| Title |
Reference gene validation for normalization of RT-qPCR assay associated with germination and survival of rice under hypoxic condition
|
|---|---|
| Published in |
Journal of Applied Genetics, September 2018
|
| DOI | 10.1007/s13353-018-0466-1 |
| Pubmed ID | |
| Authors |
Dhananjay Kumar, Prasanta Kumar Das, Bidyut Kumar Sarmah |
| Abstract |
Study on expression of genes for the traits associated with hypoxia tolerance during the germination demands robust choice of reference genes for transcript data normalization and gene validation through real-time quantitative polymerase chain reaction (RT-qPCR). However, reliability and stability of reference genes across different rice germplasms under hypoxic condition have not been accessed yet. Stability performance of reference genes such as eukaryotic elongation factor 1 α (eEF1α), ubiquitin 10 (UBQ10), glyceraldehyde 3-phosphate dehydrogenase (GAPDH), 18S ribosomal RNA (18SrRNA), 25S ribosomal RNA (25SrRNA), β-tublin (β-TUB), actin11 (ACT11), ubiquitin C (UBC), eukaryotic elongation factor 4 α (eIF4α), and ubiquitin5 (UBQ5) was accessed through statistical algorithms like geNorm, NormFinder, Comparative ΔCt method, BestKeeper, and RefFinder in three rice germplasms (KHO, RKB, and IR-64) with varied level of tolerance to hypoxic condition during germination. Among all genes used, OsGAPDH was found to be the most suitable reference gene under hypoxic condition. The performance of the highest-ranking reference gene (OsGAPDH) in terms of stability based on statistical algorithms was further validated for its reliability and stability through RT-qPCR with hypoxia-induced target gene OsTTP7. The identified stable housekeeping gene could be used as internal control for gene expression analysis in rice under hypoxia. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 14% |
| Researcher | 4 | 14% |
| Student > Bachelor | 4 | 14% |
| Student > Master | 3 | 11% |
| Unspecified | 1 | 4% |
| Other | 2 | 7% |
| Unknown | 10 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 21% |
| Biochemistry, Genetics and Molecular Biology | 5 | 18% |
| Nursing and Health Professions | 1 | 4% |
| Unspecified | 1 | 4% |
| Computer Science | 1 | 4% |
| Other | 3 | 11% |
| Unknown | 11 | 39% |
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 21 September 2018.
All research outputs
#15,545,785
of 23,103,903 outputs
Outputs from Journal of Applied Genetics
#182
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Outputs of similar age
#215,938
of 342,063 outputs
Outputs of similar age from Journal of Applied Genetics
#2
of 12 outputs
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