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Year 2024, Volume: 41 Issue: 3, 106 - 115, 25.11.2024
https://doi.org/10.16882/hortis.1538865

Abstract

References

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QTL-Seq: Rapid, Cost-Effective, and Reliable Method for QTL Identification

Year 2024, Volume: 41 Issue: 3, 106 - 115, 25.11.2024
https://doi.org/10.16882/hortis.1538865

Abstract

QTL-seq is a powerful method that integrates whole-genome sequencing (WGS) with bulk-segregant analysis to rapidly and reliably identify quantitative trait loci (QTLs) associated with specific traits. This approach significantly advances traditional QTL mapping by eliminating the need for genome wide DNA markers such as SSR, RFLP, and INDELs, which are typically used in linkage-based QTL mapping. Instead, QTL-seq leverages WGS to detect all genetic variations such as SNPs, Indels, and Structural Variants across the entire genome, providing a comprehensive resource for marker development in marker-assisted selection. The QTL-seq process begins with the creation of genetically diverse mapping populations, such as F2 or RILs, followed by detailed phenotypic characterization. DNA from plants exhibiting similar phenotypes is pooled into bulk groups and sequenced, allowing for cost-effective and efficient QTL identification. Identified QTLs can be further validated through fine mapping using recombinant screenings and progeny testing, leading to the identification of candidate genes associated with traits of interest. In this study, we outline a user-friendly QTL-seq pipeline, from sequencing to data visualization to demonstrate its practical application. While the manuscript primarily focuses on describing the pipeline, we also conducted a case study analysis with real data to showcase its effectiveness. Our work contributes to the broader understanding of QTL-seq applications and offers practical recommendations for optimizing this method in future breeding programs.

References

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  • Ashton, D.T., Ritchie, P.A., & Wellenreuther, M. (2017). Fifteen years of quantitative trait loci studies in fish: challenges and future directions. Molecular Ecology, 26(6): 1465-1476.
  • Austin, R.S., Vidaurre, D., Stamatiou, G., Breit, R., Provart, N.J., Bonetta, D., Zhang, J., Fung, P., Gong, Y., Wang, P.W., McCourt, P., & Guttman, D.S. (2011). Next-generation mapping of Arabidopsis genes. The Plant Journal, 67(4): 715-725.
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  • Cao, M., Li, S., Deng, Q., Wang, H., & Yang, R. (2021). Identification of a major-effect QTL associated with pre-harvest sprouting in cucumber (Cucumis sativus L.) using the QTL-seq method. BMC Genomics, 22(1): 249.
  • Chen, Q., Song, J., Du, W.P., Xu, L.Y., Jiang, Y., Zhang, J., Xiang, X.L., & Yu, G.R. (2018). Identification and genetic mapping for rht-DM, a dominant dwarfing gene in mutant semi-dwarf maize using QTL-seq approach. Genes & Genomics, 40(10): 1091-1099.
  • Cheng, C.Y., Krishnakumar, V., Chan, A.P., Thibaud‐Nissen, F., Schobel, S., & Town, C.D. (2017). Araport11: a complete reannotation of the Arabidopsis thaliana reference genome. The Plant Journal, 89(4): 789-804.
  • Chiang, C., Layer, R.M., Faust, G.G., Lindberg, M.R., Rose, D.B., Garrison, E.P., Marth, G.T., Quinlan, A.R., & Hall, I.M. (2015). SpeedSeq: ultra-fast personalgenome analysis and interpretation. Nat Methods, 12(10): 966-968.
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  • Hamblin, M.T., Buckler, E.S., & Jannink, J.L. (2011). Population genetics of genomics-based crop improvement methods. Trends in Genetics, 27(3): 98-106.
  • Hong, E.P., & Park, J.W. (2012). Sample size and statistical power calculation in genetic association studies. Genomics Inform, 10(2): 117-122.
  • Illa-Berenguer, E., Van Houten, J., Huang, Z., & van der Knaap, E. (2015). Rapid and reliable identification of tomato fruit weight and locule number loci by QTL-seq. Theoretical and Applied Genetics, 128(7): 1329-1342.
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  • Jiao, Y., Peluso, P., Shi, J., Liang, T., Stitzer, M.C., Wang, B., Campbell, M.S., Stein, J.C., Wei, X., & Chin, C.S. (2017). Improved maize reference genome with single-molecule technologies. Nature, 546(7659): 524-527.
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  • Lei, L., Zheng, H., Bi, Y., Yang, L., Liu, H., Wang, J., Sun, J., Zhao, H., Li, X., Li, J., Lai, Y., & Zou, D. (2020). Identification of a major QTL and candidate gene analysis of salt tolerance at the bud burst stage in rice (Oryza sativa L.) using QTL-Seq and RNA-Seq. Rice, 13(1): 55.
  • Li, H., & Durbin, R. (2009). Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics, 25(14): 1754-1760.
  • Lu, H., Lin, T., Klein, J., Wang, S., Qi, J., Zhou, Q., Sun, J., Zhang, Z., Weng, Y., & Huang, S. (2014). QTL-seq identifies an early flowering QTL located near Flowering Locus T in cucumber. Theoretical and Applied Genetics, 127(7): 1491-1499.
  • Mackay, T.F. (2001). The genetic architecture of quantitative traits. Annual Review of Genetics, 35(1): 303-339.
  • Madhusudhana, R. (2015). Linkage mapping. Sorghum Molecular Breeding, 47-70.
  • Mansfeld, B.N., & Grumet, R. (2018). QTLseqr: An R Package for bulk segregant analysis with next-generation sequencing. The Plant Genome, 11(2): 180006.
  • McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., & DePristo, M.A. (2010). The genome analysis toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research, 20(9): 1297-1303.
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  • Pandey, M.K., Khan, A.W., Singh, V.K., Vishwakarma, M.K., Shasidhar, Y., Kumar, V., Garg, V., Bhat, R.S., Chitikineni, A., Janila, P., Guo, B., & Varshney, R.K. (2017). QTL-seq approach identified genomic regions and diagnostic markers for rust and late leaf spot resistance in groundnut (Arachis hypogaea L.). Plant Biotechnology Journal, 15(8): 927-941.
  • Qiao, A., Fang, X., Liu, S., Liu, H., Gao, P., & Luan, F. (2021). QTL-seq identifies major quantitative trait loci of stigma color in melon. Horticultural Plant Journal, 7(4): 318-326.
  • Ribaut, J.M., & Hoisington, D. (1998). Marker-assisted selection: new tools and strategies. Trends in Plant Science, 3(6): 236-239.
  • Salleh, S.B., Rafii, M.Y., Ismail, M.R., Ramli, A., Chukwu, S.C., Yusuff, O., & Hasan, N.A. (2022). Genotype-by-environment interaction effects on blast disease severity and genetic diversity of advanced blast-resistant rice lines based on quantitative traits. Frontiers in Agronomy, 4.
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  • Seeb, J.E., Carvalho, G., Hauser, L., Naish, K., Roberts, S., & Seeb, L.W. (2011). Single-nucleotide polymorphism (SNP) discovery and applications of SNP genotyping in nonmodel organisms. Molecular Ecology Resources, 11(s1): 1-8.
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There are 55 citations in total.

