FAN Fengfeng, CAI Meng, LUO Xiong, LIU Manman, YUAN Huanran, CHENG Mingxing,Ayaz AHMAD, LI Nengwu, LI Shaoqing

(1State Key Laboratory of Hybrid Rice, Key Laboratory for Research and Utilization of Heterosis in Indica Rice of Ministry of Agriculture and Rural Affairs, Engineering Research Center for Plant Biotechnology and Germplasm Utilization of Ministry of Education, College of Life Science, Wuhan University, Wuhan 430072, China; 2Hubei Hongshan Laboratory, Wuhan 430072, China)

Abstract: Global warming poses a threat to rice production. Breeding heat-tolerant rice is an effective and economical approach to address this challenge. African rice is a valuable genetic resource for developing heat-tolerant crops due to its intricate mechanism for adapting to high temperatures. Oryza longistaminata, a widely distributed wild rice species in Africa, may harbor an even richer gene pool for heat tolerance, which remains untapped. In this study, we identified three heat tolerance QTLs from O.longistaminata at the seedling stage, including novel heat tolerance loci qTT4 and qTT5. Our findings demonstrated that the O. longistaminata alleles for these two QTLs can enhance the heat tolerance of rice seedlings. Remarkably, qTT5 was mapped to a region spanning approximately 287.2 kb, which contains 46 expressing genes. Through the analysis of Gene Ontology and expression differences under heat induction, we identified four candidate genes. Our results lay the foundation for discovering heat tolerance genes underlying O. longistaminata and developing new genetic resources for heat-tolerant rice breeding.

Key words: wild rice; Oryza longistaminata; heat tolerance; QTL

Since the 1980s, the issue of global warming has been recognized as an unprecedented challenge, posing a significant threat to the future of human society (Lobell et al, 2011). Among the sectors most vulnerable to the impacts of global warming, agricultural production stands out due to its close dependence on the environment.The rise in the global mean temperature has the potential to cause substantial losses in crop yields. For instance, a 1 °C rise in the global mean temperature can reduce crop yields by 6.0% for wheat, 3.2% for rice, 7.4% for maize, and 3.1% for soybean (Zhaoet al,2017). Rice (Oryza sativaL.) is a staple crop for more than half of the world’s population, and its yield and quality are essential for the dietary energy security of billions of people (Xuet al, 2021). Furthermore, rice is a heat-sensitive crop, and exposure to high temperatures can significantly diminish both its yield and grain quality, causing issues such as low gel consistency and chalkiness (Nevameet al, 2018).Given the role of rice in global food security and the detrimental effects of heat stress on its yield and quality, there is an urgent need to breed heat-tolerant rice.

