The 3,000 rice genomes project

Genome-Wide Association Analysis Dissects the Genetic Basis of the Grain Carbon and Nitrogen Contents in Milled Rice

BACKGROUND

Carbon (C) and nitrogen (N) are two fundamental components of starch and protein, which are important determinants of grain yield and quality. The food preferences of consumers and the expected end-use of grains in different rice-growing regions require diverse varieties that differ in terms of the grain N content (GNC) and grain C content (GCC) of milled rice. Thus, it is important that quantitative trait loci (QTLs)/genes with large effects on the variation of GNC and GCC are identified in breeding programs.

RESULTS

To dissect the genetic basis of the variation of GNC and GCC in rice, the Dumas combustion method was used to analyze 751 diverse accessions regarding the GNC, GCC, and C/N ratio of the milled grains. The GCC and GNC differed significantly among the rice subgroups, especially between Xian/Indica (XI) and Geng/Japonica (GJ). Interestingly, in the GJ subgroup, the GNC was significantly lower in modern varieties (MV) than in landraces (LAN). In the XI subgroup, the GCC was significantly higher in MV than in LAN. One, six, and nine QTLs, with 55 suggestively associated single nucleotide polymorphisms, were detected for the GNC, GCC, and C/N ratio in three panels during a single-locus genome-wide association study (GWAS). Three of these QTLs were also identified in a multi-locus GWAS. We screened 113 candidate genes in the 16 QTLs in gene-based haplotype analyses. Among these candidate genes, LOC_Os01g06240 at qNC-1.1, LOC_Os05g33300 at qCC-5.1, LOC_Os01g04360 at qCN-1.1, and LOC_Os05g43880 at qCN-5.2 may partially explain the significant differences between the LAN and MV. These candidate genes should be cloned and may be useful for molecular breeding to rapidly improve the GNC, GCC, and C/N ratio of rice.

CONCLUSIONS

Our findings represent valuable information regarding the genetic basis of the GNC and GCC and may be relevant for enhancing the application of favorable haplotypes of candidate genes for the molecular breeding of new rice varieties with specific grain N and C contents.

Gigwa v2-Extended and improved genotype investigator

Background

The study of genetic variations is the basis of many research domains in biology. From genome structure to population dynamics, many applications involve the use of genetic variants. The advent of next-generation sequencing technologies led to such a flood of data that the daily work of scientists is often more focused on data management than data analysis. This mass of genotyping data poses several computational challenges in terms of storage, search, sharing, analysis, and visualization. While existing tools try to solve these challenges, few of them offer a comprehensive and scalable solution.

Results

Gigwa v2 is an easy-to-use, species-agnostic web application for managing and exploring high-density genotyping data. It can handle multiple databases and may be installed on a local computer or deployed as an online data portal. It supports various standard import and export formats, provides advanced filtering options, and offers means to visualize density charts or push selected data into various stand-alone or online tools. It implements 2 standard RESTful application programming interfaces, GA4GH, which is health-oriented, and BrAPI, which is breeding-oriented, thus offering wide possibilities of interaction with third-party applications. The project home page provides a list of live instances allowing users to test the system on public data (or reasonably sized user-provided data).

Conclusions

This new version of Gigwa provides a more intuitive and more powerful way to explore large amounts of genotyping data by offering a scalable solution to search for genotype patterns, functional annotations, or more complex filtering. Furthermore, its user-friendliness and interoperability make it widely accessible to the life science community.

Rice Stress-Resistant SNP Database

BACKGROUND

Rice (Oryza sativa L.) yield is limited inherently by environmental stresses, including biotic and abiotic stresses. Thus, it is of great importance to perform in-depth explorations on the genes that are closely associated with the stress-resistant traits in rice. The existing rice SNP databases have made considerable contributions to rice genomic variation information but none of them have a particular focus on integrating stress-resistant variation and related phenotype data into one web resource.

RESULTS

Rice Stress-Resistant SNP database (http://bioinformatics.fafu.edu.cn/RSRS) mainly focuses on SNPs specific to biotic and abiotic stress-resistant ability in rice, and presents them in a unified web resource platform. The Rice Stress-Resistant SNP (RSRS) database contains over 9.5 million stress-resistant SNPs and 797 stress-resistant candidate genes in rice, which were detected from more than 400 stress-resistant rice varieties. We incorporated the SNPs function, genome annotation and phenotype information into this database. Besides, the database has a user-friendly web interface for users to query, browse and visualize a specific SNP efficiently. RSRS database allows users to query the SNP information and their relevant annotations for individual variety or more varieties. The search results can be visualized graphically in a genome browser or displayed in formatted tables. Users can also align SNPs between two or more rice accessions.

CONCLUSION

RSRS database shows great utility for scientists to further characterize the function of variants related to environmental stress-resistant ability in rice.

Genome-Wide Association Analysis of the Genetic Basis for Sheath Blight Resistance in Rice

BACKGROUND

Sheath blight (ShB), caused by Rhizoctonia solani Kühn, is one of the most destructive rice diseases. Developing ShB-resistant rice cultivars represents the most economical and environmentally sound strategy for managing ShB.

RESULTS

To characterize the genetic basis for ShB resistance in rice, we conducted association studies for traits related to ShB resistance, namely culm length (CL), lesion height (LH), and relative lesion height (RLH). Combined a single locus genome-wide scan and a multi-locus method using 2,977,750 single-nucleotide polymorphisms to analyse 563 rice accessions, we detected 134, 562, and 75 suggestive associations with CL, LH, and RLH, respectively. The adjacent signals associated with RLH were merged into 27 suggestively associated loci (SALs) based on the estimated linkage disequilibrium blocks. More than 44% of detected RLH-SALs harboured multiple QTLs/genes associated with ShB resistance, while the other RLH-SALs were putative novel ShB resistance loci. A total of 261 ShB resistance putative functional genes were screened from 23 RLH-SALs according to bioinformatics and haplotype analyses. Some of the annotated genes were previously reported to encode defence-related and pathogenesis-related proteins, suggesting that quantitative resistance to ShB in rice is mediated by SA- and JA-dependent signalling pathways.

CONCLUSIONS

Our findings may improve the application of germplasm resources as well as knowledge-based ShB management and the breeding of ShB-resistant rice cultivars.

Harmonizing technological advances in phenomics and genomics for enhanced salt tolerance in rice from a practical perspective

Half of the global human population is dependent on rice as a staple food crop and more than 25% increase in rice productivity is required to feed the global population by 2030. With increase in irrigation, global warming and rising sea level, rising salinity has become one of the major challenges to enhance the rice productivity. Since the loss on this account is to the tune of US$12 billion per annum, it necessitates the global attention. In the era of technological advancement, substantial progress has been made on phenomics and genomics data generation but reaping benefit of this in rice salinity variety development in terms of cost, time and precision requires their harmonization. There is hardly any comprehensive holistic review for such combined approach. Present review describes classical salinity phenotyping approaches having morphological, physiological and biochemical components. It also gives a detailed account of invasive and non-invasive approaches of phenomic data generation and utilization. Classical work of rice salinity QLTs mapping in the form of chromosomal atlas has been updated. This review describes how QTLs can be further dissected into QTN by GWAS and transcriptomic approaches. Opportunities and progress made by transgenic, genome editing, metagenomics approaches in combating rice salinity problems are discussed. Major aim of this review is to provide a comprehensive over-view of hitherto progress made in rice salinity tolerance research which is required to understand bridging of phenotype based breeding with molecular breeding. This review is expected to assist rice breeders in their endeavours by fetching greater harmonization of technological advances in phenomics and genomics for better pragmatic approach having practical perspective.

