeding stable high-yielding rice in Bangladesh.

Genomic, transcriptomic, and metabolomic analyses provide insights into the evolution and development of a medicinal plant Saposhnikovia divaricata (Apiaceae)

Saposhnikovia divaricata, 2n = 2x = 16, as a perennial species, is widely distributed in China, Mongolia, Russia, etc. It is a traditional Chinese herb used to treat tetanus, rubella pruritus, rheumatic arthralgia, and other diseases. Here, we assembled a 2.07 Gb and N50 scaffold length of 227.67 Mb high-quality chromosome-level genome of S. divaricata based on the PacBio Sequel II sequencing platform. The total number of genes identified was 42 948, and 42 456 of them were functionally annotated. A total of 85.07% of the genome was composed of repeat sequences, comprised mainly of long terminal repeats (LTRs) which represented 73.7% of the genome sequence. The genome size may have been affected by a recent whole-genome duplication event. Transcriptional and metabolic analyses revealed bolting and non-bolting S. divaricata differed in flavonoids, plant hormones, and some pharmacologically active components. The analysis of its genome, transcriptome, and metabolome helped to provide insights into the evolution of bolting and non-bolting phenotypes in wild and cultivated S. divaricata and lays the basis for genetic improvement of the species.

OsLSC6 Regulates Leaf Sheath Color and Cold Tolerance in Rice Revealed by Metabolite Genome Wide Association Study

Plant metabolites including anthocyanins play an important role in the growth of plants, as well as in regulating biotic and abiotic stress responses to the environment. Here we report comprehensive profiling of 3315 metabolites and a further metabolic-based genome-wide association study (mGWAS) based on 292,485 SNPs obtained from 311 rice accessions, including 160 wild and 151 cultivars. We identified hundreds of common variants affecting a large number of secondary metabolites with large effects at high throughput. Finally, we identified a novel gene namely OsLSC6 (Oryza sativa leaf sheath color 6), which encoded a UDP 3-O-glucosyltransferase and involved in the anthocyanin biosynthesis of Cyanidin-3-Galc (sd1825) responsible for leaf sheath color, and resulted in significant different accumulation of sd1825 between wild (purple) and cultivars (green). The results of knockout transgenic experiments showed that OsLSC6 regulated the biosynthesis and accumulation of sd1825, controlled the purple leaf sheath. Our further research revealed that OsLSC6 also confers resistance to cold stress during the seedling stage in rice. And we identified that a SNP in OsLSC6 was responsible for the leaf sheath color and chilling tolerance, supporting the importance of OsLSC6 in plant adaption. Our study could not only demonstrate that OsLSC6 is a vital regulator during anthocyanin biosynthesis and abiotic stress responses, but also provide a powerful complementary tool based on metabolites-to-genes analysis by mGWAS for functional gene identification andpromising candidate in future rice breeding and improvement.

Genomic variation in weedy and cultivated broomcorn millet accessions uncovers the genetic architecture of agronomic traits

Large-scale genomic variations are fundamental resources for crop genetics and breeding. Here we sequenced 1,904 genomes of broomcorn millet to an average of 40× sequencing depth and constructed a comprehensive variation map of weedy and cultivated accessions. Being one of the oldest cultivated crops, broomcorn millet has extremely low nucleotide diversity and remarkably rapid decay of linkage disequilibrium. Genome-wide association studies identified 186 loci for 12 agronomic traits. Many causative candidate genes, such as PmGW8 for grain size and PmLG1 for panicle shape, showed strong selection signatures during domestication. Weedy accessions contained many beneficial variations for the grain traits that are largely lost in cultivated accessions. Weedy and cultivated broomcorn millet have adopted different loci controlling flowering time for regional adaptation in parallel. Our study uncovers the unique population genomic features of broomcorn millet and provides an agronomically important resource for cereal crops.

Revisiting growth-defence trade-offs and breeding strategies in crops

Plants have evolved a multi-layered immune system to fight off pathogens. However, immune activation is costly and is often associated with growth and development penalty. In crops, yield is the main breeding target and is usually affected by high disease resistance. Therefore, proper balance between growth and defence is critical for achieving efficient crop improvement. This review highlights recent advances in attempts designed to alleviate the trade-offs between growth and disease resistance in crops mediated by resistance (R) genes, susceptibility (S) genes and pleiotropic genes. We also provide an update on strategies for optimizing the growth-defence trade-offs to breed future crops with desirable disease resistance and high yield.

Functional differentiation and genetic diversity of rice cation exchanger (CAX) genes and their potential use in rice improvement

Cation exchanger (CAX) genes play an important role in plant growth/development and response to biotic and abiotic stresses. Here, we tried to obtain important information on the functionalities and phenotypic effects of CAX gene family by systematic analyses of their expression patterns, genetic diversity (gene CDS haplotypes, structural variations, gene presence/absence variations) in 3010 rice genomes and nine parents of 496 Huanghuazhan introgression lines, the frequency shifts of the predominant gcHaps at these loci to artificial selection during modern breeding, and their association with tolerances to several abiotic stresses. Significant amounts of variation also exist in the cis-regulatory elements (CREs) of the OsCAX gene promoters in 50 high-quality rice genomes. The functional differentiation of OsCAX gene family were reflected primarily by their tissue and development specific expression patterns and in varied responses to different treatments, by unique sets of CREs in their promoters and their associations with specific agronomic traits/abiotic stress tolerances. Our results indicated that OsCAX1a and OsCAX2 as general signal transporters were in many processes of rice growth/development and responses to diverse environments, but they might be of less value in rice improvement. OsCAX1b, OsCAX1c, OsCAX3 and OsCAX4 was expected to be of potential value in rice improvement because of their associations with specific traits, responsiveness to specific abiotic stresses or phytohormones, and relatively high gcHap and CRE diversity. Our strategy was demonstrated to be highly efficient to obtain important genetic information on genes/alleles of specific gene family and can be used to systematically characterize the other rice gene families.

Genome-Wide Association Study of Early Vigour-Related Traits for a Rice (Oryza sativa L.) japonica Diversity Set Grown in Aerobic Conditions

Aerobic rice production is a relatively new system in which rice is direct-seeded and grown in non-flooded but well-watered conditions to improve water productivity. Early vigour-related traits are likely to be important in aerobic conditions. This study aimed to identify quantitative trait loci (QTL) and candidate genes associated with early vigour-related traits in aerobic conditions using a japonica rice diversity set. Field experiments and glasshouse experiments conducted under aerobic conditions revealed significant genotypic variation in early vigour-related traits. Genome-wide association analysis identified 32 QTL associated with early vigour-related traits. Notably, two QTL, qAEV1.5 and qAEV8, associated with both early vigour score and mesocotyl length, explained up to 22.1% of the phenotypic variance. In total, 23 candidate genes related to plant growth development and abiotic stress response were identified in the two regions. This study provides novel insights into the genetic basis of early vigour under aerobic conditions. Validation of identified QTL and candidate genes in different genetic backgrounds is crucial for future studies. Moreover, testing the effect of QTL on yield under different environments would be valuable. After validation, these QTL and genes can be considered for developing markers in marker-assisted selection for aerobic rice production.

Genomic basis determining root system architecture in maize

KEY MESSAGE

A total of 389 and 344 QTLs were identified by GWAS and QTL mapping explaining accumulatively 32.2-65.0% and 23.7-63.4% of phenotypic variation for 14 shoot-borne root traits using more than 1300 individuals across multiple field trails. Efficient nutrient and water acquisition from soils depends on the root system architecture (RSA). However, the genetic determinants underlying RSA in maize remain largely unexplored. In this study, we conducted a comprehensive genetic analysis for 14 shoot-borne root traits using 513 inbred lines and 800 individuals from four recombinant inbred line (RIL) populations at the mature stage across multiple field trails. Our analysis revealed substantial phenotypic variation for these 14 root traits, with a total of 389 and 344 QTLs identified through genome-wide association analysis (GWAS) and linkage analysis, respectively. These QTLs collectively explained 32.2-65.0% and 23.7-63.4% of the trait variation within each population. Several a priori candidate genes involved in auxin and cytokinin signaling pathways, such as IAA26, ARF2, LBD37 and CKX3, were found to co-localize with these loci. In addition, a total of 69 transcription factors (TFs) from 27 TF families (MYB, NAC, bZIP, bHLH and WRKY) were found for shoot-borne root traits. A total of 19 genes including PIN3, LBD15, IAA32, IAA38 and ARR12 and 19 GWAS signals were overlapped with selective sweeps. Further, significant additive effects were found for root traits, and pyramiding the favorable alleles could enhance maize root development. These findings could contribute to understand the genetic basis of root development and evolution, and provided an important genetic resource for the genetic improvement of root traits in maize.

Genome-wide association study and development of molecular markers for yield and quality traits in peanut (Arachis hypogaea L.)

BACKGROUND

This study aims to decipher the genetic basis governing yield components and quality attributes of peanuts, a critical aspect for advancing molecular breeding techniques. Integrating genotype re-sequencing and phenotypic evaluations of seven yield components and two grain quality traits across four distinct environments allowed for the execution of a genome-wide association study (GWAS).

RESULTS

The nine phenotypic traits were all continuous and followed a normal distribution. The broad heritability ranged from 88.09 to 98.08%, and the genotype-environment interaction effects were all significant. There was a highly significant negative correlation between protein content (PC) and oil content (OC). The 10× genome re-sequencing of 199 peanut accessions yielded a total of 631,988 high-quality single nucleotide polymorphisms (SNPs), with 374 significant SNP loci identified in association with the nine traits of interest. Notably, 66 of these pertinent SNPs were detected in multiple environments, and 48 of them were linked to multiple traits of interest. Five loci situated on chromosome 16 (Chr16) exhibited pleiotropic effects on yield traits, accounting for 17.64-32.61% of the observed phenotypic variation. Two loci on Chr08 were found to be strongly associated with protein and oil contents, accounting for 12.86% and 14.06% of their respective phenotypic variations, respectively. Linkage disequilibrium (LD) block analysis of these seven loci unraveled five nonsynonymous variants, leading to the identification of one yield-related candidate gene and two quality-related candidate genes. The correlation between phenotypic variation and SNP loci in these candidate genes was validated by Kompetitive allele-specific PCR (KASP) marker analysis.

CONCLUSIONS

Overall, molecular markers were developed for genetic loci associated with yield and quality traits through a GWAS investigation of 199 peanut accessions across four distinct environments. These molecular tools can aid in the development of desirable peanut germplasm with an equilibrium of yield and quality through marker-assisted breeding.

Potassium transporter OsHAK9 regulates seed germination under salt stress by preventing gibberellin degradation through mediating OsGA2ox7 in rice

Soil salinity has a major impact on rice seed germination, severely limiting rice production. Herein, a rice germination defective mutant under salt stress (gdss) was identified by using chemical mutagenesis. The GDSS gene was detected via MutMap and shown to encode potassium transporter OsHAK9. Phenotypic analysis of complementation and mutant lines demonstrated that OsHAK9 was an essential regulator responsible for seed germination under salt stress. OsHAK9 is highly expressed in germinating seed embryos. Ion contents and non-invasive micro-test technology results showed that OsHAK9 restricted K+ efflux in salt-exposed germinating seeds for the balance of K+/Na+. Disruption of OsHAK9 significantly reduced gibberellin 4 (GA4) levels, and the germination defective phenotype of oshak9a was partly rescued by exogenous GA3 treatment under salt stress. RNA sequencing (RNA-seq) and real-time quantitative polymerase chain reaction analysis demonstrated that the disruption of OsHAK9 improved the GA-deactivated gene OsGA2ox7 expression in germinating seeds under salt stress, and the expression of OsGA2ox7 was significantly inhibited by salt stress. Null mutants of OsGA2ox7 created using clustered, regularly interspaced, short palindromic repeat (CRISPR)/CRISPR-associated nuclease 9 approach displayed a dramatically increased seed germination ability under salt stress. Overall, our results highlight that OsHAK9 regulates seed germination performance under salt stress involving preventing GA degradation by mediating OsGA2ox7, which provides a novel clue about the relationship between GA and OsHAKs in rice.

