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Pantoea ananatis is a phytopathogen infecting many economically important crops, including rice worldwide. Here, we report the complete genome of P. ananatis strain TZ39 identified as causative agent of a new bacterial blight of rice that emerged in China in 2020. The assembled genome consists of one circular chromosome of 4,483,976 bp and two plasmids of 135,135 and 276,579 bp. This complete genome of the first Chinese pathogenic P. ananatis strain will provide new insights into the traits of pathogenicity on genomic level from China and worldwide.

Sheath blight is a serious rice disease that causes great yield losses worldwide. Sheath blight resistance is controlled by genes with minor effect. It is an urgent need to identify the resistance genes in rice germplasm and utilize them in breeding. The purpose of this study is to identify the sheath blight-resistant alleles in different rice germplasm by association mapping and explore the potential of the resistance alleles in utilization. A total of 273 rice genotypes were inoculated and evaluated for sheath blight resistance in the field for 5 years, and 158 genotypes with relatively stable disease resistance phenotype were chosen for association mapping. A wide range of phenotypic variation for sheath blight resistance was observed in the 158-genotype population. Structure analyses divided the 158 genotypes into 4 subgroups, which was consistent with principal component analysis and cluster analysis. Association mapping performed using mixed linear model with 213 markers identified 14 resistance loci, locating on all chromosomes except chromosome 6, 10 and 12. Three novel resistance loci (D704, D855, and D905) which were different from the previously reported were detected. Thirty-eight alleles were detected at the 14 loci, among which favorable alleles at 11 loci showed consistent resistance across 5 years. It was found that the favorable resistance alleles can be pyramided to improve sheath blight resistance. These results enhance the understanding of how different resistance alleles at multiple loci in regulating sheath blight resistance, and provide markers for sheath blight resistance breeding in rice.

The seed setting rate (spikelet fertility) is an important determinant of rice yield. In the past few decades, genes that control rice seed set have been cloned, and many quantitative trait loci (QTL) have been identified. However, the epistasis influencing rice seed set remains largely unclear. In this study, a recombinant inbred line population, which consisted of 219 lines developed by crossing the Lemont and Yangdao4 rice cultivars, was grown in five environments to identify the QTL and epistatic loci related to seed set. A total of 26 minor-effect QTL were detected by multiple interval mapping, which explained less than 12.7% of the phenotypic variation individually. A pair of new epistatic loci were detected and confirmed by two-way analysis of variance; the homozygous Yangdao4 allele at the qSS6.1 locus interacted with the homozygous Lemont allele at the qSS8.1 locus and resulted in a low seed setting rate. A linear regression analysis and a multiple comparison test suggested that eight alleles at four QTL (qSS1.3, qSS6.3, qSS7.1, and qSS8.1) control seed set simultaneously. Marker-assisted selection using these four loci guaranteed a greater than 70% average seed setting rate in all five environments.

To identify stable quantitative trait loci (QTLs) responsible for sheath blight resistance, a recombinant inbred line mapping population consisting of 219 lines was developed by crossing Lemont and Yangdao 4. Average disease rating, average lesion length, maximum disease rating and maximum lesion length were assayed in six different environments. A total of 128 minor effect QTLs were detected by multiple interval mapping. These QTLs explained less than 11.2% of the phenotypic variations individually, and 106 QTLs were clustered in 20 QTL-rich regions/putative loci. Significant QTL × environment interactions were detected at three putative loci (qSBR11.1, qSBR11.2 and qSBR11.3), indicating that these three loci were not stable. The other 17 stable loci (qSBR1.1, qSBR1.2, qSBR2.1, qSBR2.3, qSBR3.1, qSBR3.2, qSBR3.5, qSBR3.6, qSBR5.1, qSBR7.1, qSBR8.1, qSBR9.1, qSBR9.2, qSBR9.3, qSBR12.1, qSBR12.2 and qSBR12.4) provided a foundation for marker-assisted selection in breeding. Analysis of allelic effect on the 20 putative loci identified 7 highly stable loci, including qSBR3.2, qSBR7.1, qSBR8.1, qSBR9.2, qSBR9.3, qSBR12.1 and qSBR12.2. Keywords: Rice, Sheath blight resistance, Quantitative trait locus, Recombinant inbred line