TASUKE+: a web-based platform for exploring genome-wide association studies results and large-scale resequencing data

Recent revolutionary advancements in sequencing technologies have made it possible to obtain mass quantities of genome-scale sequence data in a cost-effective manner and have drastically altered molecular biological studies. To utilize these sequence data, genome-wide association studies (GWASs) have become increasingly important. Hence, there is an urgent need to develop a visualization tool that enables efficient data retrieval, integration of GWAS results with diverse information and rapid public release of such large-scale genotypic and phenotypic data. We developed a web-based genome browser TASUKE+ (https://tasuke.dna.affrc.go.jp/), which is equipped with the following functions: (i) interactive GWAS results visualization with genome resequencing data and annotation information, (ii) PCR primer design, (iii) phylogenetic tree reconstruction and (iv) data sharing via the web. GWAS results can be displayed in parallel with polymorphism data, read depths and annotation information in an interactive and scalable manner. Users can design PCR primers for polymorphic sites of interest. In addition, a molecular phylogenetic tree of any region can be reconstructed so that the overall relationship among the examined genomes can be understood intuitively at a glance. All functions are implemented through user-friendly web-based interfaces so that researchers can easily share data with collaborators in remote places without extensive bioinformatics knowledge.

Diagnostic kit for rice blight resistance

Blight-resistant rice lines are the most effective solution for bacterial blight, caused by Xanthomonas oryzae pv. oryzae (Xoo). Key resistance mechanisms involve SWEET genes as susceptibility factors. Bacterial transcription activator-like (TAL) effectors bind to effector-binding elements (EBEs) in SWEET gene promoters and induce SWEET genes. EBE variants that cannot be recognized by TAL effectors abrogate induction, causing resistance. Here we describe a diagnostic kit to enable analysis of bacterial blight in the field and identification of suitable resistant lines. Specifically, we include a SWEET promoter database, RT–PCR primers for detecting SWEET induction, engineered reporter rice lines to visualize SWEET protein accumulation and knock-out rice lines to identify virulence mechanisms in bacterial isolates. We also developed CRISPR–Cas9 genome-edited Kitaake rice to evaluate the efficacy of EBE mutations in resistance, software to predict the optimal resistance gene set for a specific geographic region, and two resistant ‘mega’ rice lines that will empower farmers to plant lines that are most likely to resist rice blight.

Strategic deployment of blight-resistant rice lines is enabled by a molecular diagnostic kit.

Variation in seed longevity among diverse Indica rice varieties

BACKGROUND AND AIMS

Understanding variation in seed longevity, especially within closely related germplasm, will lead to better understanding of the molecular basis of this trait, which is particularly important for seed genebanks, but is also relevant to anyone handling seeds. We therefore set out to determine the relative seed longevity of diverse Indica rice accessions through storage experiments. Since antioxidants are purported to play a role in seed storability, the antioxidant activity and phenolic content of caryopses were determined.

METHODS

Seeds of 299 Indica rice accessions harvested at 31, 38 and 45 d after heading (DAH) between March and May 2015 and differing in harvest moisture content (MC) were subsequently stored at 10.9 % MC and 45 °C. Samples were taken at regular intervals and sown for germination. Germination data were subjected to probit analysis and the resulting parameters that describe the loss of viability during storage were used for genome-wide association (GWA) analysis.

KEY RESULTS

The seed longevity parameters, Ki [initial viability in normal equivalent deviates (NED)], -σ-1 (σ is the time for viability to fall by 1 NED in experimental storage) and p50 [time for viability to fall to 50 % (0 NED)], varied considerably across the 299 Indica accessions. Seed longevity tended to increase as harvest MC decreased and to decrease as harvest MC increased. Eight major loci associated with seed longevity parameters were identified through GWA analysis. The favourable haplotypes on chromosomes 1, 3, 4, 9 and 11 enhanced p50 by ratios of 0.22-1.86.

CONCLUSIONS

This is the first study to describe the extent of variation in σ within a species' variety group. A priori candidate genes selected based on rice genome annotation and gene network ontology databases suggested that the mechanisms conferring high seed longevity might be related to DNA repair and transcription, sugar metabolism, reactive oxygen species scavenging and embryonic/root development.

Dissecting the genome-wide genetic variants of milling and appearance quality traits in rice

Higher head rice yield (HRY), which represents the proportion of intact grains that survive milling, and lower grain chalkiness (opacity) are key quality traits. We investigated the genetic basis of HRY and chalkiness in 320 diverse resequenced accessions of indica rice with integrated single- and multi-locus genome-wide association studies using 2.26 million single-nucleotide polymorphisms. We identified novel haplotypes that underly higher HRY on chromosomes 3, 6, 8, and 11, and that lower grain chalkiness in a fine-mapped region on chromosome 5. Whole-genome sequencing of 92 IRRI breeding lines was performed to identify the genetic variants of HRY and chalkiness. Rare and novel haplotypes were found for lowering chalkiness, but missing alleles hindered progress towards enhancing HRY in breeding material. The novel haplotypes that we identified have potential use in breeding programs aimed at improving these important traits in the rice crop.

Rice quality: How is it defined by consumers, industry, food scientists, and geneticists?

BACKGROUND

Quality is a powerful engine in rice value chain upgrading. However, there is no consensus on how "rice quality" should be defined and measured in the rice sector.

SCOPE AND APPROACH

We adopt a Lancasterian definition of rice quality as a bundle of intrinsic and extrinsic attributes. We then review how rice quality is (i) perceived and defined by consumers and industry stakeholders in rice value chains in Southeast and South Asia; (ii) measured and defined by food technologists; and (iii) predicted through genetics.

KEY FINDINGS AND CONCLUSIONS

Consumers are heterogeneous with respect to their perceived differentiation of rice quality among regions, countries, cities, and urbanization levels. Premium quality is defined by nutritional benefits, softness and aroma in Southeast Asia, and by the physical appearance of the grains (uniformity, whiteness, slenderness), satiety, and aroma in South Asia. These trends are found to be consistent with industry perceptions and have important implications for regional and national breeding programs in terms of tailoring germplasm to regions and rice varieties to specific local market segments. Because rice is traded internationally, there is a need to standardize definitions of rice quality. However, food technologists have not reached unanimity on quality classes and measurement; routine indicators need to be complemented by descriptive profiles elicited through sensory evaluation panels. Finally, because rice quality is controlled by multiple interacting genes expressed through environmental conditions, predicting grain quality requires associating genetic information with grain quality phenotypes in different environments.

