The 3,000 rice genomes project

Exploring crop genomes: assembly features, gene prediction accuracy, and implications for proteomics studies

Plant genomics plays a pivotal role in enhancing global food security and sustainability by offering innovative solutions for improving crop yield, disease resistance, and stress tolerance. As the number of sequenced genomes grows and the accuracy and contiguity of genome assemblies improve, structural annotation of plant genomes continues to be a significant challenge due to their large size, polyploidy, and rich repeat content. In this paper, we present an overview of the current landscape in crop genomics research, highlighting the diversity of genomic characteristics across various crop species. We also assessed the accuracy of popular gene prediction tools in identifying genes within crop genomes and examined the factors that impact their performance. Our findings highlight the strengths and limitations of BRAKER2 and Helixer as leading structural genome annotation tools and underscore the impact of genome complexity, fragmentation, and repeat content on their performance. Furthermore, we evaluated the suitability of the predicted proteins as a reliable search space in proteomics studies using mass spectrometry data. Our results provide valuable insights for future efforts to refine and advance the field of structural genome annotation.

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.

Toward breeding pigmented rice balancing nutrition and yield

A recent study by Sedeek et al. provides multiomic resources that illustrate the genetic diversity, metabolites, elemental composition, and the possibility of agronomic trait improvement, through genome-editing technology, for nutrient-rich pigmented rice. This will guide future rice breeding programs for balancing optimal agronomic traits and excellent nutritional quality.

A comprehensive benchmark of graph-based genetic variant genotyping algorithms on plant genomes for creating an accurate ensemble pipeline

BACKGROUND

Although sequencing technologies have boosted the measurement of the genomic diversity of plant crops, it remains challenging to accurately genotype millions of genetic variants, especially structural variations, with only short reads. In recent years, many graph-based variation genotyping methods have been developed to address this issue and tested for human genomes. However, their performance in plant genomes remains largely elusive. Furthermore, pipelines integrating the advantages of current genotyping methods might be required, considering the different complexity of plant genomes.

RESULTS

Here we comprehensively evaluate eight such genotypers in different scenarios in terms of variant type and size, sequencing parameters, genomic context, and complexity, as well as graph size, using both simulated and real data sets from representative plant genomes. Our evaluation reveals that there are still great challenges to applying existing methods to plants, such as excessive repeats and variants or high resource consumption. Therefore, we propose a pipeline called Ensemble Variant Genotyper (EVG) that can achieve better genotyping performance in almost all experimental scenarios and comparably higher genotyping recall and precision even using 5× reads. Furthermore, we demonstrate that EVG is more robust with an increasing number of graphed genomes, especially for insertions and deletions.

CONCLUSIONS

Our study will provide new insights into the development and application of graph-based genotyping algorithms. We conclude that EVG provides an accurate, unbiased, and cost-effective way for genotyping both small and large variations and will be potentially used in population-scale genotyping for large, repetitive, and heterozygous plant genomes.

Oryza CLIMtools: A genome-environment association resource reveals adaptive roles for heterotrimeric G proteins in the regulation of rice agronomic traits

Modern crop varieties display a degree of mismatch between their current distributions and the suitability of the local climate for their productivity. To address this issue, we present Oryza CLIMtools (https://gramene.org/CLIMtools/oryza_v1.0/), the first resource for pan-genome prediction of climate-associated genetic variants in a crop species. Oryza CLIMtools consists of interactive web-based databases that enable the user to (1) explore the local environments of traditional rice varieties (landraces) in South-East Asia and (2) investigate the environment by genome associations for 658 Indica and 283 Japonica rice landrace accessions collected from georeferenced local environments and included in the 3K Rice Genomes Project. We demonstrate the value of these resources by identifying an interplay between flowering time and temperature in the local environment that is facilitated by adaptive natural variation in OsHD2 and disrupted by a natural variant in OsSOC1. Prior quantitative trait locus analysis has suggested the importance of heterotrimeric G proteins in the control of agronomic traits. Accordingly, we analyzed the climate associations of natural variants in the different heterotrimeric G protein subunits. We identified a coordinated role of G proteins in adaptation to the prevailing potential evapotranspiration gradient and revealed their regulation of key agronomic traits, including plant height and seed and panicle length. We conclude by highlighting the prospect of targeting heterotrimeric G proteins to produce climate-resilient crops.

Screening of Rice (Oryza sativa L.) Genotypes for Salinity Tolerance and Dissecting Determinants of Tolerance Mechanism

Soil salinity imposes osmotic, ionic, and oxidative stresses on plants, resulting in growth inhibition, developmental changes, metabolic adaptations, and ion sequestration or exclusion. Identifying salinity-tolerant resources and understanding physiological and molecular mechanisms of salinity tolerance could lay a foundation for the improvement of salinity tolerance in rice. In this study, a series of salinity-tolerance-related morphological and physiological traits were investigated in 46 rice genotypes, including Sea Rice 86, to reveal the main strategies of rice in responding to salinity stress at the seedling stage. No genotypes showed the same tolerance level as the two landraces Pokkali and Nona Bokra, which remain the donors for improving the salinity tolerance of rice. However, due to undesirable agronomic traits of these donors, alternative cultivars such as JC118S and R1 are recommended as novel source of salinity tolerance. Correlation and principal component analyses revealed that the salinity tolerance of rice seedlings is not only controlled by growth vigor but also regulated by ion transport pathways such as long-distance Na+ transport, root Na+ sequestration, and root K+ retention. Therefore, such key traits should be targeted in future breeding programs as the strategy of obtaining better Na+ exclusion is still the bottleneck for improving salinity tolerance in rice.

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.

Identification of hub genes that variate the qCSS12-mediated cold tolerance between indica and japonica rice using WGCNA

KEY MESSAGE

Cold-tolerant QTL qCSS12-regulated 14 hub genes are involved in the chloroplastic biological processes and in the protein synthesis and degradation processes in japonica rice. Low temperature is a main constraint factor for rice growth and production. To better understand the regulatory mechanisms underlying the cold tolerance phenotype in rice, here, we selected a cold-sensitive nearly isogenic line (NIL) NIL(qcss12) as materials to identify hub genes that are mediated by the cold-tolerant locus qCSS12 through weighted gene co-expression network analysis (WGCNA). Fourteen cold-responsive genes were identified, of which, 6 are involved in regulating biological processes in chloroplasts, including the reported EF-Tu, Prk, and ChlD, and 8 are involved in the protein synthesis and degradation processes. Differential expression of these genes between NIL(qcss12) and its controls under cold stress may be responsible for qCSS12-mediated cold tolerance in japonica rice. Moreover, natural variations in 12 of these hub genes are highly correlated with the cold tolerance divergence in two rice subspecies. The results provide deep insights into a better understanding of the molecular basis of cold adaptation in rice and provide a theoretical basis for molecular breeding.

Oryza CLIMtools: A Genome-Environment Association Resource Reveals Adaptive Roles for Heterotrimeric G Proteins in the Regulation of Rice Agronomic Traits

Modern crop varieties display a degree of mismatch between their current distributions and the suitability of the local climate for their productivity. To this end, we present Oryza CLIMtools (https://gramene.org/CLIMtools/oryza_v1.0/), the first resource for pan-genome prediction of climate-associated genetic variants in a crop species. Oryza CLIMtools consists of interactive web-based databases that allow the user to: i) explore the local environments of traditional rice varieties (landraces) in South-Eastern Asia, and; ii) investigate the environment by genome associations for 658 Indica and 283 Japonica rice landrace accessions collected from georeferenced local environments and included in the 3K Rice Genomes Project. We exemplify the value of these resources, identifying an interplay between flowering time and temperature in the local environment that is facilitated by adaptive natural variation in OsHD2 and disrupted by a natural variant in OsSOC1. Prior QTL analysis has suggested the importance of heterotrimeric G proteins in the control of agronomic traits. Accordingly, we analyzed the climate associations of natural variants in the different heterotrimeric G protein subunits. We identified a coordinated role of G proteins in adaptation to the prevailing Potential Evapotranspiration gradient and their regulation of key agronomic traits including plant height and seed and panicle length. We conclude by highlighting the prospect of targeting heterotrimeric G proteins to produce crops that are climate resilient.

