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.

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.

Oryza glumaepatula: A wild relative to improve drought tolerance in cultivated rice.

Developing drought-resistant rice (Oryza sativa, L.) is essential for improving field productivity, especially in rain-fed areas affected by climate change. Wild relatives of rice are potential sources for drought-resistant traits. Therefore, we compared root growth and drought response among 22 wild Oryza species, from which Oryza glumaepatula was selected as a promising source for further exploration. A geographically diverse panel of 69 O. glumaepatula accessions was then screened for drought stress-related traits, and 6 of these accessions showed lower shoot dry weight (SDW) reduction, greater percentage of deep roots, and lower stomatal density (STO) under drought than the drought tolerant O. sativa variety, Sahbhagi dhan. Based on whole-genome resequencing of all 69 O. glumaepatula accessions and variant calling to a high-quality O. glumaepatula reference genome, we detected multiple genomic loci colocating for SDW, root dry weight at 30 to 45 cm depth, and STO in consecutive drought trials. Geo-referencing indicated that the potential drought donors originated in flood-prone locations, corroborating previous hypotheses about the coexistence of flood and drought tolerance within individual Oryza genomes. These findings present potential donor accessions, traits, and genomic loci from an AA genome wild relative of rice that, together with the recently developed reference genome, may be useful for further introgression of drought tolerance into the O. sativa backgrounds.

Pan-genome inversion index reveals evolutionary insights into the subpopulation structure of Asian rice.

Understanding and exploiting genetic diversity is a key factor for the productive and stable production of rice. Here, we utilize 73 high-quality genomes that encompass the subpopulation structure of Asian rice (Oryza sativa), plus the genomes of two wild relatives (O. rufipogon and O. punctata), to build a pan-genome inversion index of 1769 non-redundant inversions that span an average of ~29% of the O. sativa cv. Nipponbare reference genome sequence. Using this index, we estimate an inversion rate of ~700 inversions per million years in Asian rice, which is 16 to 50 times higher than previously estimated for plants. Detailed analyses of these inversions show evidence of their effects on gene expression, recombination rate, and linkage disequilibrium. Our study uncovers the prevalence and scale of large inversions (≥100 bp) across the pan-genome of Asian rice and hints at their largely unexplored role in functional biology and crop performance.

Response of Southeast Asian rice root architecture and anatomy phenotypes to drought stress.

Drought stress in Southeast Asia greatly affects rice production, and the rice root system plays a substantial role in avoiding drought stress. In this study, we examined the phenotypic and genetic correlations among root anatomical, morphological, and agronomic phenotypes over multiple field seasons. A set of >200 rice accessions from Southeast Asia (a subset of the 3000 Rice Genomes Project) was characterized with the aim to identify root morphological and anatomical phenotypes related to productivity under drought stress. Drought stress resulted in slight increases in the basal metaxylem and stele diameter of nodal roots. Although few direct correlations between root phenotypes and grain yield were identified, biomass was consistently positively correlated with crown root number and negatively correlated with stele diameter. The accessions with highest grain yield were characterized by higher crown root numbers and median metaxylem diameter and smaller stele diameter. Genome-wide association study (GWAS) revealed 162 and 210 significant SNPs associated with root phenotypes in the two seasons which resulted in identification of 59 candidate genes related to root development. The gene OsRSL3 was found in a QTL region for median metaxylem diameter. Four SNPs in OsRSL3 were found that caused amino acid changes and significantly associated with the root phenotype. Based on the haplotype analysis for median metaxylem diameter, the rice accessions studied were classified into five allele combinations in order to identify the most favorable haplotypes. The candidate genes and favorable haplotypes provide information useful for the genetic improvement of root phenotypes under drought stress.

State of ex situ conservation of landrace groups of 25 major crops.

Crop landraces have unique local agroecological and societal functions and offer important genetic resources for plant breeding. Recognition of the value of landrace diversity and concern about its erosion on farms have led to sustained efforts to establish ex situ collections worldwide. The degree to which these efforts have succeeded in conserving landraces has not been comprehensively assessed. Here we modelled the potential distributions of eco-geographically distinguishable groups of landraces of 25 cereal, pulse and starchy root/tuber/fruit crops within their geographic regions of diversity. We then analysed the extent to which these landrace groups are represented in genebank collections, using geographic and ecological coverage metrics as a proxy for genetic diversity. We find that ex situ conservation of landrace groups is currently moderately comprehensive on average, with substantial variation among crops; a mean of 63% ± 12.6% of distributions is currently represented in genebanks. Breadfruit, bananas and plantains, lentils, common beans, chickpeas, barley and bread wheat landrace groups are among the most fully represented, whereas the largest conservation gaps persist for pearl millet, yams, finger millet, groundnut, potatoes and peas. Geographic regions prioritized for further collection of landrace groups for ex situ conservation include South Asia, the Mediterranean and West Asia, Mesoamerica, sub-Saharan Africa, the Andean mountains of South America and Central to East Asia. With further progress to fill these gaps, a high degree of representation of landrace group diversity in genebanks is feasible globally, thus fulfilling international targets for their ex situ conservation.