Benchmarking variant identification tools for plant diversity discovery

BACKGROUND

The ability to accurately and comprehensively identify genomic variations is critical for plant studies utilizing high-throughput sequencing. Most bioinformatics tools for processing next-generation sequencing data were originally developed and tested in human studies, raising questions as to their efficacy for plant research. A detailed evaluation of the entire variant calling pipeline, including alignment, variant calling, variant filtering, and imputation was performed on different programs using both simulated and real plant genomic datasets.

RESULTS

A comparison of SOAP2, Bowtie2, and BWA-MEM found that BWA-MEM was consistently able to align the most reads with high accuracy, whereas Bowtie2 had the highest overall accuracy. Comparative results of GATK HaplotypCaller versus SAMtools mpileup indicated that the choice of variant caller affected precision and recall differentially depending on the levels of diversity, sequence coverage and genome complexity. A cross-reference experiment of S. lycopersicum and S. pennellii reference genomes revealed the inadequacy of single reference genome for variant discovery that includes distantly-related plant individuals. Machine-learning-based variant filtering strategy outperformed the traditional hard-cutoff strategy resulting in higher number of true positive variants and fewer false positive variants. A 2-step imputation method, which utilized a set of high-confidence SNPs as the reference panel, showed up to 60% higher accuracy than direct LD-based imputation.

CONCLUSIONS

Programs in the variant discovery pipeline have different performance on plant genomic dataset. Choice of the programs is subjected to the goal of the study and available resources. This study serves as an important guiding information for plant biologists utilizing next-generation sequencing data for diversity characterization and crop improvement.

Soybean-VCF2Genomes: a database to identify the closest accession in soybean germplasm collection

BACKGROUND

The development of next generation sequencer (NGS) and the analytical methods allowed the researchers to profile their samples more precisely and easier than before. Especially for agriculture, the certification of the genomic background of their plant materials would be important for the reliability of seed market and stable yield as well as for quarantine procedure. However, the analysis of NGS data is still difficult for non-computational researchers or breeders to verify their samples because majority of current softwares for NGS analysis require users to access unfamiliar Linux environment.

MAIN BODY

Here, we developed a web-application, "Soybean-VCF2Genomes", http://pgl.gnu.ac.kr/soy_vcf2genome/ to map single sample variant call format (VCF) file against known soybean germplasm collection for identification of the closest soybean accession. Based on principal component analysis (PCA), we simplified genotype matrix for lowering computational burden while maintaining accurate clustering. With our web-application, users can simply upload single sample VCF file created by more than 10x resequencing strategy to find the closest samples along with linkage dendrogram of the reference genotype matrix.

CONCLUSION

The information of the closest soybean cultivar will allow breeders to estimate relative germplasmic position of their query sample to determine soybean breeding strategies. Moreover, our VCF2Genomes scheme can be extended to other plant species where the whole genome sequences of core collection are publicly available.

The rice genome revolution: from an ancient grain to Green Super Rice

Rice is a staple crop for half the world's population, which is expected to grow by 3 billion over the next 30 years. It is also a key model for studying the genomics of agroecosystems. This dual role places rice at the centre of an enormous challenge facing agriculture: how to leverage genomics to produce enough food to feed an expanding global population. Scientists worldwide are investigating the genetic variation among domesticated rice species and their wild relatives with the aim of identifying loci that can be exploited to breed a new generation of sustainable crops known as Green Super Rice.

Integrating a genome-wide association study with a large-scale transcriptome analysis to predict genetic regions influencing the glycaemic index and texture in rice

Reliably generating rice varieties with low glycaemic index (GI) is an important nutritional intervention given the high rates of Type II diabetes incidences in Asia where rice is staple diet. We integrated a genome-wide association study (GWAS) with a transcriptome-wide association study (TWAS) to determine the genetic basis of the GI in rice. GWAS utilized 305 re-sequenced diverse indica panel comprising ~2.4 million single nucleotide polymorphisms (SNPs) enriched in genic regions. A novel association signal was detected at a synonymous SNP in exon 2 of LOC_Os05g03600 for intermediate-to-high GI phenotypic variation. Another major hotspot region was predicted for contributing intermediate-to-high GI variation, involves 26 genes on chromosome 6 (GI6.1). These set of genes included GBSSI, two hydrolase genes, genes involved in signalling and chromatin modification. The TWAS and methylome sequencing data revealed cis-acting functionally relevant genetic variants with differential methylation patterns in the hot spot GI6.1 region, narrowing the target to 13 genes. Conversely, the promoter region of GBSSI and its alternative splicing allele (G allele of Wxa ) explained the intermediate-to-high GI variation. A SNP (C˃T) at exon-10 was also highlighted in the preceding analyses to influence final viscosity (FV), which is independent of amylose content/GI. The low GI line with GC haplotype confirmed soft texture, while other two low GI lines with GT haplotype were characterized as hard and cohesive. The low GI lines were further confirmed through clinical in vivo studies. Gene regulatory network analysis highlighted the role of the non-starch polysaccharide pathway in lowering GI.

An asymmetric allelic interaction drives allele transmission bias in interspecific rice hybrids

Hybrid sterility (HS) between Oryza sativa (Asian rice) and O. glaberrima (African rice) is mainly controlled by the S1 locus. However, our limited understanding of the HS mechanism hampers utilization of the strong interspecific heterosis. Here, we show that three closely linked genes (S1A4, S1TPR, and S1A6) in the African S1 allele (S1-g) constitute a killer-protector system that eliminates gametes carrying the Asian allele (S1-s). In Asian–African rice hybrids (S1-gS1-s), the S1TPR-S1A4-S1A6 interaction in sporophytic tissues generates an abortion signal to male and female gametes. However, S1TPR can rescue S1-g gametes, while the S1-s gametes selectively abort for lacking S1TPR. Knockout of any of the S1-g genes eliminates the HS. Evolutionary analysis suggests that S1 may have arisen from newly evolved genes, multi-step recombination, and nucleotide variations. Our findings will help to overcome the interspecific reproductive barrier and use Asian–African hybrids for increasing rice production.

Our limited understanding of the hybrid sterility (HS) mechanism in Asian–African rice hybrids hampers utilization of the interspecific heterosis for rice production. Here, the authors identify S1-mediated HS-related tripartite gamete killer-protector system, and explore their evolutionary relationship.

