Abstract
Targeting Induced Local Lesions IN Genomes (TILLING) is a reverse genetics strategy for the high-throughput screening of induced mutations. γ radiation, which often induces both insertion/deletion (Indel) and point mutations, has been widely used in mutation induction and crop breeding. The present study aimed to develop a simple, high-throughput TILLING system for screening γ ray-induced mutations using high-resolution melting (HRM) analysis. Pooled rice (Oryza sativa) samples mixed at a 1:7 ratio of Indel mutant to wild-type DNA could be distinguished from the wild-type controls by HRM analysis. Thus, an HRM-TILLING system that analyzes pooled samples of four M2 plants is recommended for screening γ ray-induced mutants in rice. For demonstration, a γ ray-mutagenized M2 rice population (n=4560) was screened for mutations in two genes, OsLCT1 and SPDT, using this HRM-TILLING system. Mutations including one single nucleotide substitution (G→A) and one single nucleotide insertion (A) were identified in OsLCT1, and one trinucleotide (TTC) deletion was identified in SPDT. These mutants can be used in rice breeding and genetic studies, and the findings are of importance for the application of γ ray mutagenesis to the breeding of rice and other seed crops.
中文概要
目的
建立适用于筛选伽马射线诱发突变的、基于高分辨率熔解曲线(high-resolution melting,HRM)技术的高通量定向诱导基因组局部突变技术 (Targeting Induced Local Lesions IN Genomes, TILLING)体系。
创新点
建立起了基于HRM技术、适用于伽玛射线诱发的小片段插入/缺失突变的高通量TILLING体系(HRM-TILLING)。
方法
通过不同野生型/突变型比例混池DNA的HRM分析,确定HRM检测不同类型插入/缺失突变的能力,确定M2植株突变检测的适宜混池比例,并用一个伽玛诱变M2 群体(n=4560)筛选OsLCT1和SPDT两个基因的突变体,确定实际效果。
结论
以4 株M2植株混样,采用HRM可以有效检出突变。建立的基于HRM的TILLING体系适用于伽玛射线诱发突变的高通量筛选。
Similar content being viewed by others
References
Acanda Y, Martínez Ó, Prado MJ, et al., 2014. EMS mutagenesis and qPCR-HRM prescreening for point mutations in an embryogenic cell suspension of grapevine. Plant Cell Rep, 33(3):471–481. https://doi.org/10.1007/s00299-013-1547-6
Ahloowalia BS, Maluszynski M, Nichterlein K, 2004. Global impact of mutation-derived varieties. Euphytica, 135(2):187–204. https://doi.org/10.1023/B:EUPH.0000014914.85465.4f
Botticella E, Sestili F, Hernandez-Lopez A, et al., 2011. High resolution melting analysis for the detection of EMS induced mutations in wheat Sbella genes. BMC Plant Biol, 11:156. https://doi.org/10.1186/1471-2229-11-156
Bovina R, Brunazzi A, Gasparini G, et al., 2014. Development of a TILLING resource in durum wheat for reverse-and forward-genetic analyses. Crop Pasture Sci, 65(1):112–124. https://doi.org/10.1071/cp13226
Bush SM, Krysan PJ, 2010. ITILLING: a personalized approach to the identification of induced mutations in Arabidopsis. Plant Physiol, 154(1):25–35. https://doi.org/10.1104/pp.110.159897
Colasuonno P, Incerti O, Lozito ML, et al., 2016. DHPLC technology for high-throughput detection of mutations in a durum wheat TILLING population. BMC Genet, 17:43. https://doi.org/10.1186/s12863-016-0350-0
Colbert T, Till BJ, Tompa R, et al., 2001. High-throughput screening for induced point mutations. Plant Physiol, 126(2):480–484. https://doi.org/10.1104/pp.126.2.480
Cousins MM, Donnell D, Eshleman SH, 2013. Impact of mutation type and amplicon characteristics on genetic diversity measures generated using a high-resolution melting diversity assay. J Mol Diagn, 15(1):130–137. https://doi.org/10.1016/j.jmoldx.2012.08.008
Dong CM, Vincent K, Sharp P, 2009. Simultaneous mutation detection of three homoeologous genes in wheat by high resolution melting analysis and mutation surveyor®. BMC Plant Biol, 9:143. https://doi.org/10.1186/1471-2229-9-143
