Reducing Seed Shattering in Weedy Rice by Editing SH4 and qSH1 Genes: Implications in Environmental Biosafety and Weed Control through Transgene Mitigation.

Mitigating the function of acquired transgenes in crop wild/weedy relatives can provide an ideal strategy to reduce the possible undesired environmental impacts of pollen-mediated transgene flow from genetically engineered (GE) crops. To explore a transgene mitigation system in rice, we edited the seed-shattering genes, SH4 and qSH1, using a weedy rice line ("C9") that originally had strong seed shattering. We also analyzed seed size-related traits, the total genomic transcriptomic data, and RT-qPCR expression of the SH4 or qSH1 gene-edited and SH4/qSH1 gene-edited weedy rice lines. Substantially reduced seed shattering was observed in all gene-edited weedy rice lines. The single gene-edited weedy rice lines, either the SH4 or qSH1 gene, did not show a consistent reduction in their seed size-related traits. In addition, reduced seed shattering was closely linked with the weakness and absence of abscission layers and reduced abscisic acid (ABA). Additionally, the genes closely associated with ABA biosynthesis and signaling transduction, as well as cell-wall hydrolysis, were downregulated in all gene-edited weedy rice lines. These findings facilitate our deep insights into the underlying mechanisms of reduced seed shattering in plants in the rice genus Oryza. In addition, such a mitigating technology also has practical applications for reducing the potential adverse environmental impacts caused by transgene flow and for managing the infestation of weedy rice by acquiring the mitigator from GE rice cultivars through natural gene flow.

Control of Thousand-Grain Weight by OsMADS56 in Rice.

Grain weight and size are important traits determining grain yield and influencing grain quality in rice. In a previous study, a quantitative trait locus controlling thousand-grain weight (TGW) in rice, qTGW10-20.8, was mapped in a 70.7 kb region on chromosome 10. Validation of the candidate gene for qTGW10-20.8, OsMADS56 encoding a MADS-box transcription factor, was performed in this study. In a near-isogenic line (NIL) population segregated only at the OsMADS56 locus, NILs carrying the OsMADS56 allele of IRBB52 were 1.9% and 2.9% lower in TGW than NILs carrying the OsMADS56 allele of Teqing in 2018 and 2020, respectively. Using OsMADS56 knock-out mutants and overexpression transgenic plants, OsMADS56 was validated as the causal gene for qTGW10-20.8. Compared with the recipients, the TGW of the knock-out mutants was reduced by 6.0-15.0%. In these populations, decreased grain weight and size were associated with a reduction in the expression of OsMADS56. In transgenic populations of OsMADS56 driven by a strong constitutive promoter, grain weight and size of the positive plants were significantly higher than those of the negative plants. Haplotype analysis showed that the Teqing-type allele of OsMADS56 is the major type presented in cultivated rice and used in variety improvement. Cloning of OsMADS56 provides a new gene resource to improve grain weight and size through molecular design breeding.

Dissection of the qTGW1.1 region into two tightly-linked minor QTLs having stable effects for grain weight in rice.