Tiller angle, controlled by quantitative trait loci (QTL), is crucial for achieving ideal plant architecture in rice, which affects its final yield values. It is important to understand the genetic mechanisms underlying tiller angle when breeding new plant-type varieties. To uncover the genetic regulation mechanisms in cultivated rice, we performed QTL analysis using a recombinant inbred line (RIL) mapping population consisting of 219 lines developed by crossing two rice cultivars, Lemont and Yangdao4. The angle between the side tiller (ST) and the horizontal ground was measured as a tiller angle-related trait in QTL analysis. Twenty-three QTLs responsible for ST-ground angle were detected using multiple interval mapping in four mapping environments. A major QTL, qTA9, was detected on chromosome 9, which explained 12.9, 39.8, 37.9, and 28.3% of the phenotypic variation in the four mapping environments, respectively. Another QTL, qTA8, with a relatively large effect, was detected on chromosome 8. The other 21 QTLs explained

Rice sheath blight (SB) disease is a global issue that causes great yield losses each year. To explore whether SB field resistance can be predicted, 273 rice genotypes were inoculated and evaluated for SB field resistance across nine environments from 2012 to 2019 to identify loci associated with SB resistance by association mapping. A total of 80 significant marker–trait associations were detected in nine environments, among which six loci (D130B, D230A, D304B, D309, D427A, and RM409) were repeatedly detected in at least two environments. A linear regression model for predicting SB lesion length was developed using genotypic data of these six loci and SB field resistance data of the 273 rice genotypes: y = 34.44 – 0.56x, where y is the predicted value of lesion length, and x is the total genotypic value of the six loci. A recombinant inbred line (RIL) population consisting of 219 lines that was grown in six environments (from 2013 to 2018) for evaluation of SB field resistance was used to check the prediction accuracy of the prediction model. The average absolute error between the predicted lesion length and real lesion length for the RIL population was 6.67 cm. The absolute errors between predicted and real lesion lengths were

In autumn 2020, leaf blight was observed on rice (Oryza sativa L., variety Zhongzao39, Yongyou9, Yongyou12, Yongyou15, Yongyou18, Yongyou1540, Zhongzheyou8, Jiafengyou2, Xiangliangyou900 and Jiyou351) in the fields of 17 towns in Zhejiang and Jiangxi Provinces, China. The disease incidence was 45%-60%. Initially, water-soaked, linear, light brown lesions emerged in the upper blades of the leaves, and then spread down to leaf margins, which ultimately caused leaf curling and blight during the booting-harvest stage (Fig. S1). The disease symptoms were assumed to be caused by Xanthomonas oryzae pv. oryzae (Xoo), the pathogen of rice bacterial blight. 63 isolates were obtained from the collected diseased leaves as previously described (Hou et al. 2020). All isolates showed circular, smooth-margined, yellow colonies when cultured on peptone sugar agar (PSA) medium for 24h at 28℃. The cells were all gram-negative and rod-shaped with three to six peritrichous flagella; positive for catalase, indole, glucose fermentation and citrate utilization, while negative for oxidase, alkaline, phenylalanine deaminase, urease, and nitrate reductase reactions. 16S rRNA gene sequence analysis from the 6 isolates (FY43, JH31, JH99, TZ20, TZ39 and TZ68) revealed that the amplified fragments shared 98% similarity with Pantoea ananatis type strain LMG 2665T (GenBank JFZU01) (Table S3). To further verify P. ananatis identity of these isolates, fragments of three housekeeping genes including gyrB, leuS and rpoB from the 6 isolates were amplified and sequenced, which showed highest homology to LMG 2665T with a sequence similarity of 95%-100% (Table S3). Primers (Brady et al. 2008) and GenBank accession numbers of gene sequences from the 6 isolates are listed in Table S1 and Table S2. Phylogenetic analysis of gyrB, leuS and rpoB concatenated sequences indicated that the 6 isolates were clustered in a stable branch with P. ananatis (Fig. S2). Based on the above morphological, physiological, biochemical and molecular data, the isolates are identified as P. ananatis. For pathogenicity tests, bacterial suspension at 108 CFU/mL was inoculated into flag leaves of rice (cv. Zhongzao39) at the late booting stage using clipping method. Water was used as a negative control. The clipped leaves displayed water-soaked lesions at 3 to 5 days after inoculation (DAI); then the lesion spread downward and turned light brown. At about 14 DAI, blight was shown with similar symptoms to those samples collected from the rice field of Zhejiang and Jiangxi provinces (Fig. S1). In contrast, the control plants remained healthy and symptomless. The same P. ananatis was re-isolated in the inoculated rice plants, fulfilling Koch's postulates. In the past decade, P. ananatis has been reported to cause grain discoloration in Hangzhou, China (Yan et al. 2010) and induce leaf blight as a companion of Enterobacter asburiae in Sichuan province, China (Xue et al. 2020). Nevertheless, to the best of our knowledge, this is the first report of P. ananatis as the causative agent of rice leaf blight in southeast China. This study raises the alarm that the emerging rice bacterial leaf blight in southeast China might be caused by a new pathogen P. ananatis, instead of Xoo as traditionally assumed. Further, the differences of occurrence, spread and control between two rice bacterial leaf blight diseases caused by P. ananatis and Xoo, respectively need to be determined in the future.