Fu HW, Li YF, Shu QY, 2008. A revisit of mutation induction by gamma rays in rice (Oryza sativa L.): implications of microsatellite markers for quality control. Mol Breed, 22(2):281–288. https://doi.org/10.1007/s11032-008-9173-7
Gady ALF, Herman FWK, van de Wal MHBJ, et al., 2009. Implementation of two high through-put techniques in a novel application: detecting point mutations in large EMS mutated plant populations. Plant Methods, 5:13. https://doi.org/10.1186/1746-4811-5-13
Hofinger BJ, Jing HC, Hammond-Kosack KE, et al., 2009. High-resolution melting analysis of cDNA-derived PCR amplicons for rapid and cost-effective identification of novel alleles in barley. Theor Appl Genet, 119(5):851–865. https://doi.org/10.1007/s00122-009-1094-2
Hwang JE, Jang DS, Lee KJ, et al., 2017. Identification of gamma ray irradiation-induced mutations in membrane transport genes in a rice population by TILLING. Genes Genet Syst, 91(5):245–256. https://doi.org/10.1266/ggs.15-00052
Kumar APK, McKeown PC, Boualem A, et al., 2017. TILLING by sequencing (TbyS) for targeted genome mutagenesis in crops. Mol Breed, 37(2):14. https://doi.org/10.1007/s11032-017-0620-1
Li S, Zheng YC, Cui HR, et al., 2016. Frequency and type of inheritable mutations induced by γ rays in rice as revealed by whole genome sequencing. J Zhejiang Univ-Sci B (Biomed & Biotechnol), 17(12):905–915. https://doi.org/10.1631/jzus.B1600125
Lochlainn SÓ, Amoah S, Graham NS, et al., 2011. High resolution melt (HRM) analysis is an efficient tool to genotype EMS mutants in complex crop genomes. Plant Methods, 7:43. https://doi.org/10.1186/1746-4811-7-43
Lu HP, Zhang HL, Fu HW, et al., 2016. Identification and characterization of a novel lesion mimic mutant in rice. J Nucl Agric Sci, 30(6):1037–1044 (in Chinese). https://doi.org/10.11869/j.issn.100-8551.2016.06.1037
Mader E, Lukas B, Novak J, 2008. A strategy to setup codominant microsatellite analysis for high-resolutionmelting-curve-analysis (HRM). BMC Genet, 9:69. https://doi.org/10.1186/1471-2156-9-69
Matoulkova E, Michalova E, Vojtesek B, et al., 2012. The role of the 3' untranslated region in post-transcriptional regulation of protein expression in mammalian cells. RNA Biol, 9(5):563–576. https://doi.org/10.4161/rna.20231
McCallum CM, Comai L, Greene EA, et al., 2000. Targeting induced local lesions in genomes (TILLING) for plant functional genomics. Plant Physiol, 123(2):439–442. https://doi.org/10.1104/pp.123.2.439
Nawaz Z, Shu QY, 2014. Molecular nature of chemically and physically induced mutants in plants: a review. Plant Genet Res, 12(S1):S74–S78. https://doi.org/10.1017/S1479262114000318
Nida H, Blum S, Zielinski D, et al., 2016. Highly efficient de novo mutant identification in a Sorghum bicolor TILLING population using the ComSeq approach. Plant J, 86(4):349–359. https://doi.org/10.1111/tpj.13161
Reed GH, Kent JO, Wittwer CT, 2007. High-resolution DNA melting analysis for simple and efficient molecular diagnostics. Pharmacogenomics, 8(6):597–608. https://doi.org/10.2217/14622416.8.6.597
Ririe KM, Rasmussen RP, Wittwer CT, 1997. Product differentiation by analysis of DNA melting curves during the polymerase chain reaction. Anal Biochem, 245(2):154–160. https://doi.org/10.1006/abio.1996.9916
Rogers C, Wen JQ, Chen RJ, et al., 2009. Deletion-based reverse genetics in Medicago truncatula. Plant Physiol, 151(3):1077–1086. https://doi.org/10.1104/pp.109.142919
Sato Y, Shirasawa K, Takahashi Y, et al., 2006. Mutant selection from progeny of gamma-ray-irradiated rice by DNA heteroduplex cleavage using brassica petiole extract. Breed Sci, 56(2):179–183. https://doi.org/10.1270/jsbbs.56.179
