Natural variation in Tiller Number 1 affects its interaction with TIF1 to regulate tillering in rice.

Tiller number per plant-a cardinal component of ideal plant architecture-affects grain yield potential. Thus, alleles positively affecting tillering must be mined to promote genetic improvement. Here, we report a Tiller Number 1 (TN1) protein harbouring a bromo-adjacent homology domain and RNA recognition motifs, identified through genome-wide association study of tiller numbers. Natural variation in TN1 affects its interaction with TIF1 (TN1 interaction factor 1) to affect DWARF14 expression and negatively regulate tiller number in rice. Further analysis of variations in TN1 among indica genotypes according to geographical distribution revealed that low-tillering varieties with TN1-hapL are concentrated in Southeast Asia and East Asia, whereas high-tillering varieties with TN1-hapH are concentrated in South Asia. Taken together, these results indicate that TN1 is a tillering regulatory factor whose alleles present apparent preferential utilization across geographical regions. Our findings advance the molecular understanding of tiller development.

High-precision early warning system for rice cadmium accumulation risk assessment.

Rapid global industrialization has resulted in widespread cadmium contamination in agricultural soils and products. A considerable proportion of rice consumers are exposed to Cd levels above the provisional safe intake limit, raising widespread environmental concerns on risk management. Therefore, a generalized approach is urgently needed to enable correct evaluation and early warning of cadmium contaminants in rice products. Combining big data and computer science together, this study developed a system named "SMART Cd Early Warning", which integrated 4 modules including genotype-to-phenotype (G2P) modelling, high-throughput sequencing, G2P prediction and rice Cd contamination risk assessment, for rice cadmium accumulation early warning. This system can rapidly assess the risk of rice cadmium accumulation by genotyping leaves at seeding stage. The parameters including statistical methods, population size, training population-testing population ratio, SNP density were assessed to ensure G2P model exhibited superior performance in terms of prediction precision (up to 0.76 ± 0.003) and computing efficiency (within 2 h). In field trials of cadmium-contaminated farmlands in Wenling and Fuyang city, Zhejiang Province, "SMART Cd Early Warning" exhibited superior capability for identification risk rice varieties, suggesting a potential of "SMART Cd Early-Warning system" in OsGCd risk assessment and early warning in the age of smart.

Large-scale genomic and transcriptomic profiles of rice hybrids reveal a core mechanism underlying heterosis.

BACKGROUND: Heterosis is widely used in agriculture. However, its molecular mechanisms are still unclear in plants. Here, we develop, sequence, and record the phenotypes of 418 hybrids from crosses between two testers and 265 rice varieties from a mini-core collection. RESULTS: Phenotypic analysis shows that heterosis is dependent on genetic backgrounds and environments. By genome-wide association study of 418 hybrids and their parents, we find that nonadditive QTLs are the main genetic contributors to heterosis. We show that nonadditive QTLs are more sensitive to the genetic background and environment than additive ones. Further simulations and experimental analysis support a novel mechanism, homo-insufficiency under insufficient background (HoIIB), underlying heterosis. We propose heterosis in most cases is not due to heterozygote advantage but homozygote disadvantage under the insufficient genetic background. CONCLUSION: The HoIIB model elucidates that genetic background insufficiency is the intrinsic mechanism of background dependence, and also the core mechanism of nonadditive effects and heterosis. This model can explain most known hypotheses and phenomena about heterosis, and thus provides a novel theory for hybrid rice breeding in future.

Selective and comparative genome architecture of Asian cultivated rice (Oryza sativa L.) attributed to domestication and modern breeding.

INTRODUCTION: Rice, Oryza sativa L. (Os), is one of the oldest domesticated cereals that has also gone through extensive improvement in modern breeding. OBJECTIVES: How rice was domesticated and impacted by modern breeding. METHODS: We performed comprehensive analyses of genomic sequences of 504 accessions of Os and 456 accessions of O. rufipogon/O. nivara (Or). RESULTS: The natural selection on Or before domestication and the natural and artificial selection during domestication together shaped the well-differentiated genomes of two subspecies, geng(j) (japonica) and xian(i) (indica), while breeding has made apparent genomic imprints between landrace and modern varieties of each subspecies, and also between primary modern and advanced modern varieties of xian(i). Selection during domestication and breeding left genome-wide selective signals covering âˆ¼ 22.8 % and âˆ¼ 8.6 % of the Os genome, significantly reduced within-population genomic diversity by âˆ¼ 22 % in xian(i) and âˆ¼ 53 % in geng(j) plus more pronounced subspecific differentiation. Only âˆ¼ 10 % reduction in the total genomic diversity was observed between the Os and Or populations, indicating domestication did not suffer severe genetic bottleneck. CONCLUSION: Our results revealed clear differentiation of the Or accessions into three large populations, two of which correspond to the well-differentiated Os subspecies, geng(j) and xian(i). Improved productivity and common changes in the same suit of adaptive traits in xian(i) and geng(j) during domestication and breeding resulted apparently from compensatory and convergent selections for different genes/alleles acting in the common KEGG terms and/or same gene families, and thus maintaining or even increasing the within population diversity and subspecific differentiation of Os, while more genes/alleles of novel function were selected during domestication than modern breeding. Our results supported the multiple independent domestication of Os in Asia and suggest the more efficient utilization of the rich diversity within Os by exploiting inter-subspecific and among population diversity in future rice improvement.

