Rice (Oryza sativa) grain shape, which is controlled by quantitative trait loci (QTL), has a strong effect on yield production and quality. However, the molecular basis for grain development remains largely unknown. In this study, we identified a novel QTL, Slender grain on chromosome 7 (SLG7), that is responsible for grain shape, using backcross introgression lines derived from 9311 and Azucena. The SLG7 allele from Azucena produces longer and thinner grains, although it has no influence on grain weight and yield production. SLG7 encodes a protein homologous to LONGIFOLIA 1 and LONGIFOLIA 2, both of which increase organ length in Arabidopsis. SLG7 is constitutively expressed in various tissues in rice, and the SLG7 protein is located in plasma membrane. Morphological and cellular analyses suggested that SLG7 produces slender grains by longitudinally increasing cell length, while transversely decreasing cell width, which is independent from cell division. Our findings show that the functions of SLG7 family members are conserved across monocots and dicots and that the SLG7 allele could be applied in breeding to modify rice grain appearance.KEYWORDS rice; quantitative trait loci; grain shape; cell elongation R ICE (Oryza sativa L.) is a staple food for half of the world's population (Khush 2001). Three major components, panicle number per plant, grain number per panicle, and grain weight, determine rice yield production. Grain weight is associated with grain size and shape, which are defined as grain length, grain width, and grain thickness (Duan et al. 2014). There is a striking diversity of grain size among the rice species worldwide. The grains of domesticated rice range from 3 to 11 mm in length and from 1.2 to 3.8 mm in width (Fitzgerald et al. 2009). Despite the influence of several environmental factors on plant growth and development, such as water supply and fertilizer level, the final grain size of rice is reasonably constant within a given species.Rice grain traits are quantitatively inherited. In the past decade, several quantitative trait loci (QTL) controlling grain size and shape have been cloned. GS3, encoding a transmembrane protein containing four putative domains, was the first characterized QTL that regulates grain length (Fan et al. 2006). qGL3 encodes a putative protein phosphatase with a Kelch-like repeat domain, and an aspartate-to-glutamate transition in the second Kelch domain leads to a long-grain phenotype (Zhang et al. 2012). GW6 encodes a GNAT-like protein that harbors intrinsic histone acetyltransferase activity, and an elevated expression enhances grain length and weight by enlarging spikelet hulls and accelerating grain filling (Song et al. 2015). GW2, GW5/qSW5, GS5, and GW8 were identified as regulators of rice grain width. GW2 encodes a previously unknown RING-type protein with E3 ubiquitin ligase, which negatively regulates cell division by degrading its substrate(s) through the ubiquitin-proteasome pathway (Song et al. 2007). GW5/qSW5 encodes a nuclearlocated protein t...

Polyamines, including putrescine (Put), spermidine (Spd), and spermine (Spm), play essential roles in a wide variety of prokaryotic and eukaryotic organisms. Rice (Oryza sativa) contains four putative spermidine/spermine synthase (SPMS)-encoding genes (OsSPMS1, OsSPMS2, OsSPMS3, and OsACAULIS5), but none have been functionally characterized. In this study, we used a reverse genetic strategy to investigate the biological function of OsSPMS1. We generated several homozygous RNA interference (RNAi) and overexpression (OE) lines of OsSPMS1. Phenotypic analysis indicated that OsSPMS1 negatively regulates seed germination, grain size, and grain yield per plant. The ratio of Spm to Spd was significantly lower in the RNAi lines and considerably higher in the OE lines than in the wild-type (WT), suggesting that OsSPMS1 may function as a spermine synthase. S-adenosyl-L-methionine is a common precursor of polyamines and ethylene biosynthesis. The 1-aminocyclopropane-1-carboxylic acid (ACC) and ethylene contents in seeds significantly increased in RNAi lines and decreased in OE lines, respectively, compared with wild-type. Additionally, the reduced germination rates and growth defects of OE lines could be rescued with ACC treatment. These data suggest that OsSPMS1 affects ethylene synthesis and may regulate seed germination and plant growth by affecting the ACC and ethylene pathways. Most importantly, an OsSPMS1 knockout mutant showed an increase in grain yield per plant in a high-yield variety, Suken118, suggesting that OsSPMS1 is an important target for yield enhancement in rice.