Molecular screening of major rice blast resistance genes was determined with molecular markers, which showed close-set linkage to 11 major rice blast resistance genes (Pi-d2, Pi-z, Piz-t, Pi-9, Pi-36, Pi-37, Pi5, Pi-b, Pik-p, Pik-h and Pi-ta2), in a collection of 32 accessions resistant to Magnaporthe oryzae. Out of the 32 accessions, the Pi-d2 and Pi-z appeared to be omnipresent and gave positive express. As the second dominant, Pi-b and Piz-t gene frequencies were 96.9% and 87.5%. And Pik-h and Pik-p gene frequencies were 43.8% and 28.1%, respectively. The molecular marker linkage to Pi-ta2 produced positive bands in eleven accessions, while the molecular marker linkage to Pi-36 and Pi-37 in only three and four accessions, respectively. The natural field evaluation analysis showed that 30 of the 32 accessions were resistant, one was moderately resistant and one was susceptible. Infection types were negatively correlated with the genotype scores of Pi-9, Pi5, Pi-b, Pi-ta2 and Pik-p, although the correlation coefficients were very little. These results are useful in identification and incorporation of functional resistance genes from these germplasms into elite cultivars through marker-assisted selection for improved blast resistance in China and worldwide.

Plant height (PH) is controlled by quantitative trait loci (QTLs) in rice. In the present study, a recombinant inbred line population developed by crossing two rice cultivars, Lemont and Yangdao4, was grown in eight environments for QTL analysis. Multiple interval mapping detected 53 PH-QTLs, 39 of which clustered at 12 chromosome regions/putative loci. An examination of the 12 putative loci identified 24 alleles that are simultaneously involved in controlling PH. Linear regression analyses suggested that these 24 alleles function additively across the 12 loci to control PH, and plants carrying more PH-increasing alleles at the 12 loci were taller than those carrying more PH-decreasing alleles. Multiple comparison tests indicated that the effect of a single allele at the 12 loci was small and that multiple alleles must be pyramided to attain a statistically significant effect. The closest markers to the 12 loci can be used directly in marker-assisted breeding to manipulate PH.

Background Bakanae disease, caused by the fungus Fusarium fujikuroi, occurs widely throughout Asia and Europe and sporadically in other rice production areas. Recent changes in climate and cropping patterns have aggravated this disease. To gain a better understanding of the molecular mechanisms of rice bakanae disease resistance, we employed a 6-plex tandem mass tag approach for relative quantitative proteomic comparison of infected and uninfected rice seedlings 7 days post-inoculation with two genotypes: the resistant genotype 93–11 and the susceptible genotype Nipponbare. Results In total, 123 (77.2% up-regulated, 22.8% down-regulated) and 91 (94.5% up-regulated, 5.5% down-regulated) differentially expressed proteins (DEPs) accumulated in 93–11 and Nipponbare, respectively. Only 11 DEPs were both shared by the two genotypes. Clustering results showed that the protein regulation trends for the two genotypes were highly contrasting, which suggested obviously different interaction mechanisms of the host and the pathogen between 93 and 11 and Nipponbare. Further analysis showed that a noticeable aquaporin, PIP2–2, was sharply upregulated with a fold change (FC) of 109.2 in 93–11, which might be related to pathogen defense and the execution of bakanae disease resistance. Certain antifungal proteins were regulated in both 93–11 and Nipponbare with moderate FCs. These proteins might participate in protecting the cellular integrity required for basic growth of the susceptible genotype. Correlation analysis between the transcriptome and proteome revealed that Pearson correlation coefficients of R = 0.677 (P = 0.0005) and R = − 0.097 (P = 0.702) were obtained for 93–11 and Nipponbare, respectively. Our findings raised an intriguing result that a significant positive correlation only in the resistant genotype, while no correlation was found in the susceptible genotype. The differences in codon usage was hypothesized for the cause of the result. Conclusions Quantitative proteomic analysis of the rice genotypes 93-11and Nipponbare after F. fujikuroi infection revealed that the aquaporin protein PIP2–2 might execute bakanae disease resistance. The difference in the correlation between the transcriptome and proteome might be due to the differences in codon usage between 93-11and Nipponbare. Overall, the protein regulation trends observed under bakanae disease stress are highly contrasting, and the molecular mechanisms of disease defense are obviously different between 93 and 11 and Nipponbare. In summary, these findings deepen our understanding of the functions of proteins induced by bakanae disease and the mechanisms of rice bakanae disease resistance. Electronic supplementary material The online version of this article (10.1186/s12864-019-5435-5) contains supplementary material, which is available to authorized users.