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.

Novel Sources of Pre-Harvest Sprouting Resistance for Japonica Rice Improvement.

Pre-harvest sprouting (PHS), induced by unexpected weather events, such as typhoons, at the late seed maturity stage, is becoming a serious threat to rice production, especially in the state of California, USA, Japan, and the Republic of Korea, where japonica varieties (mostly susceptible to PHS) are mainly cultivated. A projected economic loss by severe PHS in these three countries could range between 8-10 billion USD per year during the next 10 years. Here, we present promising rice germplasm with strong resistance to PHS that were selected from a diverse rice panel of accessions held in the International Rice Genebank (IRG) at the International Rice Research Institute (IRRI). To induce PHS, three panicle samples per accession were harvested at 20 and 30 days after flowering (DAF), respectively, and incubated at 100% relative humidity (RH), 30 °C in a growth chamber for 15 days. A genome-wide association (GWA) analysis using a 4.8 million single nucleotide polymorphisms (SNP) marker set was performed to identify loci and candidate genes conferring PHS resistance. Interestingly, two tropical japonica and four temperate japonica accessions showed outstanding PHS resistance as compared to tolerant indica accessions. Two major loci on chromosomes 1 and 4 were associated with PHS resistance. A priori candidate genes interactions with rice gene networks, which are based on the gene ontology (GO), co-expression, and other evidence, suggested that a key resistance mechanism is related to abscisic acid (ABA), gibberellic acid (GA), and auxin mediated signaling pathways.

Enriched-GWAS and Transcriptome Analysis to Refine and Characterize a Major QTL for Anaerobic Germination Tolerance in Rice.

Tolerance of anaerobic germination (AG) is a key trait in the development of direct seeded rice. Through rapid and sustained coleoptile elongation, AG tolerance enables robust seedling establishment under flooded conditions. Previous attempts to fine map and characterize AG2 (qAG7.1), a major centromere-spanning AG tolerance QTL, derived from the indica variety Ma-Zhan Red, have failed. Here, a novel approach of "enriched haplotype" genome-wide association study based on the Ma-Zhan Red haplotype in the AG2 region was successfully used to narrow down AG2 from more than 7 Mb to less than 0.7 Mb. The AG2 peak region contained 27 genes, including the Rc gene, responsible for red pericarp development in pigmented rice. Through comparative variant and transcriptome analysis between AG tolerant donors and susceptible accessions several candidate genes potentially controlling AG2 were identified, among them several regulatory genes. Genome-wide comparative transcriptome analysis suggested differential regulation of sugar metabolism, particularly trehalose metabolism, as well as differential regulation of cell wall modification and chloroplast development to be implicated in AG tolerance mechanisms.

A platinum standard pan-genome resource that represents the population structure of Asian rice.

As the human population grows from 7.8 billion to 10 billion over the next 30 years, breeders must do everything possible to create crops that are highly productive and nutritious, while simultaneously having less of an environmental footprint. Rice will play a critical role in meeting this demand and thus, knowledge of the full repertoire of genetic diversity that exists in germplasm banks across the globe is required. To meet this demand, we describe the generation, validation and preliminary analyses of transposable element and long-range structural variation content of 12 near-gap-free reference genome sequences (RefSeqs) from representatives of 12 of 15 subpopulations of cultivated Asian rice. When combined with 4 existing RefSeqs, that represent the 3 remaining rice subpopulations and the largest admixed population, this collection of 16 Platinum Standard RefSeqs (PSRefSeq) can be used as a template to map resequencing data to detect virtually all standing natural variation that exists in the pan-genome of cultivated Asian rice.

Fine Scale Genomic Signals of Admixture and Alien Introgression among Asian Rice Landraces.

