Skip to main content

Integrated Genomic Strategies for Cereal Genetic Enhancement: Combining QTL and Association Mapping

  • Protocol
  • First Online:
Cereal Genomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2072))

Abstract

Identification of genetic basis for important agronomic traits is essential for marker-assisted crop improvement. Linkage mapping is one of the most popular approaches utilized for identification of major quantitative trait loci (QTLs) governing important agronomic traits in cereals. However, the identified QTLs usually span large genomic intervals and very few of these are subsequently fine mapped to single major effect gene. This hinders application of these QTLs in marker-aided breeding and crop genetic enhancement. On the contrary, association mapping, another popular approach for identification of QTLs, provides very high resolution but suffers from high level of false positives. Joint linkage-association analysis provides a way to combine advantages and avoid the pitfalls associated with both these methods. In this context, we recently developed MetaQTL specific regional association analysis and demonstrated its utility to rapidly narrow down previously identified QTL intervals to few candidate genes. Here, we describe the detailed step-by-step guide for performing MetaQTL specific regional association analysis to identify important genomic regions and underlying potential major effect genes governing traits of agronomic importance in cereals.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Tester M, Langridge P (2010) Breeding technologies to increase cropping production in a changing world. Science 327:818–822

    Article  CAS  Google Scholar 

  2. Alexandratos N, Bruinsma J (2012) World agriculture towards 2030/2050: the 2012 revision. FAO: ESA Working Paper No. 12-03.

    Google Scholar 

  3. Moose SP, Mumm RH (2008) Molecular plant breeding as the foundation for 21st century crop improvement. Plant Physiol 147:969–977

    Article  CAS  Google Scholar 

  4. Dar MH, de Janvry A, Emerick K et al (2013) Flood-tolerant rice reduces yield variability and raises expected yield, differentially benefitting socially disadvantaged groups. Sci Rep 3:3315

    Article  Google Scholar 

  5. Ellur RK, Khanna A, Yadav A et al (2016) Improvement of Basmati rice varieties for resistance to blast and bacterial blight diseases using marker assisted backcross breeding. Plant Sci 242:330–341

    Article  CAS  Google Scholar 

  6. Doerge RW (2002) Mapping and analysis of quantitative trait loci in experimental populations. Nat Rev Genet 3:43–52

    Article  CAS  Google Scholar 

  7. Fan C, Xing Y, Mao H et al (2006) GS3, a major QTL for grain length and weight and minor QTL for grain width and thickness in rice, encodes a putative transmembrane protein. Theor Appl Genet 112:1164–1171

    Article  CAS  Google Scholar 

  8. Ronald PC, Albano B, Tabien R et al (1992) Genetic and physical analysis of the rice bacterial blight disease resistance locus, Xa21. Mol Gen Genet 236:113–120

    Google Scholar 

  9. Gamuyao R, Chin JH, Pariasca-Tanaka J et al (2012) The protein kinase Pstol1 from traditional rice confers tolerance of phosphorus deficiency. Nature 488:535–539

    Article  CAS  Google Scholar 

  10. Kumar J, Gupta DS, Gupta S et al (2017) Quantitative trait loci from identification to exploitation for crop improvement. Plant Cell Rep 36:1187–1213

    Article  CAS  Google Scholar 

  11. Takagi H, Abe A, Yoshida K et al (2013) QTL-seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations. Plant J 74:174–183

    Article  CAS  Google Scholar 

  12. Shu J, Liu Y, Zhang L et al (2018) QTL-seq for rapid identification of candidate genes for flowering time in broccoli × cabbage. Theor Appl Genet 131:917–928

    Article  CAS  Google Scholar 

  13. Srivastava R, Upadhyaya HD, Kumar R et al (2017) A multiple QTL-Seq strategy delineates potential genomic loci governing flowering time in chickpea. Front Plant Sci 8:1105

    Article  Google Scholar 

  14. Huang X, Han B (2014) Natural variations and genome-wide association studies in cereals. Annu Rev Plant Biol 65:531–551

    Article  CAS  Google Scholar 

  15. Xiao Y, Liu H, Wu L et al (2017) Genome-wide association studies in maize: praise and stargaze. Mol Plant 10:359–374

    Article  CAS  Google Scholar 

  16. Zhou Z, Jiang Y, Wang Z et al (2015) Resequencing 302 wild and cultivated accessions identifies genes related to domestication and improvement in soybean. Nat Biotechnol 33:408–414

    Article  CAS  Google Scholar 

  17. Teo YY (2008) Common statistical issues in genome-wide association studies: a review on power, data quality control, genotype calling and population structure. Curr Opin Lipidol 19:133–143

    Article  CAS  Google Scholar 

  18. Korte A, Farlow A (2013) The advantages and limitations of trait analysis with GWAS: a review. Plant Methods 9:29

    Article  CAS  Google Scholar 

  19. Lu Y, Zhang S, Shah T et al (2010) Joint linkage-linkage disequilibrium mapping is a powerful approach to detecting quantitative trait loci underlying drought tolerance in maize. Proc Natl Acad Sci U S A 107:19585–19590

    Article  CAS  Google Scholar 

  20. Wu X, Li Y, Shi Y et al (2016) Joint-linkage mapping and GWAS reveal extensive genetic loci that regulate male inflorescence size in maize. Plant Biotechnol J 14:1551–1562

    Article  CAS  Google Scholar 

  21. Daware AV, Srivastava R, Singh AK et al (2017) Regional association analysis of MetaQTLs delineates candidate grain size genes in rice. Front Plant Sci 8:807

    Article  Google Scholar 

  22. Zhang Z, Ersoz E, Lai CQ et al (2010) Mixed linear model approach adapted for genome-wide association studies. Nat Genet 42:355–360

    Article  CAS  Google Scholar 

  23. Pritchard JK (2001) Are rare variants responsible for susceptibility to complex diseases? Am J Hum Genet 69:124–137

    Article  CAS  Google Scholar 

  24. Zöllner S, Pritchard JK (2005) Coalescent-based association mapping and fine mapping of complex trait loci. Genetics 169:1071–1092

    Article  Google Scholar 

  25. Guan Y, Stephens M (2011) Bayesian variable selection regression for genome-wide association studies, and other large-scale problems. Ann Appl Stat 5:1780–1815

    Article  Google Scholar 

Download references

Acknowledgments

The work in lab is supported by grants from DBT and SERB, Government of India.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Swarup K. Parida or Akhilesh K. Tyagi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Daware, A., Parida, S.K., Tyagi, A.K. (2020). Integrated Genomic Strategies for Cereal Genetic Enhancement: Combining QTL and Association Mapping. In: Vaschetto, L. (eds) Cereal Genomics. Methods in Molecular Biology, vol 2072. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9865-4_3

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-9865-4_3

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-4939-9864-7

  • Online ISBN: 978-1-4939-9865-4

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics