Tools for using the International Rice Genebank to breed for climate-resilient varieties.

Traditional rice varieties have been critical for developing improved stress-tolerant rice varieties. Tools to analyze the genome sequences of traditional varieties are accelerating the identification and deployment of genes conferring climate change resilience.

A high-performance computational workflow to accelerate GATK SNP detection across a 25-genome dataset.

BACKGROUND: Single-nucleotide polymorphisms (SNPs) are the most widely used form of molecular genetic variation studies. As reference genomes and resequencing data sets expand exponentially, tools must be in place to call SNPs at a similar pace. The genome analysis toolkit (GATK) is one of the most widely used SNP calling software tools publicly available, but unfortunately, high-performance computing versions of this tool have yet to become widely available and affordable. RESULTS: Here we report an open-source high-performance computing genome variant calling workflow (HPC-GVCW) for GATK that can run on multiple computing platforms from supercomputers to desktop machines. We benchmarked HPC-GVCW on multiple crop species for performance and accuracy with comparable results with previously published reports (using GATK alone). Finally, we used HPC-GVCW in production mode to call SNPs on a "subpopulation aware" 16-genome rice reference panel with ~ 3000 resequenced rice accessions. The entire process took ~ 16 weeks and resulted in the identification of an average of 27.3 M SNPs/genome and the discovery of ~ 2.3 million novel SNPs that were not present in the flagship reference genome for rice (i.e., IRGSP RefSeq). CONCLUSIONS: This study developed an open-source pipeline (HPC-GVCW) to run GATK on HPC platforms, which significantly improved the speed at which SNPs can be called. The workflow is widely applicable as demonstrated successfully for four major crop species with genomes ranging in size from 400 Mb to 2.4 Gb. Using HPC-GVCW in production mode to call SNPs on a 25 multi-crop-reference genome data set produced over 1.1 billion SNPs that were publicly released for functional and breeding studies. For rice, many novel SNPs were identified and were found to reside within genes and open chromatin regions that are predicted to have functional consequences. Combined, our results demonstrate the usefulness of combining a high-performance SNP calling architecture solution with a subpopulation-aware reference genome panel for rapid SNP discovery and public deployment.

Meta-Analysis of Rice Phosphoproteomics Data to Understand Variation in Cell Signaling Across the Rice Pan-Genome.

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have reanalyzed publicly available mass spectrometry proteomics data sets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,565 phosphosites on serine, threonine, and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety and clustered the data to identify groups of sites with similar patterns across rice family groups. The data has been loaded into UniProt Knowledge-Base─enabling researchers to visualize sites alongside other data on rice proteins, e.g., structural models from AlphaFold2, PeptideAtlas, and the PRIDE database─enabling visualization of source evidence, including scores and supporting mass spectra.

Identification of the rice Rc gene as a main regulator of seed survival under dry storage conditions.

Seed deterioration during storage results in poor germination, reduced vigour, and non-uniform seedling emergence. The aging rate depends on storage conditions and genetic factors. This study aims to identify these genetic factors determining the longevity of rice (Oryza sativa L.) seeds stored under experimental aging conditions mimicking long-term dry storage. Genetic variation for tolerance to aging was studied in 300 Indica rice accessions by storing dry seeds under an elevated partial pressure of oxygen (EPPO) condition. A genome-wide association analysis identified 11 unique genomic regions for all measured germination parameters after aging, differing from those previously identified in rice under humid experimental aging conditions. The significant single nucleotide polymorphism in the most prominent region was located within the Rc gene, encoding a basic helix-loop-helix transcription factor. Storage experiments using near-isogenic rice lines (SD7-1D (Rc) and SD7-1d (rc) with the same allelic variation confirmed the role of the wildtype Rc gene, providing stronger tolerance to dry EPPO aging. In the seed pericarp, a functional Rc gene results in accumulation of proanthocyanidins, an important sub-class of flavonoids having strong antioxidant activity, which may explain the variation in tolerance to dry EPPO aging.

Gene B5 in Cotton Confers High and Broad Resistance to Bacterial Blight and Conditions High Amounts of Sesquiterpenoid Phytoalexins.