Modern rice cultivars are adapted to a range of environmental conditions and human preferences. At the root of this diversity is a marked genetic structure, owing to multiple foundation events. Admixture and recurrent introgression from wild sources have played upon this base to produce the myriad adaptations existing today. Genome-wide studies bring support to this idea, but understanding the history and nature of particular genetic adaptations requires the identification of specific patterns of genetic exchange. In this study, we explore the patterns of haplotype similarity along the genomes of a subset of rice cultivars available in the 3,000 Rice Genomes data set. We begin by establishing a custom method of classification based on a combination of dimensionality reduction and kernel density estimation. Through simulations, the behavior of this classifier is studied under scenarios of varying genetic divergence, admixture, and alien introgression. Finally, the method is applied to local haplotypes along the genome of a Core set of Asian Landraces. Taking the Japonica, Indica, and cAus groups as references, we find evidence of reciprocal introgressions covering 2.6% of reference genomes on average. Structured signals of introgression among reference accessions are discussed. We extend the analysis to elucidate the genetic structure of the group circum-Basmati: we delimit regions of Japonica, cAus, and Indica origin, as well as regions outlier to these groups (13% on average). Finally, the approach used highlights regions of partial to complete loss of structure that can be attributed to selective pressures during domestication.

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.

An imputation platform to enhance integration of rice genetic resources.

As sequencing and genotyping technologies evolve, crop genetics researchers accumulate increasing numbers of genomic data sets from various genotyping platforms on different germplasm panels. Imputation is an effective approach to increase marker density of existing data sets toward the goal of integrating resources for downstream applications. While a number of imputation software packages are available, the limitations to utilization for the rice community include high computational demand and lack of a reference panel. To address these challenges, we develop the Rice Imputation Server, a publicly available web application leveraging genetic information from a globally diverse rice reference panel assembled here. This resource allows researchers to benefit from increased marker density without needing to perform imputation on their own machines. We demonstrate improvements that imputed data provide to rice genome-wide association (GWA) results of grain amylose content and show that the major functional nucleotide polymorphism is tagged only in the imputed data set.

Genomic variation in 3,010 diverse accessions of Asian cultivated rice.

Here we analyse genetic variation, population structure and diversity among 3,010 diverse Asian cultivated rice (Oryza sativa L.) genomes from the 3,000 Rice Genomes Project. Our results are consistent with the five major groups previously recognized, but also suggest several unreported subpopulations that correlate with geographic location. We identified 29 million single nucleotide polymorphisms, 2.4 million small indels and over 90,000 structural variations that contribute to within- and between-population variation. Using pan-genome analyses, we identified more than 10,000 novel full-length protein-coding genes and a high number of presence-absence variations. The complex patterns of introgression observed in domestication genes are consistent with multiple independent rice domestication events. The public availability of data from the 3,000 Rice Genomes Project provides a resource for rice genomics research and breeding.

High temperature effects on Pi54 conferred resistance to Magnaporthe oryzae in two genetic backgrounds of Oryza sativa.

The global temperatures are predicted to rise due to climate change. However, knowledge on the mechanisms underlying the effect of high temperature (HT) on plant pathogen interaction is limited. We investigated the effect of elevated temperature on host phenotypic, biochemical and gene expression patterns in the rice-Magnaporthe oryzae (Mo) pathosystem using two genetic backgrounds, Co39 (Oryzae sativa-indica) and LTH (O. sativa-japonica) with (CO and LT) and without (Co39 and LTH) R gene (Pi54). After exposure to 28°C and 35°C the two genetic backgrounds showed contrasting responses to Mo. At 28°C, CO, Co39 and LTH displayed a more severe disease phenotype than LT. Surprisingly, CO became resistant to Mo after exposure to 35°C. CO and LT were used for further analysis to determine the defence related biochemical and transcriptome changes associated with HT induced resistance. Pre-exposure to 35°C triggered intense callose deposits and cell wall fluorescence of the attacked epidermal cells, as well as, increased hydrogen peroxide (H2O2) and salicylic acid (SA) levels. Transcriptional changes due to combined stress (35°C+Mo) were largely overridden by pathogen infection in both backgrounds, suggesting that the plants tended to shift their response to the pathogen. However, significant differences in global gene expression patterns occurred between CO and LT in response to both single (35°C and Mo) and double stress (35°C+Mo). Collectively, our results suggest that rice lines carrying Pi54 respond to Mo by rapid induction of callose and H2O2, and that these resistance mechanisms are amplified at HT. The relative difference in disease severity between CO and LT at 28°C suggests that the genetic background of japonica rice facilitates the function of Pi54 more than the background of indica rice. The phenotypic plasticity and gene expression differences between CO and LT reveal the presence of intricate background specific molecular signatures that may potentially influence adaptation to plant stresses.

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.