Understanding the physiological, biochemical, genetic,and molecular characteristics of rice in response to heat stress is essential for thermotolerance breeding.Currently, several genes related to heat stress have been identified in rice, including heat shock proteins(HSPs) and heat shock transcription factors (HSFs),which are the main types of proteins involved (Xuet al,2021). HSPs act as molecular chaperones, aiding in the stabilization and renaturation of unfolded and aggregated proteins induced by heat stress, thus playing a crucial role in plant stress tolerance (Zouet al, 2009;Müller and Rieu, 2016). For example,OsHSP26.7encodes a chloroplast-localized HSP that protects chloroplasts from oxidative damage caused by high temperatures and ultraviolet light (Leeet al, 2000).Over-expression studies have demonstrated that increasing the expression of thesHSP17.7gene significantly enhances rice heat tolerance (Sato and Yokoya, 2008). HSFs, on the other hand, are responsible for signal transduction and the activation of HSP expression during heat stress (Kan and Lin,2021). For instance,OsHSF7can up-regulate protective HSP genes during heat stress, thereby enhancing thermotolerance in plants (Liuet al, 2009). In addition to HSPs and HSFs, other genes encoding various types of proteins are also involved in improving rice heat tolerance, such asHYR(Ambavaramet al, 2014),PGL(Yanget al, 2016),FLO2(Sheet al, 2010),RBG1(Loet al, 2020), andOsFIE1(Dhattet al, 2021).Functional analysis of these genes can provide valuable insights into the physiological and biochemical characteristics, as well as the molecular mechanisms underlying rice heat tolerance. However, most studies on these genes are limited to molecular mechanisms,and there is a lack of excellent alleles that can be directly applied to rice heat tolerance breeding. Mapping heat tolerance QTLs using F2, backcross inbred line(BIL), recombinant inbred line (RIL), and chromosome segment substitution line (CSSL) populations is essential for identifying excellent heat tolerance alleles in rice (Caoet al, 2020; Xuet al, 2021).While more than 60 heat tolerance QTLs have been located, only a few have been cloned and functionally validated (Xu et al, 2021; Zhanget al, 2022).OsHTAS, a dominant QTL on chromosome 9, has been shown to confer tolerance to a temperature of 48 °C in rice seedlings(Liuet al, 2016). The heat tolerance QTLTT1has been identified from African rice CG14, and itsTT1CG14allele has stronger thermotolerance and shows greater potential for thermotolerance breeding (Liet al,2015).TT2is a natural QTL fromO. glaberrimathat confers heat tolerance without negatively affecting yield, making it a potential gene resource for rice thermotolerant breeding (Kanet al, 2022).TT3is a QTL contributing to rice thermotolerance, and theTT3CG14allele from African rice results in a heat-tolerant phenotype (Zhanget al, 2022). Interestingly, the three QTLsTT1,TT2, andTT3of African rice demonstrate good breeding potential, consistent with the distribution of African rice in tropical regions and the evolution of delicate mechanisms for adapting to high temperatures(Linares, 2002; Sakaiet al, 2011). Therefore, it is crucial to further investigate heat tolerance QTLs in African rice for heat tolerance breeding.O. longistaminata,a widely distributed wild rice in Africa, has been found to harbor rich genetic resources (Jinet al, 2018;Fanet al, 2019; Liuet al, 2020; Huanget al, 2022),suggesting that it may serve as a potential gene resource for rice thermotolerance breeding.

A QTL analysis was performed on 146 BILs(BC2F20) derived fromO. longistaminataat the seedling stage to identify QTLs responsible for heat tolerance.Three heat tolerance QTLs (qTT4,qTT5, andqTT6)were identified fromO. longistaminata, among whichqTT4O.longistaminataandqTT5O.longistaminataalleles exhibited heat tolerance. Subsequently,qTT5was further analyzed,and its potential heat-tolerant candidate genes were screened. These QTLs provide potential genetic resources for rice thermotolerance breeding.

RESULTS

Evaluation of heat tolerance of BILs from O.longistaminata

To identify heat tolerance QTLs inO. longistaminata,we evaluated 146 BILs at the seedling stage using two indices: heat tolerance grade (HTG) and seedling survival rate under heat stress (HTSR) (Fig. 1-A). The results demonstrated abundant variations in HTG and HTSR among the BILs, with average values surpassing those of the heat-sensitive parent 9311 (Fig. 1-B and Table 1). Furthermore, the phenotypic values of HTG and HTSR in the BILs exhibited continuous and skewed distribution patterns (Fig. 1-C and -D), with abroad-sense heritability of approximately 70% (Table 1). Correlation analysis revealed a strong association between HTG and HTSR, indicating that both indices can reflect heat resistance (Fig. 1-E and -F). These results suggested that this BIL population is well-suited for exploring heat-tolerant resources and conducting further QTL analysis.

Table 1. Heat tolerance phenotypic variations in 9311 and backcross inbred lines (BILs) in two tests.

Fig. 1. Identification of heat tolerance in backcross inbred line (BIL) population and their correlations at seedling stage.