Details

Primary Language English
Subjects Agricultural Engineering (Other)
Journal Section Araştırma Makalesi
Authors

Yasin Topcu 0000-0001-5296-2939

Manoj Sapkota This is me 0000-0002-9987-1193

Serkan Aydın 0000-0001-6513-3005

Early Pub Date September 6, 2024
Publication Date November 25, 2024
Submission Date May 28, 2024
Acceptance Date August 26, 2024
Published in Issue Year 2024 Volume: 41 Issue: 3

Cite

APA Topcu, Y., Sapkota, M., & Aydın, S. (2024). QTL-Seq: Rapid, Cost-Effective, and Reliable Method for QTL Identification. Horticultural Studies, 41(3), 106-115. https://doi.org/10.16882/hortis.1538865
AMA Topcu Y, Sapkota M, Aydın S. QTL-Seq: Rapid, Cost-Effective, and Reliable Method for QTL Identification. HortiS. November 2024;41(3):106-115. doi:10.16882/hortis.1538865
Chicago Topcu, Yasin, Manoj Sapkota, and Serkan Aydın. “QTL-Seq: Rapid, Cost-Effective, and Reliable Method for QTL Identification”. Horticultural Studies 41, no. 3 (November 2024): 106-15. https://doi.org/10.16882/hortis.1538865.
EndNote Topcu Y, Sapkota M, Aydın S (November 1, 2024) QTL-Seq: Rapid, Cost-Effective, and Reliable Method for QTL Identification. Horticultural Studies 41 3 106–115.
IEEE Y. Topcu, M. Sapkota, and S. Aydın, “QTL-Seq: Rapid, Cost-Effective, and Reliable Method for QTL Identification”, HortiS, vol. 41, no. 3, pp. 106–115, 2024, doi: 10.16882/hortis.1538865.
ISNAD Topcu, Yasin et al. “QTL-Seq: Rapid, Cost-Effective, and Reliable Method for QTL Identification”. Horticultural Studies 41/3 (November 2024), 106-115. https://doi.org/10.16882/hortis.1538865.
JAMA Topcu Y, Sapkota M, Aydın S. QTL-Seq: Rapid, Cost-Effective, and Reliable Method for QTL Identification. HortiS. 2024;41:106–115.
MLA Topcu, Yasin et al. “QTL-Seq: Rapid, Cost-Effective, and Reliable Method for QTL Identification”. Horticultural Studies, vol. 41, no. 3, 2024, pp. 106-15, doi:10.16882/hortis.1538865.
Vancouver Topcu Y, Sapkota M, Aydın S. QTL-Seq: Rapid, Cost-Effective, and Reliable Method for QTL Identification. HortiS. 2024;41(3):106-15.