↓ Skip to main content

High Resolution Mapping of QTLs for Heat Tolerance in Rice Using a 5K SNP Array

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

Mentioned by

twitter
2 X users

Citations

dimensions_citation
96 Dimensions

Readers on

mendeley
102 Mendeley
Title
High Resolution Mapping of QTLs for Heat Tolerance in Rice Using a 5K SNP Array
Published in
Rice, June 2017
DOI 10.1186/s12284-017-0167-0
Pubmed ID
Authors

Shanmugavadivel PS, Amitha Mithra SV, Chandra Prakash, Ramkumar MK, Ratan Tiwari, Trilochan Mohapatra, Nagendra Kumar Singh

Abstract

Heat stress is one of the major abiotic threats to rice production, next to drought and salinity stress. Incidence of heat stress at reproductive phase of the crop results in abnormal pollination leading to floret sterility, low seed set and poor grain quality. Identification of QTLs and causal genes for heat stress tolerance at flowering will facilitate breeding for improved heat tolerance in rice. In the present study, we used 272 F8 recombinant inbred lines derived from a cross between Nagina22, a well-known heat tolerant Aus cultivar and IR64, a heat sensitive popular Indica rice variety to map the QTLs for heat tolerance. To enable precise phenotyping for heat stress tolerance, we used a controlled phenotyping facility available at ICAR-Indian Institute of Wheat and Barley Research, Karnal, India. Based on 'days to 50% flowering' data of the RILs, we followed staggered sowing to synchronize flowering to impose heat stress at uniform stage. Using the Illumina infinium 5K SNP array for genotyping the parents and the RILs, and stress susceptibility and stress tolerance indices (SSI and STI) of percent spikelet sterility and yield per plant (g), we identified five QTLs on chromosomes 3, 5, 9 and 12. The identified QTLs explained phenotypic variation in the range of 6.27 to 21. 29%. Of these five QTLs, two high effect QTLs, one novel (qSTIPSS9.1) and one known (qSTIY5.1/qSSIY5.2), were mapped in less than 400 Kbp genomic regions, comprising of 65 and 54 genes, respectively. The present study identified two major QTLs for heat tolerance in rice in narrow physical intervals, which can be employed for crop improvement by marker assisted selection (MAS) after development of suitable scorable markers for breeding of high yielding heat tolerant rice varieties. This is the first report of a major QTL for heat tolerance on chromosome 9 of rice. Further, a known QTL for heat tolerance on chromosome 5 was narrowed down from 23 Mb to 331 Kbp in this study.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 102 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 20%
Researcher 18 18%
Student > Master 11 11%
Student > Bachelor 7 7%
Student > Doctoral Student 5 5%
Other 10 10%
Unknown 31 30%
Readers by discipline Count As %
Agricultural and Biological Sciences 53 52%
Biochemistry, Genetics and Molecular Biology 5 5%
Arts and Humanities 2 2%
Medicine and Dentistry 2 2%
Nursing and Health Professions 1 <1%
Other 4 4%
Unknown 35 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 June 2017.
All research outputs
#18,554,389
of 22,979,862 outputs
Outputs from Rice
#251
of 388 outputs
Outputs of similar age
#241,900
of 317,195 outputs
Outputs of similar age from Rice
#9
of 15 outputs
Altmetric has tracked 22,979,862 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 388 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 317,195 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.