GWAS identifies two important genes involved in Chinese chestnut weight and leaf length regulation

There are many factors that affect the yield of Chinese chestnut (Castanea mollissima), with single nut weight (SNW) being one of the most important. Leaf length is also related to Chinese chestnut yield. However, the genetic architecture and gene function associated with Chinese chestnut nut yield have not been fully explored. In this study, we performed genotyping by sequencing 151 Chinese chestnut cultivars, followed by a genome-wide association study (GWAS) on six horticultural traits. First, we analyzed the phylogeny of the Chinese chestnut and found that the Chinese chestnut cultivars divided into two ecotypes, a northern and southern cultivar group. Differences between the cultivated populations were found in the pathways of plant growth and adaptation to the environment. In the selected regions, we also found interesting tandemly arrayed genes that may influence Chinese chestnut traits and environmental adaptability. To further investigate which horticultural traits were selected, we performed a GWAS using six horticultural traits from 151 cultivars. Forty-five loci that strongly associated with horticultural traits were identified, and six genes highly associated with these traits were screened. In addition, a candidate gene associated with SNW, APETALA2 (CmAP2), and another candidate gene associated with leaf length (LL), CRYPTOCHROME INTERACTING BASIC HELIX-LOOP-HELIX 1 (CmCIB1), were verified in Chinese chestnut and Arabidopsis (Arabidopsis thaliana). Our results showed that CmAP2 affected SNW by negatively regulating cell size. CmCIB1 regulated the elongation of new shoots and leaves by inducing cell elongation, potentially affecting photosynthesis. This study provided valuable information and insights for Chinese chestnut breeding research.

A double-stranded RNA binding protein enhances drought resistance via protein phase separation in rice

Drought stress significantly impacts global rice production, highlighting the critical need to understand the genetic basis of drought resistance in rice. Here, through a genome-wide association study, we reveal that natural variations in DROUGHT RESISTANCE GENE 9 (DRG9), encoding a double-stranded RNA (dsRNA) binding protein, contribute to drought resistance. Under drought stress, DRG9 condenses into stress granules (SGs) through liquid-liquid phase separation via a crucial α-helix. DRG9 recruits the mRNAs of OsNCED4, a key gene for the biosynthesis of abscisic acid, into SGs and protects them from degradation. In drought-resistant DRG9 allele, natural variations in the coding region, causing an amino acid substitution (G267F) within the zinc finger domain, increase DRG9's binding ability to OsNCED4 mRNA and enhance drought resistance. Introgression of the drought-resistant DRG9 allele into the elite rice Huanghuazhan significantly improves its drought resistance. Thus, our study underscores the role of a dsRNA-binding protein in drought resistance and its promising value in breeding drought-resistant rice.

Population genomic analysis unravels the evolutionary roadmap of pericarp color in rice

Pigmented rice stands out for its nutritional value and is gaining more and more attention. Wild rice, domesticated red rice, and weedy rice all have a red pericarp and a comprehensive genetic background in terms of the red-pericarp phenotype. We performed population genetic analyses using 5104 worldwide rice accessions, including 2794 accessions with red or black pericarps, 85 of which were newly sequenced in this study. The results suggested an evolutionary trajectory of red landraces originating from wild rice, and the split times of cultivated red and white rice populations were estimated to be within the past 3500 years. Cultivated red rice was found to feralize to weedy rice, and weedy rice could be further re-domesticated to cultivated red rice. A genome-wide association study based on the 2794 accessions with pigmented pericarps revealed several new candidate genes associated with the red-pericarp trait for further functional characterization. Our results provide genomic evidence for the origin of pigmented rice and a valuable genomic resource for genetic investigation and breeding of pigmented rice.

High-throughput UAV-based rice panicle detection and genetic mapping of heading-date-related traits

Introduction

Rice (Oryza sativa) serves as a vital staple crop that feeds over half the world's population. Optimizing rice breeding for increasing grain yield is critical for global food security. Heading-date-related or Flowering-time-related traits, is a key factor determining yield potential. However, traditional manual phenotyping methods for these traits are time-consuming and labor-intensive.

Method

Here we show that aerial imagery from unmanned aerial vehicles (UAVs), when combined with deep learning-based panicle detection, enables high-throughput phenotyping of heading-date-related traits. We systematically evaluated various state-of-the-art object detectors on rice panicle counting and identified YOLOv8-X as the optimal detector.

Results

Applying YOLOv8-X to UAV time-series images of 294 rice recombinant inbred lines (RILs) allowed accurate quantification of six heading-date-related traits. Utilizing these phenotypes, we identified quantitative trait loci (QTL), including verified loci and novel loci, associated with heading date.

Discussion

Our optimized UAV phenotyping and computer vision pipeline may facilitate scalable molecular identification of heading-date-related genes and guide enhancements in rice yield and adaptation.

Designing salt stress-resilient crops: Current progress and future challenges

Excess soil salinity affects large regions of land and is a major hindrance to crop production worldwide. Therefore, understanding the molecular mechanisms of plant salt tolerance has scientific importance and practical significance. In recent decades, studies have characterized hundreds of genes associated with plant responses to salt stress in different plant species. These studies have substantially advanced our molecular and genetic understanding of salt tolerance in plants and have introduced an era of molecular design breeding of salt-tolerant crops. This review summarizes our current knowledge of plant salt tolerance, emphasizing advances in elucidating the molecular mechanisms of osmotic stress tolerance, salt-ion transport and compartmentalization, oxidative stress tolerance, alkaline stress tolerance, and the trade-off between growth and salt tolerance. We also examine recent advances in understanding natural variation in the salt tolerance of crops and discuss possible strategies and challenges for designing salt stress-resilient crops. We focus on the model plant Arabidopsis (Arabidopsis thaliana) and the four most-studied crops: rice (Oryza sativa), wheat (Triticum aestivum), maize (Zea mays), and soybean (Glycine max).

A wild rice CSSL population facilitated identification of salt tolerance genes and rice germplasm innovation

Salt stress is one of the major factors that limits rice production. Therefore, identification of salt-tolerant alleles from wild rice is important for rice breeding. In this study, we constructed a set of chromosome segment substitution lines (CSSLs) using wild rice as the donor parent and cultivated rice Nipponbare (Nip) as the recurrent parent. Salt tolerance germinability (STG) was evaluated, and its association with genotypes was determined using this CSSL population. We identified 17 QTLs related to STG. By integrating the transcriptome and genome data, four candidate genes were identified, including the previously reported AGO2 and WRKY53. Compared with Nip, wild rice AGO2 has a structure variation in its promoter region and the expression levels were upregulated under salt treatments; wild rice WRKY53 also has natural variation in its promoter region, and the expression levels were downregulated under salt treatments. Wild rice AGO2 and WRKY53 alleles have combined effects for improving salt tolerance at the germination stage. One CSSL line, CSSL118 that harbors these two alleles was selected. Compared with the background parent Nip, CSSL118 showed comprehensive salt tolerance and higher yield, with improved transcript levels of reactive oxygen species scavenging genes. Our results provided promising genes and germplasm resources for future rice salt tolerance breeding.