Genetic bases of resistance to the rice hoja blanca disease deciphered by a quantitative trait locus approach

Rice hoja blanca (RHB) is one of the most serious diseases in rice-growing areas in tropical Americas. Its causal agent is RHB virus (RHBV), transmitted by the planthopper Tagosodes orizicolus Müir. Genetic resistance is the most effective and environment-friendly way of controlling the disease. So far, only 1 major quantitative trait locus (QTL) of Oryza sativa ssp. japonica origin, qHBV4.1, that alters the incidence of the virus symptoms in 2 Colombian cultivars has been reported. This resistance has already started to be broken, stressing the urgent need for diversifying the resistance sources. In the present study, we performed a search for new QTLs of O. sativa indica origin associated with RHB resistance. We used 4 F2:3-segregating populations derived from indica-resistant varieties crossed with a highly susceptible japonica pivot parent. Besides the standard method for measuring disease incidence, we developed a new method based on computer-assisted image processing to determine the affected leaf area (ALA) as a measure of symptom severity. Based on the disease severity and incidence scores in the F3 families under greenhouse conditions and SNP genotyping of the F2 individuals, we identified 4 new indica QTLs for RHB resistance on rice chromosomes 4, 6, and 11, namely, qHBV4.2WAS208, qHBV6.1PTB25, qHBV11.1, and qHBV11.2, respectively. We also confirmed the wide-range action of qHBV4.1. Among the 5 QTLs, qHBV4.1 and qHBV11.1 had the largest effects on incidence and severity, respectively. These results provide a more complete understanding of the genetic bases of RHBV resistance in the cultivated rice gene pool and can be used to develop marker-aided breeding strategies to improve RHB resistance. The power of joint- and meta-analyses allowed precise mapping and candidate gene identification, providing the basis for positional cloning of the 2 major QTLs qHBV4.1 and qHBV11.1.

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.

Genomic Variations Explorer (GenVarX): a toolset for annotating promoter and CNV regions using genotypic and phenotypic differences

The rapid growth of sequencing technology and its increasing popularity in biology-related research over the years has made whole genome re-sequencing (WGRS) data become widely available. A large amount of WGRS data can unlock the knowledge gap between genomics and phenomics through gaining an understanding of the genomic variations that can lead to phenotype changes. These genomic variations are usually comprised of allele and structural changes in DNA, and these changes can affect the regulatory mechanisms causing changes in gene expression and altering the phenotypes of organisms. In this research work, we created the GenVarX toolset, that is backed by transcription factor binding sequence data in promoter regions, the copy number variations data, SNPs and Indels data, and phenotypes data which can potentially provide insights about phenotypic differences and solve compelling questions in plant research. Analytics-wise, we have developed strategies to better utilize the WGRS data and mine the data using efficient data processing scripts, libraries, tools, and frameworks to create the interactive and visualization-enhanced GenVarX toolset that encompasses both promoter regions and copy number variation analysis components. The main capabilities of the GenVarX toolset are to provide easy-to-use interfaces for users to perform queries, visualize data, and interact with the data. Based on different input windows on the user interface, users can provide inputs corresponding to each field and submit the information as a query. The data returned on the results page is usually displayed in a tabular fashion. In addition, interactive figures are also included in the toolset to facilitate the visualization of statistical results or tool outputs. Currently, the GenVarX toolset supports soybean, rice, and Arabidopsis. The researchers can access the soybean GenVarX toolset from SoyKB via https://soykb.org/SoybeanGenVarX/, rice GenVarX toolset, and Arabidopsis GenVarX toolset from KBCommons web portal with links https://kbcommons.org/system/tools/GenVarX/Osativa and https://kbcommons.org/system/tools/GenVarX/Athaliana, respectively.

Genome-wide association study of cooking-caused grain expansion in rice (Oryza sativa L.)

Cooking-caused rice grain expansion (CCRGE) is a critical trait for evaluating the cooking quality of rice. Previous quantitative trait locus (QTL) mapping studies on CCRGE have been limited to bi-parental populations, which restrict the exploration of natural variation and mapping resolution. To comprehensively and precisely dissect the genetic basis of CCRGE, we performed a genome-wide association study (GWAS) on three related indices: grain breadth expansion index (GBEI), grain length expansion index (GLEI), and grain length-breadth ratio expansion index (GREI), using 345 rice accessions grown in two years (environments) and 193,582 SNP markers. By analyzing each environment separately using seven different methods (3VmrMLM, mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB, ISIS EM-BLASSO), we identified a total of 32, 19 and 27 reliable quantitative trait nucleotides (QTNs) associated with GBEI, GLEI and GREI, respectively. Furthermore, by jointly analyzing the two environments using 3VmrMLM, we discovered 19, 22 and 25 QTNs, as well as 9, 5 and 7 QTN-by-environment interaction (QEIs) associated with GBEI, GLEI and GREI, respectively. Notably, 12, 9 and 15 QTNs for GBEI, GLEI and GREI were found within the intervals of previously reported QTLs. In the vicinity of these QTNs or QEIs, based on analyses of mutation type, gene ontology classification, haplotype, and expression pattern, we identified five candidate genes that are related to starch synthesis and endosperm development. The five candidate genes, namely, LOC_Os04g53310 (OsSSIIIb, near QTN qGREI-4.5s), LOC_Os05g02070 (OsMT2b, near QTN qGLEI-5.1s), LOC_Os06g04200 (wx, near QEI qGBEI-6.1i and QTNs qGREI-6.1s and qGLEI-6.1t), LOC_Os06g12450 (OsSSIIa, near QTN qGLEI-6.2t), and LOC_Os08g09230 (OsSSIIIa, near QTN qGBEI-8.1t), are predicted to be involved in the process of rice grain starch synthesis and to influence grain expansion after cooking. Our findings provide valuable insights and will facilitate genetic research and improvement of CCRGE.

Genetic-based dissection of resistance to bacterial leaf streak in rice by GWAS

BACKGROUND

Rice is the second-largest food crop in the world and vulnerable to bacterial leaf streak disease. A thorough comprehension of the genetic foundation of agronomic traits was essential for effective implementation of molecular marker-assisted selection.

RESULTS

Our study aimed to evaluate the vulnerability of rice to bacterial leaf streak disease (BLS) induced by the gram-negative bacterium Xanthomonas oryzae pv. oryzicola (Xoc). In order to accomplish this, we first analyzed the population structure of 747 accessions and subsequently assessed their phenotypes 20 days after inoculation with a strain of Xoc, GX01. We conducted genome-wide association studies (GWAS) on a population of 747 rice accessions, consisting of both indica and japonica subpopulations, utilizing phenotypic data on resistance to bacterial leaf streak (RBLS) and sequence data. We identified a total of 20 QTLs associated with RBLS in our analysis. Through the integration of linkage mapping, sequence analysis, haplotype analysis, and transcriptome analysis, we were able to identify five potential candidate genes (OsRBLS1-OsRBLS5) that possess the potential to regulate RBLS in rice. In order to gain a more comprehensive understanding of the genetic mechanism behind resistance to bacterial leaf streak, we conducted tests on these genes in both the indica and japonica subpopulations, ultimately identifying superior haplotypes that suggest the potential utilization of these genes in breeding disease-resistant rice varieties.

CONCLUSIONS

The findings of our study broaden our comprehension of the genetic mechanisms underlying RBLS in rice and offer significant insights that can be applied towards genetic improvement and breeding of disease-resistant rice in rapidly evolving environmental conditions.

