Evaluation of heat stress resistance and its molecular machanism of four indica rice cultivars at seedling stage
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摘要:目的
明确4种不同籼稻品种苗期耐热性差异，为水稻品种选育与推广应用提供理论参考和技术支持。
方法采用水稻基因组重测序、表型鉴定结合转录水平分析综合评价华南地区高产常规水稻品种‘南秀美占’、杂交稻恢复系‘R5518’及香稻品种‘九里香’和‘南晶香占’的苗期耐热性。
结果‘南晶香占’苗期耐热性相对较弱，‘R5518’耐热性中等，‘九里香’和‘南秀美占’表现出苗期耐热性强于另外2个品种；通过比较水稻抗热相关基因在这4个品种的单倍型、荧光定量数据与表型数据，发现‘九里香’在OsTT1表现出较多的变异，而其他水稻耐热QTLs上，4个品种单倍型较为一致，可能OsTT1贡献了‘九里香’部分耐热性；表达模式上，OsHSF7、OsHSP71.1和OsHTS1基因表达趋势与水稻耐热性评价比较一致，表明这3个基因可能参与该研究中的4个籼稻品种耐热性调控。
结论由于一些耐热相关基因的表达差异、基因移码、剪切转录本出错，造成基因失活，导致不同籼稻品种的苗期耐热性差异。该项研究结果可为水稻耐热性育种全基因组选择提供新的思路。
Abstract:ObjectiveTo identify the variation in heat stress resistance among seedlings of four different indica rice cultivars grown in South China, and provide theoretical reference and technical support for the breeding and promotion of rice varieties.
MethodWe performed whole-genome re-sequencing, phenotype identification, and transcriptional level analysis to comprehensively evaluate the heat stress resistance for seedlings of high-yield conventional rice cultivar ‘Nan Xiu Mei Zhan’ (NXMZ), hybrid rice restorer cultivar ‘R5518’, and aromatic rice cultivars ‘Jiu Li Xiang’ (JLX) and ‘Nan Jing Xiang Zhan’ (NJXZ) in South China.
ResultThe ‘NJXZ’ was sensitive to heat stress. The ‘R5518’ showed medium resistance to heat stress. The resistances to heat stress of ‘JLX’ and ‘NXMZ’at seedling stage were relatively high in comparison to other two rice cultivars. We compared the haplotypes of heat resistance related genes, the relative expression levels and phenotypes, and found that many SNPs appeared in OsTT1 from‘JLX’, while the haplotypes of four cultivars with other heat-related QTLs remained relatively consistent, suggesting that the OsTT1 might contribute to partial heat stress resistance in ‘JLX’. The gene expression patterns in OsHSF7, OsHSP71.1 and OsHTS1 were consistent with the evaluation in heat stress resistance of rice cultivars, indicating that these three genes might associate with regulation in heat stress resistance of four indica rice cultivars.
ConclusionThe gene expression difference, gene shift and transcript error in certain genes result in variations in heat stress resistance of different indica rice cultivars at seedling stage. These results can provide new ideas for genome-wide selection for heat tolerance breeding in rice.