Extreme trait GWAS (Et-GWAS): Unraveling rare variants in the 3,000 rice genome

Identifying high-impact, rare genetic variants associated with specific traits is crucial for crop improvement. The 3,010 rice genome (3K RG) dataset offers a valuable resource for discovering genomic regions with potential applications in crop breeding. We used Extreme Trait GWAS (Et-GWAS), employing bulk pooling and allele frequency measurement to efficiently extract rare variants from the 3K RG. This innovative approach facilitates the detection of associations between genetic variants and target traits, concentrating and quantifying rare alleles. In our study, on grain yield under drought stress, Et-GWAS successfully identified five key genes (OsPP2C11, OsK5.2, OsIRO2, OsPEX1, and OsPWA1) known for enhancing yield under drought. In addition, we examined the overlap of our results with previously reported qDTY-QTLs and observed that OsUCH1 and OsUCH2 genes were located within qDTY2.2 We compared Et-GWAS with conventional GWAS, finding it effectively capturing most candidate genes associated with the target trait. Validation with resistant starch showed similar results. To enhance user-friendliness, we developed a GUI for Et-GWAS; https://et-gwas.shinyapps.io/Et-GWAS/.

A genomic variation map provides insights into peanut diversity in China and associations with 28 agronomic traits

Peanut (Arachis hypogaea L.) is an important allotetraploid oil and food legume crop. China is one of the world's largest peanut producers and consumers. However, genomic variations underlying the migration and divergence of peanuts in China remain unclear. Here we reported a genome-wide variation map based on the resequencing of 390 peanut accessions, suggesting that peanuts might have been introduced into southern and northern China separately, forming two cultivation centers. Selective sweep analysis highlights asymmetric selection between the two subgenomes during peanut improvement. A classical pedigree from South China offers a context for the examination of the impact of artificial selection on peanut genome. Genome-wide association studies identified 22,309 significant associations with 28 agronomic traits, including candidate genes for plant architecture and oil biosynthesis. Our findings shed light on peanut migration and diversity in China and provide valuable genomic resources for peanut improvement.

Transcription factor encoding gene OsC1 regulates leaf sheath color through anthocyanidin metabolism in Oryza rufipogon and Oryza sativa

Carbohydrates, proteins, lipids, minerals and vitamins are nutrient substances commonly seen in rice grains, but anthocyanidin, with benefit for plant growth and animal health, exists mainly in the common wild rice but hardly in the cultivated rice. To screen the rice germplasm with high intensity of anthocyanidins and identify the variations, we used metabolomics technique and detected significant different accumulation of anthocyanidins in common wild rice (Oryza rufipogon, with purple leaf sheath) and cultivated rice (Oryza sativa, with green leaf sheath). In this study, we identified and characterized a well-known MYB transcription factor, OsC1, through phenotypic (leaf sheath color) and metabolic (metabolite profiling) genome-wide association studies (pGWAS and mGWAS) in 160 common wild rice (O. rufipogon) and 151 cultivated (O. sativa) rice varieties. Transgenic experiments demonstrated that biosynthesis and accumulation of cyanidin-3-Galc, cyanidin 3-O-rutinoside and cyanidin O-syringic acid, as well as purple pigmentation in leaf sheath were regulated by OsC1. A total of 25 sequence variations of OsC1 constructed 16 functional haplotypes (higher accumulation of the three anthocyanidin types within purple leaf sheath) and 9 non-functional haplotypes (less accumulation of anthocyanidins within green leaf sheath). Three haplotypes of OsC1 were newly identified in our germplasm, which have potential values in functional genomics and molecular breeding of rice. Gene-to-metabolite analysis by mGWAS and pGWAS provides a useful and efficient tool for functional gene identification and omics-based crop genetic improvement.

New insights into QTNs and potential candidate genes governing rice yield via a multi-model genome-wide association study

BACKGROUND

Rice (Oryza sativa L.) is one of the globally important staple food crops, and yield-related traits are prerequisites for improved breeding efficiency in rice. Here, we used six different genome-wide association study (GWAS) models for 198 accessions, with 553,229 single nucleotide markers (SNPs) to identify the quantitative trait nucleotides (QTNs) and candidate genes (CGs) governing rice yield.

RESULTS

Amongst the 73 different QTNs in total, 24 were co-localized with already reported QTLs or loci in previous mapping studies. We obtained fifteen significant QTNs, pathway analysis revealed 10 potential candidates within 100kb of these QTNs that are predicted to govern plant height, days to flowering, and plot yield in rice. Based on their superior allelic information in 20 elite and 6 inferior genotypes, we found a higher percentage of superior alleles in the elite genotypes in comparison to inferior genotypes. Further, we implemented expression analysis and enrichment analysis enabling the identification of 73 candidate genes and 25 homologues of Arabidopsis, 19 of which might regulate rice yield traits. Of these candidate genes, 40 CGs were found to be enriched in 60 GO terms of the studied traits for instance, positive regulator metabolic process (GO:0010929), intracellular part (GO:0031090), and nucleic acid binding (GO:0090079). Haplotype and phenotypic variation analysis confirmed that LOC_OS09G15770, LOC_OS02G36710 and LOC_OS02G17520 are key candidates associated with rice yield.

CONCLUSIONS

Overall, we foresee that the QTNs, putative candidates elucidated in the study could summarize the polygenic regulatory networks controlling rice yield and be useful for breeding high-yielding varieties.

Identification of Novel QTL for Mercury Accumulation in Maize Using an Enlarged SNP Panel

Mercury (Hg) pollution not only poses a threat to the environment but also adversely affects the growth and development of plants, with potential repercussions for animals and humans through bioaccumulation in the food chain. Maize, a crucial source of food, industrial materials, and livestock feed, requires special attention in understanding the genetic factors influencing mercury accumulation. Developing maize varieties with low mercury accumulation is vital for both maize production and human health. In this study, a comprehensive genome-wide association study (GWAS) was conducted using an enlarged SNP panel comprising 1.25 million single nucleotide polymorphisms (SNPs) in 230 maize inbred lines across three environments. The analysis identified 111 significant SNPs within 78 quantitative trait loci (QTL), involving 169 candidate genes under the Q model. Compared to the previous study, the increased marker density and optimized statistical model led to the discovery of 74 additional QTL, demonstrating improved statistical power. Gene ontology (GO) enrichment analysis revealed that most genes participate in arsenate reduction and stress responses. Notably, GRMZM2G440968, which has been reported in previous studies, is associated with the significant SNP chr6.S_155668107 in axis tissue. It encodes a cysteine proteinase inhibitor, implying its potential role in mitigating mercury toxicity by inhibiting cysteine. Haplotype analyses provided further insights, indicating that lines carrying hap3 exhibited the lowest mercury content compared to other haplotypes. In summary, our study significantly enhances the statistical power of GWAS, identifying additional genes related to mercury accumulation and metabolism. These findings offer valuable insights into unraveling the genetic basis of mercury content in maize and contribute to the development of maize varieties with low mercury accumulation.

