High-throughput UAV-based rice panicle detection and genetic mapping of heading-date-related traits.

Introduction: Rice (Oryza sativa) serves as a vital staple crop that feeds over half the world's population. Optimizing rice breeding for increasing grain yield is critical for global food security. Heading-date-related or Flowering-time-related traits, is a key factor determining yield potential. However, traditional manual phenotyping methods for these traits are time-consuming and labor-intensive. Method: Here we show that aerial imagery from unmanned aerial vehicles (UAVs), when combined with deep learning-based panicle detection, enables high-throughput phenotyping of heading-date-related traits. We systematically evaluated various state-of-the-art object detectors on rice panicle counting and identified YOLOv8-X as the optimal detector. Results: Applying YOLOv8-X to UAV time-series images of 294 rice recombinant inbred lines (RILs) allowed accurate quantification of six heading-date-related traits. Utilizing these phenotypes, we identified quantitative trait loci (QTL), including verified loci and novel loci, associated with heading date. Discussion: Our optimized UAV phenotyping and computer vision pipeline may facilitate scalable molecular identification of heading-date-related genes and guide enhancements in rice yield and adaptation.

Structure and function of rice hybrid genomes reveal genetic basis and optimal performance of heterosis.

Exploitation of crop heterosis is crucial for increasing global agriculture production. However, the quantitative genomic analysis of heterosis was lacking, and there is currently no effective prediction tool to optimize cross-combinations. Here 2,839 rice hybrid cultivars and 9,839 segregation individuals were resequenced and phenotyped. Our findings demonstrated that indica-indica hybrid-improving breeding was a process that broadened genetic resources, pyramided breeding-favorable alleles through combinatorial selection and collaboratively improved both parents by eliminating the inferior alleles at negative dominant loci. Furthermore, we revealed that widespread genetic complementarity contributed to indica-japonica intersubspecific heterosis in yield traits, with dominance effect loci making a greater contribution to phenotypic variance than overdominance effect loci. On the basis of the comprehensive dataset, a genomic model applicable to diverse rice varieties was developed and optimized to predict the performance of hybrid combinations. Our data offer a valuable resource for advancing the understanding and facilitating the utilization of heterosis in rice.

The WD40 domain-containing protein Ehd5 positively regulates flowering in rice (Oryza sativa).

Heading date (flowering time), which greatly influences regional and seasonal adaptability in rice (Oryza sativa), is regulated by many genes in different photoperiod pathways. Here, we characterized a heading date gene, Early heading date 5 (Ehd5), using a modified bulked segregant analysis method. The ehd5 mutant showed late flowering under both short-day and long-day conditions, as well as reduced yield, compared to the wild type. Ehd5, which encodes a WD40 domain-containing protein, is induced by light and follows a circadian rhythm expression pattern. Transcriptome analysis revealed that Ehd5 acts upstream of the flowering genes Early heading date 1 (Ehd1), RICE FLOWERING LOCUS T 1 (RFT1), and Heading date 3a (Hd3a). Functional analysis showed that Ehd5 directly interacts with Rice outermost cell-specific gene 4 (Roc4) and Grain number, plant height, and heading date 8 (Ghd8), which might affect the formation of Ghd7-Ghd8 complexes, resulting in increased expression of Ehd1, Hd3a, and RFT1. In a nutshell, these results demonstrate that Ehd5 functions as a positive regulator of rice flowering and provide insight into the molecular mechanisms underlying heading date.

Usage, acceptability, and preliminary effectiveness of an mHealth-based integrated modality for smoking cessation interventions in Western China.