Bacterial blight resistance gene B5 has received little attention since it was first described in 1950. A near-isogenic line (NIL) of Gossypium hirsutum cotton, AcB5, was generated in an otherwise bacterial-blight-susceptible 'Acala 44' background. The introgressed locus B5 in AcB5 conferred strong and broad-spectrum resistance to bacterial blight. Segregation patterns of test crosses under Oklahoma field conditions indicated that AcB5 is likely homozygous for resistance at two loci with partial dominance gene action. In controlled-environment conditions, two of the four copies of B5 were required for effective resistance. Contrary to expectations of gene-for-gene theory, AcB5 conferred high resistance toward isogenic strains of Xanthomonas citri subsp. malvacearum carrying cloned avirulence genes avrB4, avrb7, avrBIn, avrB101, and avrB102, respectively, and weaker resistance toward the strain carrying cloned avrb6. The hypothesis that each B gene, in the absence of a polygenic complex, triggers sesquiterpenoid phytoalexin production was tested by measurement of cadalene and lacinilene phytoalexins during resistant responses in five NILs carrying different B genes, four other lines carrying multiple resistance genes, as well as susceptible Ac44E. Phytoalexin production was an obvious, but variable, response in all nine resistant lines. AcB5 accumulated an order of magnitude more of all four phytoalexins than any of the other resistant NILs. Its total levels were comparable to those detected in OK1.2, a highly resistant line that possesses several B genes in a polygenic background.

Structural variants in 3000 rice genomes.

Investigation of large structural variants (SVs) is a challenging yet important task in understanding trait differences in highly repetitive genomes. Combining different bioinformatic approaches for SV detection, we analyzed whole-genome sequencing data from 3000 rice genomes and identified 63 million individual SV calls that grouped into 1.5 million allelic variants. We found enrichment of long SVs in promoters and an excess of shorter variants in 5' UTRs. Across the rice genomes, we identified regions of high SV frequency enriched in stress response genes. We demonstrated how SVs may help in finding causative variants in genome-wide association analysis. These new insights into rice genome biology are valuable for understanding the effects SVs have on gene function, with the prospect of identifying novel agronomically important alleles that can be utilized to improve cultivated rice.

Aus rice root architecture variation contributing to grain yield under drought suggests a key role of nodal root diameter class.

The aus rice variety group originated in stress-prone regions and is a promising source for the development of new stress-tolerant rice cultivars. In this study, an aus panel (~220 genotypes) was evaluated in field trials under well-watered and drought conditions and in the greenhouse (basket, herbicide and lysimeter studies) to investigate relationships between grain yield and root architecture, and to identify component root traits behind the composite trait of deep root growth. In the field trials, high and stable grain yield was positively related to high and stable deep root growth (r = 0.16), which may indicate response to within-season soil moisture fluctuations (i.e., plasticity). When dissecting component traits related to deep root growth (including angle, elongation and branching), the number of nodal roots classified as 'large-diameter' was positively related to deep root growth (r = 0.24), and showed the highest number of colocated genome-wide association study (GWAS) peaks with grain yield under drought. The role of large-diameter nodal roots in deep root growth may be related to their branching potential. Two candidate loci that colocated for yield and root traits were identified that showed distinct haplotype distributions between contrasting yield/stability groups and could be good candidates to contribute to rice improvement.

Progress in single-access information systems for wheat and rice crop improvement.

Improving productivity of the staple crops wheat and rice is essential to feed the growing global population, particularly in the context of a changing climate. However, current rates of yield gain are insufficient to support the predicted population growth. New approaches are required to accelerate the breeding process, and many of these are driven by the application of large-scale crop data. To leverage the substantial volumes and types of data that can be applied for precision breeding, the wheat and rice research communities are working towards the development of integrated systems to access and standardize the dispersed, heterogeneous available data. Here, we outline the initiatives of the International Wheat Information System (WheatIS) and the International Rice Informatics Consortium (IRIC) to establish Web-based single-access systems and data mining tools to make the available resources more accessible, drive discovery and accelerate the production of new crop varieties. We discuss the progress of WheatIS and IRIC towards unifying specialized wheat and rice databases and building custom software platforms to manage and interrogate these data. Single-access crop information systems will strengthen scientific collaboration, optimize the use of public research funds and help achieve the required yield gains in the two most important global food crops.

Leaf morphology, rather than plant water status, underlies genetic variation of rice leaf rolling under drought.