Identification and Regulation of Hypoxia-Tolerant and Germination-Related Genes in Rice

In direct seeding, hypoxia is a major stress faced by rice plants. Therefore, dissecting the response mechanism of rice to hypoxia stress and the molecular regulatory network is critical to the development of hypoxia-tolerant rice varieties and direct seeding of rice. This review summarizes the morphological, physiological, and ecological changes in rice under hypoxia stress, the discovery of hypoxia-tolerant and germination-related genes/QTLs, and the latest research on candidate genes, and explores the linkage of hypoxia tolerance genes and their distribution in indica and japonica rice through population variance analysis and haplotype network analysis. Among the candidate genes, OsMAP1 is a typical gene located on the MAPK cascade reaction for indica-japonica divergence; MHZ6 is involved in both the MAPK signaling and phytohormone transduction pathway. MHZ6 has three major haplotypes and one rare haplotype, with Hap3 being dominated by indica rice varieties, and promotes internode elongation in deep-water rice by activating the SD1 gene. OsAmy3D and Adh1 have similar indica-japonica varietal differentiation, and are mainly present in indica varieties. There are three high-frequency haplotypes of OsTPP7, namely Hap1 (n = 1109), Hap2 (n = 1349), and Hap3 (n = 217); Hap2 is more frequent in japonica, and the genetic background of OsTPP7 was derived from the japonica rice subpopulation. Further artificial selection, natural domestication, and other means to identify more resistance mechanisms of this gene may facilitate future research to breed superior rice cultivars. Finally, this study discusses the application of rice hypoxia-tolerant germplasm in future breeding research.

Structure-based prediction of protein-protein interaction network in rice

Comprehensive protein-protein interaction (PPI) maps are critical for understanding the functional organization of the proteome, but challenging to produce experimentally. Here, we developed a computational method for predicting PPIs based on protein docking. Evaluation of performance on benchmark sets demonstrated the ability of the docking-based method to accurately identify PPIs using predicted protein structures. By employing the docking-based method, we constructed a structurally resolved PPI network consisting of 24,653 interactions between 2,131 proteins, which greatly extends the current knowledge on the rice protein-protein interactome. Moreover, we mapped the trait-associated single nucleotide polymorphisms (SNPs) to the structural interactome, and computationally identified 14 SNPs that had significant consequences on PPI network. The protein structural interactome map provided a resource to facilitate functional investigation of PPI-perturbing alleles associated with agronomically important traits in rice.

A Genome-Wide Association Study Reveals the Genetic Mechanisms of Nutrient Accumulation in Spinach

Spinach is a significant source of vitamins, minerals, and antioxidants. These nutrients make it delicious and beneficial for human health. However, the genetic mechanism underlying the accumulation of nutrients in spinach remains unclear. In this study, we analyzed the content of chlorophyll a, chlorophyll b, oxalate, nitrate, crude fiber, soluble sugars, manganese, copper, and iron in 62 different spinach accessions. Additionally, 3,356,182 high-quality, single-nucleotide polymorphisms were found using resequencing and used in a genome-wide association study. A total of 2077 loci were discovered that significantly correlated with the concentrations of the nutritional elements. Data mining identified key genes in these intervals for four traits: chlorophyll, oxalate, soluble sugar, and Fe. Our study provides insights into the genetic architecture of nutrient variation and facilitates spinach breeding for good nutrition.

Genome-wide association studies for a comprehensive understanding of the genetic architecture of culm strength and yield traits in rice

Lodging resistance in rice is a complex trait determined by culm morphological and culm physical strength traits, and these traits are a major determinant of yield. We made a detailed analysis of various component traits with the aim of deriving optimized parameters for measuring culm strength. Genotyping by sequencing (GBS)-based genome-wide association study (GWAS) was employed among 181 genotypes for dissecting the genetic control of culm strength traits. The VanRaden kinship algorithm using 6,822 filtered single-nucleotide polymorphisms (SNPs) revealed the presence of two sub-groups within the association panel with kinship values concentrated at<0.5 level, indicating greater diversity among the genotypes. A wide range of phenotypic variation and high heritability for culm strength and yield traits were observed over two seasons, as reflected in best linear unbiased prediction (BLUP) estimates. The multi-locus model for GWAS resulted in the identification of 15 highly significant associations (p< 0.0001) for culm strength traits. Two novel major effect marker-trait associations (MTAs) for section modulus and bending stress were identified on chromosomes 2 and 12 with a phenotypic variance of 21.87% and 10.14%, respectively. Other MTAs were also noted in the vicinity of previously reported putative candidate genes for lodging resistance, providing an opportunity for further research on the biochemical basis of culm strength. The quantitative trait locus (QTL) hotspot identified on chromosome 12 with the synergistic association for culm strength trait (section modulus, bending stress, and internode breaking weight) and grain number can be considered a novel genomic region that can serve a dual purpose of enhancing culm strength and grain yield. Elite donors in the indica background with beneficial alleles of the identified major QTLs could be a valuable resource with greater significance in practical plant breeding programs focusing on improving lodging resistance in rice.