INTRODUCTION: Many smokers have not accessed professional smoking cessation assistance due to limited smoking cessation services. We developed a novel mHealth-based integrated modality for smoking cessation (WeChat + Quitline modality, WQ modality) and applied it to a large public welfare project (China Western-QUIT Program) in western China. This study evaluated the usage, acceptability, and preliminary effectiveness of the WQ modality in the population of western China. METHODS: A prospective cohort study was conducted between April and August 2021. Smokers or their relatives were recruited through online advertisements and medical staff referrals. After using the services of the WQ modality for one month, the self-reported awareness, use, and satisfaction with each service among the participants were collected by a telephone interview. We also evaluated the self-reported 7-day point prevalence of abstinence (PPA) and quit attempt rate among baseline current smokers. The usage data of each service were downloaded from quitline and WeChat platforms. RESULTS: Of the 17326 people from western China using the WQ modality, the largest number of users was WeChat official account (11173), followed by WeChat mini program (3734), WeChat group (669), and quitline (541 inbound calls, 605 outbound calls). At one month follow-up, over 70% of participants who completed the baseline survey (n=2221) were aware of WeChat-based services, and over 50% used them. However, the awareness rate (11.1%) and utilization rate (0.5%) of quitline were relatively low. The median satisfaction scores across all services were 9 out of 10 points (IQR: 8-9). Among the baseline current smokers (n=1257), self-reported 7-day PPA was 41.8% (526/1257), and another 225 smokers (17.9%) reported making a quit attempt. CONCLUSIONS: The WQ modality could be well used and accepted, and it has great potential to motivate and aid short-term smoking cessation in smokers from western China.

Armadillo repeat only protein GS10 negatively regulates brassinosteroid signaling to control rice grain size.

Grain yield and grain quality are major determinants in modern breeding controlled by many quantitative traits loci (QTLs) in rice (Oryza sativa). However, the mechanisms underlying grain shape and quality are poorly understood. Here, we characterize a QTL for grain size and grain quality via map-based cloning from wild rice (W1943), GS10 (Grain Size on Chromosome 10), which encodes a protein with 6 tandem armadillo repeats. The null mutant gs10 shows slender and narrow grains with altered cell size, which has a pleiotropic effect on other agronomical traits. Functional analysis reveals that GS10 interacts with TUD1 (Taihu Dwarf1) and is epistatic to OsGSK2 (glycogen synthase kinase 2) through regulating grain shape and lamina joint inclination, indicating it is negatively involved in brassinosteroid (BR) signaling. Pyramiding gs10 and the grain size gene GW5 into cultivar GLA4 substantially improved grain shape and appearance quality. Natural variation analysis revealed that gs10 from the wild rice Oryza rufipogon W1943 is a rare allele across the rice population. Collectively, these findings advance our understanding of the underlying mechanism of grain shape and provide the beneficial allele of gs10 for future rice breeding and genetic improvement.

A retrotransposon insertion in MUTL-HOMOLOG 1 affects wild rice seed set and cultivated rice crossover rate.

Wild rice (Oryza rufipogon) has a lower panicle seed setting rate (PSSR) and gamete fertility than domesticated rice (Oryza sativa), but the genetic mechanisms of this phenomenon remain unknown. Here, we cloned a null allele of OsMLH1, an ortholog of MutL-homolog 1 to yeast and mammals, from wild rice O. rufipogon W1943 and revealed a 5.4-kb retrotransposon insertion in OsMLH1 is responsible for the low PSSR in wild rice. In contrast to the wild-type, a near isogenic line NIL-mlh1 exhibits defective crossover (CO) formation during meiosis, resulting in reduced pollen viability, partial embryo lethality, and low PSSR. Except for the mutant of mismatch repair gene postmeiotic segregation 1 (Ospms1), all other MutL mutants from O. sativa indica subspecies displayed male and female semi-sterility similar to NIL-mlh1, but less severe than those from O. sativa japonica subspecies. MLH1 and MLH3 did not contribute in an additive fashion to fertility. Two types of MutL heterodimers, MLH1-PMS1 and MLH1-MLH3, were identified in rice, but only the latter functions in promoting meiotic CO formation. Compared to japonica varieties, indica cultivars had greater numbers of CO events per meiosis. Our results suggest that low fertility in wild rice may be caused by different gene defects, and indica and japonica subspecies have substantially different CO rates responsible for the discrepancy between the fertility of mlh1 and mlh3 mutants.