RGN1 controls grain number and shapes panicle architecture in rice.

Yield in rice is determined mainly by panicle architecture. Using map-based cloning, we identified an R2R3 MYB transcription factor REGULATOR OF GRAIN NUMBER1 (RGN1) affecting grain number and panicle architecture. Mutation of RGN1 caused an absence of lateral grains on secondary branches. We demonstrated that RGN1 controls lateral grain formation by regulation of LONELY GUY (LOG) expression, thus controlling grain number and shaping panicle architecture. A novel favourable allele, RGN1C , derived from the Or-I group in wild rice affected panicle architecture by means longer panicles. Identification of RGN1 provides a theoretical basis for understanding the molecular mechanism of lateral grain formation in rice; RGN1 will be an important gene resource for molecular breeding for higher yield.

Natural variation of RGN1a regulates grain number per panicle in japonica rice.

The grain number per panicle (GNP) is an important yield component. Identifying naturally favorable variations in GNP will benefit high-yield rice breeding. Here, we performed a genome-wide association study using a mini-core collection of 266 cultivated rice accessions with deep sequencing data and investigated the phenotype for three years. Three genes, i.e., TOTOU1 (TUT1), Grain height date 7 (Ghd7), and Days to heading 7/Grain height date 7.1/Pseudo-Response Regulator37 (DTH7/Ghd7.1/OsPRR37), which regulate GNP, were found in the quantitative trait loci (QTL) identified in this study. A stable QTL, qGNP1.3, which showed a strong correlation with variations in GNP, was repeatedly detected. After functional and transgenic phenotype analysis, we identified a novel gene, regulator of grain number 1a (RGN1a), which codes for protein kinase, controlling GNP in rice. The RGN1a mutation caused 37.2%, 27.8%, 51.2%, and 25.5% decreases in grain number, primary branch number per panicle, secondary branch number per panicle, and panicle length, respectively. Furthermore, breeding utilization analysis revealed that the additive effects of the dominant allelic variants of RGN1a and DTH7 played a significant role in increasing the grain number per panicle in japonica rice. Our findings enrich the gene pool and provide an effective strategy for the genetic improvement of grain numbers.

Genetic basis and network underlying synergistic roots and shoots biomass accumulation revealed by genome-wide association studies in rice.

Genetic basis and network studies underlying synergistic biomass accumulation of roots and shoots (SBA) are conducive for rational design of high-biomass rice breeding. In this study, association signals for root weight, shoot weight, and the ratio of root-to-shoot mass (R/S) were identified using 666 rice accessions by genome-wide association study, together with their sub-traits, root length, root thickness and shoot length. Most association signals for root weight and shoot weight did not show association with their sub-traits. Based on the results, we proposed a top-to-bottom model for SBA, i.e. root weight, shoot weight and R/S were determined by their highest priority in contributing to biomass in the regulatory pathway, followed by a lower priority pathway for their sub-traits. Owing to 37 enriched clusters with more than two association signals identified, the relationship among the six traits could be also involved in linkage and pleiotropy. Furthermore, a discrimination of pleiotropy and LD at sequencing level using the known gene OsPTR9 for root weight, R/S and root length was provided. The results of given moderate correlation between traits and their corresponding sub-traits, and moderate additive effects between a trait and the accumulation of excellent alleles corresponding to its sub-traits supported a bottom-to-top regulation model for SBA. This model depicted each lowest-order trait (root length, root thickness and shoot length) was determined by its own regulation loci, and competition among different traits, as well as the pleiotropy and LD. All above ensure the coordinated development of each trait and the accumulation of the total biomass, although the predominant genetic basis of SBA is still indistinguishable. The presentation of the above two models and evidence of this study shed light on dissecting the genetic architecture of SBA.