Background The heterotrimeric G protein β subunit RGB1 plays an important role in plant growth and development. However, the molecular mechanisms underlying the regulation of rice growth by RGB1 remain elusive. Results Here, the rgb1 mutants rgb1–1 (+ 1 bp), rgb1–2 (− 1 bp), and rgb1–3 (− 11 bp) were isolated using the CRISPR/Cas9 system, and they were arrested at 1 day after germination and ultimately exhibited seedling lethality. The dynamic anatomical characteristics of the embryos of the rgb1 seedlings and WT during early postgermination and according to TUNEL assays showed that the suppressed growth of the rgb1 mutants was caused by cell death. In addition to the limited shoot and root development, the development of the embryo shoot-root axis was suppressed in the rgb1 mutants. RGB1 was expressed mainly in the root epidermal and vascular tissues of the embryo. Moreover, transcript profiling analysis revealed that the expression of a large number of auxin-, cytokinin-, and brassinosteroid-inducible genes was upregulated or downregulated in the rgb1 mutant compared to the wild type during seedling development. Conclusions Overall, the rgb1 mutants provide an ideal material for exploring the molecular mechanism underlying rice seedling formation during early postgermination development by G proteins. Significance statement The heterotrimeric G protein β subunit RGB1 acts as a crucial factor in promoting early postgermination seedling development in rice. Electronic supplementary material The online version of this article (10.1186/s12284-019-0313-y) contains supplementary material, which is available to authorized users.

We constructed 128 chromosome segment substitution lines (CSSLs), derived from a cross between indica rice (Oryza sativa L.) 9311 and japonica rice Nipponbare, to investigate the genetic mechanism of heterosis. Three photo-thermo-sensitive-genic male sterile lines (Guangzhan63-4s, 036s, and Lian99s) were selected to cross with each CSSL to produce testcross populations (TCs). Field experiments were carried out in 2009, 2011, and 2015 to evaluate yield and yield-related traits in the CSSLs and TCs. Four traits (plant height, spikelet per panicle, thousand-grain weight, and grain yield per plant) were significantly related between CSSLs and TCs. In the TCs, plant height, panicle length, seed setting rate, thousand-grain weight, and grain yield per plant showed partial dominance, indicating that dominance largely contributes to heterosis of these five traits. While overdominance may be more important for heterosis of panicles per plant and spikelet per panicle. Based on the bin-maps of CSSLs and TCs, we detected 62 quantitative trait loci (QTLs) and 97 heterotic loci (HLs) using multiple linear regression analyses. Some of these loci were clustered together. The identification of QTLs and HLs for yield and yield-related traits provide useful information for hybrid rice breeding, and help to uncover the genetic basis of rice heterosis.

The market success of any rice cultivar is exceedingly dependent on its grain appearance, as well as its grain yield, which define its demand by consumers as well as growers. The present study was undertaken to explore the contribution of nine major genes, qPE9~1, GW2, SLG7, GW5, GS3, GS7, GW8, GS5, and GS2, in regulating four size and weight related traits, i.e., grain length (GL), grain width (GW), grain thickness (GT), and thousand grain weight (TGW) in 204 diverse rice germplasms using Insertion/Deletion (InDel) markers. The studied germplasm displayed wide-ranging variability in the four studied traits. Except for three genes, all six genes showed considerable association with these traits with varying strengths. Whole germplasm of 204 genotypes could be categorized into three major clusters with different grain sizes and weights that could be utilized in rice breeding programs where grain appearance and weight are under consideration. The study revealed that TGW was 24.9% influenced by GL, 37.4% influenced by GW, and 49.1% influenced by GT. Hence, assuming the trend of trait selection, i.e., GT > GW > GL, for improving TGW in the rice yield enhancement programs. The InDel markers successfully identified a total of 38 alleles, out of which 27 alleles were major and were found in more than 20 genotypes. GL was associated with four genes (GS3, GS7, GW8, and GS2). GT was also found to be regulated by four different genes (GS3, GS7, GW8, and GS2) out of the nine studied genes. GW was found to be under the control of three studied genes (GW5, GW8, and GS2), whereas TGW was found to be under the influence of four genes (SLG7, GW5, GW8, and GS5) in the germplasm under study. The Unweighted Pair Group Method with Arithmetic means (UPGMA) tree based on the studied InDel marker loci segregated the whole germplasm into three distinct clusters with dissimilar grain sizes and weights. A two-dimensional scatter plot constructed using Principal Coordinate Analysis (PCoA) based on InDel markers further separated the 204 rice germplasms into four sub-populations with prominent demarcations of extra-long, long, medium, and short grain type germplasms that can be utilized in breeding programs accordingly. The present study could help rice breeders to select a suitable InDel marker and in formulation of breeding strategies for improving grain appearance, as well as weight, to develop rice varieties to compete international market demands with higher yield returns. This study also confirms the efficient application of InDel markers in studying diverse types of rice germplasm, allelic frequencies, multiple-gene allele contributions, marker-trait associations, and genetic variations that can be explored further.