Genome-wide association study reveals GmFulb as candidate gene for maturity time and reproductive length in soybeans (Glycine max)

The ability of soybean [Glycine max (L.) Merr.] to adapt to different latitudes is attributed to genetic variation in major E genes and quantitative trait loci (QTLs) determining flowering time (R1), maturity (R8), and reproductive length (RL). Fully revealing the genetic basis of R1, R8, and RL in soybeans is necessary to enhance genetic gains in soybean yield improvement. Here, we performed a genome-wide association analysis (GWA) with 31,689 single nucleotide polymorphisms (SNPs) to detect novel loci for R1, R8, and RL using a soybean panel of 329 accessions with the same genotype for three major E genes (e1-as/E2/E3). The studied accessions were grown in nine environments and observed for R1, R8 and RL in all environments. This study identified two stable peaks on Chr 4, simultaneously controlling R8 and RL. In addition, we identified a third peak on Chr 10 controlling R1. Association peaks overlap with previously reported QTLs for R1, R8, and RL. Considering the alternative alleles, significant SNPs caused RL to be two days shorter, R1 two days later and R8 two days earlier, respectively. We identified association peaks acting independently over R1 and R8, suggesting that trait-specific minor effect loci are also involved in controlling R1 and R8. From the 111 genes highly associated with the three peaks detected in this study, we selected six candidate genes as the most likely cause of R1, R8, and RL variation. High correspondence was observed between a modifying variant SNP at position 04:39294836 in GmFulb and an association peak on Chr 4. Further studies using map-based cloning and fine mapping are necessary to elucidate the role of the candidates we identified for soybean maturity and adaptation to different latitudes and to be effectively used in the marker-assisted breeding of cultivars with optimal yield-related traits.

Efficient identification of QTL for agronomic traits in foxtail millet (Setaria italica) using RTM- and MLM-GWAS

KEY MESSAGE

Eleven QTLs for agronomic traits were identified by RTM- and MLM-GWAS, putative candidate genes were predicted and two markers for grain weight were developed and validated. Foxtail millet (Setaria italica), the second most cultivated millet crop after pearl millet, is an important grain crop in arid regions. Seven agronomic traits of 408 diverse foxtail millet accessions from 15 provinces in China were evaluated in three environments. They were clustered into two divergent groups based on genotypic data using ADMIXTURE, which was highly consistent with their geographical distribution. Two models for genome-wide association studies (GWAS), namely restricted two-stage multi-locus multi-allele (RTM)-GWAS and mixed linear model (MLM)-GWAS, were used to dissect the genetic architecture of the agronomic traits based on 13,723 SNPs. Eleven quantitative trait loci (QTLs) for seven traits were identified using two models (RTM- and MLM-GWAS). Among them, five were considered stable QTLs that were identified in at least two environments using MLM-GWAS. One putative candidate gene (SETIT_006045mg, Chr4: 744,701-746,852) that can enhance grain weight per panicle was identified based on homologous gene comparison and gene expression analysis and was validated by haplotype analysis of 330 accessions with high-depth (10×) resequencing data (unpublished). In addition, homologous gene comparison and haplotype analysis identified one putative foxtail millet ortholog (SETIT_032906mg, Chr2: 5,020,600-5,029,771) with rice affecting the target traits. Two markers (cGWP6045 and kTGW2906) were developed and validated and can be used for marker-assisted selection of foxtail millet with high grain weight. The results provide a fundamental resource for foxtail millet genetic research and breeding and demonstrate the power of integrating RTM- and MLM-GWAS approaches as a complementary strategy for investigating complex traits in foxtail millet.

Multi-model genome-wide association studies for appearance quality in rice

Improving the quality of the appearance of rice is critical to meet market acceptance. Mining putative quality-related genes has been geared towards the development of effective breeding approaches for rice. In the present study, two SL-GWAS (CMLM and MLM) and three ML-GWAS (FASTmrEMMA, mrMLM, and FASTmrMLM) genome-wide association studies were conducted in a subset of 3K-RGP consisting of 198 rice accessions with 553,831 SNP markers. A total of 594 SNP markers were identified using the mixed linear model method for grain quality traits. Additionally, 70 quantitative trait nucleotides (QTNs) detected by the ML-GWAS models were strongly associated with grain aroma (AR), head rice recovery (HRR, %), and percentage of grains with chalkiness (PGC, %). Finally, 39 QTNs were identified using single- and multi-locus GWAS methods. Among the 39 reliable QTNs, 20 novel QTNs were identified for the above-mentioned three quality-related traits. Based on annotation and previous studies, four functional candidate genes (LOC_Os01g66110, LOC_Os01g66140, LOC_Os07g44910, and LOC_Os02g14120) were found to influence AR, HRR (%), and PGC (%), which could be utilized in rice breeding to improve grain quality traits.

Genome-Wide Association Study of Arsenic Accumulation in Polished Rice

The accumulation of arsenic (As) in rice poses a significant threat to food safety and human health. Breeding rice varieties with low As accumulation is an effective strategy for mitigating the health risks associated with arsenic-contaminated rice. However, the genetic mechanisms underlying As accumulation in rice grains remain incompletely understood. We evaluated the As accumulation capacity of 313 diverse rice accessions grown in As-contaminated soils with varying As concentrations. Six rice lines with low As accumulation were identified. Additionally, a genome-wide association studies (GWAS) analysis identified 5 QTLs significantly associated with As accumulation, with qAs4 being detected in both of the experimental years. Expression analysis demonstrated that the expression of LOC_Os04g50680, which encodes an MYB transcription factor, was up-regulated in the low-As-accumulation accessions compared to the high-As-accumulation accessions after As treatment. Therefore, LOC_Os04g50680 was selected as a candidate gene for qAs4. These findings provide insights for exploiting new functional genes associated with As accumulation and facilitating the development of low-As-accumulation rice varieties through marker-assisted breeding.

Genome-wide association study on resistance of cultivated soybean to Fusarium oxysporum root rot in Northeast China

BACKGROUND

Fusarium oxysporum is a prevalent fungal pathogen that diminishes soybean yield through seedling disease and root rot. Preventing Fusarium oxysporum root rot (FORR) damage entails on the identification of resistance genes and developing resistant cultivars. Therefore, conducting fine mapping and marker development for FORR resistance genes is of great significance for fostering the cultivation of resistant varieties. In this study, 350 soybean germplasm accessions, mainly from Northeast China, underwent genotyping using the SoySNP50K Illumina BeadChip, which includes 52,041 single nucleotide polymorphisms (SNPs). Their resistance to FORR was assessed in a greenhouse. Genome-wide association studies utilizing the general linear model, mixed linear model, compressed mixed linear model, and settlement of MLM under progressively exclusive relationship models were conducted to identify marker-trait associations while effectively controlling for population structure.