Soil drying causes leaf rolling in rice, but the relationship between leaf rolling and drought tolerance has historically confounded selection of drought-tolerant genotypes. In this study on tropical japonica and aus diversity panels (170-220 genotypes), the degree of leaf rolling under drought was more affected by leaf morphology than by stomatal conductance, leaf water status, or maintenance of shoot biomass and grain yield. A range of canopy temperature and leaf rolling (measured as change in normalized difference vegetation index [ΔNDVI]) combinations were observed among aus genotypes, indicating that some genotypes continued transpiration while rolled. Association mapping indicated colocation of genomic regions for leaf rolling score and ΔNDVI under drought with previously reported leaf rolling genes and gene networks related to leaf anatomy. The relatively subtle variation across these large diversity panels may explain the lack of agreement of this study with earlier reports that used small numbers of genotypes that were highly divergent in hydraulic traits driving leaf rolling differences. This study highlights the large range of physiological responses to drought among rice genotypes and emphasizes that drought response processes should be understood in detail before incorporating them into a varietal selection programme.

Variation in seed longevity among diverse Indica rice varieties.

BACKGROUND AND AIMS: Understanding variation in seed longevity, especially within closely related germplasm, will lead to better understanding of the molecular basis of this trait, which is particularly important for seed genebanks, but is also relevant to anyone handling seeds. We therefore set out to determine the relative seed longevity of diverse Indica rice accessions through storage experiments. Since antioxidants are purported to play a role in seed storability, the antioxidant activity and phenolic content of caryopses were determined. METHODS: Seeds of 299 Indica rice accessions harvested at 31, 38 and 45 d after heading (DAH) between March and May 2015 and differing in harvest moisture content (MC) were subsequently stored at 10.9 % MC and 45 °C. Samples were taken at regular intervals and sown for germination. Germination data were subjected to probit analysis and the resulting parameters that describe the loss of viability during storage were used for genome-wide association (GWA) analysis. KEY RESULTS: The seed longevity parameters, Ki [initial viability in normal equivalent deviates (NED)], -σ-1 (σ is the time for viability to fall by 1 NED in experimental storage) and p50 [time for viability to fall to 50 % (0 NED)], varied considerably across the 299 Indica accessions. Seed longevity tended to increase as harvest MC decreased and to decrease as harvest MC increased. Eight major loci associated with seed longevity parameters were identified through GWA analysis. The favourable haplotypes on chromosomes 1, 3, 4, 9 and 11 enhanced p50 by ratios of 0.22-1.86. CONCLUSIONS: This is the first study to describe the extent of variation in σ within a species' variety group. A priori candidate genes selected based on rice genome annotation and gene network ontology databases suggested that the mechanisms conferring high seed longevity might be related to DNA repair and transcription, sugar metabolism, reactive oxygen species scavenging and embryonic/root development.

Rice SNP-seek database update: new SNPs, indels, and queries.

We describe updates to the Rice SNP-Seek Database since its first release. We ran a new SNP-calling pipeline followed by filtering that resulted in complete, base, filtered and core SNP datasets. Besides the Nipponbare reference genome, the pipeline was run on genome assemblies of IR 64, 93-11, DJ 123 and Kasalath. New genotype query and display features are added for reference assemblies, SNP datasets and indels. JBrowse now displays BAM, VCF and other annotation tracks, the additional genome assemblies and an embedded VISTA genome comparison viewer. Middleware is redesigned for improved performance by using a hybrid of HDF5 and RDMS for genotype storage. Query modules for genotypes, varieties and genes are improved to handle various constraints. An integrated list manager allows the user to pass query parameters for further analysis. The SNP Annotator adds traits, ontology terms, effects and interactions to markers in a list. Web-service calls were implemented to access most data. These features enable seamless querying of SNP-Seek across various biological entities, a step toward semi-automated gene-trait association discovery. URL: http://snp-seek.irri.org.

SNP-Seek database of SNPs derived from 3000 rice genomes.

We have identified about 20 million rice SNPs by aligning reads from the 3000 rice genomes project with the Nipponbare genome. The SNPs and allele information are organized into a SNP-Seek system (http://www.oryzasnp.org/iric-portal/), which consists of Oracle database having a total number of rows with SNP genotypes close to 60 billion (20 M SNPs × 3 K rice lines) and web interface for convenient querying. The database allows quick retrieving of SNP alleles for all varieties in a given genome region, finding different alleles from predefined varieties and querying basic passport and morphological phenotypic information about sequenced rice lines. SNPs can be visualized together with the gene structures in JBrowse genome browser. Evolutionary relationships between rice varieties can be explored using phylogenetic trees or multidimensional scaling plots.

Identification of stable QTLs causing chalk in rice grains in nine environments.