BACKGROUND: Most agronomical traits of crop species are complex traits controlled by multiple genes and affected by environmental factors. While considerable efforts have been made to fine-map and clone major quantitative trait loci (QTLs) for yield-related traits in rice, it is not until recently that the attention has been paid to minor QTLs. Following previous dissection of QTLs for grain weight and grain size in a 12-Mb interval on the long arm of chromosome 1 in rice, this study targeted at one putative QTL region for a more precise mapping and for analyzing the genotype-by-environment interaction of minor QTLs. RESULTS: Four BC2F10 plants of the indica rice cross ZS97///ZS97//ZS97/MY46 were selected. They carried overlapped heterozygous segments that jointly covered the entire putative region for qTGW1.1 detected previously. Four sets of near isogenic lines (NILs) were developed from selfing progenies of the four plants. Each NIL set consisted of 32 ZS97 homozygous lines and 32 MY46 homozygous lines that differed in the corresponding heterozygous region. They were grown in two locations having distinct ecological conditions and measured for 1000-grain weight, grain length and grain width. Two QTLs were separated in an 835.2-kb interval flanked by DNA markers Wn28447 and RM11569. They both showed consistent effects across the two environments. The qTGW1.1a located within the 120.4-kb interval Wn28447 - RM11543 significantly affect all the three traits with the enhancing allele derived from ZS97, showing a stronger influence on grain weight than on grain length and width. The qTGW1.1b located in the 521.8-kb interval RM11554 - RM11569 significantly affect grain weight and length with the enhancing allele derived from MY46, having a stronger influence on grain length than on grain weight. Consistent performance of the two QTLs was confirmed in a validation experiment using five NIL-F2 populations segregated for either qTGW1.1a or qTGW1.1b. CONCLUSION: Separation of closely-linked QTLs having small effects is achievable in the absence of major-QTL segregation. Minor QTLs for complex traits could act consistently in diverse environments, offering the potential of pyramiding beneficial alleles of multiple minor QTLs through marker-assisted selection.

Three genetic systems controlling growth, development and productivity of rice (Oryza sativa L.): a reevaluation of the 'Green Revolution'.

The Green Revolution (GR-I) included worldwide adoption of semi-dwarf rice cultivars (SRCs) with mutant alleles at GA20ox2 or SD1 encoding gibberellin 20-oxidase. Two series of experiments were conducted to characterize the pleiotropic effects of SD1 and its relationships with large numbers of QTLs affecting rice growth, development and productivity. The pleiotropic effects of SD1 in the IR64 genetic background for increased height, root length/mass and grain weight, and for reduced spikelet fertility and delayed heading were first demonstrated using large populations derived from near isogenic IR64 lines of SD1. In the second set of experiments, QTLs controlling nine growth and yield traits were characterized using a new molecular quantitative genetics model and the phenotypic data of the well-known IR64/Azucena DH population evaluated across 11 environments, which revealed three genetic systems: the SD1-mediated, SD1-repressed and SD1-independent pathways that control rice growth, development and productivity. The SD1-mediated system comprised 43 functional genetic units (FGUs) controlled by GA. The SD1-repressed system was the alternative one comprising 38 FGUs that were only expressed in the mutant sd1 backgrounds. The SD1-independent one comprised 64 FGUs that were independent of SD1. GR-I resulted from the overall differences between the former two systems in the three aspects: (1) trait/environment-specific contributions; (2) distribution of favorable alleles for increased productivity in the parents; and (3) different responses to (fertilizer) inputs. Our results suggest that at 71.4 % of the detected loci, a QTL resulted from the difference between a functional allele and a loss-of-function mutant, whereas at the remaining 28.6 % of loci, from two functional alleles with differentiated effects. Our results suggest two general strategies to achieve GR-II (1) by further exploiting the genetic potential of the SD1-repressed and SD1-independent pathways and (2) by restoring the SD1-mediated pathways, or 'back to the nature' to fully exploit the genetic diversity of those loci in the SD1-mediated pathways which are virtually inaccessible to most rice-breeding programs worldwide that are exclusively based on sd1.

A major QTL, Ghd8, plays pleiotropic roles in regulating grain productivity, plant height, and heading date in rice.

Rice yield and heading date are two distinct traits controlled by quantitative trait loci (QTLs). The dissection of molecular mechanisms underlying rice yield traits is important for developing high-yielding rice varieties. Here, we report the cloning and characterization of Ghd8, a major QTL with pleiotropic effects on grain yield, heading date, and plant height. Two sets of near isogenic line populations were developed for the cloning of Ghd8. Ghd8 was narrowed down to a 20-kb region containing two putative genes, of which one encodes the OsHAP3 subunit of a CCAAT-box binding protein (HAP complex); this gene was regarded as the Ghd8 candidate. A complementary test confirmed the identity and pleiotropic effects of the gene; interestingly, the genetic effect of Ghd8 was dependent on its genetic background. By regulating Ehd1, RFT1, and Hd3a, Ghd8 delayed flowering under long-day conditions, but promoted flowering under short-day conditions. Ghd8 up-regulated MOC1, a key gene controlling tillering and branching; this increased the number of tillers, primary and secondary branches, thus producing 50% more grains per plant. The ectopic expression of Ghd8 in Arabidopsis caused early flowering by 10 d-a situation similar to the one observed by its homolog AtHAP3b, when compared to wild-type under long-day conditions; these findings indicate the conserved function of Ghd8 and AtHAP3b in flowering in Arabidopsis. Our results demonstrated the important roles of Ghd8 in rice yield formation and flowering, as well as its opposite functions in flowering between rice and Arabidopsis under long-day conditions.