Distinct nucleotide patterns among three subgenomes of bread wheat and their potential origins during domestication after allopolyploidization.

BACKGROUND: The speciation and fast global domestication of bread wheat have made a great impact on three subgenomes of bread wheat. DNA base composition is an essential genome feature, which follows the individual-strand base equality rule and [AT]-increase pattern at the genome, chromosome, and polymorphic site levels among thousands of species. Systematic analyses on base compositions of bread wheat and its wild progenitors could facilitate further understanding of the evolutionary pattern of genome/subgenome-wide base composition of allopolyploid species and its potential causes. RESULTS: Genome/subgenome-wide base-composition patterns were investigated by using the data of polymorphic site in 93 accessions from worldwide populations of bread wheat, its diploid and tetraploid progenitors, and their corresponding reference genome sequences. Individual-strand base equality rule and [AT]-increase pattern remain in recently formed hexaploid species bread wheat at the genome, subgenome, chromosome, and polymorphic site levels. However, D subgenome showed the fastest [AT]-increase across polymorphic site from Aegilops tauschii to bread wheat than that on A and B subgenomes from wild emmer to bread wheat. The fastest [AT]-increase could be detected almost all chromosome windows on D subgenome, suggesting different mechanisms between D and other two subgenomes. Interestingly, the [AT]-increase is mainly contributed by intergenic regions at non-selective sweeps, especially the fastest [AT]-increase of D subgenome. Further transition frequency and sequence context analysis indicated that three subgenomes shared same mutation type, but D subgenome owns the highest mutation rate on high-frequency mutation type. The highest mutation rate on D subgenome was further confirmed by using a bread-wheat-private SNP set. The exploration of loci/genes related to the [AT] value of D subgenome suggests the fastest [AT]-increase of D subgenome could be involved in DNA repair systems distributed on three subgenomes of bread wheat. CONCLUSIONS: The highest mutation rate is detected on D subgenome of bread wheat during domestication after allopolyploidization, leading to the fastest [AT]-increase pattern of D subgenome. The phenomenon may come from the joint action of multiple repair systems inherited from its wild progenitors.

Genetic architecture to cause dynamic change in tiller and panicle numbers revealed by genome-wide association study and transcriptome profile in rice.

Panicle number (PN) is one of the three yield components in rice. As one of the most unstable traits, the dynamic change in tiller number (DCTN) may determine the final PN. However, the genetic basis of DCTN and its relationship with PN remain unclear. Here, 377 deeply re-sequenced rice accessions were used to perform genome-wide association studies (GWAS) for tiller/PN. It was found that the DCTN pattern rather than maximum tiller number or effective tiller ratio is the determinant factor of high PN. The DCTN pattern that affords more panicles exhibits a period of stable tillering peak between 30 and 45 days after transplant (called DT30 and DT45, respectively), which was believed as an ideal pattern contributing to the steady transition from tiller development to panicle development (ST-TtP). Consistently, quantitative trait loci (QTL) expressed near DT30-DT45 were especially critical to the rice DCTN and in supporting the ST-TtP. The spatio-temporal expression analysis showed that the expression pattern of keeping relatively high expression in root at 24:00 (R24-P2) from about DT30 to DT45 is a typical expression pattern of cloned tiller genes, and the candidate genes with R24-P2 can facilitate the prediction of PN. Moreover, gene OsSAUR27 was identified by an integrated approach combining GWAS, bi-parental QTL mapping and transcription. These findings related to the genetic basis underlying the DCTN will provide the genetic theory in making appropriate decisions on field management, and in developing new varieties with high PN and ideal dynamic plant architecture.

Author Correction: Variation of a major facilitator superfamily gene contributes to differential cadmium accumulation between rice subspecies.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Variation of a major facilitator superfamily gene contributes to differential cadmium accumulation between rice subspecies.

Cadmium (Cd) accumulation in rice grain poses a serious threat to human health. While several transport systems have been reported, the complicity of rice Cd transport and accumulation indicates the necessity of identifying additional genes, especially those that are responsible for Cd accumulation divergence between indica and japonica rice subspecies. Here, we show that a gene, OsCd1, belonging to the major facilitator superfamily is involved in root Cd uptake and contributes to grain accumulation in rice. Natural variation in OsCd1 with a missense mutation Val449Asp is responsible for the divergence of rice grain Cd accumulation between indica and japonica. Near-isogenic line tests confirm that the indica variety carrying the japonica allele OsCd1V449 can reduce the grain Cd accumulation. Thus, the japonica allele OsCd1V449 may be useful for reducing grain Cd accumulation of indica rice cultivars through breeding.