KEY MESSAGE: A novel QTL cluster for chalkiness on Chr04 was identified using single environment analysis and joint mapping across 9 environments in Asia and South American. QTL NILs showed that each had a significant effect on chalk. Chalk in rice grains leads to a significant loss in the proportion of marketable grains in a harvested crop, leading to a significant financial loss to rice farmers and traders. To identify the genetic basis of chalkiness, two sets of recombinant inbred lines (RILs) derived from reciprocal crosses between Lemont and Teqing were used to find stable QTLs for chalkiness. The RILs were grown in seven locations in Asia and Latin American and in two controlled environments in phytotrons. A total of 32 (21) and 46 (22) QTLs for DEC and PGWC, most of them explaining more than 10% of phenotypic variation, were detected based on single environment analysis in T/L (L/T) population, respectively. Seven (2) and 7 (3) QTLs for DEC and PGWC were identified in the T/L (L/T) population using joined analysis across all environments, respectively. Six major QTLs clusters were found on five chromosomes: 1, 2, 4, 5 and 11. The biggest cluster at id4007289-RM252 on Chr04 was a novelty, including 16 and 4 QTLs detected by single environment analysis and joint mapping across all environments, respectively. The detected digenic epistatic QTLs explained up to 13% of phenotypic variation, suggesting that epistasis play an important role in the genetic control of chalkiness in rice. QTL NILs showed that each QTL cluster had a significant effect on chalk. These chromosomal regions could be targets for MAS, fine mapping and map-based cloning for low chalkiness breeding.

RicePilaf: a post-GWAS/QTL dashboard to integrate pangenomic, coexpression, regulatory, epigenomic, ontology, pathway, and text-mining information to provide functional insights into rice QTLs and GWAS loci.

BACKGROUND: As the number of genome-wide association study (GWAS) and quantitative trait locus (QTL) mappings in rice continues to grow, so does the already long list of genomic loci associated with important agronomic traits. Typically, loci implicated by GWAS/QTL analysis contain tens to hundreds to thousands of single-nucleotide polmorphisms (SNPs)/genes, not all of which are causal and many of which are in noncoding regions. Unraveling the biological mechanisms that tie the GWAS regions and QTLs to the trait of interest is challenging, especially since it requires collating functional genomics information about the loci from multiple, disparate data sources. RESULTS: We present RicePilaf, a web app for post-GWAS/QTL analysis, that performs a slew of novel bioinformatics analyses to cross-reference GWAS results and QTL mappings with a host of publicly available rice databases. In particular, it integrates (i) pangenomic information from high-quality genome builds of multiple rice varieties, (ii) coexpression information from genome-scale coexpression networks, (iii) ontology and pathway information, (iv) regulatory information from rice transcription factor databases, (v) epigenomic information from multiple high-throughput epigenetic experiments, and (vi) text-mining information extracted from scientific abstracts linking genes and traits. We demonstrate the utility of RicePilaf by applying it to analyze GWAS peaks of preharvest sprouting and genes underlying yield-under-drought QTLs. CONCLUSIONS: RicePilaf enables rice scientists and breeders to shed functional light on their GWAS regions and QTLs, and it provides them with a means to prioritize SNPs/genes for further experiments. The source code, a Docker image, and a demo version of RicePilaf are publicly available at https://github.com/bioinfodlsu/rice-pilaf.

Systems genomics of salinity stress response in rice.

Populations can adapt to stressful environments through changes in gene expression. However, the role of gene regulation in mediating stress response and adaptation remains largely unexplored. Here, we use an integrative field dataset obtained from 780 plants of Oryza sativa ssp. indica (rice) grown in a field experiment under normal or moderate salt stress conditions to examine selection and evolution of gene expression variation under salinity stress conditions. We find that salinity stress induces increased selective pressure on gene expression. Further, we show that trans-eQTLs rather than cis-eQTLs are primarily associated with rice's gene expression under salinity stress, potentially via a few master-regulators. Importantly, and contrary to the expectations, we find that cis-trans reinforcement is more common than cis-trans compensation which may be reflective of rice diversification subsequent to domestication. We further identify genetic fixation as the likely mechanism underlying this compensation/reinforcement. Additionally, we show that cis- and trans-eQTLs are under different selection regimes, giving us insights into the evolutionary dynamics of gene expression variation. By examining genomic, transcriptomic, and phenotypic variation across a rice population, we gain insights into the molecular and genetic landscape underlying adaptive salinity stress responses, which is relevant for other crops and other stresses.

New allelic variants found in key rice salt-tolerance genes: an association study.