QTL mapping for heat tolerance from O.longistaminata

Association analysis revealed that seven QTLs were responsible for heat tolerance at the seedling stage in wild riceO. longistaminata, explaining 4.61% to 20.08%of the phenotypic variations (Table S1). These QTLs were located on chromosomes 2, 8, and 9 (Fig. 2).Interestingly, QTLs for HTG and HTSR were found to be clustered together (Fig. 2), consistent with the significant correlation between the two indices. Among these QTLs,qHTG-2.1/qHTG-2.2/qHTSR-2andqHTG-8/qHTSR-8were detected in two tests and were newly discovered heat tolerance loci (Fig. 2 and Table S1).In the BIL population, the locus ofqHTG-2.1/qHTG-2.2/qHTSR-2explained 20.08% of phenotypic variations for HTG and 18.41% for HTSR (Table S1),indicating its importance as a novel locus contributing to heat tolerance. Therefore, we renamed this QTL asqTT4(QTL of thermotolerance 4).qHTG-8/qHTSR-8explained 13.92% of phenotypic variations for HTG and 11.94% for HTSR in the BIL population (Table S1).Accordingly, we renamed this QTL asqTT5.qHTG-9/qHTSR-9explained 4.61%of phenotypic variations for HTG and 5.74% for HTSR in the BIL population(Table S1), and was renamed asqTT6.This QTL overlapped with theOsHSP74.8gene, which is involved in the heat stress response (Table S1).

Validation of qTT4 and qTT5

To validate the genetic effects of the newly identified QTLs fromO. longistaminata, we conducted an analysis of the heat-tolerant effects ofqTT4andqTT5in the BIL population. Results showed that lines containingqTT4fromO. longistaminatadisplayed higher heat tolerance than those containingqTT4from 9311 (Fig.3-A). Subsequently, we selected five lines containing theqTT49311allele and five lines containing theqTT4O.longistaminataallele for heat tolerant identification at the seedling stage. In the results, lines containing theqTT49311allele died, while those containing theqTT4O.longistaminataallele survived (Fig. 3-C and -D).Similarly, theqTT5O.longistaminataallele demonstrated greater heat tolerance (Fig. 3-B, -E, and -F). These results indicated that the alleles ofqTT4andqTT5derived fromO. longistaminatacan improve the heat tolerance of rice seedlings.

Fig. 2. QTLs for heat tolerance at seedling stage detected in Oryza longistaminata.

To further confirm the effects ofqTT5on heat tolerance, we first screened the genetic background of all 146 BILs. Among them, B1795 contained a region ofqTT5that was genetically closest to 9311. Afterward,B1795 was backcrossed with 9311 twice and selfcrossed homozygotes. In the obtained homozygous lines,we screened out aqTT5-carrying CSSL, which only contained five small fragments fromO. longistaminata(Fig. S1). Compared with 9311, CSSL exhibited stronger thermotolerance, with the HTSR of seedlings being about 5-fold higher (Fig. 4). These results indicated thatqTT5derived fromO. longistaminatacan confer thermotolerance in rice seedlings.

Analysis of candidate genes of qTT5

Fig. 4. qTT5 improves heat tolerance of rice at seedling stage.

Fig. 5. Analysis of qTT5 candidate genes.

Progeny tests were conducted to further determine thatqTT5was delimited to a 287.2-kb stretch flanked by Bin8-130 and Bin8-131 based on the variance of HTSR in BIL populations (Fig. 5-A). According to the MH63 genome (http://rice.hzau.edu.cn/rice/), this genomic region contains 46 predicted genes (Fig. 5-B; Table S2).Among these genes, 20 were annotated to be involved in metabolic process and response to stimulus in the Gene Ontology analysis (Fig. 5-C; Table S3), which may contribute toqTT5heat tolerance. Next, we selected 10 BIL lines, consisting of 5 heat-sensitive and 5 heat-tolerant lines, to measure the expression levels of the 20 predicted candidate genes after 8 h of high temperature treatment. Among these, the expression levels of five genes (MH08g0014900,MH08g0018300,MH08g0018400,MH08g0018800, andMH08g0018900)were significantly different between heat-sensitive and heat-tolerant lines (Figs. 5-D and S2). We further investigated whether these five genes were candidates forqTT5by measuring their expression levels in 9311 and CSSL under heat stress for different periods in the phytotron (Fig. 6). All five genes showed some degree of heat induction. The expression levels ofMH08g0014900,MH08g0018800, andMH08g0018900were significantly higher in CSSL than in 9311 at all sampling sites (excluding 0 h). The expression levels ofMH08g0018300were significantly higher in CSSL than in 9311 at all sampling sites. When CSSL was examined at 0, 2, and 4 h after heat treatment,MH08g0018400showed significantly higher expression than 9311. However, after 4 h of treatment,MH08g0018400showed lower expression than at 0 h. This indicated that the heat induction intensity ofMH08g0018400in CSSL is not stronger than that in 9311. Based on these results,MH08g0014900,MH08g0018300,MH08g0018800,andMH08g0018900were potential candidate genes for the heat response within theqTT5locus.