Functional characterization and allelic mining of OsGLR genes for potential uses in rice improvement

Glutamate-like receptor (GLR) genes are a group of regulatory genes involved in many physiological processes of plants. With 26 members in the rice genome, the functionalities of most rice GLR genes remain unknown. To facilitate their potential uses in rice improvement, an integrated strategy involving CRISPR-Cas9 mediated knockouts, deep mining and analyses of transcriptomic responses to different abiotic stresses/hormone treatments and gene CDS haplotype (gcHap) diversity in 3,010 rice genomes was taken to understand the functionalities of the 26 rice GLR genes, which led us to two conclusions. First, the expansion of rice GLR genes into a large gene family during evolution had gone through repeated gene duplication events occurred primarily in two large GLR gene clusters on rice chromosomes 9 and 6, which was accompanied with considerable functional differentiation. Secondly, except for two extremely conserved ones (OsGLR6.2 and OsGLR6.3), rich gcHap diversity exists at the remaining GLR genes which played important roles in rice population differentiation and rice improvement, evidenced by their very strong sub-specific and population differentiation, by their differentiated responses to day-length and different abiotic stresses, by the large phenotypic effects of five GLR gene knockout mutants on rice yield traits, by the significant association of major gcHaps at most GLR loci with yield traits, and by the strong genetic bottleneck effects and artificial selection on the gcHap diversity in populations Xian (indica) and Geng (japonica) during modern breeding. Our results suggest the potential values of the natural variation at most rice GLR loci for improving the productivity and tolerances to abiotic stresses. Additional efforts are needed to determine the phenotypic effects of major gcHaps at these GLR loci in order to identify 'favorable' alleles at specific GLR loci specific target traits in specific environments to facilitate their application to rice improvement in future.

Identification of quantitative trait loci controlling nitrogen use efficiency-related traits in rice at the seedling stage under salt condition by genome-wide association study

Rice cultivation is facing both salt intrusion and overuse of nitrogen fertilizers. Hence, breeding new varieties aiming to improve nitrogen use efficiency (NUE), especially under salt conditions, is indispensable. We selected 2,391 rice accessions from the 3K Rice Genomes Project to evaluate the dry weight under two N concentrations [2.86 mM - standard N (SN), and 0.36 mM - low N (LN)] crossed with two NaCl concentrations [0 (0Na) and 60 mM (60Na)] at the seedling stage. Genome-wide association studies for shoot, root, and plant dry weight (DW) were carried out. A total of 55 QTLs - 32, 16, and 7 in the whole, indica, and japonica panel - associated with one of the tested traits were identified. Among these, 27 QTLs co-localized with previously identified QTLs for DW-related traits while the other 28 were newly detected; 24, 8, 11, and 4 QTLs were detected in SN-0Na, LN-0Na, SN-60Na, and LN-60Na, respectively, and the remaining 8 QTLs were for the relative plant DW between treatments. Three of the 11 QTLs in SN-60Na were close to the regions containing three QTLs detected in SN-0Na. Eleven candidate genes for eight important QTLs were identified. Only one of them was detected in both SN-0Na and SN-60Na, while 5, 0, 3, and 2 candidate genes were identified only once under SN-0Na, LN-0Na, SN-60Na, and LN-60Na, respectively. The identified QTLs and genes provide useful materials and genetic information for future functional characterization and genetic improvement of NUE in rice, especially under salt conditions.

Fantastic genes: where and how to find them? Exploiting rice genetic resources for the improvement of yield, tolerance, and resistance to a wide array of stresses in rice

Rice production is a critical component of global food security. To date, rice is grown in over 100 countries and is the primary source of food for more than 3 billion people. Despite its importance, rice production is facing numerous challenges that threaten its future viability. One of the primary problems is the advent of climate change. The changing climatic conditions greatly affect the growth and productivity of rice crop and the quality of rice yield. Similarly, biotic stresses brought about by pathogen and pest infestations are greatly affecting the productivity of rice. To address these issues, the utilization of rice genetic resources is necessary to map, identify, and understand the genetics of important agronomic traits. This review paper highlights the role of rice genetic resources for developing high-yielding and stress-tolerant rice varieties. The integration of genetic, genomic, and phenomic tools in rice breeding programs has led to the development of high-yielding and stress-tolerant rice varieties. The collaboration of multidisciplinary teams of experts, sustainable farming practices, and extension services for farmers is essential for accelerating the development of high-yielding and stress-tolerant rice varieties.

Genome-wide association analysis for emergence of deeply sown rice (Oryza sativa) reveals novel aus-specific phytohormone candidate genes for adaptation to dry-direct seeding in the field

Dry direct-seeded rice (dry-DSR) is typically sown deeply to circumvent the need for irrigation, and thus seedling emergence is a crucial trait affecting plant stand and yield. To breed elite cultivars that use less water and are climate-resilient, an understanding of the genomic regions and underlying genes that confer emergence in deeply sown dry-DSR would be highly advantageous. A combined diversity panel of 470 rice accessions (RDP1 plus aus subset of 3K RGP) was evaluated with 2.9 million single nucleotide polymorphisms (SNPs) to identify associations with dry-DSR traits in the field and component traits in a controlled-environment experiment. Using genome-wide association study (GWAS) analyses, we identified 18 unique QTLs on chromosomes 1, 2, 4, 5, 6, 7, 9, 10, and 11, explaining phenotypic variance ranging from 2.6% to 17.8%. Three QTLs, namely, qSOE-1.1, qEMERG-AUS-1.2, and qEMERG-AUS-7.1, were co-located with previously reported QTLs for mesocotyl length. Among the identified QTLs, half were associated with the emergence of aus, and six were unique to the aus genetic group. Based on functional annotation, we identified eleven compelling candidate genes that primarily regulate phytohormone pathways such as cytokinin, auxin, gibberellic acid, and jasmonic acid. Prior studies indicated that these phytohormones play a critical role in mesocotyl length under deep sowing. This study provides new insight into the importance of aus and indica as desirable genetic resources to mine favorable alleles for deep-sowing tolerance in rice. The candidate genes and marker-tagged desirable alleles identified in this study should benefit rice breeding programs directly.

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.

Evolution of flowering time genes in rice: From the paleolithic to the anthropocene

The evolutionary paths of humans and plants have crossed more than once throughout millennia. While agriculture contributed to the evolution of societies in prehistory, human selection of desirable traits contributed to the evolution of crops during centuries of cultivation. Among cereal crops, rice is currently grown around the globe and represents staple food for almost half of the world population. Over time, rice cultivation has expanded from subtropical to temperate regions thanks to artificial selection of mutants with impaired response to photoperiod. Additional regulatory mechanisms control flowering in response to diverse environmental cues, anticipating or delaying the floral transition to produce seeds in more favourable conditions. Nevertheless, the changing climate is threatening grain production because modern cultivars are sensitive to external fluctuations that go beyond their physiological range. One possibility to guarantee food production could be the exploitation of novel varieties obtained by crossing highly productive Asian rice with stress tolerant African rice. This review explores the genetic basis of the key traits that marked the long journey of rice cultivation from the end of the paleolithic to the anthropocene, with a focus on heading date. By 2050, will rice plants of the future flower in the outer space?