RESULTS

The results demonstrated that these models effectively managed population structure. Eight SNP loci significantly associated with FORR resistance in soybean were detected, primarily located on Chromosome 6. Notably, there was a strong linkage disequilibrium between the large-effect SNPs ss715595462 and ss715595463, contributing substantially to phenotypic variation. Within the genetic interval encompassing these loci, 28 genes were present, with one gene Glyma.06G088400 encoding a protein kinase family protein containing a leucine-rich repeat domain identified as a potential candidate gene in the reference genome of Williams82. Additionally, quantitative real-time reverse transcription polymerase chain reaction analysis evaluated the gene expression levels between highly resistant and susceptible accessions, focusing on primary root tissues collected at different time points after F. oxysporum inoculation. Among the examined genes, only this gene emerged as the strongest candidate associated with FORR resistance.

CONCLUSIONS

The identification of this candidate gene Glyma.06G088400 improves our understanding of soybean resistance to FORR and the markers strongly linked to resistance can be beneficial for molecular marker-assisted selection in breeding resistant soybean accessions against F. oxysporum.

10k-level integrated rice database shows power for exploiting rare variants

This Highlight features a recent study by Shang Lianguang and Qian Qian's groups, who re-analyzed published resequencing data covering 10,548 accessions of Asian cultivated rice Oryza sativa and wild rice Oryza rufipogon from 98 countries worldwide to generate a super-large rice genomic variation dataset.

Integration of genome-wide association studies reveal loci associated with salt tolerance score of rice at the seedling stage

Salt threatens rice cultivation in many countries. Hence, breeding new varieties with high salt tolerance is important.A panel of 2,391 rice accessions from the 3 K Rice Genome Project was selected to evaluate salt tolerance via the standard evaluation score (SES) in hydroponics under 60 mM NaCl at the seedling stage. Three sub-population panels including 1,332, 628, and 386 accessions from the original 2,391 ones were constructed based on low relatedness revealed by a phylogenetic tree generated by Archaeopteryx Tree. A genome-wide association study (GWAS) was conducted on the entire and sub-population panels using SES data and a selection of 5, 10, 20, and 40% of SNPs selected from the original 1,011,601 SNPs by filtering minor allele frequency > 5% and missing rate < 5%. To perform GWAS, three methods implemented in three different software packages were utilized.Using the integration of GWAS programs, a total of four QTLs associated with SES scores were identified in different panels. Some QTLs co-located with previously detected QTL-related traits. qSES1.1 was detected in three panels, qSES1.3 and qSES2.1 in two panels, and qSES3.1 in one panel through GWAS by all three methods used and selected SNPs. These four QTLs were selected to detect candidate genes. Combining gene-based association study plus haplotype analysis in the entire population and the three sub-populations let us shortlist three candidate genes, viz. LOC_Os01g23640 and LOC_Os01g23680 for qSES1.1, and LOC_Os01g71240 for qSES1.3 region affecting salt tolerance. The identified QTLs and candidate genes provided useful materials and genetic information for future functional characterization and genetic improvement of salt tolerance in rice.

Knockout of transcription factor OsERF65 enhances ROS scavenging ability and confers resistance to rice sheath blight

Rice sheath blight (ShB) is a devastating disease that severely threatens rice production worldwide. Induction of cell death represents a key step during infection by the ShB pathogen Rhizoctonia solani. Nonetheless, the underlying mechanisms remain largely unclear. In the present study, we identified a rice transcription factor, OsERF65, that negatively regulates resistance to ShB by suppressing cell death. OsERF65 was significantly upregulated by R. solani infection in susceptible cultivar Lemont and was highly expressed in the leaf sheath. Overexpression of OsERF65 (OsERF65OE) decreased rice resistance, while the knockout mutant (oserf65) exhibited significantly increased resistance against ShB. The transcriptome assay revealed that OsERF65 repressed the expression of peroxidase genes after R. solani infection. The antioxidative enzyme activity was significantly increased in oserf65 plants but reduced in OsERF65OE plants. Consistently, hydrogen peroxide content was apparently reduced in oserf65 plants but accumulated in OsERF65OE plants. OsERF65 directly bound to the GCC box in the promoter regions of four peroxidase genes and suppressed their transcription, reducing the ability to scavenge reactive oxygen species (ROS). The oserf65 mutant exhibited a slight decrease in plant height but increased grain yield. Overall, our results revealed an undocumented role of OsERF65 that acts as a crucial regulator of rice resistance to R. solani and a potential target for improving both ShB resistance and rice yield.

Transcriptome-wide association analyses reveal the impact of regulatory variants on rice panicle architecture and causal gene regulatory networks

Panicle architecture is a key determinant of rice grain yield and is mainly determined at the 1-2 mm young panicle stage. Here, we investigated the transcriptome of the 1-2 mm young panicles from 275 rice varieties and identified thousands of genes whose expression levels were associated with panicle traits. Multimodel association studies suggested that many small-effect genetic loci determine spikelet per panicle (SPP) by regulating the expression of genes associated with panicle traits. We found that alleles at cis-expression quantitative trait loci of SPP-associated genes underwent positive selection, with a strong preference for alleles increasing SPP. We further developed a method that integrates the associations of cis- and trans-expression components of genes with traits to identify causal genes at even small-effect loci and construct regulatory networks. We identified 36 putative causal genes of SPP, including SDT (MIR156j) and OsMADS17, and inferred that OsMADS17 regulates SDT expression, which was experimentally validated. Our study reveals the impact of regulatory variants on rice panicle architecture and provides new insights into the gene regulatory networks of panicle traits.

A rice variation map derived from 10 548 rice accessions reveals the importance of rare variants

Detailed knowledge of the genetic variations in diverse crop populations forms the basis for genetic crop improvement and gene functional studies. In the present study, we analyzed a large rice population with a total of 10 548 accessions to construct a rice super-population variation map (RSPVM), consisting of 54 378 986 single nucleotide polymorphisms, 11 119 947 insertion/deletion mutations and 184 736 presence/absence variations. Assessment of variation detection efficiency for different population sizes revealed a sharp increase of all types of variation as the population size increased and a gradual saturation of that after the population size reached 10 000. Variant frequency analysis indicated that ∼90% of the obtained variants were rare, and would therefore likely be difficult to detect in a relatively small population. Among the rare variants, only 2.7% were predicted to be deleterious. Population structure, genetic diversity and gene functional polymorphism of this large population were evaluated based on different subsets of RSPVM, demonstrating the great potential of RSPVM for use in downstream applications. Our study provides both a rich genetic basis for understanding natural rice variations and a powerful tool for exploiting great potential of rare variants in future rice research, including population genetics and functional genomics.