DISCUSSION

Rice is an important crop for ensuring food security,but its growth process faces numerous challenges,including heat stress. With rising global warming and extreme weather conditions, heat stress poses an increasing threat to rice production (Zhaoet al, 2017).To overcome this challenge, it is essential to develop heat-tolerant rice varieties. Scientists have made significant efforts toward this goal, identifying several heat tolerance QTLs and cloning some of the associated genes, but only a few of these genes have practical applications (Caoet al, 2020; Kan and Lin,2021; Huet al, 2022). Among the promising QTLs identified,TT1,TT2, andTT3, all derived fromO.glaberrima, have demonstrated great potential (Liet al,2015; Kanet al, 2022; Zhanget al, 2022). This highlights the importance of selecting suitable materials for mining and utilizing heat tolerance gene resources.African rice possesses subtle mechanisms that enable it to adapt to high temperatures, making it a valuable genetic resource for rice thermotolerance breeding(Linares, 2002; Sakaiet al, 2011). Additionally, wild rice is known to contain more abundant gene resources than cultivated rice (Reuscheret al, 2018;Yuanet al, 2022). Therefore, wild rice, specificallyO.longistaminata, which is widely distributed in Africa,may contain abundant heat tolerance gene resources.However, no heat tolerance QTLs have been identified or cloned fromO. longistaminatauntil now. In this study, we identified three heat tolerance QTLs fromO.longistaminataat the seedling stage (Fig. 2).qTT6contains OsHSP74.8 (Table S2), an HSP involved in the heat stress response (Zouet al, 2009). The other QTLs,qTT4andqTT5, are novel heat tolerance loci found inO. longistaminata. We demonstrated that theO.longistaminataallele of these two QTLs could improve the heat tolerance of rice seedlings (Fig. 3).Then, we screened and identified aqTT5-carrying CSSL, which exhibited stronger heat tolerance at the seedling stage (Fig. 4). Interestingly, this CSSL also demonstrated robust high temperature tolerance during the unusually high temperatures in Ezhou, Hubei Province, China in 2022 (Fig. S3), indicating thatqTT5confers heat tolerance at both the seedling and heading stages. These results suggested that the discovery of these QTLs provides new genetic resources for rice heat tolerance breeding.

Fig. 6. Expression analysis of candidate genes in plants exposed to 45 °C heat stress in a phytotron for different time periods.