Insights into genomic variations in rice Hsp100 genes across diverse rice accessions

The Hsp101 gene is present across all sequenced rice genomes. However, as against Japonica rice, Hsp101 protein of most indica and aus rice contain insertion of glutamic acid at 907th position. The understanding of the heat stress response of rice plants is important for worldwide food security. We examined the presence/absence variations (PAVs) of heat shock proteins (Hsps)/heat shock transcription factor (Hsf) genes in cultivated rice accessions. While 53 Hsps/Hsfs genes showed variable extent of PAVs, 194 genes were the core genes present in all the rice accessions. ClpB1/Hsp101 gene, which is critically important for thermotolerance in plants, showed 100% distribution across the rice types. Within the ClpB1 gene sequence, 40 variation sites consisting of nucleotide polymorphisms (SNPs) and short insertion/deletions (InDels) were discerned. An InDel in ClpB1 leading to an in-frame insertion of 3 nucleotides (TCC) thereby an additional amino acid (glutamic acid) at 907th amino acid position was noted in most of the indica and aus as against japonica rice types. Three rice types namely Moroberekan (japonica), IR64 (indica) and N22 (aus) were further analyzed to address the question of ClpB1 genomic variations and its protein levels with the heat tolerance phenotype. The growth profiling analysis in the post heat stress (HS) period showed that N22 seedlings were most tolerant, IR64 moderately tolerant and Moroberekan highly sensitive. Importantly, the ClpB1 protein sequences of these three rice types showed distinct differences in terms of SNPs. As the ClpB1 protein levels accumulated post HS were generally higher in Moroberekan than N22 seedlings in our study, it is proposed that some additional gene loci in conjunction with ClpB1 regulate the overall rice heat stress response.

Cruz PC, Borromeo TH, Lalusin AG, Mauleon R, McNally KL, Swamy BPM. 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: qZn_5.2, qFe_7.1, qGY_10.1, qDF_7.1, qPH_1.1, qNT_4.1, qPT_4.1, qPL_1.2, qTGW_5.1, qGL_3.1 , and qGW_6.1 , which can be used in rice genomics assisted breeding. A major QTL (qZn_5.2 ) 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. qPH_6.1 epistatically interacted with qZn_5.1 and qGY_6.2 . Most of QTLs were co-located with functionally related candidate genes indicating the accuracy of QTL mapping. The genomic region of qZn_5.2 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.

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.

Genomic Insights into the Origin of a Thermotolerant Tomato Line and Identification of Candidate Genes for Heat Stress

Climate change represents the main problem for agricultural crops, and the constitution of heat-tolerant genotypes is an important breeder’s strategy to reduce yield losses. The aim of the present study was to investigate the whole genome of a heat-tolerant tomato genotype (E42), in order to identify candidate genes involved in its response to high temperature. E42 presented a high variability for chromosomes 1, 4, 7 and 12, and phylogenetic analysis highlighted its relationship with the wild S. pimpinellifolium species. Variants with high (18) and moderate (139) impact on protein function were retrieved from two lists of genes related to heat tolerance and reproduction. This analysis permitted us to prioritize a subset of 35 candidate gene mapping in polymorphic regions, some colocalizing in QTLs controlling flowering in tomato. Among these genes, we identified 23 HSPs, one HSF, six involved in flowering and five in pollen activity. Interestingly, one gene coded for a flowering locus T1 and mapping on chromosome 11 resides in a QTL region controlling flowering and also showed 100% identity with an S. pimpinellifolium allele. This study provides useful information on both the E42 genetic background and heat stress response, and further studies will be conducted to validate these genes.

Evolution of different rice ecotypes and genetic basis of flooding adaptability in Deepwater rice by GWAS

BACKGROUND

Rice is the world's second largest food crop and accelerated global climate change due to the intensification of human activities has a huge impact on rice. Research on the evolution of different rice ecotypes is essential for enhancing the adaptation of rice to the unpredictable environments.

RESULTS

The sequencing data of 868 cultivated and 140 wild rice accessions were used to study the domestication history and signatures of adaptation in the distinct rice ecotypes genome. The different populations had formed distinct rice ecotypes by phylogenetic analyses and were domesticated independently in the two subspecies of rice, especially deepwater and upland rice. The domestication history of distinct rice ecotypes was confirmed and the four predicted admixture events mainly involved gene flow between wild rice and cultivated rice. Importantly, we identified numerous selective sweeps that have occurred during the domestication of different rice ecotypes and one candidate gene (LOC_Os11g21804) for deepwater based on transcriptomic evidence. In addition, many regions of genomic differentiation between the different rice ecotypes were identified. Furthermore, the main reason for the increase in genetic diversity in the ecotypes of xian (indica) rice was the high proportion of alternative allele frequency in new mutations. Genome-wide association analysis revealed 28 QTLs associated with flood tolerance which contained 12 related cloned genes, and 20 candidate genes within 13 deepwater QTLs were identified by transcriptomic and haplotype analyses.

CONCLUSIONS

These results enhanced our understanding of domestication history in different rice ecotypes and provided valuable insights for genetic improvement and breeding of rice in the current changing environments.

Genetic background- and environment-independent QTL and candidate gene identification of appearance quality in three MAGIC populations of rice

Many QTL have been identified for grain appearance quality by linkage analysis (LA) in bi-parental mapping populations and by genome-wide association study (GWAS) in natural populations in rice. However, few of the well characterized genes/QTL have been successfully applied in molecular rice breeding due to genetic background (GB) and environment effects on QTL expression and deficiency of favorable alleles. In this study, GWAS and LA were performed to identify QTL for five grain appearance quality-related traits using three multi-parent advanced generation inter-cross (MAGIC) populations. A total of 22 QTL on chromosomes 1-3, 5-8 were identified by GWAS for five traits in DC1, DC2 and 8way, and four combined populations DC12 (DC1+DC2), DC18 (DC1+8way), DC28 (DC2+8way) and DC128 (DC1+DC2+8way). And a total of 42 QTL were identified on all 12 chromosomes except 10 by LA in the three single populations. Among 20 QTL identified by GWAS in DC1, DC2 and 8way, 10, four and three QTL were commonly detected in DC18, DC28, and DC128, respectively. Similarly, among 42 QTL detected by LA in the three populations, four, one and two QTL were commonly detected in DC18, DC28, and DC128, respectively. There was no QTL mapped together in DC12 by both two mapping methods, indicating that GB could greatly affect the mapping results, and it was easier to map the common QTL among populations with similar GB. The 8way population was more powerful for QTL mapping than the DC1, DC2 and various combined populations. Compared with GWAS, LA can not only identify large-effect QTL, but also identify minor-effect ones. Among 11 QTL simultaneously detected by the two methods in different GBs and environments, eight QTL corresponded to known genes, including AqGL3b and AqGLWR3a for GL and GLWR, AqGW5a, AqGLWR5, AqDEC5 and AqPGWC5 for GW, GLWR, DEC and PGWC, and AqDEC6b and AqPGWC6b for DEC and PGWC, respectively. AqGL7, AqGL3c/AqGLWR3b, AqDEC6a/AqPGWC6a, and AqPGWC7 were newly identified and their candidate genes were analyzed and inferred. It was discussed to further improve grain appearance quality through designed QTL pyramiding strategy based on the stable QTL identified in the MAGIC populations.

Introgression of a Complex Genomic Structural Variation Causes Hybrid Male Sterility in GJ Rice (Oryza sativa L.) Subspecies

Hybrids between different subspecies of rice Oryza sativa L. commonly show hybrid sterility. Here we show that a widely planted commercial japonica/GJ variety, DHX2, exhibited hybrid sterility when crossing with other GJ varieties. Using the high-quality genome assembly, we identified three copies of the Sc gene in DHX2, whereas Nipponbare (Nip) had only one copy of Sc. Knocking out the extra copies of Sc in DHX2 significantly improved the pollen fertility of the F1 plant of DHX2/Nip cross. The population structure analysis revealed that a slight introgression from Basmati1 might occur in the genome of DHX2. We demonstrated that both DHX2 and Basmati1 harbored three copies of Sc. Moreover, the introgression of GS3 and BADH2/fgr from Basmati1 confers the slender and fragrance grain of DHX2. These results add to our understanding of the hybrid sterility of inter-subspecies and intra-subspecies and may provide a novel strategy for hybrid breeding.