Rice sheath blight (SB) is the most serious rice disease in China. Resistance of rice to SB is a quantitative trait that is easily influenced by the environment; however, the extent of environmental influence on SB field resistance is still poorly understood. To identify rice genotype by environment interactions for SB resistance, 211 rice genotypes originating from 15 countries were planted and evaluated for SB field resistance in six different environments between 2012 and 2016 after inoculation with the SB pathogen isolate ZJ03. In addition, 65 rice genotypes were evaluated for SB field resistance in another four environments between 2013 and 2016 using ZJ03. Variations in SB field resistance were observed in different genotypes in different environments using objective and subjective rating methods. Two-way analysis of variance indicated that the interaction between the genotype and environment had a highly significant effect on SB field resistance. This analysis indicated that the environment had more of an influence than the genotype itself on SB field resistance, and the genotype by environment interaction was the greatest obstacle in obtaining a precise determination of SB field resistance in rice. The most resistant genotype, GD66, is a good candidate for genetic studies and breeding.

Rice bakanae disease, caused by the pathogen Fusarium fujikuroi, is becoming severely detrimental to rice production worldwide. To understand the interaction between rice and F. fujikuroi, a moderate resistant genotype, 93-11 (Oryza sativa indica), and a susceptible genotype, Nipponbare (Oryza sativa japonica), were used for transcriptome analysis. Several cDNA libraries were constructed using mRNA isolated from the leaves of non-stressed 93-11 and NIPPONBARE plants and from the leaves of both genotypes inoculated with F. fujikuroi. In total, 1152 and 1052 transcripts were differentially expressed between the controls and the treatments for 93-11 and NIPPONBARE, respectively. Comparative transcriptome analysis revealed different expression patterns for the two genotypes. Although some common defense-related enriched GO terms were shared in both genotypes, specific defense-related terms were enriched exclusively in 93-11. A detailed comparison of defense-related differentially expressed genes revealed that certain WRKYs, WAK and MAP3Ks were responsible for the bakanae disease resistance in 93-11. The OsWAK112d gene was up-regulated in the resistant genotype. The POEI gene response to abiotic stress was modulated in Nipponbare. Further analysis suggested that the defense-related genes WRKYs and MARKs on chromosome 1 that are modulated in 93-11 upon infection might play a crucial role in the rice–F. fujikuroi interaction. Further characterization of these resistance genes may provide candidate genes for the development of molecular markers for rice bakanae resistance breeding programs. Transcriptomic dissection of the rice–F. fujikuroi interaction provides valuable information for future studies on the molecular mechanisms of rice bakanae resistance.

Rice blast, bacterial blight (BB) and brown planthopper (BPH) are the three main pests of rice. This study investigated pyramiding genes resistant to blast, BB and BPH to develop restorer lines. Ten new lines with blast, BB and/or BPH resistance genes were developed using marker-assisted selection (MAS) technique and agronomic trait selection (ATS) method. Only HR13 with resistance genes to blast, BB and BPH was obtained. In addition to blast and BB resistance, four lines (HR39, HR41, HR42, HR43) demonstrated moderate resistance to BPH, but MAS for BPH resistance genes were not conducted in developing these four lines. These data suggested that there were unknown elite BPH resistance genes in the Zhongzu 14 donor parent. A more effective defense was demonstrated in the lines with Pi1 and Pi2 genes although the weather in 2012 was favorable to disease incidence. Blast resistance of the lines with a single resistance gene, Pita, was easily influenced by the weather. Overall, the information obtained through pyramiding multiple resistance genes on developing the restorer lines is helpful for rice resistance breeding.