AirMeasurer: open-source software to quantify static and dynamic traits derived from multiseason aerial phenotyping to empower genetic mapping studies in rice.

Low-altitude aerial imaging, an approach that can collect large-scale plant imagery, has grown in popularity recently. Amongst many phenotyping approaches, unmanned aerial vehicles (UAVs) possess unique advantages as a consequence of their mobility, flexibility and affordability. Nevertheless, how to extract biologically relevant information effectively has remained challenging. Here, we present AirMeasurer, an open-source and expandable platform that combines automated image analysis, machine learning and original algorithms to perform trait analysis using 2D/3D aerial imagery acquired by low-cost UAVs in rice (Oryza sativa) trials. We applied the platform to study hundreds of rice landraces and recombinant inbred lines at two sites, from 2019 to 2021. A range of static and dynamic traits were quantified, including crop height, canopy coverage, vegetative indices and their growth rates. After verifying the reliability of AirMeasurer-derived traits, we identified genetic variants associated with selected growth-related traits using genome-wide association study and quantitative trait loci mapping. We found that the AirMeasurer-derived traits had led to reliable loci, some matched with published work, and others helped us to explore new candidate genes. Hence, we believe that our work demonstrates valuable advances in aerial phenotyping and automated 2D/3D trait analysis, providing high-quality phenotypic information to empower genetic mapping for crop improvement.

Enhancing rice grain production by manipulating the naturally evolved cis-regulatory element-containing inverted repeat sequence of OsREM20.

Grain number per panicle (GNP) is an important agronomic trait that contributes to rice grain yield. Despite its importance in rice breeding, the molecular mechanism underlying GNP regulation remains largely unknown. In this study, we identified a previously unrecognized regulatory gene that controls GNP in rice, Oryza sativa REPRODUCTIVE MERISTEM 20 (OsREM20), which encodes a B3 domain transcription factor. Through genetic analysis and transgenic validation we found that genetic variation in the CArG box-containing inverted repeat (IR) sequence of the OsREM20 promoter alters its expression level and contributes to GNP variation among rice varieties. Furthermore, we revealed that the IR sequence regulates OsREM20 expression by affecting the direct binding of OsMADS34 to the CArG box within the IR sequence. Interestingly, the divergent pOsREM20IR and pOsREM20ΔIR alleles were found to originate from different Oryza rufipogon accessions, and were independently inherited into the japonica and indica subspecies, respectively, during domestication. Importantly, we demonstrated that IR sequence variations in the OsREM20 promoter can be utilized for germplasm improvement through either genome editing or traditional breeding. Taken together, our study characterizes novel genetic variations responsible for GNP diversity in rice, reveals the underlying molecular mechanism in the regulation of agronomically important gene expression, and provides a promising strategy for improving rice production by manipulating the cis-regulatory element-containing IR sequence.

The PLATZ Transcription Factor GL6 Affects Grain Length and Number in Rice.

Grain size is one of the key determinants of grain yield. Although a number of genes that control grain size in rice (Oryza sativa) have been identified, the overall regulatory networks behind this process remain poorly understood. Here, we report the map-based cloning and functional characterization of the quantitative trait locus GL6, which encodes a plant-specific plant AT-rich sequence- and zinc-binding transcription factor that regulates rice grain length and spikelet number. GL6 positively controls grain length by promoting cell proliferation in young panicles and grains. The null gl6 mutant possesses short grains, whereas overexpression of GL6 results in large grains and decreased grain number per panicle. We demonstrate that GL6 participates in RNA polymerase III transcription machinery by interacting with RNA polymerase III subunit C53 and transcription factor class C1 to regulate the expression of genes involved in rice grain development. Our findings reveal a further player involved in the regulation of rice grain size that may be exploited in future rice breeding.

Publisher Correction: Pan-genome analysis highlights the extent of genomic variation in cultivated and wild rice.