Development of an inclusive 580K SNP array and its application for genomic selection and genome-wide association studies in rice

Rice is a globally cultivated crop and is primarily a staple food source for more than half of the world's population. Various single-nucleotide polymorphism (SNP) arrays have been developed and utilized as standard genotyping methods for rice breeding research. Considering the importance of SNP arrays with more inclusive genetic information for GWAS and genomic selection, we integrated SNPs from eight different data resources: resequencing data from the Korean World Rice Collection (KRICE) of 475 accessions, 3,000 rice genome project (3 K-RGP) data, 700 K high-density rice array, Affymetrix 44 K SNP array, QTARO, Reactome, and plastid and GMO information. The collected SNPs were filtered and selected based on the breeder's interest, covering all key traits or research areas to develop an integrated array system representing inclusive genomic polymorphisms. A total of 581,006 high-quality SNPs were synthesized with an average distance of 200 bp between adjacent SNPs, generating a 580 K Axiom Rice Genotyping Chip (580 K _ KNU chip). Further validation of this array on 4,720 genotypes revealed robust and highly efficient genotyping. This has also been demonstrated in genome-wide association studies (GWAS) and genomic selection (GS) of three traits: clum length, heading date, and panicle length. Several SNPs significantly associated with cut-off, -log10 p-value >7.0, were detected in GWAS, and the GS predictabilities for the three traits were more than 0.5, in both rrBLUP and convolutional neural network (CNN) models. The Axiom 580 K Genotyping array will provide a cost-effective genotyping platform and accelerate rice GWAS and GS studies.

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.

Genome-Wide Association Study Reveals Candidate Genes for Root-Related Traits in Rice

Root architecture is a determinant factor of drought resistance in rice and plays essential roles in the absorption of water and nutrients for the survival of rice plants. Dissection of the genetic basis for root structure can help to improve stress-resistance and grain yield in rice breeding. In this study, a total of 391 rice (Oryz asativa L.) accessions were used to perform a genome-wide association study (GWAS) on three root-related traits in rice, including main root length (MRL), average root length (ARL), and total root number (TRN). As a result, 13 quantitative trait loci (QTLs) (qMRL1.1, qMRL1.2, qMRL3.1, qMRL3.2, qMRL3.3, qMRL4.1, qMRL7.1, qMRL8.1, qARL1.1, qARL9.1, qTRN9.1, qTRN9.2, and qTRN11.1) significantly associated with the three traits were identified, among which three (qMRL3.2, qMRL4.1 and qMRL8.1) were overlapped with OsGNOM1, OsARF12 and qRL8.1, respectively, and ten were novel QTLs. Moreover, we also detected epistatic interactions affecting root-related traits and identified 19 related genetic interactions. These results lay a foundation for cloning the corresponding genes for rice root structure, as well as provide important genomic resources for breeding high yield rice varieties.

Discovery and Validation of Grain Shape Loci in U.S. Rice Germplasm Through Haplotype Characterization

Rice grain shape is a major determinant of rice market value and the end-use. We mapped quantitative trait loci (QTL) for grain shape traits in a bi-parental recombinant inbred line population (Trenasse/Jupiter) and discovered two major grain length QTLs—qGL3.1 and qGL7.1. Previously, a major grain shape gene GS3 was reported in the qGL3.1 region and grain length gene GL7 was reported to be encompassing qGL7.1 locus. The re-sequencing SNP data on the International Rice Research Institute (IRRI) 3K Rice Genome Project (RGP) panel were obtained from the IRRI SNP-Seek database for both genes and haplotype diversity was characterized for each gene in this diverse panel. United States rice germplasm was not well represented in the IRRI 3K RGP database. Therefore, a minimum SNP set was identified for each gene that could differentiate all the characterized haplotypes. These haplotypes in the 3K RGP panel were screened across 323 elite U.S. genotypes using the minimum SNP set. The screening of haplotypes and phenotype association confirmed the role of GS3 under qGL3.1. However, screening of the GL7 haplotypes in the U.S. germplasm panel showed that GL7 did not play a role in qGL7.1, and in addition, GL7.1 did not segregate in the Trenasse/Jupiter RIL population. This concluded that qGL7.1 is a novel QTL discovered on chr7 for grain shape in the Trenasse/Jupiter RIL population. A high-throughput KASP-based SNP marker for each locus (GS3 and qGL7.1) was identified and validated in elite U.S. rice germplasm to be used in an applied rice breeding program.

Genomic revolution of US weedy rice in response to 21st century agricultural technologies

Weedy rice is a close relative of cultivated rice that devastates rice productivity worldwide. In the southern United States, two distinct strains have been historically predominant, but the 21^st century introduction of hybrid rice and herbicide resistant rice technologies has dramatically altered the weedy rice selective landscape. Here, we use whole-genome sequences of 48 contemporary weedy rice accessions to investigate the genomic consequences of crop-weed hybridization and selection for herbicide resistance. We find that population dynamics have shifted such that most contemporary weeds are now crop-weed hybrid derivatives, and that their genomes have subsequently evolved to be more like their weedy ancestors. Haplotype analysis reveals extensive adaptive introgression of cultivated alleles at the resistance gene ALS, but also uncovers evidence for convergent molecular evolution in accessions with no signs of hybrid origin. The results of this study suggest a new era of weedy rice evolution in the United States.

Analysis of a rice blast resistance gene Pita-Fuhui2663 and development of selection marker

Rice blast is a detrimental rice disease caused by the fungus Magnaporthe oryzae. Here, we identified a resistance gene from the rice cultivar Fuhui 2663 which is resistant to the rice blast isolate KJ201. Through isolated population analyses and sequencing approaches, the candidate gene was traced to chromosome 12. With the use of a map-based cloning strategy, the resistance gene was ultimately mapped to an 80-kb resistance locus region containing the Pita gene. Candidate gene prediction and cDNA sequencing indicated that the target resistance gene in Fuhui 2663 was allelic to Pita, thus being referred to as Pita-Fuhui2663 hereafter. Further analysis showed that the Fuhui 2663 protein had one amino acid change: Ala (A) residue 918 in Pita-Fuhui2663 was replaced by Ser (S) in Pita-S, leading to a significant change in the 3D structure of the Pita-S protein. CRISPR/Cas9 knockout experiments confirmed that Pita-Fuhui2663 is responsible for the resistance phenotype of Fuhui 2663. Importantly, Pita-Fuhui2663 did not affect the main agronomic traits of the variety compared to the Pita gene as verified by knockout experiments, indicative of potential applications of Pita-Fuhui2663 in broader breeding programs. Furthermore, a Pita-Fuhui2663-dCAPS molecular marker with good specificity and high efficiency was developed to facilitate rice breeding for resistance to this devastating disease.

Transposable element polymorphisms improve prediction of complex agronomic traits in rice

Transposon insertion polymorphisms can improve prediction of complex agronomic traits in rice compared to using SNPs only, especially when accessions to be predicted are less related to the training set. Transposon insertion polymorphisms (TIPs) are significant sources of genetic variation. Previous work has shown that TIPs can improve detection of causative loci on agronomic traits in rice. Here, we quantify the fraction of variance explained by single nucleotide polymorphisms (SNPs) compared to TIPs, and we explore whether TIPs can improve prediction of traits when compared to using only SNPs. We used eleven traits of agronomic relevance from by five different rice population groups (Aus, Indica, Aromatic, Japonica, and Admixed), 738 accessions in total. We assess prediction by applying data split validation in two scenarios. In the within-population scenario, we predicted performance of improved Indica varieties using the rest of Indica accessions. In the across population scenario, we predicted all Aromatic and Admixed accessions using the rest of populations. In each scenario, Bayes C and a Bayesian reproducible kernel Hilbert space regression were compared. We find that TIPs can explain an important fraction of total genetic variance and that they also improve genomic prediction. In the across population prediction scenario, TIPs outperformed SNPs in nine out of the eleven traits analyzed. In some traits like leaf senescence or grain width, using TIPs increased predictive correlation by 30-50%. Our results evidence, for the first time, that TIPs genotyping can improve prediction on complex agronomic traits in rice, especially when accessions to be predicted are less related to training accessions.