Sheath blight (SB) disease, caused by Rhizoctonia solani Kuhn, is one of the most serious diseases causing rice (Oryza sativa L.) yield loss worldwide. A doubled haploid (DH) population was constructed from a cross between a japonica variety CJ06 and an indica variety TN1, and to analyze the quantitative trait loci (QTLs) for SB resistance under three different environments (environments 1–3). Two traits were recorded to evaluate the SB resistance, namely lesion height (LH) and disease rating (DR). Based on field evaluation of SB resistance and a genetic map constructed with 214 markers, a total of eight QTLs were identified for LH and eight QTLs for DR under three environments, respectively. The QTLs for LH were anchored on chromosomes 1, 3, 4, 5, 6, and 8, and explained 4.35–17.53% of the phenotypic variation. The SB resistance allele of qHNLH4 from TN1 decreased LH by 3.08 cm, and contributed to 17.53% of the variation at environment 1. The QTL for LH (qHZaLH8) detected on chromosome 8 in environment 2 explained 16.71% of the variation, and the resistance allele from CJ06 reduced LH by 4.4 cm. Eight QTLs for DR were identified on chromosomes 1, 5, 6, 8, 9, 11, and 12 under three conditions with the explained variation from 2.0 to 11.27%. The QTL for DR (qHZaDR8), which explained variation of 11.27%, was located in the same interval as that of qHZaLH8, both QTLs were detected in environment 2. A total of six pairs of digenic epistatic loci for DR were detected in three conditions, but no epistatic locus was observed for LH. In addition, we detected 12 QTLs for plant height (PH) in three environments. None of the PH-QTLs were co-located with the SB-QTLs. The results facilitate our understanding of the genetic basis for SB resistance in rice.

Rice sheath blight (ShB), which is caused by Rhizoctonia solani, has become the most serious rice disease in China. Yangdao 4, a cultivar with partial resistance to ShB, was crossed with Lemont, a susceptible cultivar, to develop mapping populations that were used to analyze quantitative trait loci (QTL) that confer resistance to ShB. QTL analysis were performed in 3 environments (E1-E3) using 2 F2 and 1 F2:3 populations, respectively. Three traits were recorded to evaluate ShB resistance, including disease rating (DR), lesion height (LH), and percentage of lesion height (PLH). Based on field evaluation of ShB resistance and the 2 genetic maps constructed, we identified a total of 8 QTLs for DR (4 in E1, 4 in E2, and 3 in E3), 6 QTLs for LH (1 in E1, 3 in E2, and 2 in E3), and 7 QTLs for PLH (1 in E1, 4 in E2, and 2 in E3). Sixteen of the ShB-QTLs co-localized as 6 clusters on chromosomes 3, 7, 11, and 12. Four of the 6 clusters contained ShB-QTLs that were detected in 2 environments, while the other 2 clusters with ShB-QTLs were detected in 1 environment. Three ShB-QTLs (qSBD-3-2, qSBL-3-1, and qSBPL-3-1) were delimited to a 581-kb region flanked by markers D333B and D334 on chromosome 3. The resistance alleles of Yangdao 4 at the qSBD-3-2 locus decreased DR by 0.68 and 0.79 in E2 and E3, respectively.

Rice sheath blight (ShB), caused by Rhizoctonia solani, leads to severe yield losses in many rice production areas worldwide. Resistance to rice ShB is a typical quantitative trait controlled by quantitative trait loci (QTLs). To identify the QTLs responsible for ShB resistance, phenotypes for ShB resistance have been surveyed in different individuals/lines in various mapping populations. The 0–9 rating system, based on the percentage of plant height (PH) above the water line with ShB symptoms, is extensively used in the evaluation of ShB in rice communities. By reviewing previous ShB-QTL-mapping studies, we found that the ShB disease score attained using the 0–9 system was inevitably affected by PH and resulted in the colocalization of QTLs for PH and ShB resistance, i.e., some of the PH-QTLs were mistaken as “ShB-QTLs” and had pleiotropic effects. These colocalizing “ShB-QTLs” are irrelevant to physiological ShB resistance and should not be targeted for utilization. We analyzed the ways in which PH affects ShB resistance through the 0–9 rating system and suggest solutions for improving the accuracy of QTL mapping for rice ShB resistance. We also developed the first physical map of the ShB-QTLs and PH-QTLs detected since 1995. This map will be useful in the marker-assisted selection of ShB-resistant QTLs. Under current circumstances, we believe that conventional breeding remains an effective approach for developing ShB-resistant varieties.