Salt stress is a complex physiological trait affecting plants by limiting growth and productivity. Rice, one of the most important food crops, is rated as salt-sensitive. High-throughput screening methods are required to exploit novel sources of genetic variation in rice and further improve salinity tolerance in breeding programmes. To search for genotypic differences related to salt stress, we genotyped 392 rice accessions by EcoTILLING. We targeted five key salt-related genes involved in mechanisms such as Na(+) /K(+) ratio equilibrium, signalling cascade and stress protection, and we found 40 new allelic variants in coding sequences. By performing association analyses using both general and mixed linear models, we identified 11 significant SNPs related to salinity. We further evaluated the putative consequences of these SNPs at the protein level using bioinformatic tools. Amongst the five nonsynonymous SNPs significantly associated with salt-stress traits, we found a T67K mutation that may cause the destabilization of one transmembrane domain in OsHKT1;5, and a P140A alteration that significantly increases the probability of OsHKT1;5 phosphorylation. The K24E mutation can putatively affect SalT interaction with other proteins thus impacting its function. Our results have uncovered allelic variants affecting salinity tolerance that may be important in breeding.

Traces of Introgression from cAus into Tropical Japonica Observed in African Upland Rice Varieties.

BACKGROUND: Asian rice Oryza sativa, first domesticated in East Asia, has considerable success in African fields. When and where this introduction occurred is unclear. Rice varieties of Asian origin may have evolved locally during and after migration to Africa, resulting in unique adaptations, particularly in relation to upland cultivation as frequently practiced in Africa. METHODS: We investigated the genetic differentiation between Asian and African varieties using the 3000 Rice Genomes SNP dataset. African upland cultivars were first characterized using principal component analysis among 292 tropical Japonica accessions from Africa and Asia. The particularities of African accessions were then explored using two inference techniques, PCA-KDE for supervised classification and chromosome painting, and ELAI for individual allelic dosage monitoring. KEY RESULTS: Ambiguities of local differentiation between Japonica and other groups pointed at genomic segments that potentially resulted from genetic exchange. Those specific to West African upland accessions were concentrated on chromosome 6 and featured several cAus introgression signals, including a large one between 17.9 and 21.7 Mb. We found iHS statistics in support of positive selection in this region and we provide a list of candidate genes enriched in GO terms that have regulatory functions involved in stress responses that could have facilitated adaptation to harsh upland growing conditions.

A meta-analysis of rice phosphoproteomics data to understand variation in cell signalling across the rice pan-genome.

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have re-analysed publicly available mass spectrometry proteomics datasets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,522 phosphosites on serine, threonine and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety. The data was clustered to identify groups of sites with similar patterns across rice family groups, for example those highly conserved in Japonica, but mostly absent in Aus type rice varieties - known to have different responses to drought. These resources can assist rice researchers to discover alleles with significantly different functional effects across rice varieties. The data has been loaded into UniProt Knowledge-Base - enabling researchers to visualise sites alongside other data on rice proteins e.g. structural models from AlphaFold2, PeptideAtlas and the PRIDE database - enabling visualisation of source evidence, including scores and supporting mass spectra.

Molecular dissection of connected rice populations revealed important genomic regions for agronomic and biofortification traits.

Breeding staple crops with increased micronutrient concentration is a sustainable approach to address micronutrient malnutrition. We carried out Multi-Cross QTL analysis and Inclusive Composite Interval Mapping for 11 agronomic, yield and biofortification traits using four connected RILs populations of rice. Overall, MC-156 QTLs were detected for agronomic (115) and biofortification (41) traits, which were higher in number but smaller in effects compared to single population analysis. The MC-QTL analysis was able to detect important QTLs viz: qZn5.2, qFe7.1, qGY10.1, qDF7.1, qPH1.1, qNT4.1, qPT4.1, qPL1.2, qTGW5.1, qGL3.1 , and qGW6.1 , which can be used in rice genomics assisted breeding. A major QTL (qZn5.2 ) for grain Zn concentration has been detected on chromosome 5 that accounted for 13% of R2. In all, 26 QTL clusters were identified on different chromosomes. qPH6.1 epistatically interacted with qZn5.1 and qGY6.2 . Most of QTLs were co-located with functionally related candidate genes indicating the accuracy of QTL mapping. The genomic region of qZn5.2 was co-located with putative genes such as OsZIP5, OsZIP9, and LOC_OS05G40490 that are involved in Zn uptake. These genes included polymorphic functional SNPs, and their promoter regions were enriched with cis-regulatory elements involved in plant growth and development, and biotic and abiotic stress tolerance. Major effect QTL identified for biofortification and agronomic traits can be utilized in breeding for Zn biofortified rice varieties.