Whole Genome Sequencing and Morphological Trait-Based Evaluation of UPOV Option 2 for DUS Testing in Rice

To evaluate the application potential of high-density SNPs in rice distinctness, uniformity, and stability (DUS) testing, we screened 37,929 SNP loci distributed on 12 rice chromosomes based on whole-genome resequencing of 122 rice accessions. These SNP loci were used to analyze the DUS testing of rice varieties based on the correlation between the molecular and phenotypic distances of varieties according to UPOV option 2. The results showed that statistical algorithms and the number of phenotypic traits and SNP loci all affected the correlation between the molecular and phenotypic distances of rice varieties. Relative to the other nine algorithms, the Jaccard similarity algorithm had the highest correlation of 0.6587. Both the number of SNPs and the number of phenotypes had a ceiling effect on the correlation between the molecular and phenotypic distances of varieties, and the ceiling effect of the number of SNP loci was more obvious. To overcome the correlation bottleneck, we used the genome-wide prediction method to predict 30 phenotypic traits and found that the prediction accuracy of some traits, such as the basal sheath anthocyanin color, glume length, and intensity of the green color of the leaf blade, was very low. In combination with group comparison analysis, we found that the key to overcoming the ceiling effect of correlation was to improve the resolution of traits with low predictive values. In addition, we also performed distinctness testing on rice varieties by using the molecular distance and phenotypic distance, and we found that there were large differences between the two methods, indicating that UPOV option 2 alone cannot replace the traditional phenotypic DUS testing. However, genotype and phenotype analysis together can increase the efficiency of DUS testing.

Natural and artificial sources of genetic variation used in crop breeding: A baseline comparator for genome editing

Traditional breeding has successfully selected beneficial traits for food, feed, and fibre crops over the last several thousand years. The last century has seen significant technological advancements particularly in marker assisted selection and the generation of induced genetic variation, including over the last few decades, through mutation breeding, genetic modification, and genome editing. While regulatory frameworks for traditional varietal development and for genetic modification with transgenes are broadly established, those for genome editing are lacking or are still evolving in many regions. In particular, the lack of "foreign" recombinant DNA in genome edited plants and that the resulting SNPs or INDELs are indistinguishable from those seen in traditional breeding has challenged development of new legislation. Where products of genome editing and other novel breeding technologies possess no transgenes and could have been generated via traditional methods, we argue that it is logical and proportionate to apply equivalent legislative oversight that already exists for traditional breeding and novel foods. This review analyses the types and the scale of spontaneous and induced genetic variation that can be selected during traditional plant breeding activities. It provides a base line from which to judge whether genetic changes brought about by techniques of genome editing or other reverse genetic methods are indeed comparable to those routinely found using traditional methods of plant breeding.

An alanine to valine mutation of glutamyl-tRNA reductase enhances 5-aminolevulinic acid synthesis in rice

An alanine to valine mutation of glutamyl-tRNA reductase's 510th amino acid improves 5-aminolevulinic acid synthesis in rice. 5-aminolevulinic acid (ALA) is the common precursor of all tetrapyrroles and plays an important role in plant growth regulation. ALA is synthesized from glutamate, catalyzed by glutamyl-tRNA synthetase (GluRS), glutamyl-tRNA reductase (GluTR), and glutamate-1-semialdehyde aminotransferase (GSAT). In Arabidopsis, ALA synthesis is the rate-limiting step in tetrapyrrole production via GluTR post-translational regulations. In rice, mutations of GluTR and GSAT homologs are known to confer chlorophyll deficiency phenotypes; however, the enzymatic activity of rice GluRS, GluTR, and GSAT and the post-translational regulation of rice GluTR have not been investigated experimentally. We have demonstrated that a suppressor mutation in rice partially reverts the xantha trait. In the present study, we first determine that the suppressor mutation results from a G → A nucleotide substitution of OsGluTR (and an A → V change of its 510th amino acid). Protein homology modeling and molecular docking show that the OsGluTR^A510V mutation increases its substrate binding. We then demonstrate that the OsGluTR^A510V mutation increases ALA synthesis in Escherichia coli without affecting its interaction with OsFLU. We further explore homologous genes encoding GluTR across 193 plant species and find that the amino acid (A) is 100% conserved at the position, suggesting its critical role in GluTR. Thus, we demonstrate that the gain-of-function OsGluTR^A510V mutation underlies suppression of the xantha trait, experimentally proves the enzymatic activity of rice GluRS, GluTR, and GSAT in ALA synthesis, and uncovers conservation of the alanine corresponding to the 510th amino acid of OsGluTR across plant species.

Molecular tools, potential frontiers for enhancing salinity tolerance in rice: A critical review and future prospective

Improvement of salinity tolerance in rice can minimize the stress-induced yield losses. Rice (Oryza sativa) is one of Asia's most widely consumed crops, native to the subtropical regions, and is generally associated with sensitivity to salinity stress episodes. Salt-tolerant rice genotypes have been developed using conventional breeding methods; however, the success ratio is limited because of the complex nature of the trait and the high cost of development. The narrow genetic base of rice limited the success of conventional breeding methods. Hence, it is critical to launch the molecular tools for screening rice novel germplasm for salt-tolerant genes. In this regard, the latest molecular techniques like quantitative trait loci (QTL) mapping, genetic engineering (GE), transcription factors (TFs) analysis, and clustered regularly interspaced short palindromic repeats (CRISPR) are reliable for incorporating the salt tolerance in rice at the molecular level. Large-scale use of these potent genetic approaches leads to identifying and editing several genes/alleles, and QTL/genes are accountable for holding the genetic mechanism of salinity tolerance in rice. Continuous breeding practices resulted in a huge decline in rice genetic diversity, which is a great worry for global food security. However, molecular breeding tools are the only way to conserve genetic diversity by exploring wild germplasm for desired genes in salt tolerance breeding programs. In this review, we have compiled the logical evidences of successful applications of potent molecular tools for boosting salinity tolerance in rice, their limitations, and future prospects. This well-organized information would assist future researchers in understanding the genetic improvement of salinity tolerance in rice.

Whole-Genome Sequencing of KMR3 and Oryza rufipogon-Derived Introgression Line IL50-13 (Chinsurah Nona 2/Gosaba 6) Identifies Candidate Genes for High Yield and Salinity Tolerance in Rice

The genomes of an elite rice restorer line KMR3 (salinity-sensitive) and its salinity-tolerant introgression line IL50-13, a popular variety of coastal West Bengal, India, were sequenced. High-quality paired-end reads were obtained for KMR3 (147.6 million) and IL50-13 (131.4 million) with a sequencing coverage of 30X-39X. Scaffolds generated from the pre-assembled contigs of each sequenced genome were mapped separately onto the reference genome of Oryza sativa ssp. japonica cultivar Nipponbare to identify genomic variants in terms of SNPs and InDels. The SNPs and InDels identified for KMR3 and IL50-13 were then compared with each other to identify polymorphic SNPs and InDels unique and common to both the genomes. Functional enrichment analysis of the protein-coding genes with unique InDels identified GO terms involved in protein modification, ubiquitination, deubiquitination, peroxidase activity, and antioxidant activity in IL50-13. Linoleic acid metabolism, circadian rhythm, and alpha-linolenic acid metabolism pathways were enriched in IL50-13. These GO terms and pathways are involved in reducing oxidative damage, thus suggesting their role in stress responses. Sequence analysis of QTL markers or genes known to be associated with grain yield and salinity tolerance showed polymorphism in 20 genes, out of which nine were not previously reported. These candidate genes encoded Nucleotide-binding adaptor shared by APAF-1, R proteins, and CED-4 (NB-ARC) domain-containing protein, cyclase, receptor-like kinase, topoisomerase II-associated protein PAT1 domain-containing protein, ion channel regulatory protein, UNC-93 domain-containing protein, subunit A of the heteromeric ATP-citrate lyase, and three conserved hypothetical genes. Polymorphism was observed in the coding, intron, and untranslated regions of the genes on chromosomes 1, 2, 4, 7, 11, and 12. Genes showing polymorphism between the two genomes were considered as sequence-based new candidates derived from Oryza rufipogon for conferring high yield and salinity tolerance in IL50-13 for further functional studies.