Hybrid rice has contributed greatly to the self-sufficiency of the food supply in China. However, bacterial blight is a major disease that limits hybrid rice production in China. The study was conducted to develop an efficient breeding technique to improve the bacterial blight resistance in hybrid rice. A marker-assisted backcross breeding technique was adopted to improve HN189, an elite restorer line containing the Pi1 gene. This breeding technique was simplified to foreground selection with only one generation of backcrossing and background selection based on phenotypic selection. A novel bacterial blight resistance gene, Xa23, was introgressed into HN189. Two improved restorer lines, HBH145 (with one generation of backcrossing) and HBH146 (with two generations of backcrossing), were obtained that had a significant bacterial blight resistance advantage over HN189. The corresponding hybrid combination Tianyou H145 (Tianfeng A / HBH145) was certified one year earlier than Qianyou H146 (Qianjiang 1A / HBH146). The use of the marker-assisted backcross breeding technique with one generation of backcrossing and without background selection in rice breeding programs shortened the breeding period of the rice.

A rice lesion mimic mutant, lm3, was obtained by the mutagenesis of an indica cultivar, 93-11, using γ-ray radiation. Brownish lesions appeared on the leaves of lm3 at the young seedling stage and persisted until the ripening stage. The lm3 mutant was characterised by a shorter plant height and delayed heading compared with the wild-type 93-11. A genetic analysis indicated that the lesion mimic phenotype was controlled by a single recessive gene. Using simple sequence repeat (SSR) markers, the target gene LM3 was first located between marker RM5748 and RM14906 on chromosome 3. We then developed Insertion-Deletion (InDel) markers to fine-map LM3, and the locus was localised to a 29 kb region defined by two InDel markers, In12571 and In12600. Five ORFs were predicted in the candidate region, and DNA sequencing detected a single-nucleotide polymorphism (SNP) in the coding region of LOC Os03g21900. The SNP in the fourth exon (C in 93-11; T in lm3) of LOC_Os03g21900 results in the substitution of a proline (P) with a serine (S) at the 140th amino acid of the deduced uroporphyrinogen decarboxylase protein. We did not detect polymorphisms in the other predicted ORF regions between lm3 and 93-11. These results suggest that LOC_Os03g21900 is the most likely candidate gene for LM3.

Five physiological and eleven yield traits of two pairs of sister lines generated from a high generation with similar genetic background (SLs) for purple pericarp were investigated to explore the reasons behind low-yield production of colored rice. Of the five physiological traits examined, except grain anthocyanin content, there were generally similar trends between the P (purple-pericarp) lines and the corresponding W (white-pericarp) lines over two seasons (in the year 2009 and 2010 separately). The results demonstrated that the chlorophyll content of flag leaves, the net photosynthetic rate of flag leaves, and the grain anthocyanin content could be easily influenced by the environment. The physiological functions of the traits for the P lines were more active than those of the corresponding W lines in the year 2010. The grain anthocyanin content of the P lines was much greater in the year 2010 than in the year 2009 during the growth period. The investigation of yield traits revealed that the P lines had reduced 1000-grain weight, yield per plot and grain/brown rice thickness compared to the W lines. A difference comparison of these traits and a source-sink and transportation relationship analysis for these SLs suggested that small sink size was a key reason behind yield reduction of purple pericarp rice.

Uniformity in the height of main stem and tillers is a key factor affecting ideal plant type, a key component in super high-yielding rice breeding. An understanding of the genetic basis of the panicle layer uniformity may thus contribute to breeding varieties with good plant type and high yield. In the present study, a doubled haploid (DH) population, derived from a cross between indica rice variety Zhai-Ye-Qing 8 (ZYQ8) and japonica rice variety Jing-Xi 17 (JX17) was used to analyze quantitative trait loci (QTL) for panicle layer uniformity related traits. Six, four and three QTL were detected for the highest panicle height (HPH), lowest panicle height (LPH) and panicle layer dis-uniformity (PLD), respectively. qHPH-1-1 and qPLD-1 were located at the same interval on chromosome 1. The JX17 allele(s) of these QTL increased HPH and PLD by 2.57 and 1.26 cm, respectively. Similarly, qPLD-7 and qHPH-7 were located at the same interval on chromosome 7, where the ZYQ8 allele(s) increased HPH and PLD by 3.74 and 1.96 cm, respectively. These four QTL were unfavourable for panicle layer uniformity improvement because a decrease of the PLD was accompanied by decrease of the plant height. qPLD-6 and qLPH-6-1 were located at the same interval on chromosome 6, however here the JX17 allele(s) increased LPH, but decreased PLD, suggesting that this QTL was favourable for improvement of panicle layer uniformity. The markers identified in this study are potential for marker assisted breeding for the improvement of the panicle layer uniformity and ideal plant type.