When published, this article did not initially appear open access. This error has been corrected, and the open access status of the paper is noted in all versions of the paper.

Pan-genome analysis highlights the extent of genomic variation in cultivated and wild rice.

The rich genetic diversity in Oryza sativa and Oryza rufipogon serves as the main sources in rice breeding. Large-scale resequencing has been undertaken to discover allelic variants in rice, but much of the information for genetic variation is often lost by direct mapping of short sequence reads onto the O. sativa japonica Nipponbare reference genome. Here we constructed a pan-genome dataset of the O. sativa-O. rufipogon species complex through deep sequencing and de novo assembly of 66 divergent accessions. Intergenomic comparisons identified 23 million sequence variants in the rice genome. This catalog of sequence variations includes many known quantitative trait nucleotides and will be helpful in pinpointing new causal variants that underlie complex traits. In particular, we systemically investigated the whole set of coding genes using this pan-genome data, which revealed extensive presence and absence of variation among rice accessions. This pan-genome resource will further promote evolutionary and functional studies in rice.

An-1 encodes a basic helix-loop-helix protein that regulates awn development, grain size, and grain number in rice.

Long awns are important for seed dispersal in wild rice (Oryza rufipogon), but are absent in cultivated rice (Oryza sativa). The genetic mechanism involved in loss-of-awn in cultivated rice remains unknown. We report here the molecular cloning of a major quantitative trait locus, An-1, which regulates long awn formation in O. rufipogon. An-1 encodes a basic helix-loop-helix protein, which regulates cell division. The nearly-isogenic line (NIL-An-1) carrying a wild allele An-1 in the genetic background of the awnless indica Guangluai4 produces long awns and longer grains, but significantly fewer grains per panicle compared with Guangluai4. Transgenic studies confirmed that An-1 positively regulates awn elongation, but negatively regulates grain number per panicle. Genetic variations in the An-1 locus were found to be associated with awn loss in cultivated rice. Population genetic analysis of wild and cultivated rice showed a significant reduction in nucleotide diversity of the An-1 locus in rice cultivars, suggesting that the An-1 locus was a major target for artificial selection. Thus, we propose that awn loss was favored and strongly selected by humans, as genetic variations at the An-1 locus that cause awn loss would increase grain numbers and subsequently improve grain yield in cultivated rice.

Identification of QTLs associated with tissue culture response through sequencing-based genotyping of RILs derived from 93-11 × Nipponbare in rice (Oryza sativa).

KEY MESSAGE : The performance of callus induction and callus differentiation was evaluated by 9 indices for 140 RILs; 2 major QTLs associated with plant regeneration were identified. In order to investigate the genetic mechanisms of tissue culture response, 140 recombinant inbred lines (RILs) derived from 93-11 (Oryza sativa ssp. indica) × Nipponbare (Oryza sativa ssp. japonica) and a high quality genetic map based on the SNPs generated from deep sequencing of the RIL genomes, were used to identify the quantitative trait loci (QTLs) associated with in vitro tissue culture response (TCR) from mature seed in rice. The performance of callus induction was evaluated by indices of induced-callus color (ICC), induced-callus size (ICS), induced-callus friability (ICF) and callus induction rate (CIR), respectively, and the performance of callus differentiation was evaluated by indices of callus proliferation ability (CPA), callus browning tendency (CBT), callus greening ability (CGA), the average number of regenerated shoots per callus (NRS) and regeneration rate (%, RR), respectively. A total of 25 QTLs, 2 each for ICC, ICS, ICF, CIR and CBA, 3 for CPA, 4 each for CGA, NRS and RR, respectively, were detected and located on 8 rice chromosomes. Significant correlations were observed among the traits of CGA, NRS and RR, and QTLs identified for these three indices were co-located on chromosomes 3 and 7, and the additive effects came from both Nipponbare and 93-11, respectively. The results obtained from this study provide guidance for further fine mapping and gene cloning of the major QTL of TCR and the knowledge of the genes underlying the traits investigated would be very helpful for revealing the molecular bases of tissue culture response.