Genome-Wide Association Study Unravels Quantitative Trait Loci and Genes Associated with Yield-Related Traits in Sugarcane

Sugarcane, a major sugar and energy crop worldwide faces an increasing demand for higher yields. Identifying yield-related markers and candidate genes is valuable for breeding high-yield varieties using molecular techniques. In this work, seven yield-related traits were evaluated in a diversity panel of 159 genotypes, derived from Tripidium arundinaceum, Saccharum spontaneum, and modern sugarcane genotypes. All traits exhibited significant genetic variance with high heritability and high correlations. Genetic diversity analysis reveals a genomic decay of 23 kb and an average single nucleotide polymorphism (SNP) number of 25,429 per genotype. These 159 genotypes were divided into 4 subgroups. Genome-wide association analysis identified 47 SNPs associated with brix, spanning 36 quantitative trait loci (QTLs), and 138 SNPs for other traits across 104 QTLs, covering all 32 chromosomes. Interestingly, 12 stable QTLs associated with yield-related traits were identified, which contained 35 candidate genes. This work provides markers and candidate genes for marker-assisted breeding to improve sugarcane yields.

Molecular-Assisted Breeding of Cadmium Pollution-Safe Cultivars

Cadmium (Cd) contamination in edible agricultural products, especially in crops intended for consumption, has raised worldwide concerns regarding food safety. Breeding of Cd pollution-safe cultivars (Cd-PSCs) is an effective solution to preventing the entry of Cd into the food chain from contaminated agricultural soil. Molecular-assisted breeding methods, based on molecular mechanisms for cultivar-dependent Cd accumulation and bioinformatic tools, have been developed to accelerate and facilitate the breeding of Cd-PSCs. This review summarizes the recent progress in the research of the low Cd accumulation traits of Cd-PSCs in different crops. Furthermore, the application of molecular-assisted breeding methods, including transgenic approaches, genome editing, marker-assisted selection, whole genome-wide association analysis, and transcriptome, has been highlighted to outline the breeding of Cd-PSCs by identifying critical genes and molecular biomarkers. This review provides a comprehensive overview of the development of Cd-PSCs and the potential future for breeding Cd-PSC using modern molecular technologies.

Genome-wide association study of powdery mildew resistance in cultivated soybean from Northeast China

Powdery mildew (PMD), caused by the pathogen Microsphaera diffusa, leads to substantial yield decreases in susceptible soybean under favorable environmental conditions. Effective prevention of soybean PMD damage can be achieved by identifying resistance genes and developing resistant cultivars. In this study, we genotyped 331 soybean germplasm accessions, primarily from Northeast China, using the SoySNP50K BeadChip, and evaluated their resistance to PMD in a greenhouse setting. To identify marker-trait associations while effectively controlling for population structure, we conducted genome-wide association studies utilizing factored spectrally transformed linear mixed models, mixed linear models, efficient mixed-model association eXpedited, and compressed mixed linear models. The results revealed seven single nucleotide polymorphism (SNP) loci strongly associated with PMD resistance in soybean. Among these, one SNP was localized on chromosome (Chr) 14, and six SNPs with low linkage disequilibrium were localized near or in the region of previously mapped genes on Chr 16. In the reference genome of Williams82, we discovered 96 genes within the candidate region, including 17 resistance (R)-like genes, which were identified as potential candidate genes for PMD resistance. In addition, we performed quantitative real-time reverse transcription polymerase chain reaction analysis to evaluate the gene expression levels in highly resistant and susceptible genotypes, focusing on leaf tissues collected at different times after M. diffusa inoculation. Among the examined genes, three R-like genes, including Glyma.16G210800, Glyma.16G212300, and Glyma.16G213900, were identified as strong candidates associated with PMD resistance. This discovery can significantly enhance our understanding of soybean resistance to PMD. Furthermore, the significant SNPs strongly associated with resistance can serve as valuable markers for genetic improvement in breeding M. diffusa-resistant soybean cultivars.

Mining novel genomic regions and candidate genes of heading and flowering dates in bread wheat by SNP- and haplotype-based GWAS

Bread wheat (Triticum aestivum L.) is a global staple crop vital for human nutrition. Heading date (HD) and flowering date (FD) are critical traits influencing wheat growth, development, and adaptability to diverse environmental conditions. A comprehensive study were conducted involving 190 bread wheat accessions to unravel the genetic basis of HD and FD using high-throughput genotyping and multi-environment field trials. Seven independent quantitative trait loci (QTLs) were identified to be significantly associated with HD and FD using two GWAS methods, which explained a proportion of phenotypic variance ranging from 1.43% to 9.58%. Notably, QTLs overlapping with known vernalization genes Vrn-D1 were found, validating their roles in regulating flowering time. Moreover, novel QTLs on chromosome 2A, 5B, 5D, and 7B associated with HD and FD were identified. The effects of these QTLs on HD and FD were confirmed in an additional set of 74 accessions across different environments. An increase in the frequency of alleles associated with early flowering in cultivars released in recent years was also observed, suggesting the influence of molecular breeding strategies. In summary, this study enhances the understanding of the genetic regulation of HD and FD in bread wheat, offering valuable insights into crop improvement for enhanced adaptability and productivity under changing climatic conditions. These identified QTLs and associated markers have the potential to improve wheat breeding programs in developing climate-resilient varieties to ensure food security.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01422-z.

Deciphering the evolution and complexity of wheat germplasm from a genomic perspective

Bread wheat provides an essential fraction of the daily calorific intake for humanity. Due to its huge and complex genome, progress in studying on the wheat genome is substantially trailed behind those of the other two major crops, rice and maize, for at least a decade. With rapid advances in genome assembling and reduced cost of high-throughput sequencing, emerging de novo genome assemblies of wheat and whole-genome sequencing data are leading to a paradigm shift in wheat research. Here, we review recent progress in dissecting the complex genome and germplasm evolution of wheat since the release of the first high-quality wheat genome. New insights have been gained in the evolution of wheat germplasm during domestication and modern breeding progress, genomic variations at multiple scales contributing to the diversity of wheat germplasm, and complex transcriptional and epigenetic regulations of functional genes in polyploid wheat. Genomics databases and bioinformatics tools meeting the urgent needs of wheat genomics research are also summarized. The ever-increasing omics data, along with advanced tools and well-structured databases, are expected to accelerate deciphering the germplasm and gene resources in wheat for future breeding advances.