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图 1 4个水稻品种苗期耐热性评价
A~D：九里香(A)、南秀美占(B)、R5518(C)和南晶香占(D)种子萌发14 d正常培养表型图；E~H：九里香(E)、南秀美占(F)、R5518(G)和南晶香占(H)种子萌发14 d，高温处理3 d，正常条件下恢复生长7 d后的表型图；比例尺为2 cm
Figure 1. Evaluation of heat stress resistance of four rice cultivars at seedling stage
A−D: The phenotypes of 14 day seedlings after germination under normal condition of JLX (A), NXMZ (B), R5518 (C), and NJXZ (D); E−H: The phenotypes of JLX (E), NXMZ (F), R5518 (G), and NJXZ (H) seedlings after 14 days post germination, three days of heat treatment and seven days of recovery; Scale bar = 2 cm
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图 4 4个水稻品种耐热QTLs的单倍型分布图
图上特殊颜色区域表明与参考序列有差异
Figure 4. Haplotypes of heat tolerance related QTLs among four rice cultivars
The special colors in the bam files show the variation in comparisons to the reference genome
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图 5 4个水稻品种高温处理前后12个耐热相关基因的qRT-PCR转录水平差异
图中数据为3次生物学重复的平均值±标准差；Actin作为内参进行均一化计算基因表达量；‘九里香’处理前样品标准化为1
Figure 5. Differences in qRT-PCR transcription levels of twelve heat tolerance related genes among four rice cultivars before and after heat treatment
The data in the figure represents the mean ± standard deviation of three biological replicates; Actin was used for internal control to normalize the gene expression data; The sample of ‘Jiulixiang’ before treatment was standardized to 1
表 1 耐热相关基因及其对应的qRT-PCR引物信息
Table 1 The corresponding qRT-PCR primer information of selected heat tolerance related genes
基因
Gene基因号
Gene number正向序列(5′→3′)
Forward sequence反向序列(5′→3′)
Reverse sequence产物大小/bp
Product sizeTT1 LOC_Os03g26970 TGGAGCTTGACGATGCCATT CCTTGATCTCTGCAGGGCTC 141 TT2 Os03g0407400 CTCCAGATGCTGCAGAGAGG GCTCTGCACAAACAGCGAAA 132 TT3.1 LOC_Os03g49900 CTAGCTCATCATCAGCGGCA GTCAGGAAGACCACAGAGCC 104 OsWR2 LOC_Os06g40150 AATGGACGACGAGGAGAGGA GACGAGGCTACCTTCACCAC 112 
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续表 1 Continued table 1 基因
Gene基因号
Gene number正向序列(5′→3′)
Forward sequence反向序列(5′→3′)
Reverse sequence产物大小/bp
Product sizeTT3.2 LOC_Os03g49940 CACGATCCCCAAGCTGACTT AAGAACACCGCGGCTAAGAA 123 HTS1 LOC_Os04g30760 GACCCATGTTGCAGCTGTTG TGCACCCAGCTTTTCCAAGA 134 AET1 LOC_Os05g45890 GCCAACAGCGAGTACGAGTA AGAATCGGTGGAAGTGGCAG 109 TOGR1 LOC_Os03g46610 TAAGGTCGAGGTAGCGTCCA ATCATGCTCCCTGGCAACTC 126 OsER1 LOC_Os06g10230 CGACAATGCACGAGGTTGTG GCTGGTGCCTCTTAAGCTGA 143 OsMADS7 LOC_Os08g41950 GCAATTGAAAGCTAGCCGCA GCTGCTTCTCTAGGCTCTCG 137 OsFAD7 LOC_Os03g18070 GTTGAACAGCGTGGTTGGAC GACATGACCGTGGTTCTGGT 103 OsWRKY11 LOC_Os01g43650 GTTGATCACCTCGAGGACGG GCTTCTTCACACCGCACTTG 118 OsHCI1 LOC_Os10g30850 TCTCTCTCTTTTGCAGGGCG ATCCACTGCACGAGGAAGTG 106 OsHsfA2c LOC_Os10g28340 TGGAATCCCTGAGCTGGAGA AACAGCTCTGCCCAGAAGTC 129 OsHSBP1 LOC_Os09g20830 CCCGGCAGATATGACAGCAT TTCAGGTCGTTGACGCTCTG 144 OsHTAS LOC_Os09g15430 AACATCCGCATGCCCCTTTA CGGGTGGTTGTTCAGGTTCT 132 NAL11 LOC_Os07g09450 AAACGCCCATCCTGAGAAGG CCCCCTCCTTTTGTCTTCCC 141 HSA32 LOC_Os06g46900 CTCTACGGGCAGACATCGTC TCCACGAACAGATTCACCCG 133 OsHSBP2 LOC_Os06g16270 GCATCCCCATCAAGGCTGAT GGAACCTGGTTTGCATCTGC 105 HSP101 LOC_Os05g44340 GGTCGGCAAGAACTCCATGA ACCTTCCTGAGTTGCTCGTG 138 HTH5 LOC_Os05g05740 GCCTTGATCGTGTGGTAGCT CGAGATTCGGGCAGCCTAAT 150 OsHSP1 LOC_Os04g01740 CGTCAAGAAGCACTCCGAGT TCCTTGCCTTTGGAGTCGTC 117 OsHSP71.1 LOC_Os03g16860 CTGATCCCCAGGAACACCAC TCACCCTCGTACACCTGGAT 101 OsHSF7 LOC_Os03g06630 GATGGTGAAGGAGGAGTGGC CAGGTCGAACGTCTTGGTCA 115
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表 2 4个水稻品种测序深度及覆盖度统计1)
Table 2 Sequencing depth and coverage of four rice cultivars