Identification of chromosome regions associated with seedling vigor in rice.

Seedling vigor is important for optimum stand establishment in rice cropping. In this paper,a set of 264 F12 recombinant inbred lines (RILs) derived by single seed descent from a cross between Lemont (japonica) and Teqing (indica) was phenotyped for three seedling vigor related traits, including seed germination rate (GR), seedling shoot length and dry weight by the rolled paper towel tests. The phenotype data and a linkage map consisting of 198 DNA markers were combined to map quantitative trait loci (QTL) for seedling vigor by using a computer program QTLMapper1.0. A total of 13 putative main-effect QTL were detected. All of these QTL had much smaller effects on the traits with a mean R2 of 6.2%, ranging from 2.9% to 12.7%. As for digenic interaction, 18 pairs of epistatic loci with R2 > or = 5% were resolved with a mean R2 of 6.9% ,ranging from 5.1% to 11.8%, which was slightly larger than that of the main-effect QTL identified for the traits. The majority of the main-effect and epistatic loci detected for seedling vigor related traits were clustered in a few chromosome regions. Together, seven such chromosome regions (CRs), each with three or more seedling vigor main-effect and epistatic loci, were found to be highly associated with seedling vigor. These CRs can be classified into three types, i.e. M-CRs, E-CRs and ME-CRs. For some CRs just like CR(SV-6), the QTL within one CR were found to interact simultaneously with QTL within more than one other CRs to affect different seedling vigor related traits. The above results revealed that seedling vigor in rice is controlled by many loci, most of which have relatively small effects. Comparatively, epistasis as a genetic factor would be more important than main-effects of QTL for seedling vigor in rice. Nevertheless, the effects of the QTL are still large enough to be detected and in fact several chromosome regions were found to be highly associated with seedling vigor in very different populations as compared with previous studies. Molecular tagging of favorable alleles and marker-aided selection strategy may, therefore, be a promising approach to the improvement of rice seedling vigor.

Genetic analysis of the panicle traits related to yield sink size of rice.

In the study, ten panicle traits associated with yield sink size were measured in a recombinant inbred population derived from Zhenshan 97 x Minghui 63. Generally, spikelets per panicle were more closely correlated with number of secondary branch per panicle, spikelets on secondary branch per secondary branch, and spikelet density. A total of 53 QTL were detected for ten traits in two years. Approximately 43.4% QTLs were detected in both two years, suggesting environmental effects on traits. Five chromosomal regions (G359-RG532 and C567-C86-RG236 on chromosome 1, R712-RM29 on chromosome 2, P-RG424 on chromosome 6, C148-RM258 on chromosome 10) were detected to have effects on multiple panicle traits. QTLs for traits, which were correlated, were generally localized in similar chromosomal regions, suggesting that pleiotropy and (or) linkage are the molecular basis of relationship between them. A large number of digenic interactions were detected, 18.2% of which were detected simultaneously in both two years. The proportion of common interactions was trait-depended, ranging 8.7% for spikelets on secondary branch per secondary branch to 32.6% for panicle length. Approximately 26.7% of common two-locus combinations had pleiotropic effects by simultaneously influencing two or more traits. Overall, the results indicate that each panicle trait is controlled by several QTLs, genotype x environment interaction, and a large number of epistatic interactions.