A map of rice genome variation reveals the origin of cultivated rice.

Crop domestications are long-term selection experiments that have greatly advanced human civilization. The domestication of cultivated rice (Oryza sativa L.) ranks as one of the most important developments in history. However, its origins and domestication processes are controversial and have long been debated. Here we generate genome sequences from 446 geographically diverse accessions of the wild rice species Oryza rufipogon, the immediate ancestral progenitor of cultivated rice, and from 1,083 cultivated indica and japonica varieties to construct a comprehensive map of rice genome variation. In the search for signatures of selection, we identify 55 selective sweeps that have occurred during domestication. In-depth analyses of the domestication sweeps and genome-wide patterns reveal that Oryza sativa japonica rice was first domesticated from a specific population of O. rufipogon around the middle area of the Pearl River in southern China, and that Oryza sativa indica rice was subsequently developed from crosses between japonica rice and local wild rice as the initial cultivars spread into South East and South Asia. The domestication-associated traits are analysed through high-resolution genetic mapping. This study provides an important resource for rice breeding and an effective genomics approach for crop domestication research.

Identification of QTLs for eight agronomically important traits using an ultra-high-density map based on SNPs generated from high-throughput sequencing in sorghum under contrasting photoperiods.

The productivity of sorghum is mainly determined by agronomically important traits. The genetic bases of these traits have historically been dissected and analysed through quantitative trait locus (QTL) mapping based on linkage maps with low-throughput molecular markers, which is one of the factors that hinder precise and complete information about the numbers and locations of the genes or QTLs controlling the traits. In this study, an ultra-high-density linkage map based on high-quality single nucleotide polymorphisms (SNPs) generated from low-coverage sequences (~0.07 genome sequence) in a sorghum recombinant inbred line (RIL) population was constructed through new sequencing technology. This map consisted of 3418 bin markers and spanned 1591.4 cM of genome size with an average distance of 0.5 cM between adjacent bins. QTL analysis was performed and a total of 57 major QTLs were detected for eight agronomically important traits under two contrasting photoperiods. The phenotypic variation explained by individual QTLs varied from 3.40% to 33.82%. The high accuracy and quality of this map was evidenced by the finding that genes underlying two cloned QTLs, Dw3 for plant height (chromosome 7) and Ma1 for flowering time (chromosome 6), were localized to the correct genomic regions. The close associations between two genomic regions on chromosomes 6 and 7 with multiple traits suggested the existence of pleiotropy or tight linkage. Several major QTLs for heading date, plant height, numbers of nodes, stem diameter, panicle neck length, and flag leaf width were detected consistently under both photoperiods, providing useful information for understanding the genetic mechanisms of the agronomically important traits responsible for the change of photoperiod.

A pyramid breeding of eight grain-yield related quantitative trait loci based on marker-assistant and phenotype selection in rice (Oryza sativa L.).

1000-Grain weight and spikelet number per panicle are two important components for rice grain yield. In our previous study, eight quantitative trait loci (QTLs) conferring spikelet number per panicle and 1000-grain weight were mapped through sequencing-based genotyping of 150 rice recombinant inbred lines (RILs). In this study, we validated the effects of four QTLs from Nipponbare using chromosome segment substitution lines (CSSLs), and pyramided eight grain yield related QTLs. The new lines containing the eight QTLs with positive effects showed increased panicle and spikelet size as compared with the parent variety 93-11. We further proposed a novel pyramid breeding scheme based on marker-assistant and phenotype selection (MAPS). This scheme allowed pyramiding of as many as 24 QTLs at a single hybridization without massive cross work. This study provided insights into the molecular basis of rice grain yield for direct wealth for high-yielding rice breeding.

Genome-wide association study of flowering time and grain yield traits in a worldwide collection of rice germplasm.