Simultaneous heading of plants within the same rice variety, also refer to heading synchrony, is an important factor that affects simultaneous ripening of the variety. Understanding of the genetic basis of heading synchrony may contribute to molecular breeding of rice with simultaneous heading and ripening. In the present study, a doubled haploid (DH) population, derived from a cross between Chunjiang 06 and TN1 was used to analyze quantitative trait locus (QTL) for heading synchrony related traits, i.e., early heading date (EHD), late heading date (LHD), heading asynchrony (HAS), and tiller number (PN). A total of 19 QTLs for four traits distributed on nine chromosomes were detected in two environments. One QTL, qHAS-8 for HAS, explained 27.7% of the phenotypic variation, co-located with the QTLs for EHD and LHD, but it was only significant under long-day conditions in Hangzhou, China. The other three QTLs, qHAS-6, qHAS-9, and qHAS-10, were identified under short-day conditions in Hainan, China, each of which explained about 11% of the phenotypic variation. Two of them, qHAS-6 and qHAS-9, were co-located with the QTLs for EHD and LHD. Two QTLs, qPN-4 and qPN-5 for PN, were detected in Hangzhou, and qPN-5 was also detected in Hainan. However, none of them was co-located with QTLs for EHD, LHD, and HAS, suggesting that PN and HAS were controlled by different genetic factors. The results of this study can be useful in marker assisted breeding for improvement of heading synchrony.

Thousand-grain weight (TGWT) is an important factor affecting grain yield as well as grain quality in rice. A quantitative trait locus (QTL) qTGWT1-1 for TGWT was detected previously near DNA marker RG532 on the short arm of chromosome 1 in a recombinant inbred line (RIL) population derived from the indica-indica rice cross Zhengshan97B (ZS97B)/Milyang46 (MY46). In this study, two residual heterozygous lines (RHLs), Ch1 and Ch2, derived from the ZS97B/MY46 RIL F7 population, were used to develop two F6 populations, RIL-1 and RIL-2. The genome of Ch1 and Ch2 contains a heterozygous region flanked by RM1–RM3746 and RM151–RM243 on the short arm of chromosome 1, respectively, but is homozygous in other regions. Two tightly linked QTLs, Gw1-1 and Gw1-2, with the same additive direction and similar effect on TGWT, were detected in the region of QTL qTGWT1-1 in population RIL-2. No QTL was detected in the population RIL-1. Four individual RHLs from the population RIL-2 carrying heterozygous segments flanked by RM151–RM10404, RM10381–RM243, RM10435–RM259 and RM10398–RM5359, respectively, were chosen to develop four F2 populations. Ten maternal homozygotes and 10 paternal homozygotes were selected from each of the four F2 populations derived from the four RHLs. The four sets of near isogenic lines (NILs) were grown for phenotyping of TGWT and delimitation of Gw1-1 and Gw1-2. Results showed that Gw1-1 and Gw1-2 were located in the intervals RM10376–RM10398 and RM10404–RM1344 which cover 392.9 and 308.5 kb regions, respectively. The enhancing alleles were from ZS97B at both loci, and no significant interactions were detected. Genetic dissection of Gw1-1 and Gw1-2 has laid a foundation for their cloning and molecular breeding of grain yield and quality in rice.

A total of 32 rice genotypes carrying different dwarf or semi-dwarf genes were inoculated with the fungus Fusarium moniliforme Sheldon or treated with 50 mg l-1 GA3 in order to select resources resistant to rice bakanae disease from the dwarf materials. The length of the elongated seedlings was measured, and the percentage of death of the seedlings after transplanting to field was also counted. A significant correlation was found between the length of the seedling treated with GA3 and disease injury by bakanae fungus. Rice materials carrying dwarf gene such as sd1 were not only sensitivity to GA3 but also susceptive to rice bakanae disease. Materials carrying dwarf gene d1 were insensitive to GA3 but susceptive to bakanae. On the other hand, all materials carrying d29, sd6 or sdq(t) genes showed resistance to bakanae. The present study indicated that dwarf and semi-dwarf rice materials might be useful resources for improvement of bakanae resistance in rice breeding programs.