品种
Cultivar比对读数
Comparative
reads总读数
Total
reads比对率/%
Comparison
rate平均测序深度
Average sequencing
depth1×覆盖度/%
1× coverage4×覆盖度/%
4× coverage5×覆盖度/%
5× coverage九里香 JLX 68 508 565 69 806 334 98.14 22.62 94.48 91.58 92.58 南秀美占 NXMZ 71 978 559 73 338 268 98.15 24.39 94.87 92.17 93.17 R5518 68 952 835 73 150 652 94.26 23.30 94.75 92.10 93.10 南晶香占 NJXZ 71 235 025 72 695 318 97.99 24.32 94.81 92.40 93.40 1) 比对读数是测序读数比对到参考基因组的总读数(包括单端比对和双端比对)；总读数指有效测序数据的总reads数；比对率指比对到参考基因组的读数比例；平均测序深度指比对到参考基因组的碱基总数除以覆盖的基因组大小；1×、4×和5×覆盖度分别指参考基因组至少有1个、连续4个和5个碱基覆盖的位点占基因组的百分比
1) The comparative reads number is the total number of sequencing reads which paired to the reference genome (including single-end paired and double-end paired); The total reads refers to the total number of valid reads paired to the reference genome; The average sequencing depth refers to the total number of reads paired to the reference genome divided by the size of the genome; 1×, 4× and 5× coverages refer to the percentages of the genome covered by at least 1 base, serial 4 bases and 5 bases respectively in the reference genome
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表 3 4个水稻品种基因组不同种类变异的数量统计1)
Table 3 Counting of different types of genomic variations in four rice cultivars
品种 Cultivar SNP InDel SV CNV 九里香 JLX 857923 148394 12036 6802 南秀美占 NXMZ 800685 139065 12201 6375 R5518 920843 159588 13125 7050 南晶香占 NJXZ 859302 148878 12401 7208 1) SNP指由单个核苷酸的变异所引起的DNA序列多态性；InDel指小于50 bp的小片段的插入和缺失；SV指50 bp以上的大片段的插入、缺失、倒置、易位；CNV指基因组片段的拷贝数增加或者减少
1)SNP refers to the DNA polymorphism caused by variation in a single nucleotide; InDel refers to the insertions and deletions of small fragments (< 50 bp); SV refers to large fragments (≥ 50 bp) of insertions, deletions, inversions, and translocations; CNV refers to the increase or decrease of the copy gene numbers in genome
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[1] ZHAO C, LIU B, PIAO S, et al. Temperature increase reduces global yields of major crops in four independent estimates[J]. Proceedings of the National Academy of Sciences of the United States of America, 2017, 114(35): 9326-9331.
[2] 陈祖龙, 郑珍珍, 王慧, 等. 水稻耐热育种研究及其展望[J]. 滁州学院学报, 2023, 25(2): 23-28. [3] LIU H, ZENG B, ZHAO J, et al. Genetic research progress: Heat tolerance in rice[J]. International Journal of Molecular Sciences, 2023, 24(8): 7140.
[4] NUBANKOH P, WANCHANA S, SAENSUK C, et al. QTL-seq reveals genomic regions associated with spikelet fertility in response to a high temperature in rice (Oryza sativa L.)[J]. Plant Cell Reports, 2020, 39(1): 149-162. doi: 10.1007/s00299-019-02477-z
[5] YE C, TENORIO F A, ARGAYOSO M A, et al. Identifying and confirming quantitative trait loci associated with heat tolerance at flowering stage in different rice populations[J]. BMC Genetics, 2015, 16: 41.
[6] ZHU S, HUANG R, WAI H P, et al. Mapping quantitative trait loci for heat tolerance at the booting stage using chromosomal segment substitution lines in rice[J]. Physiology and Molecular Biology of Plants, 2017, 23(4): 817-825. doi: 10.1007/s12298-017-0465-4
[7] 王丰, 程方民, 刘奕, 等. 不同温度下灌浆期水稻籽粒内源激素含量的动态变化[J]. 作物学报, 2006, 32(1): 25-29. [8] LI X M, CHAO D Y, WU Y, et al. Natural alleles of a proteasome alpha2 subunit gene contribute to thermotolerance and adaptation of African rice[J]. Nature Genetics, 2015, 47(7): 827-833. doi: 10.1038/ng.3305
[9] KAN Y, MU X R, ZHANG H, et al. TT2 controls rice thermotolerance through SCT1-dependent alteration of wax biosynthesis[J]. Nature Plants, 2022, 8(1): 53-67.
