With the completion of the rice genome sequencing project, the next major challenge is the largescale determination of gene function. As an important crop and a model organism, rice provides major insights into gene functions important for crop growth or production. Phenomics with detailed information about tagged populations provides a good tool for functional genomics analysis. By a T-DNA insertional mutagenesis approach, we have generated a rice mutant population containing 55,000 promoter trap and gene activation or knockout lines. Approximately 20,000 of these lines have known integration sites. The T0 and T1 plants were grown in net ''houses'' for two cropping seasons each year since 2003, with the mutant phenotypes recorded. Detailed data describing growth and development of these plants, in 11 categories and 65 subcategories, over the entire four-month growing season are available in a searchable database, along with the genetic segregation information and flanking sequence data. With the detailed data from more than 20,000 T1 lines and 12 plants per line, we estimated the mutation rates of the T1 population, as well the frequency of the dominant T0 mutants. The correlations among different mutation phenotypes are also calculated. Together, the information about mutant lines, their integration sites, and the phenotypes make this collection, the Taiwan Rice Insertion Mutants (TRIM), a good resource for rice phenomics study. Ten T2 seeds per line can be distributed to researchers upon request.

No abstract

BACKGROUNDTo gain a better understanding of how Pyricularia oryzae population shifts is important for selecting suitable resistance genes for rice breeding programs. However, the relationships between P. oryzae pathogenic dynamics, geographic distribution, rice varieties, and timeline are not well studied.RESULTSResistance genes Piz‐5, Pi9(t), Pi12(t), Pi20(t), Pita‐2, and Pi11 showed stable resistance to the Taiwan rice blast fungus over 8 years of observations. Furthermore, 1749 rice blast isolates were collected from 2014 to 2021 and categorized into five pathotype clusters based on their correlation analysis between the geographic sources and virulence of Lijiangxintuanheigu monogenic lines. A detailed map of their distributions in Taiwan is presented. Isolates collected from the western region of Taiwan had greater pathotype diversity than those from the east region. Isolates collected from the subtropical region had greater diversity than those from the tropical region. Rice cultivars carrying Pik alleles were highly susceptible to pathotype L4. Cultivars with Piz‐t were highly susceptible to pathotype L5, and those with Pish were highly susceptible to pathotype L1. The geographical distribution of each pathotype was distinct, and the population size of each pathotype fluctuated significantly each year.CONCLUSIONThe regional mega cultivars significantly impact the evolution of Pyricularia oryzae in Taiwan within the span of 8 years. However, the annual fluctuation of pathotype populations likely correlate to the rising annual temperatures that selected pathotype clusters by their optimal growth temperature. The results will provide useful information for effective disease management, and enable the R‐genes to prolong their function in the fields. © 2023 Society of Chemical Industry.

MicroRNAs (miRNAs) are known to play critical roles in plant development and stress-response regulation, and they frequently display multi-targeting characteristics. The control of defined rice phenotypes occurs through multiple genes; however, evidence demonstrating the relationship between agronomic traits and miRNA expression profiles is lacking. In this study, we investigated eight yield-related traits in 187 local rice cultivars and profiled the expression levels of 193 miRNAs in these cultivars using microarray analyses. By integrating the miRBase database, the rice annotation project database, and the miRanda and psRNATarget web servers, we constructed a database (RiceATM) that can be employed to investigate the association between rice agronomic traits and miRNA expression. The functions of this platform include phenotype selection, sample grouping, microarray data pretreatment, statistical analysis and target gene predictions. To demonstrate the utility of RiceATM, we used the database to identify four miRNAs associated with the heading date and validated their expression trends in the cultivars with early or late heading date by real-time PCR. RiceATM is a useful tool for researchers seeking to characterize the role of certain miRNAs for a specific phenotype and discover potential biomarkers for breeding or functional studies.Database URL: http://syslab3.nchu.edu.tw/rice/