Improving Head Rice Yield and Milling Quality: State-of-the-Art and Future Prospects

Increasing paddy yield in rice does not directly translate to enhancing food security because significant decrease in grain yield can happen during postharvest processing of the rice paddy. In parallel with enhancing paddy yield, improving the milling quality of rice is essential in ensuring food security by mitigating the impact of significant losses during the postharvest processing of rice grains. From an industrial standpoint, maximizing the milling recovery of whole grain polished rice is crucial in fetching higher revenues to rice farmers. Significant advances in rice postharvest processing technology have been achieved which are geared toward reducing the incidence of fissures and chalkiness to increase head rice yield (HRY) in rice. The genetic bases of kernel development and grain dimension are also characterized. In addition to these advancements, an integrated phenotyping suite to simultaneously characterize phenotypes related to milling quality will help in screening for breeding lines with high HRY. Toward this goal, modern imaging tools and computer algorithms are currently being developed for high-throughput characterization of rice milling quality. With the availability of more sophisticated, affordable, automated, and nondestructive phenotyping methods of milling quality, it is envisioned that significant improvement in HRY will be made possible to ensure rice food security in the future.

Rice Galaxy: an open resource for plant science

BACKGROUND

Rice molecular genetics, breeding, genetic diversity, and allied research (such as rice-pathogen interaction) have adopted sequencing technologies and high-density genotyping platforms for genome variation analysis and gene discovery. Germplasm collections representing rice diversity, improved varieties, and elite breeding materials are accessible through rice gene banks for use in research and breeding, with many having genome sequences and high-density genotype data available. Combining phenotypic and genotypic information on these accessions enables genome-wide association analysis, which is driving quantitative trait loci discovery and molecular marker development. Comparative sequence analyses across quantitative trait loci regions facilitate the discovery of novel alleles. Analyses involving DNA sequences and large genotyping matrices for thousands of samples, however, pose a challenge to non-computer savvy rice researchers.

FINDINGS

The Rice Galaxy resource has shared datasets that include high-density genotypes from the 3,000 Rice Genomes project and sequences with corresponding annotations from 9 published rice genomes. The Rice Galaxy web server and deployment installer includes tools for designing single-nucleotide polymorphism assays, analyzing genome-wide association studies, population diversity, rice-bacterial pathogen diagnostics, and a suite of published genomic prediction methods. A prototype Rice Galaxy compliant to Open Access, Open Data, and Findable, Accessible, Interoperable, and Reproducible principles is also presented.

CONCLUSIONS

Rice Galaxy is a freely available resource that empowers the plant research community to perform state-of-the-art analyses and utilize publicly available big datasets for both fundamental and applied science.

The Genomics of Oryza Species Provides Insights into Rice Domestication and Heterosis

Here, we review recent progress in genetic and genomic studies of the diversity of Oryza species. In recent years, unlocking the genetic diversity of Oryza species has provided insights into the genomics of rice domestication, heterosis, and complex traits. Genome sequencing and analysis of numerous wild rice (Oryza rufipogon) and Asian cultivated rice (Oryza sativa) accessions have enabled the identification of genome-wide signatures of rice domestication and the unlocking of the origin of Asian cultivated rice. Moreover, similar studies on genome variations of African rice (Oryza glaberrima) cultivars and their closely related wild progenitor Oryza barthii accessions have provided strong evidence to support a theory of independent domestication in African rice. Integrated genomic approaches have efficiently investigated many heterotic loci in hybrid rice underlying yield heterosis advantages and revealed the genomic architecture of rice heterosis. We conclude that in-depth unlocking of genetic variations among Oryza species will further enhance rice breeding.

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.

Directions for research and training in plant omics: Big Questions and Big Data

A key remit of the NSF-funded "Arabidopsis Research and Training for the 21st Century" (ART-21) Research Coordination Network has been to convene a series of workshops with community members to explore issues concerning research and training in plant biology, including the role that research using Arabidopsis thaliana can play in addressing those issues. A first workshop focused on training needs for bioinformatic and computational approaches in plant biology was held in 2016, and recommendations from that workshop have been published (Friesner et al., Plant Physiology, 175, 2017, 1499). In this white paper, we provide a summary of the discussions and insights arising from the second ART-21 workshop. The second workshop focused on experimental aspects of omics data acquisition and analysis and involved a broad spectrum of participants from academics and industry, ranging from graduate students through post-doctorates, early career and established investigators. Our hope is that this article will inspire beginning and established scientists, corporations, and funding agencies to pursue directions in research and training identified by this workshop, capitalizing on the reference species Arabidopsis thaliana and other valuable plant systems.

Edit at will: Genotype independent plant transformation in the era of advanced genomics and genome editing

The combination of advanced genomics, genome editing and plant transformation biology presents a powerful platform for basic plant research and crop improvement. Together these advances provide the tools to identify genes as targets for direct editing as single base pair changes, deletions, insertions and site specific homologous recombination. Recent breakthrough technologies using morphogenic regulators in plant transformation creates the ability to introduce reagents specific toward their identified targets and recover stably transformed and/or edited plants which are genotype independent. These technologies enable the possibility to alter a trait in any variety, without genetic disruption which would require subsequent extensive breeding, but rather to deliver the same variety with one trait changed. Regulatory issues regarding this technology will predicate how broadly these technologies will be implemented. In addition, education will play a crucial role for positive public acceptance. Taken together these technologies comprise a platform for advanced breeding which is an imperative for future world food security.

Plant genome sequences: past, present, future

The green plants (Viridiplantae) are an essential kingdom of life, responsible via photosynthesis for the majority of global primary production, and directly utilized by humankind for nutrition, animal feed, fuel, clothing, medicine and other purposes. There are an estimated 391 000 species of land plants, in addition to 8000 species of green algae. Their genomes are unusually diverse compared to those of other kingdoms, ranging in size from ∼10 Mb to over 100 Gb. Knowledge of plant genomes initially lagged behind those of other kingdoms but has greatly increased with the development of new technologies for DNA sequencing; bioinformatic analysis, rather than data production, is increasingly the bottleneck to further knowledge. Recent proposals are now contemplating the sequencing, assembly and annotation of the genomes of all of the world's plant species; meanwhile, low coverage sequencing to measure diversity across collections and wild populations has already become commonplace for many species, especially those utilized as crops.

Genetic dissection of seedling vigour in a diverse panel from the 3,000 Rice (Oryza sativa L.) Genome Project

Seedling vigour (SV) is important for direct seeding rice (Oryza sativa L.), especially in a paddy-direct seeding system, but the genetic mechanisms behind the related traits remain largely unknown. Here, we used 744 germplasms, having at least two subsets, for the detection of quantitative trait loci (QTLs) affecting the SV-related traits tiller number, plant height, and aboveground dry weight at three sampling stages, 27, 34, and 41 d after sowing. A joint map based on GAPIT and mrMLM produced a satisfying balance between type I and II errors. In total, 42 QTL regions, containing 18 (42.9%) previously reported overlapping QTL regions and 24 new ones, responsible for SV were detected throughout the genome. Four QTL regions, qSV1a, qSV3e, qSV4c, and qSV7c, were delimited and harboured quantitative trait nucleotides that are responsible for SV-related traits. Favourable haplotype mining for the candidate genes within these four regions, as well as the early SV gene OsGA20ox1, was performed, and the favourable haplotypes were presented with donors from the 3,000 Rice Genome Project. This work provides new information and materials for the future molecular breeding of direct seeding rice, especially in paddy-direct seeding cultivation systems.