[10] ZHANG H, ZHOU J F, KAN Y, et al. A genetic module at one locus in rice protects chloroplasts to enhance thermotolerance[J]. Science, 2022, 376(6599): 1293-1300. doi: 10.1126/science.abo5721
[11] CAO Z B, TANG H W, CAI Y H, et al. Natural variation of HTH5 from wild rice, Oryza rufipogon Griff., is involved in conferring high-temperature tolerance at the heading stage[J]. Plant Biotechnology Journal, 2022, 20(8): 1591-1605.
[12] WANG D, QIN B X, LI X, et al. Nucleolar DEAD-Box RNA helicase TOGR1 regulates thermotolerant growth as a Pre-rRNA chaperone in rice[J]. PLoS Genetics, 2016, 12(2): e1005844. doi: 10.1371/journal.pgen.1005844
[13] SHEN H, ZHONG X B, ZHAO F F, et al. Overexpression of receptor-like kinase ERECTA improves thermotolerance in rice and tomato[J]. Nature Biotechnology, 2015, 33(9): 996-1003.
[14] YANG Y, YU J, QIAN Q, et al. Enhancement of heat and drought stress tolerance in rice by genetic manipulation: A systematic review[J]. Rice, 2022, 15(1): 67. doi: 10.1186/s12284-022-00614-z
[15] YU H, LIU Y, SUN B, et al. Genetic diversity and breeding signatures for regional Indica rice improvement in Guangdong of Southern China[J]. Rice, 2023, 16(1): 25. doi: 10.1186/s12284-023-00642-3
[16] WANG J, YANG W, ZHANG S, et al. A pangenome analysis pipeline provides insights into functional gene identification in rice[J]. Genome Biology, 2023, 24(1): 19.
[17] WEI X, QIU J, YONG K, et al. A quantitative genomics map of rice provides genetic insights and guides breeding[J]. Nature Genetics, 2021, 53(2): 243-253. doi: 10.1038/s41588-020-00769-9
[18] 刘传光, 周新桥, 陈达刚, 等. 广东丝苗米品种南晶香占的选育与栽培技术[J]. 农业与技术, 2022, 42(7): 94-97. [19] LETUNIC I, BORK P. Interactive tree of Life (iTOL) v5: An online tool for phylogenetic tree display and annotation[J]. Nucleic Acids Research, 2021, 49(W1): W293-W296. doi: 10.1093/nar/gkab301
[20] CHEN K, YE C, GUO J, et al. Agrobacterium-mediated transformation efficiency and grain phenotypes in six indica and japonica rice cultivars[J]. Seed Biology, 2023, 2: 4. doi: 10.48130/SeedBio-2023-0004.
[21] ROBINSON J T, THORVALDSDOTTIR H, TURNER D, et al. Igv. js: An embeddable JavaScript implementation of the Integrative Genomics Viewer (IGV)[J]. Bioinformatics, 2023, 39(1): btac830.
[22] GOPALAKRISHNAN N, KANG I, MOON B, et al. Effects of low temperature stress on rice (Oryza sativa L. ) plastid ω-3 desaturase gene, OsFAD8 and its functional analysis using T-DNA mutants[J]. Plant Cell, Tissue and Organ Culture, 2009, 98(1): 87-96. doi: 10.1007/s11240-009-9541-y
[23] MOON J, HAM D, HWANG S, et al. Molecular characterization of a heat inducible rice gene, OsHSP1, and implications for rice thermotolerance[J]. Genes & Genomics, 2014, 36(2): 151-161.
[24] LIU J G, QIN Q L, ZHANG Z, et al. OsHSF7 gene in rice, Oryza sativa L., encodes a transcription factor that functions as a high temperature receptive and responsive factor[J]. BMB Reports, 2009, 42(1): 16-21. doi: 10.5483/BMBRep.2009.42.1.016
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