Identifying natural genotypes of grain number per panicle in rice (Oryza sativa L.) by association mapping.

INTRODUCTION: As one of the main yield components, grain number per panicle (GNP) played critical role in the rice yield improvement. The identification of natural advantageous variations under different situations will promote the sustainable genetic improvement in rice yield. OBJECTIVES: This study was designed to identify natural genotypes in a rice mini-core collection, to examine the genotypic effects across the indica and japonica genetic background in different environments, and excavating the superior genotypes that had drove the modern genetic improvement. METHODS: The association mapping of GNP was carried out using a mini-core collection including 154 indica and 119 japonica accessions in seven different environments. Genotypic effects of each genotype for each QTL were calculated and genotype frequency distortion between the commercial rice cultivars and landraces was screened by χ2-test. RESULTS: In total, 74 QTLs containing stable and sensitive QTLs in various environments were detected. Within them, 20 positive and 24 negative genotypes in indica, and 24 positive and 16 negative genotypes in japonica were identified. When checking the accumulation of positive genotypes identified in indica across cultivars in each of the two subspecies, it indicated that increased number of positive genotypes identified in indica results in the substantially increased GNP in both indica and japonica across all of the environments, while this trend was not obvious for the positive genotypes identified in japonica especially in short day environments. Moreover, the positive and negative genotype frequency distortion between the landraces and commercial rice cultivars indicated that both positive selection of positive genotypes and negative selection of negative genotypes had driven the genetic improvement on GNP. CONCLUSION: Our findings suggested that the accumulation of positive genotypes and purifying negative genotypes played equivalently important roles in the improvement of rice yield, but the efficient use for some QTLs or genotypes depends on the comprehensive evaluation of their effect under diverse genetic backgrounds and environments.

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.

Genetic Basis Underlying Correlations Among Growth Duration and Yield Traits Revealed by GWAS in Rice (Oryza sativa L.).

Avoidance of disadvantageous genetic correlations among growth duration and yield traits is critical in developing crop varieties that efficiently use light and energy resources and produce high yields. To understand the genetic basis underlying the correlations among heading date and three major yield traits in rice, we investigated the four traits in a diverse and representative core collection of 266 cultivated rice accessions in both long-day and short-day environments, and conducted the genome-wide association study using 4.6 million single nucleotide polymorphisms (SNPs). There were clear positive correlation between heading date and grain number per panicle, and negative correlation between grain number per panicle and panicle number, as well as different degrees of correlations among other traits in different subspecies and environments. We detected 47 pleiotropic genes in 15 pleiotropic quantitative trait loci (pQTLs), 18 pleiotropic genes containing 37 pleiotropic SNPs in 8 pQTLs, 27 pQTLs with r2 of linkage disequilibrium higher than 0.2, and 39 pairs of interactive genes from 8 metabolic pathways that may contribute to the above phenotypic correlations, but these genetic bases were different for correlations among different traits. Distributions of haplotypes revealed that selection for pleiotropic genes or interactive genes controlling different traits focused on genotypes with weak effect or on those balancing two traits that maximized production but sometimes their utilization strategies depend on the traits and environment. Detection of pQTLs and interactive genes and associated molecular markers will provide an ability to overcome disadvantageous correlations and to utilize the advantageous correlations among traits through marker-assisted selection in breeding.

Genetic Architecture and Candidate Genes for Deep-Sowing Tolerance in Rice Revealed by Non-syn GWAS.

Dry direct-seeding of rice is rapidly increasing in China, but variable planting depth associated with machine sowing can lead to low seedling emergence rates. Phenotype analysis of 621 rice accessions showed that mesocotyl length (ML) was induced by deep soil covering and was important in deep-sowing tolerance in the field. Here, we performed and compared GWAS using three types of SNPs (non-synonymous SNP, non-synonymous SNPs and SNPs within promoters and 3 million randomly selected SNPs from the entire set of SNPs) and found that Non-Syn GWAS (GWAS using non-synonyomous SNP) decreased computation time and eliminated confounding by other loci relative to GWAS using randomly selected SNPs. Thirteen QTLs were finally detected, and two new major-effect genes, named OsML1 and OsML2, were identified by an integrated analysis. There were 2 and 7 non-synonymous SNPs in OsML1 and OsML2, respectively, from which 3 and 4 haplotypes were detected in cultivated rice. Combinations of superior haplotypes of OsML1 and OsML2 increased ML by up to 4 cm, representing high emergence rate (85%) in the field with 10 cm of soil cover. The studies provide key loci and naturally occurring alleles of ML that can be used in improving tolerance to dry direct-seeding.