Whole-genome resequencing of 472 Vitis accessions for grapevine diversity and demographic history analyses

Understanding the Vitis species at the genomic level is important for cultivar improvement of grapevine. Here we report whole-genome genetic variation at single-base resolution of 472 Vitis accessions, which cover 48 out of 60 extant Vitis species from a wide geographic distribution. The variation helps to identify a recent dramatic expansion and contraction of effective population size in the domesticated grapevines and that cultivars from the pan-Black Sea region have a unique demographic history in comparison to the other domesticated cultivars. We also find selective sweeps for berry edibility and stress resistance improvement. Furthermore, we find associations between candidate genes and important agronomic traits, such as berry shape and aromatic compounds. These results demonstrate resource value of the resequencing data for illuminating the evolutionary biology of Vitis species and providing targets for grapevine genetic improvement.

Despite the importance of grapevine cultivation in human history and the economic values of cultivar improvement, large-scale genomic variation data are lacking. Here the authors resequence 472 Vitis accessions and use the identified genetic variations for domestication history, demography, and GWAS analyses.

Analyzing large scale genomic data on the cloud with Sparkhit

Motivation

The increasing amount of next-generation sequencing data poses a fundamental challenge on large scale genomic analytics. Existing tools use different distributed computational platforms to scale-out bioinformatics workloads. However, the scalability of these tools is not efficient. Moreover, they have heavy run time overheads when pre-processing large amounts of data. To address these limitations, we have developed Sparkhit: a distributed bioinformatics framework built on top of the Apache Spark platform.

Results

Sparkhit integrates a variety of analytical methods. It is implemented in the Spark extended MapReduce model. It runs 92-157 times faster than MetaSpark on metagenomic fragment recruitment and 18-32 times faster than Crossbow on data pre-processing. We analyzed 100 terabytes of data across four genomic projects in the cloud in 21 h, which includes the run times of cluster deployment and data downloading. Furthermore, our application on the entire Human Microbiome Project shotgun sequencing data was completed in 2 h, presenting an approach to easily associate large amounts of public datasets with reference data.

Availability and implementation

Sparkhit is freely available at: https://rhinempi.github.io/sparkhit/.

Contact

asczyrba@cebitec.uni-bielefeld.de.

Supplementary information

Supplementary data are available at Bioinformatics online.

Origin of the Aromatic Group of Cultivated Rice (Oryza sativa L.) Traced to the Indian Subcontinent

The aromatic group of Asian cultivated rice is a distinct population with considerable genetic diversity on the Indian subcontinent and includes the popular Basmati types characterized by pleasant fragrance. Genetic and phenotypic associations with other cultivated groups are ambiguous, obscuring the origin of the aromatic population. From analysis of genome-wide diversity among over 1,000 wild and cultivated rice accessions, we show that aromatic rice originated in the Indian subcontinent from hybridization between a local wild population and examples of domesticated japonica that had spread to the region from their own center of origin in East Asia. Most present-day aromatic accessions have inherited their cytoplasm along with 29-47% of their nuclear genome from the local Indian rice. We infer that the admixture occurred 4,000-2,400 years ago, soon after japonica rice reached the region. We identify aus as the original crop of the Indian subcontinent, indica and japonica as later arrivals, and aromatic a specific product of local agriculture. These results prompt a reappraisal of our understanding of the emergence and development of rice agriculture in the Indian subcontinent.

Back to the future: revisiting MAS as a tool for modern plant breeding

KEY MESSAGE

New models for integration of major gene MAS with modern breeding approaches stand to greatly enhance the reliability and efficiency of breeding, facilitating the leveraging of traditional genetic diversity. Genetic diversity is well recognised as contributing essential variation to crop breeding processes, and marker-assisted selection is cited as the primary tool to bring this diversity into breeding programs without the associated genetic drag from otherwise poor-quality genomes of donor varieties. However, implementation of marker-assisted selection techniques remains a challenge in many breeding programs worldwide. Many factors contribute to this lack of adoption, such as uncertainty in how to integrate MAS with traditional breeding processes, lack of confidence in MAS as a tool, and the expense of the process. However, developments in genomics tools, locus validation techniques, and new models for how to utilise QTLs in breeding programs stand to address these issues. Marker-assisted forward breeding needs to be enabled through the identification of robust QTLs, the design of reliable marker systems to select for these QTLs, and the delivery of these QTLs into elite genomic backgrounds to enable their use without associated genetic drag. To enhance the adoption and effectiveness of MAS, rice is used as an example of how to integrate new developments and processes into a coherent, efficient strategy for utilising genetic variation. When processes are instituted to address these issues, new genes can be rolled out into a breeding program rapidly and completely with a minimum of expense.

Contribution of recent technological advances to future resistance breeding

The development of durable host resistance strategies to control crop diseases is a primary need for sustainable agricultural production in the future. This article highlights the potential of recent progress in the understanding of host resistance for future cereal breeding. Much of the novel work is based on advancements in large-scale sequencing and genomics, rapid gene isolation techniques and high-throughput molecular marker technologies. Moreover, emerging applications on the pathogen side like effector identification or field pathogenomics are discussed. The combination of knowledge from both sides of cereal pathosystems will result in new approaches for resistance breeding. We describe future applications and innovative strategies to implement effective and durable strategies to combat diseases of major cereal crops while reducing pesticide dependency.

Progress in plant genome sequencing: research directions

Since the first plant genome of Arabidopsis thaliana has been sequenced and published, genome sequencing technologies have undergone significant changes. New algorithms, sequencing technologies and bioinformatic approaches were adopted to obtain genome, transcriptome and exome sequences for model and crop species, which have permitted deep inferences into plant biology. As a result of an improved genome assembly and analysis methods, genome sequencing costs plummeted and the number of high-quality plant genome sequences is constantly growing. Consequently, more than 300 plant genome sequences have been published over the past twenty years. Although many of the published genomes are considered incomplete, they proved to be a valuable tool for identifying genes involved in the formation of economically valuable plant traits, for marker-assisted and genomic selection and for comparative analysis of plant genomes in order to determine the basic patterns of origin of various plant species. Since a high coverage and resolution of a genome sequence is not enough to detect all changes in complex samples, targeted sequencing, which consists in the isolation and sequencing of a specific region of the genome, has begun to develop. Targeted sequencing has a higher detection power (the ability to identify new differences/variants) and resolution (up to one basis). In addition, exome sequencing (the method of sequencing only protein-coding genes regions) is actively developed, which allows for the sequencing of non-expressed alleles and genes that cannot be found with RNA-seq. In this review, an analysis of sequencing technologies development and the construction of “reference” genomes of plants is performed. A comparison of the methods of targeted sequencing based on the use of the reference DNA sequence is accomplished.