Subsequently,qTT5was further analyzed and four potential heat response-related candidate genes(MH08g0014900,MH08g0018300,MH08g0018800,andMH08g0018900) were identified.MH08g0014900encodes a chloroplast localized adenylate kinase(Table S2), which catalyzes the transfer of phosphoryl groups between adenosine diphosphate molecules to form adenosine triphosphate and adenosine monophosphate (Wang and Makowski, 2018). This reaction plays a major role in cellular energy homeostasis.Chloroplasts are the main organelles in plants that respond to heat stress, which can affect chlorophyll content and photosynthetic efficiency (Szymańska et al,2017; Sharmaet al, 2020; Zhanget al, 2022). Therefore,it would be valuable to investigate whether and how this chloroplast-localized adenylate kinase contributes to rice heat tolerance.MH08g0018300encodes OsMADS26 (Table S2), a MADS-box transcription factor thatnegatively regulates the ability of rice to resist pathogens and drought tolerance (Khonget al,2015). Although OsMADS26 is involved in multiple stress responses in rice, its function in regulating heat tolerance remains unknown.MH08g0018800encodes a protein containing an RNA recognition motif, and homologs of this gene are involved in embryogenesis inArabidopsis(Liet al, 2021).MH08g0018900encodes the carboxyl terminus of Hsc70-interacting protein(CHIP), which is an E3 ubiquitin ligase associated with chaperones (Table S2). The N-terminal tetratricopeptide repeat domain of AtCHIP acts as a co-chaperone for Hsp70, while its C-terminal U-box domain serves as an E3 ubiquitin ligase, resulting in the gene’s complex and diverse functions (Ballingeret al,1999; Leeet al, 2009). Hsp70 plays an important role in protein synthesis, folding, transmembrane transport,and degradation. Increased expression of Hsp70 in cells improves plant tolerance to stress. Interestingly,both over-expression and knockout mutation ofAtCHIPlead to increased heat sensitivity, but the specific molecular mechanisms behind this phenomenon remain unclear (Yanet al, 2003; Zhouet al,2014). Based on the above analysis, we consideredMH08g0014900andMH08g0018900as the most likely candidate genes for the heat response at theqTT5locus. Obviously, this needs to be verified by subsequent transgenic testing.

The aim of mapping heat tolerance QTLs is to facilitate the breeding of rice varieties that can withstand high temperatures. One effective approach for improving heat tolerance is to pyramid multiple beneficial genes within a single variety (Fanet al,2017; Zenget al, 2017). We therefore analyzed the additive effects of the new heat tolerance QTLsqTT4andqTT5derived fromO. longistaminatain the BIL population. Results showed that lines containing bothqTT4andqTT5exhibited significantly higher heat tolerance than those containing only one of these loci.Moreover, even lines with a singleqTT4orqTT5locus showed improved heat tolerance compared with those lacking these QTLs altogether (Fig. S4). These results demonstrated the additive effects ofqTT4andqTT5on heat tolerance, highlighting their potential utility for breeding heat-tolerant rice varieties.

METHODS

Rice materials

The recurrent parent for constructing the BIL population was 9311, anindicarice variety known for being heat-sensitive and high-yielding. The heat-tolerant donor parent was wild riceO.longistaminata(IRGC103886), widely distributed in Africa and renowned for outstanding traits such as disease and insect resistance, high temperature tolerance, and robust stem (Long et al, 2023). The 146 BILs were derived fromO. longistaminataand 9311 through a series of crosses, backcrosses, and self-crosses,resulting in BC2F20lines (Jinet al, 2018; Longet al, 2023).

Evaluation of heat tolerance at seedling stage

Rice seedlings were hydroponically cultivated in Yoshida nutrient solution, as previously reported (Liet al, 2015). Before planting, rice seeds underwent soaking and germination treatment,followed by 1 d of cultivation in petri dishes. Subsequently,seeds with comparable growth potential were carefully chosen and transferred into 96-well PCR plates. Each plate consisted of three rows, accommodating eight plants in each row. Each line was represented by three randomly selected replicates.Then, the seedlings were grown in a growth chamber under a photoperiod of 14 h light (28 °C)/10 h dark (24 °C) for 14 d.After removing weak seedlings, the seedlings were treated at high temperatures. To perform genetic mapping and linkage analysis on 146 BILs, they were first treated at 45 °C for 55 h,followed by 8 d of recovery under normal conditions (28 °C, 14 h/24 °C, 10 h). For other materials, a treatment at 45 °C for 60 h was followed by a recovery under normal conditions for 8 d.The relative humidity was maintained at 75%-80% throughout the planting and treatment phases. Finally, the seedling survival rate under heat stress and the heat tolerance grade of each line were recorded. Heat tolerance grades were evaluated according to leaf yellowing, leaf area reduction, leaf tip wilt, leaf whole wilt, and leaf death, and were divided into five grades: 1, 3, 5, 7,and 9 (Sarsuet al, 2018). The entire experiment was repeated biologically twice, designated as Test 1 and Test 2, respectively.All data were subjected to statistical analysis using Microsoft Excel 2010 and GraphPad Prism software. Heritability analysis was conducted using the QTL IciMapping v3.3 software (Meng et al, 2015).

