Automated Author ProfileKokhmetova, Alma
Institute of Plant Biology and Biotechnology
Kokhmetova, Alma
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.9 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The two recombinant inbred lines (RIL) populations developed by crossing Almaly × Avocet S (206 RILs) and Almaly × Anza (162 RILs) were used to detect the novel genomic regions associated with adult plant resistance (APR) and seedling or all-stage resistance (ASR) to yellow rust (YR) and leaf rust (LR). Both the populations were evaluated for YR APR in two environments (2018 and 2019) and LR APR in three environments (2018, 2019, and 2020) in the Anza population and two environments (2018 and 2019) in the Avocet population; both the populations were phenotyped for one environment during 2020 for LR and YR ASR and genotyped using high throughput DArTseq technology. A set of 51 QTLs including 22 for YR APR, nine for LR APR, nine for YR ASR, and 11 for LR ASR were identified. Also, a set of 13 stable QTLs including nine QTLs (QYR-APR-2A.1, QYR-APR-2A.2, QYR-APR-4D.2, QYR-APR-1B, QYR-APR-2B.1, QYR-APR-2B.2, QYR-APR-3D, QYR-APR-4D.1, and QYR-APR-4D.2) for YR APR and four QTLs (QLR-APR-4A, QLR-APR-2B, QLR-APR-3B, and QLR-APR-5A.2) for LR APR were identified. In silico analysis revealed that the key putative candidate genes such as Cytochrome P450, Protein kinase-like domain superfamily, Zinc-binding ribosomal protein, SANT/Myb domain, WRKY transcription factor, Nucleotide-sugar transporter, and NAC domain superfamily were in the QTL regions and involved in the regulation of host response towards the pathogen infection. The stable QTLs identified in this study are useful for developing rust-resistant varieties through marker-assisted selection (MAS).
Authors
- Rathan, Nagenahalli Dharmegowda ;
- Kokhmetova, Alma ;
- Sehgal, Deepmala ;
- Krishnappa, Gopalareddy