Abstract
Rice is the most salt-sensitive cereal, suffering yield losses above 50% with soil salinity of 6 dS/m. Thus, understanding the mechanisms of rice salinity tolerance is key to address food security. In this chapter, we provide guidelines to assess rice salinity tolerance using a high-throughput phenotyping platform (HTP) with digital imaging at seedling/early tillering stage and suggest improved analysis methods using stress indices. The protocols described here also include computer scripts for users to improve their experimental design, run genome-wide association studies (GWAS), perform multi-testing corrections, and obtain the Manhattan plots, enabling the identification of loci associated with salinity tolerance. Notably, the computer scripts provided here can be used for any stress or GWAS experiment and independently of HTP.
Original language | English (US) |
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Title of host publication | Methods in Molecular Biology |
Publisher | Humana Press Inc. |
Pages | 339-375 |
Number of pages | 37 |
DOIs | |
State | Published - 2021 |
Publication series
Name | Methods in Molecular Biology |
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Volume | 2238 |
ISSN (Print) | 1064-3745 |
ISSN (Electronic) | 1940-6029 |
Bibliographical note
Funding Information:Financial support from King Abdullah University of Science and Technology (KAUST) is gratefully acknowledged. Sónia Negrão thanks the financial support of University College Dublin (UCD) and UCD School of Biology and Environmental Science.
Publisher Copyright:
© 2021, Springer Science+Business Media, LLC, part of Springer Nature.
Keywords
- Association mapping
- Forward genetics
- GWAS
- High-throughput phenotyping
- Plant imaging
- Rice
- Salinity
- Statistical genetics
ASJC Scopus subject areas
- Molecular Biology
- Genetics