Shu QY, Forster BP, Nakagawa H, 2012. Plant Mutation Breeding and Biotechnology. CABI Publishing, Wallingford, UK, p.123–134. https://doi.org/10.1079/9781780640853.0000
Simko I, 2016. High-resolution DNA melting analysis in plant research. Trends Plant Sci, 21(6):528–537. https://doi.org/10.1016/j.tplants.2016.01.004
Taheri S, Lee Abdullah T, Jain SM, et al., 2017. TILLING, high-resolution melting (HRM), and next-generation sequencing (NGS) techniques in plant mutation breeding. Mol Breed, 37:40. https://doi.org/10.1007/s11032-017-0643-7
Tan YY, Yu XM, Shu QY, et al., 2016. Development of an HRM-based, safe and high-throughput genotyping system for two low phytic acid mutations in soybean. Mol Breed, 36:101. https://doi.org/10.1007/s11032-016-0529-0
Till BJ, Reynolds SH, Greene EA, et al., 2003. Large-scale discovery of induced point mutations with high-throughput TILLING. Genome Res, 13(3):524–530. https://doi.org/10.1101/gr.977903
Till BJ, Cooper J, Tai TH, et al., 2007. Discovery of chemically induced mutations in rice by TILLING. BMC Plant Biol, 7:19. https://doi.org/10.1186/1471-2229-7-19
Tsai H, Howell T, Nitcher R, et al., 2011. Discovery of rare mutations in populations: TILLING by sequencing. Plant Physiol, 156(3):1257–1268. https://doi.org/10.1104/pp.110.169748
Uraguchi S, Kamiya T, Sakamoto T, et al., 2011. Low-affinity cation transporter (OsLCT1) regulates cadmium transport into rice grains. Proc Natl Acad Sci USA, 108(52):20959–20964. https://doi.org/10.1073/pnas.1116531109
Wang QZ, Fu HW, Huang JZ, et al., 2012. Generation and characterization of bentazon susceptible mutants of commercial male sterile lines and evaluation of their utility in hybrid rice production. Field Crop Res, 137:12–18. https://doi.org/10.1016/j.fcr.2012.09.001
Wittwer CT, Reed GH, Gundry CN, et al., 2003. High-resolution genotyping by amplicon melting analysis using LCGreen. Clin Chem, 49(6):853–860. https://doi.org/10.1373/49.6.853
Yamaji N, Takemoto Y, Miyaji T, et al., 2017. Reducing phosphorus accumulation in rice grains with an impaired transporter in the node. Nature, 541(7635):92–95. https://doi.org/10.1038/nature20610
Yoshida S, Forno DA, Cock J, et al., 1976. Laboratory Manual for Physiological Studies of Rice. The International Rice Research Institute, Los Banos, Manila, Philippines.
Zhang HL, Huang JZ, Chen XY, et al., 2014. Competitive amplification of differentially melting amplicons facilitates efficient genotyping of photoperiod-and temperaturesensitive genic male sterility in rice. Mol Breed, 34(4):1765–1776. https://doi.org/10.1007/s11032-014-0136-x
Zhao HJ, Liu QL, Ren XL, et al., 2008. Gene identification and allele-specific marker development for two allelic low phytic acid mutations in rice (Oryza sativa L.). Mol Breed, 22(4):603–612. https://doi.org/10.1007/s11032-008-9202-6
Author information
Authors and Affiliations
Corresponding author
Additional information
Project supported by the National Key Research and Development Program of China (No. 2016YFD0102103)
Rights and permissions
About this article
Cite this article
Li, S., Liu, Sm., Fu, Hw. et al. High-resolution melting-based TILLING of γ ray-induced mutations in rice. J. Zhejiang Univ. Sci. B 19, 620–629 (2018). https://doi.org/10.1631/jzus.B1700414
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1631/jzus.B1700414
Key words
- Mutation screening
- High-resolution melting (HRM) analysis
- Targeting Induced Local Lesions IN Genomes (TILLING)
- Mutant
- Indel
- γ ray
- Rice