A high-density haplotype map recently enabled a genome-wide association study (GWAS) in a population of indica subspecies of Chinese rice landraces. Here we extend this methodology to a larger and more diverse sample of 950 worldwide rice varieties, including the Oryza sativa indica and Oryza sativa japonica subspecies, to perform an additional GWAS. We identified a total of 32 new loci associated with flowering time and with ten grain-related traits, indicating that the larger sample increased the power to detect trait-associated variants using GWAS. To characterize various alleles and complex genetic variation, we developed an analytical framework for haplotype-based de novo assembly of the low-coverage sequencing data in rice. We identified candidate genes for 18 associated loci through detailed annotation. This study shows that the integrated approach of sequence-based GWAS and functional genome annotation has the potential to match complex traits to their causal polymorphisms in rice.

Mapping 49 quantitative trait loci at high resolution through sequencing-based genotyping of rice recombinant inbred lines.

Mapping chromosome regions responsible for quantitative phenotypic variation in recombinant populations provides an effective means to characterize the genetic basis of complex traits. We conducted a quantitative trait loci (QTL) analysis of 150 rice recombinant inbred lines (RILs) derived from a cross between two cultivars, Oryza sativa ssp. indica cv. 93-11 and Oryza sativa ssp. japonica cv. Nipponbare. The RILs were genotyped through next-generation sequencing, which accurately determined the recombination breakpoints and provided a new type of genetic markers, recombination bins, for QTL analysis. We detected 49 QTL with phenotypic effect ranging from 3.2 to 46.0% for 14 agronomics traits. Five QTL of relatively large effect (14.6-46.0%) were located on small genomic regions, where strong candidate genes were found. The analysis using sequencing-based genotyping thus offers a powerful solution to map QTL with high resolution. Moreover, the RILs developed in this study serve as an excellent system for mapping and studying genetic basis of agricultural and biological traits of rice.

Genome-wide association studies of 14 agronomic traits in rice landraces.

Uncovering the genetic basis of agronomic traits in crop landraces that have adapted to various agro-climatic conditions is important to world food security. Here we have identified ∼ 3.6 million SNPs by sequencing 517 rice landraces and constructed a high-density haplotype map of the rice genome using a novel data-imputation method. We performed genome-wide association studies (GWAS) for 14 agronomic traits in the population of Oryza sativa indica subspecies. The loci identified through GWAS explained ∼ 36% of the phenotypic variance, on average. The peak signals at six loci were tied closely to previously identified genes. This study provides a fundamental resource for rice genetics research and breeding, and demonstrates that an approach integrating second-generation genome sequencing and GWAS can be used as a powerful complementary strategy to classical biparental cross-mapping for dissecting complex traits in rice.

High-throughput genotyping by whole-genome resequencing.

The next-generation sequencing technology coupled with the growing number of genome sequences opens the opportunity to redesign genotyping strategies for more effective genetic mapping and genome analysis. We have developed a high-throughput method for genotyping recombinant populations utilizing whole-genome resequencing data generated by the Illumina Genome Analyzer. A sliding window approach is designed to collectively examine genome-wide single nucleotide polymorphisms for genotype calling and recombination breakpoint determination. Using this method, we constructed a genetic map for 150 rice recombinant inbred lines with an expected genotype calling accuracy of 99.94% and a resolution of recombination breakpoints within an average of 40 kb. In comparison to the genetic map constructed with 287 PCR-based markers for the rice population, the sequencing-based method was approximately 20x faster in data collection and 35x more precise in recombination breakpoint determination. Using the sequencing-based genetic map, we located a quantitative trait locus of large effect on plant height in a 100-kb region containing the rice "green revolution" gene. Through computer simulation, we demonstrate that the method is robust for different types of mapping populations derived from organisms with variable quality of genome sequences and is feasible for organisms with large genome sizes and low polymorphisms. With continuous advances in sequencing technologies, this genome-based method may replace the conventional marker-based genotyping approach to provide a powerful tool for large-scale gene discovery and for addressing a wide range of biological questions.