New alleles for chlorophyll content and stay-green traits revealed by a genome wide association study in rice (Oryza sativa)

Higher chlorophyll content (CC) and strong stay-green (SG) traits are conducive for improvement of photosynthetic efficiency in plants. Exploration of natural elite alleles for CC and SG, and highly resolved gene haplotypes are beneficial to rational design of breeding for high-photosynthetic efficiency. Phenotypic analysis of 368 rice accessions showed no significant correlation between CC and SG, and higher CC and stronger SG in japonica than in indica. Genome-wide association studies of six indices for CC and SG identified a large number of association signals, among which 14 were identified as pleiotropic regions for CC and SG. Twenty-five known genes and pleiotropic candidate gene OsSG1 accounted for natural variation in CC and SG. Further analysis indicated that 20 large-effect, non-synonymous SNPs within six known genes around GWAS signals and three SNPs in the promoter of OsSG1 could be functional causing significant phenotypic differences between alleles. Superior haplotypes were identified based on these potentially functional SNPs. Population analyses of 368 cultivated accessions and 446 wild accessions based on SNPs within genes for CC and SG suggested that these genes had been subjected to strong positive selection in japonica in the process of spreading from its subtropical origin to the North China temperate zone. Our studies point to important genes that account for natural variation and provide superior haplotypes of possible functional SNPs that will be beneficial in breeding for high-photosynthetic efficiency in rice.

Tracking the origin of two genetic components associated with transposable element bursts in domesticated rice

Transposable elements (TEs) shape genome evolution through periodic bursts of amplification. In this study prior knowledge of the mPing/Ping/Pong TE family is exploited to track their copy numbers and distribution in genome sequences from 3,000 accessions of domesticated Oryza sativa (rice) and the wild progenitor Oryza rufipogon. We find that mPing bursts are restricted to recent domestication and is likely due to the accumulation of two TE components, Ping16A and Ping16A_Stow, that appear to be critical for mPing hyperactivity. Ping16A is a variant of the autonomous element with reduced activity as shown in a yeast transposition assay. Transposition of Ping16A into a Stowaway element generated Ping16A_Stow, the only Ping locus shared by all bursting accessions, and shown here to correlate with high mPing copies. Finally, we show that sustained activity of the mPing/Ping family in domesticated rice produced the components necessary for mPing bursts, not the loss of epigenetic regulation.

Translational genomics and multi-omics integrated approaches as a useful strategy for crop breeding

Recent next generation sequencing-driven mass production of genomic data and multi-omics-integrated approaches have significantly contributed to broadening and deepening our knowledge on the molecular system of living organisms. Accordingly, translational genomics (TG) approach can play a pivotal role in creating an informational bridge between model systems and relatively less studied plants. This review focuses mainly on addressing recent advancement in omics-related technologies, a diverse array of bioinformatic resources and potential applications of TG for the crop breeding. To accomplish above objectives, information on omics data production, various DBs and high throughput technologies was collected, integrated, and used to analyze current status and future perspectives towards omics-assisted crop breeding. Various omics data and resources have been organized and integrated into the databases and/or bioinformatic infrastructures, and thereby serve as the ome's information center for cross-genome translation of biological data. Although the size of accumulated omics data and availability of reference genomes are different among plant families, translational approaches have been actively progressing to access particular biological characteristics. When multi-layered omics data are integrated in a synthetic manner, it will allow providing a stereoscopic view of dynamic molecular behavior and interacting networks of genes occurring in plants. Consequently, TG approach will lead us to broader and deeper insights into target traits for the plant breeding. Furthermore, such systems approach will renovate conventional breeding programs and accelerate precision crop breeding in the future.

Criteria for evaluating molecular markers: Comprehensive quality metrics to improve marker-assisted selection

Despite strong interest over many years, the usage of quantitative trait loci in plant breeding has often failed to live up to expectations. A key weak point in the utilisation of QTLs is the “quality” of markers used during marker-assisted selection (MAS): unreliable markers result in variable outcomes, leading to a perception that MAS products fail to achieve reliable improvement. Most reports of markers used for MAS focus on markers derived from the mapping population. There are very few studies that examine the reliability of these markers in other genetic backgrounds, and critically, no metrics exist to describe and quantify this reliability. To improve the MAS process, this work proposes five core metrics that fully describe the reliability of a marker. These metrics give a comprehensive and quantitative measure of the ability of a marker to correctly classify germplasm as QTL[+]/[–], particularly against a background of high allelic diversity. Markers that score well on these metrics will have far higher reliability in breeding, and deficiencies in specific metrics give information on circumstances under which a marker may not be reliable. The metrics are applicable across different marker types and platforms, allowing an objective comparison of the performance of different markers irrespective of the platform. Evaluating markers using these metrics demonstrates that trait-specific markers consistently out-perform markers designed for other purposes. These metrics also provide a superb set of criteria for designing superior marker systems for a target QTL, enabling the selection of an optimal marker set before committing to design.

Retrotranspositional landscape of Asian rice revealed by 3000 genomes

The recent release of genomic sequences for 3000 rice varieties provides access to the genetic diversity at species level for this crop. We take advantage of this resource to unravel some features of the retrotranspositional landscape of rice. We develop software TRACKPOSON specifically for the detection of transposable elements insertion polymorphisms (TIPs) from large datasets. We apply this tool to 32 families of retrotransposons and identify more than 50,000 TIPs in the 3000 rice genomes. Most polymorphisms are found at very low frequency, suggesting that they may have occurred recently in agro. A genome-wide association study shows that these activations in rice may be triggered by external stimuli, rather than by the alteration of genetic factors involved in transposable element silencing pathways. Finally, the TIPs dataset is used to trace the origin of rice domestication. Our results suggest that rice originated from three distinct domestication events.

Improvements to the Rice Genome Annotation Through Large-Scale Analysis of RNA-Seq and Proteomics Data Sets

Rice (Oryza sativa) is one of the most important worldwide crops. The genome has been available for over 10 years and has undergone several rounds of annotation. We created a comprehensive database of transcripts from 29 public RNA sequencing data sets, officially predicted genes from Ensembl plants, and common contaminants in which to search for protein-level evidence. We re-analyzed nine publicly accessible rice proteomics data sets. In total, we identified 420K peptide spectrum matches from 47K peptides and 8,187 protein groups. 4168 peptides were initially classed as putative novel peptides (not matching official genes). Following a strict filtration scheme to rule out other possible explanations, we discovered 1,584 high confidence novel peptides. The novel peptides were clustered into 692 genomic loci where our results suggest annotation improvements. 80% of the novel peptides had an ortholog match in the curated protein sequence set from at least one other plant species. For the peptides clustering in intergenic regions (and thus potentially new genes), 101 loci were identified, for which 43 had a high-confidence hit for a protein domain. Our results can be displayed as tracks on the Ensembl genome or other browsers supporting Track Hubs, to support re-annotation of the rice genome.