QTL analysis

The 146 BILs underwent whole-genome sequencing, and a high-quality bin map of ultra-high-density single nucleotide polymorphisms (SNPs) was constructed based on the sequencing data (Longet al, 2023). A total of 2 430 bin markers were obtained based on these resequencing data, and used for subsequent QTL analysis. Genetic linkage map construction and QTL mapping analysis were performed using the QTL IciMapping v3.3 software (Menget al, 2015). The threshold of LOD value was set at 2.5, and the additive effect values and contribution rates were calculated for each QTL(Menget al, 2015; Fanet al, 2019).

Construction and background screening of qTT5-carrying CSSL

B1795, a heat-tolerant BIL containingtheqTT5O.longistaminataallele, was used as the donor parent. We obtained theqTT5-carrying CSSL with 9311 as the background by backcrossing B1795 with 9311 twice and self-crossing homozygous. Then, a total of 241 simple sequence repeat markers with polymorphisms between B1795 and 9311 were used to identify the background of theqTT5-carrying CSSL. The physical map was drawn using MapMaker Version 3.0 (Landeret al, 1987).

Statistical analysis of seed-setting rate of 9311 and qTT5-carrying CSSL

9311 and CSSL were planted and investigated in the experimental field of the Ezhou Experimental Base of Wuhan University, Hubei Province, China in the summer of 2022. The seeds were sown on 8 May and the panicles started heading on 4 August. A total of 50 plants of each line were planted in a 5-row plot with 10 plants per row. Three replications were performed for each line. The meteorological data of the experimental field were monitored by the Ezhou Meteorological Station of Wuhan University in real time, and the data were obtained every 10 min.

qRT-PCR analysis

Total RNA was extracted using TRIzol reagent (Invitrogen, CA,USA) according to the manufacturer’s protocol. Reversetranscription of the full-length cDNAs was performed using ReverTra Ace qPCR RT Master Mix (Toyobo, Osaka, Japan),according to the manufacturer’s protocol. Subsequent qPCR analysis was performed on a LightCycler 480 II system (Roche,USA) using SYBR Green PCR Master Mix (Toyobo, Osaka,Japan), according to the manufacturer’s protocol. The riceUbiquitingene was used as an internal control, and each reaction was run in triplicate. The primers used for qRT-PCR are listed in Table S4.

ACKNOWLEDGEMENTS

This study was partly granted from the National Natural Science Foundation of China (Grant No. U20A2023), the Joint Open Competitive Project of the Yazhou Bay Laboratory and the China National Seed Company Limited, and the Hubei Hongshan Laboratory, China (Grant No. 2021hszd010).

SUPPLEMENTAL DATA

The following materials are available in the online version of this article at http://www.sciencedirect.com/journal/rice-science;http://www.ricescience.org.

Fig. S1. Genetic background ofqTT5-carryingchromosome segment substitution lines.

Fig. S2. Analysis of expression levels of 20 candidate genes.

Fig. S3. Seed-setting rate of 9311 andqTT5-carrying chromosome segment substitution line (CSSL) at heading stage when grown at Ezhou city, Hubei Province, China.

Fig. S4. Genetic effects ofqTT4andqTT5on heat tolerance in backcross inbred line (BIL) population.

Table S1. QTL information for heat tolerance in backcross inbred lines ofOryza longistaminata.

Table S2. Predicted functional genes atqTT5locus.

Table S3. Genes involved in metabolic process and response to stimulus in Gene Ontology analysis.

Table S4. Markers used for expression analysis in this study.