↓ Skip to main content

Identification of QTLs for yield and agronomic traits in rice under stagnant flooding conditions

Overview of attention for article published in Rice, April 2017
Altmetric Badge

Citations

dimensions_citation
37 Dimensions

Readers on

mendeley
47 Mendeley
Title
Identification of QTLs for yield and agronomic traits in rice under stagnant flooding conditions
Published in
Rice, April 2017
DOI 10.1186/s12284-017-0154-5
Pubmed ID
Authors

Anshuman Singh, Jerome Carandang, Zennia Jean C. Gonzaga, Bertrand C. Y. Collard, Abdelbagi M. Ismail, Endang M. Septiningsih

Abstract

Stagnant flooding, where water of 25-50 cm remains until harvest time, is a major problem in rainfed lowland areas. Most of the Sub1 varieties, which can withstand around 2 weeks of complete submergence, perform poorly in these conditions. Hence, varieties tolerant of stagnant flooding are essential. This paper presents the first study to map QTLs associated with tolerance to stagnant flooding, along with a parallel study under normal irrigation, using an F7 mapping population consisting of 148 RILs derived from a cross of Ciherang-Sub1 and the stagnant-flooding tolerant line IR10F365. Phenotypic data was collected for 15 key traits under both environments. Additionally, survival rate was measured under stress conditions. Genotyping was performed using the Illumina Infinium genotyping platform with a 6 K SNP chip, resulting in 469 polymorphic SNPs. Under stress and irrigated conditions, 38 and 46 QTLs were identified, respectively. Clusters of QTLs were detected in both stress and normal conditions, especially on chromosomes 3 and 5. Unique and common QTLs were identified and their physiological consequences are discussed. These beneficial QTLs can be used as targets for molecular breeding and can be further investigated to understand the underlying molecular mechanisms involved in stagnant flooding tolerance in rice.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 21%
Researcher 9 19%
Student > Master 5 11%
Student > Doctoral Student 3 6%
Student > Postgraduate 3 6%
Other 6 13%
Unknown 11 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 60%
Biochemistry, Genetics and Molecular Biology 4 9%
Environmental Science 1 2%
Nursing and Health Professions 1 2%
Arts and Humanities 1 2%
Other 0 0%
Unknown 12 26%