A web-based tool for the prediction of rice transcription factor function

Transcription factors (TFs) are an important class of regulatory molecules. Despite their importance, only a small number of genes encoding TFs have been characterized in Oryza sativa (rice), often because gene duplication and functional redundancy complicate their analysis. To address this challenge, we developed a web-based tool called the Rice Transcription Factor Phylogenomics Database (RTFDB) and demonstrate its application for predicting TF function. The RTFDB hosts transcriptome and co-expression analyses. Sources include high-throughput data from oligonucleotide microarray (Affymetrix and Agilent) as well as RNA-Seq-based expression profiles. We used the RTFDB to identify tissue-specific and stress-related gene expression. Subsequently, 273 genes preferentially expressed in specific tissues or organs, 455 genes showing a differential expression pattern in response to 4 abiotic stresses, 179 genes responsive to infection of various pathogens and 512 genes showing differential accumulation in response to various hormone treatments were identified through the meta-expression analysis. Pairwise Pearson correlation coefficient analysis between paralogous genes in a phylogenetic tree was used to assess their expression collinearity and thereby provides a hint on their genetic redundancy. Integrating transcriptome with the gene evolutionary information reveals the possible functional redundancy or dominance played by paralog genes in a highly duplicated genome such as rice. With this method, we estimated a predominant role for 83.3% (65/78) of the TF or transcriptional regulator genes that had been characterized via loss-of-function studies. In this regard, the proposed method is applicable for functional studies of other plant species with annotated genome.

CRISPR-Cas9-Mediated Genome Editing of Rice Towards Better Grain Quality

With continued economic development in Asia the demand for high yielding varieties with premium grain quality traits is set to increase. This presents a significant challenge to plant breeders because varieties must be tailored to meet regional preferences. It is already apparent that traditional breeding techniques cannot meet this challenge and so emerging genomics technologies will have to be utilized. Genome editing tools afford the ability to efficiently and precisely manipulate the genome. Among these, the bacterial clustered, regularly interspaced, short palindromic repeat (CRISPR) associated protein 9 (Cas9) or CRISPR-Cas9 has emerged as the easiest, most economic, and efficient technology to undertake genome editing in rice. This technique allows precise site-specific gene modification or integration. In this chapter we present a method for utilizing CRISPR-Cas9 for improving grain quality traits in rice; this should enable molecular breeders to quickly and efficiently produce high yielding rice varieties tailored to meet specific cultural and regional requirements for grain quality.

Improving Rice Grain Quality: State-of-the-Art and Future Prospects

Rice grain quality encompasses complex interrelated traits that cover biochemical composition, cooking, eating, nutritional, and sensory properties. Because rice endosperm is composed mainly of starch, rice grain quality is traditionally defined by characterizing starch structure and composition, which is then subsequently correlated with functional properties of the grain. The current proxy tests routinely used to describe rice grain quality preferences are rather limited to the estimation of apparent amylose content, gelatinization temperature, and gel consistency. Additional tests that characterize starch property, viscoelasticity, grain texture, and aroma are also employed in more advanced laboratories. However, these tests are not routinely applied in breeding programs to distinguish cooking quality classes to reflect evolving consumer preference and market demand. As consumer preferences in Asia and all over the world are diverse due to varied demographics and culture, defining uniform attributes to capture regional grain quality preferences becomes more challenging. Hence, novel and innovative proxy tests are needed to characterize rice grain quality to meet the demand for consumer preferences of commercially-released cultivars. In this chapter, the current methods employed in rice grain quality monitoring are succinctly reviewed. Future prospects for improvement are identified, introducing cutting edge technologies that can facilitate high-throughput screening of rice diversity panels and breeding lines. Aside from addressing the requirements for quality improvement in the traditional inbred rice breeding programs, we also tackled the need to enhance grain quality in the hybrid rice sector.

Sensitive detection of pre-integration intermediates of long terminal repeat retrotransposons in crop plants

Retrotransposons have played an important role in the evolution of host genomes^1,2. Their impact is mainly deduced from the composition of DNA sequences that have been fixed over evolutionary time². Such studies provide important 'snapshots' reflecting the historical activities of transposons but do not predict current transposition potential. We previously reported sequence-independent retrotransposon trapping (SIRT) as a method that, by identification of extrachromosomal linear DNA (eclDNA), revealed the presence of active long terminal repeat (LTR) retrotransposons in Arabidopsis³. However, SIRT cannot be applied to large and transposon-rich genomes, as found in crop plants. We have developed an alternative approach named ALE-seq (amplification of LTR of eclDNAs followed by sequencing) for such situations. ALE-seq reveals sequences of 5' LTRs of eclDNAs after two-step amplification: in vitro transcription and subsequent reverse transcription. Using ALE-seq in rice, we detected eclDNAs for a novel Copia family LTR retrotransposon, Go-on, which is activated by heat stress. Sequencing of rice accessions revealed that Go-on has preferentially accumulated in Oryza sativa ssp. indica rice grown at higher temperatures. Furthermore, ALE-seq applied to tomato fruits identified a developmentally regulated Gypsy family of retrotransposons. A bioinformatic pipeline adapted for ALE-seq data analyses is used for the direct and reference-free annotation of new, active retroelements. This pipeline allows assessment of LTR retrotransposon activities in organisms for which genomic sequences and/or reference genomes are either unavailable or of low quality.

Rice Genomics: over the Past Two Decades and into the Future

Domestic rice (Oryza sativa L.) is one of the most important cereal crops, feeding a large number of worldwide populations. Along with various high-throughput genome sequencing projects, rice genomics has been making great headway toward direct field applications of basic research advances in understanding the molecular mechanisms of agronomical traits and utilizing diverse germplasm resources. Here, we briefly review its achievements over the past two decades and present the potential for its bright future.

On the Road to Breeding 4.0: Unraveling the Good, the Bad, and the Boring of Crop Quantitative Genomics

Understanding the quantitative genetics of crops has been and will continue to be central to maintaining and improving global food security. We outline four stages that plant breeding either has already achieved or will probably soon achieve. Top-of-the-line breeding programs are currently in Breeding 3.0, where inexpensive, genome-wide data coupled with powerful algorithms allow us to start breeding on predicted instead of measured phenotypes. We focus on three major questions that must be answered to move from current Breeding 3.0 practices to Breeding 4.0: ( a) How do we adapt crops to better fit agricultural environments? ( b) What is the nature of the diversity upon which breeding can act? ( c) How do we deal with deleterious variants? Answering these questions and then translating them to actual gains for farmers will be a significant part of achieving global food security in the twenty-first century.

NGS sequencing reveals that many of the genetic variations in transgenic rice plants match the variations found in natural rice population

BACKGROUND

As the transformation process can induce mutations in host plants, molecular characterization of the associated genomic changes is important not only for practical food safety but also for understanding the fundamental theories of genome evolution.

OBJECTIVES

To investigate a population-scale comparative study of the genome-wide spectrum of sequence variants in the transgenic genome with the variations present in 3000 rice varieties.

RESULTS

On average, we identified 19,273 SNPs (including Indels) per transgenic line in which 10,729 SNPs were at the identical locations in the three transgenic rice plants. We found that these variations were predominantly present in specific regions in chromosomes 8 and 10. Majority (88%) of the identified variations were detected at the same genomic locations as those in natural rice population, implying that the transgenic induced mutations had a tendency to be common alleles.