Fine Mapping and Cloning of a Major QTL qph12, Which Simultaneously Affects the Plant Height, Panicle Length, Spikelet Number and Yield in Rice (Oryza sativa L.)

Plant height is one of the most important agronomical traits in rice (Oryza sativa L.). Introducing the semidwarf rice in the 1960s significantly enhanced the rice yield potential in Asia. Implementing near-isogenic lines (NILs) is the most powerful tool for the identification and fine mapping of quantitative trait loci (QTLs). In this study, 176 NILs were produced from the crossing and back-crossing of two rice cultivars. Specifically, the indica rice cultivar Jiafuzhan served as a recipient, and the restorer japonica cultivar Hui1586 served as a donor. Using the 176 NILs, we identified a novel major QTL for reduced plant height in the NIL36 line. The qph12 QTL was mapped to a 31 kb genomic region between the indel markers Indel12-29 and Indel12-31. The rice genome annotation indicated the presence of three candidate genes in this genomic region. Through gene prediction and cDNA sequencing, we confirmed that LOC_Os12g40890 (qPH12) is the target gene in the NIL36 line. Further analysis showed that the qph12 QTL is caused by a 1 bp deletion in the first exon that resulted in premature termination of the qPH12. Knockout experiments showed that the qph12 QTL is responsible for the reduced plant height phenotype of the NIL36 line. Although the qph12 gene from the NIL36 line showed a shorter panicle length, fewer spikelets per panicle and a lower plant grain yield, the plant also exhibited a lower plant height. Taken together, our results revealed that the qph12 have good specific application prospects in future rice breeding.

Expression of Potato StDRO1 in Arabidopsis Alters Root Architecture and Drought Tolerance

Potato (Solanum tuberosum L) is the third important crop for providing calories to a large human population, and is considered sensitive to moderately sensitive to drought stress conditions. The development of drought-tolerant, elite varieties of potato is a challenging task, which can be achieved through molecular breeding. Recently, the DEEPER ROOTING 1 (DRO1) gene has been identified in rice, which influences plant root system and regulates grain yield under drought stress conditions. The potato StDRO1 protein is mainly localized in the plasma membrane of tobacco leaf cells, and overexpression analysis of StDRO1 in Arabidopsis resulted in an increased lateral root number, but decreased lateral root angle, lateral branch angle, and silique angle. Additionally, the drought treatment analysis indicated that StDRO1 regulated drought tolerance and rescued the defective root architecture and drought-tolerant phenotypes of Atdro1, an Arabidopsis AtDRO1 null mutant. Furthermore, StDRO1 expression was significantly higher in the drought-tolerant potato cultivar "Unica" compared to the drought-sensitive cultivar "Atlantic." The transcriptional response of StDRO1 under drought stress occurred significantly earlier in Unica than in Atlantic. Collectively, the outcome of the present investigation elucidated the role of DRO1 function in the alternation of root architecture, which potentially acts as a key gene in the development of a drought stress-tolerant cultivar. Furthermore, these findings will provide the theoretical basis for molecular breeding of drought-tolerant potato cultivars for the farming community.

Genomic insights on the contribution of introgressions from Xian/Indica to the genetic improvement of Geng/Japonica rice cultivars

Hybridization between Xian/indica (XI) and Geng/japonica (GJ) rice combined with utilization of plant ideotypes has greatly contributed to yield improvements in modern GJ rice in China over the past 50 years. To explore the genomic basis of improved yield and disease resistance in GJ rice, we conducted a large-scale genomic landscape analysis of 816 elite GJ cultivars representing multiple eras of germplasm from China. We detected consistently increasing introgressions from three XI subpopulations into GJ cultivars since the 1980s and found that the XI genome introgressions significantly increased the grain number per panicle (GN) and decreased the panicle number per plant. This contributed to the improvement of plant type during modern breeding, changing multi-tiller plants to moderate tiller plants with a large panicle size and increasing the blast resistance. Notably, we found that key gene haplotypes controlling plant architecture, yield components, and pest and disease resistance, including IPA1, SMG1, DEP3, Pib, Pi-d2, and Bph3, were introduced from XI rice by introgression. By GWAS analysis, we detected a GN-related gene Gnd5, which had been consistently introgressed from XI into GJ cultivars since the 1980s. Gnd5 is a GRAS transcription factor gene, and Gnd5 knockout mutants showed a significant reduction in GN. The estimated genetic effects of genes varied among different breeding locations, which explained the distinct introgression levels of XI gene haplotypes, including Gnd5, DEP3, etc., to these GJ breeding pedigrees. These findings reveal the genomic contributions of introgressions from XI to the trait improvements of GJ rice cultivars and provide new insights for future rice genomic breeding.

Genome wide association study on development and evolution of glutinous rice

BACKGROUND

Glutinous rice as a special endosperm type is consumed as a staple food in East Asian countries by consumers' preference. Genetic studies on glutinous rice could be conducive to improve rice quality and understand its development and evolution. Therefor, we sought to explore more genes related to glutinous by genome wide association study and research the formation history for glutinous.

RESULTS

Here, genome-wide association study was performed to explore the associated loci/genes underlying glutinous rice by using 2108 rice accessions. Combining the expression patterns analysis, 127, 81, and 48 candidate genes were identified to be associated with endosperm type in whole rice panel, indica, and japonica sub-populations. There were 32 genes, including three starch synthesis-related genes Wx, SSG6, and OsSSIIa, detected simultaneously in the whole rice panel and subpopulations, playing important role in determining glutinous rice. The combined haplotype analyses revealed that the waxy haplotypes combination of three genes mainly distributed in Southeast Asia (SEA), SEA islands (SER) and East Asia islands (EAR). Through population structure and genetic differentiation, we suggest that waxy haplotypes of the three genes firstly evolved or were directly inherited from wild rice in japonica, and then introgressed into indica in SER, SEA and EAR.

CONCLUSIONS

The cloning and natural variation analysis of waxy-related genes are of great significance for the genetic improvement of quality breeding and comprehend the history in glutinous rice. This work provides valuable information for further gene discovery and understanding the evolution and formation for glutinous rice in SEA, SER and EAR.

Molecular profiling of BADH2 locus reveals distinct functional allelic polymorphism associated with fragrance variation in Indian aromatic rice germplasm

Allelic variability of the aroma gene, betaine aldehyde dehydrogenase 2 (BADH2) was studied in a random subset of indigenous aromatic rice germplasm along with a few exotic aromatic accessions. Use of functional markers of four badh2 alleles identified that the test panel possessed only two alleles, badh2-E7 and badh2-p-5'UTR. Two other alleles, badh2.2 and badh2-E4-5.2 were absent. Based on the alleles present, four functional polymorphisms (FP) were detected, namely FP1 to FP4. 188 genotypes possessed FP1 having both the badh2-p-5'UTR and badh2-E7 (71.8%) alleles. The badh2 allele with FP1 is named badh2-E7-p. 39 genotypes (14.9%) possessed only the badh2-p-5'UTR allele (FP3), while three genotypes were found to carry only the badh2-E7 allele (FP2). We also found that 32 genotypes (12.2%) did not have any of the target aroma alleles tested in this study (FP4). Interestingly, for badh2-p-5'UTR marker, the expected 198 bp amplicon for the non-aromatic allele could not be detected among any of the genotypes tested. Instead, an amplicon of 456 bp length appeared with 100% presence in the non-aromatic checks. Notwithstanding, the 456 bp allele also showed a 16% presence among the aromatic lines. This article forms the first report of this allele, named badh2-p1, among aromatic rice. Quantification of 2-Acetyl-1-Pyrroline (2AP) content and sensory evaluation among the test genotypes showed that those with FP1 are highly aromatic than the genotypes carrying other types of FPs. But, a few strongly aromatic lines showed lower 2AP content. The BADH2 characterization carried out in this study is suggestive of identifying the additional gene(s)/ allele(s) governing aroma among the Indian fragrant rice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-022-01181-9.