Pre-harvest sprouting (PHS) in rice production is usually caused by high temperature and humidity or continuous rains. It frequently happens in F1 in hybrid rice seed production. The PHS or “Physiologically germinated” seeds are of lower quality, by which the hybrid rice seed production is badly affected every three years at a loss of 20% or even 50% yield in seed production over the vast Yangtse River Valley and Southwest China. It is estimated that PHS causes an average decrease of seed activity by 10%. A recombinant inbred line population including 304 lines, derived from a cross between Indica rice (Oryza sativa L.) cultivars Zhong-156 and Gumei-2, was used to study the PHS physiology. Based on the data of sprouting rate in panicles and sprouting rate in grains, two kinds of lines, namely easy-to-sprout lines and hard-to-sprout lines, were selected to investigate their physiological differences when PHS happened. The experiment was conducted in a special field with a microclimate of higher temperature and humidity. The results indicated that it was easier to produce PHS from the female parent GM-2 than the male parent ZH-156, besides, the GA1 content and amylase activity in GM-2 grains were higher than those in ZH-156. However, the abscisic acid (ABA) content in GM-2 grains was lower than that in ZH-156. Higher temperature and higher humidity facilitated the GA1 increment from milk ripe stage to yellow ripe stage. GM-2 and the easily-sprouting lines showed an even higher increase in GA1 than ZH-156 and the hardly-sprouting lines, which enhanced the amylase activity and induced pre-harvest sprouting. This may be the physiological basis for pre-harvest sprouting induced by higher temperature and higher humidity, and these special characteristics must be inherited from their parents.

In this study, a total of 1047 insertion-deletion (InDel) primer pairs distributed across the rice genome were developed and experimentally validated. The primer pairs were designed based on the InDel length polymorphisms between 93-11 (Oryza sativa ssp indica cv.) and Nipponbare (Oryza sativa ssp japonica cv.), aiming for utilization between indica and japonica rice, or between other inter-subspecific rice cultivars. The 1047 primer pairs were dispersed across all 12 of the rice chromosomes, with one InDel marker found every 371.3 kb on average. The InDel length of the markers varied from 3 to 39 bp: 88.2% of the markers contained 6 to 25 bp, only 6.2% of markers were ≤ 5 bp, and 5.6% were ≥ 26 bp. Six hundred and twenty-three (59.5%) of the 1047 InDel markers were shown to amplify well and were polymorphic between Taichung65 and IR8, and 476 (45.5%) markers were polymorphic between Lemont and Yangdao4, while 398 (38.0%) were polymorphic in both combinations. These results demonstrated that the polymerase chain reaction-based InDel markers developed in this study could be of immediate use for rice genetic studies and breeding programs.

Uniformity of stem height in rice directly affects crop yield potential and appearance, and has become a vital index for rice improvement. In the present study, a doubled haploid (DH) population, derived from a cross between japonica rice Chunjiang 06 and indica rice TN1 was used to analyze the quantitative trait locus (QTL) for three related traits of panicle-layer-uniformity; that is, the tallest panicle height, the lowest panicle height and panicle layer disuniformity in two locations: Hangzhou (HZ) and Hainan (HN). A total of 16 QTLs for three traits distributed on eight chromosomes were detected in two different environments. Two QTLs, qTPH-4 and qTPH-8 were co-located with the QTLs for qLPH-4 and qLPH-8, which were only significant in the HZ environment, whereas the qTPH-6 and qLPH-6 located at the same interval were only significant in the HN environment. Two QTLs, qPLD-10-1 and qPLD-10-2, were closely linked to qTPH-10, and they might have been at the same locus. One QTL, qPLD-3, was detected in both environments, explaining more than 23% of the phenotypic variations. The CJ06 allele of qPLD-3 could increase the panicle layer disuniformity by 9.23 and 4.74 cm in the HZ and HN environments. Except for qPLD-3, almost all other QTLs for the same trait were detected only in one environment, indicating that these three traits were dramatically affected by environmental factors. The results may be useful for elucidation of the molecular mechanism of panicle-layer-uniformity and marker assisted breeding for super-rice.