CONCLUSION

Genomic variations in transgenic rice plants frequently occurred at the same sites as the major alleles found in the natural rice population, which implies that the sequence variations occur within the limits of a biological system to ensure survival.

DNA fingerprinting at farm level maps rice biodiversity across Bangladesh and reveals regional varietal preferences

The development, dissemination, and adoption of improved rice varieties are imperative for global food and nutritional security. Knowledge of the crop's distribution across agro-ecologies is important for impact assessment studies, varietal replacement strategies, and the development and implementation of agricultural policies. Bangladesh is the world's 4th largest rice producer. Though traditional varieties (TVs) are abundant and valued throughout Bangladesh, population growth and vulnerability to climate change, necessitate efficient deployment of high-yielding stress-tolerant modern varieties (MVs). To aid agricultural policy and strategy this study aimed to accurately assess the distribution of MVs and TVs across Bangladesh during the rainfed rice-growing season. Information derived from a survey of rice production areas were compared and combined with DNA fingerprinting information from the same locations. Biodiversity of Bangladesh rice remained high. While TVs and first generation MVs of Bangladeshi and Indian origin were still commonly grown, recently released stress-tolerant MVs were adopted in large proportions in several districts. Although farmers successfully distinguished TVs from MVs grown in their fields, a considerable lack of authenticity among MVs was observed, pinpointing shortcomings in the seed supply chain. This study identifies focal points for extension work and validates DNA fingerprinting as reliable method for impact assessment studies.

Genomic approaches for studying crop evolution

Understanding how crop plants evolved from their wild relatives and spread around the world can inform about the origins of agriculture. Here, we review how the rapid development of genomic resources and tools has made it possible to conduct genetic mapping and population genetic studies to unravel the molecular underpinnings of domestication and crop evolution in diverse crop species. We propose three future avenues for the study of crop evolution: establishment of high-quality reference genomes for crops and their wild relatives; genomic characterization of germplasm collections; and the adoption of novel methodologies such as archaeogenetics, epigenomics, and genome editing.

Chromosome-scale comparative sequence analysis unravels molecular mechanisms of genome dynamics between two wheat cultivars

BACKGROUND

Recent improvements in DNA sequencing and genome scaffolding have paved the way to generate high-quality de novo assemblies of pseudomolecules representing complete chromosomes of wheat and its wild relatives. These assemblies form the basis to compare the dynamics of wheat genomes on a megabase scale.

RESULTS

Here, we provide a comparative sequence analysis of the 700-megabase chromosome 2D between two bread wheat genotypes-the old landrace Chinese Spring and the elite Swiss spring wheat line 'CH Campala Lr22a'. Both chromosomes were assembled into megabase-sized scaffolds. There is a high degree of sequence conservation between the two chromosomes. Analysis of large structural variations reveals four large indels of more than 100 kb. Based on the molecular signatures at the breakpoints, unequal crossing over and double-strand break repair were identified as the molecular mechanisms that caused these indels. Three of the large indels affect copy number of NLRs, a gene family involved in plant immunity. Analysis of SNP density reveals four haploblocks of 4, 8, 9 and 48 Mb with a 35-fold increased SNP density compared to the rest of the chromosome. Gene content across the two chromosomes was highly conserved. Ninety-nine percent of the genic sequences were present in both genotypes and the fraction of unique genes ranged from 0.4 to 0.7%.

CONCLUSIONS

This comparative analysis of two high-quality chromosome assemblies enabled a comprehensive assessment of large structural variations and gene content. The insight obtained from this analysis will form the basis of future wheat pan-genome studies.

Loci and natural alleles underlying robust roots and adaptive domestication of upland ecotype rice in aerobic conditions

A robust (long and thick) root system is characteristic of upland japonica rice adapted to drought conditions. Using deep sequencing and large scale phenotyping data of 795 rice accessions and an integrated strategy combining results from high resolution mapping by GWAS and linkage mapping, comprehensive analyses of genomic, transcriptomic and haplotype data, we identified large numbers of QTLs affecting rice root length and thickness (RL and RT) and shortlisted relatively few candidate genes for many of the identified small-effect QTLs. Forty four and 97 QTL candidate genes for RL and RT were identified, and five of the RL QTL candidates were validated by T-DNA insertional mutation; all have diverse functions and are involved in root development. This work demonstrated a powerful strategy for highly efficient cloning of moderate- and small-effect QTLs that is difficult using the classical map-based cloning approach. Population analyses of the 795 accessions, 202 additional upland landraces, and 446 wild rice accessions based on random SNPs and SNPs within robust loci suggested that there could be much less diversity in robust-root candidate genes among upland japonica accessions than in other ecotypes. Further analysis of nucleotide diversity and allele frequency in the robust loci among different ecotypes and wild rice accessions showed that almost all alleles could be detected in wild rice, and pyramiding of robust-root alleles could be an important genetic characteristic of upland japonica. Given that geographical distribution of upland landraces, we suggest that during domestication of upland japonica, the strongest pyramiding of robust-root alleles makes it a unique ecotype adapted to aerobic conditions.

Asian cultivated rice is well-known for its rich-within-species diversity with two major subspecies, indica and japonica and subpopulation differentiation. A robust (long and thick) root system that is characteristic of upland japonica rice represents a predominant ecotype grown under aerobic and rain-fed conditions. In this study, we identified candidate genes for root length and root thickness, and validated five root length candidates by T-DNA insertional mutations. Further analyses of an Asian cultivated and wild rice population were performed based on random SNPs and SNPs within robust loci. The findings hold promise for application in improving drought resistance and also reveal the adaptive domestication history of upland rice as a unique Asian cultivated rice ecotype.

Exploiting the Genomic Diversity of Rice (Oryza sativa L.): SNP-Typing in 11 Early-Backcross Introgression-Breeding Populations

This study demonstrates genotyping-by-sequencing-based single-nucleotide polymorphism (SNP)-typing in 11 early-backcross introgression populations of rice (at BC1F5), comprising a set of 564 diverse introgression lines and 12 parents. Sequencing using 10 Ion Proton runs generated a total of ∼943.4 million raw reads, out of which ∼881.6 million reads remained after trimming for low-quality bases. After alignment, 794,297 polymorphic SNPs were identified, and filtering resulted in LMD50 SNPs (low missing data, with each SNP, genotyped in at least 50% of the samples) for each sub-population. Every data point was supported by actual sequencing data without any imputation, eliminating imputation-induced errors in SNP calling. Genotyping substantiated the impacts of novel breeding strategy revealing: (a) the donor introgression patterns in ILs were characteristic with variable introgression frequency in different genomic regions, attributed mainly to stringent selection under abiotic stress and (b) considerably lower heterozygosity was observed in ILs. Functional annotation revealed 426 non-synonymous deleterious SNPs present in 102 loci with a range of 1-4 SNPs per locus and 120 novel SNPs. SNP-typing this diversity panel will further assist in the development of markers supporting genomic applications in molecular breeding programs.