Natural Variation in Vitamin B1 and Vitamin B6 Contents in Rice Germplasm

Insufficient dietary intake of micronutrients contributes to the onset of deficiencies termed hidden hunger-a global health problem affecting approximately 2 billion people. Vitamin B1 (thiamine) and vitamin B6 (pyridoxine) are essential micronutrients because of their roles as enzymatic cofactors in all organisms. Metabolic engineering attempts to biofortify rice endosperm-a poor source of several micronutrients leading to deficiencies when consumed monotonously-have led to only minimal improvements in vitamin B1 and B6 contents. To determine if rice germplasm could be exploited for biofortification of rice endosperm, we screened 59 genetically diverse accessions under greenhouse conditions for variation in vitamin B1 and vitamin B6 contents across three tissue types (leaves, unpolished and polished grain). Accessions from low, intermediate and high vitamin categories that had similar vitamin levels in two greenhouse experiments were chosen for in-depth vitamer profiling and selected biosynthesis gene expression analyses. Vitamin B1 and B6 contents in polished seeds varied almost 4-fold. Genes encoding select vitamin B1 and B6 biosynthesis de novo enzymes (THIC for vitamin B1, PDX1.3a-c and PDX2 for vitamin B6) were differentially expressed in leaves across accessions contrasting in their respective vitamin contents. These expression levels did not correlate with leaf and unpolished seed vitamin contents, except for THIC expression in leaves that was positively correlated with total vitamin B1 contents in polished seeds. This study expands our knowledge of diversity in micronutrient traits in rice germplasm and provides insights into the expression of genes for vitamin B1 and B6 biosynthesis in rice.

Deciphering Haplotypic Variation and Gene Expression Dynamics Associated with Nutritional and Cooking Quality in Rice

Nutritional quality improvement of rice is the key to ensure global food security. Consequently, enormous efforts have been made to develop genomics and transcriptomics resources for rice. The available omics resources along with the molecular understanding of trait development can be utilized for efficient exploration of genetic resources for breeding programs. In the present study, 80 genes known to regulate the nutritional and cooking quality of rice were extensively studied to understand the haplotypic variability and gene expression dynamics. The haplotypic variability of selected genes were defined using whole-genome re-sequencing data of ~4700 diverse genotypes. The analytical workflow identified 133 deleterious single-nucleotide polymorphisms, which are predicted to affect the gene function. Furthermore, 788 haplotype groups were defined for 80 genes, and the distribution and evolution of these haplotype groups in rice were described. The nucleotide diversity for the selected genes was significantly reduced in cultivated rice as compared with that in wild rice. The utility of the approach was successfully demonstrated by revealing the haplotypic association of chalk5 gene with the varying degree of grain chalkiness. The gene expression atlas was developed for these genes by analyzing RNA-Seq transcriptome profiling data from 102 independent sequence libraries. Subsequently, weighted gene co-expression meta-analyses of 11,726 publicly available RNAseq libraries identified 19 genes as the hub of interactions. The comprehensive analyses of genetic polymorphisms, allelic distribution, and gene expression profiling of key quality traits will help in exploring the most desired haplotype for grain quality improvement. Similarly, the information provided here will be helpful to understand the molecular mechanism involved in the development of nutritional and cooking quality traits in rice.

Dissection of genetic architecture for tiller angle in rice (Oryza sativa. L) by multiple genome-wide association analyses

Background

The rice plant architecture is determined by spatially and temporally domesticated tiller angle. The deeper insight into the genetic mechanism for rice plant architecture will allow more efficient light capture by increasing the planting density, reproducibility, and the ability to survive in a stressful environment.

Methods

In this study, a natural population of 795 genotypes further divided into japonica and indica subpopulations, was evaluated for tiller angle. A significant variation with a wide range was observed. Genome-wide association analysis was performed by the general linear model (GLM), and compressed mix linear model (cMLM) for three populations to disclose the genomic associations. The population principal components and kinship matrix in 1,000 permutations were used to remove the false positives. The candidate genes were evaluated for their functional annotations and specific molecular pathways. The sequencing-based haplotype analysis was further performed to reveal the functional variation among candidate genomic regions.

Results

As a result, 37 significant QTLs with 93 annotated loci were identified. Among the loci, a known tiller angle controlling locus TAC1 was also identified. The introduction of the sequence pooling technique was observed fruitful to screen the 12 significant QTLs with 22 annotated loci. For ten of these loci, the functional variations were identified by haplotype analysis. These results were not only providing a better understanding of the genetic bases of rice plant architecture but also provide significant information for future breeding programs.

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.

Extensive allele mining discovers novel genetic diversity in the loci controlling frost tolerance in barley

Exome sequencing-based allele mining for frost tolerance suggests HvCBF14 rather than CNV at Fr-H2 locus is the main responsible of frost tolerance in barley. Wild relatives, landraces and old cultivars of barley represent a reservoir of untapped and potentially important genes for crop improvement, and the recent sequencing technologies provide the opportunity to mine the existing genetic diversity and to identify new genes/alleles for the traits of interest. In the present study, we use frost tolerance and vernalization requirement as case studies to demonstrate the power of allele mining carried out on exome sequencing data generated from > 400 barley accessions. New deletions in the first intron of VRN-H1 were identified and linked to a reduced vernalization requirement, while the allelic diversity of HvCBF2a, HvCBF4b and HvCBF14 was investigated by combining the analysis of SNPs and read counts. This approach has proven very effective to identify gene paralogs and copy number variants of HvCBF2 and the HvCBF4b-HvCBF2a segment. A multiple linear regression model which considers allelic variation at these genes suggests a major involvement of HvCBF14, rather than copy number variation of HvCBF4b-HvCBF2a, in controlling frost tolerance in barley. Overall, the present study provides powerful resource and tools to discover novel alleles at relevant genes in barley.

Tracing Mobile DNAs: From Molecular to Population Scales

Transposable elements (TEs, transposons) are mobile DNAs that are prevalent in most eukaryotic genomes. In plants, their mobility has vastly contributed to genetic diversity which is essential for adaptive changes and evolution of a species. Such mobile nature of transposon has been also actively exploited in plant science research by generating genetic mutants in non-model plant systems. On the other hand, transposon mobilization can bring about detrimental effects to host genomes and they are therefore mostly silenced by the epigenetic mechanisms. TEs have been studied as major silencing targets and acted a main feature in the remarkable growth of the plant epigenetics field. Despite the importance of transposon in plant biology and biotechnology, their mobilization and the underlying mechanisms are largely left unanswered. This is mainly because of the sequence repetitiveness of transposons, which makes their detection and analyses difficult and complicated. Recently, some attempts have been made to develop new experimental methods detecting active transposons and their mobilization behavior. These techniques reveal TE mobility in various levels, including the molecular, cellular, organismal and population scales. In this review, we will highlight the novel technical approaches in the study of mobile genetic elements and discuss how these techniques impacted on the advancement of transposon research and broadened our understanding of plant genome plasticity.