| Title |
Investigating successive Australian barley breeding populations for stable resistance to leaf rust
|
|---|---|
| Published in |
Theoretical and Applied Genetics, August 2017
|
| DOI | 10.1007/s00122-017-2970-9 |
| Pubmed ID | |
| Authors |
L. A. Ziems, J. D. Franckowiak, G. J. Platz, E. S. Mace, R. F. Park, D. Singh, D. R. Jordan, L. T. Hickey |
| Abstract |
Genome-wide association studies of barley breeding populations identified candidate minor genes for pairing with the adult plant resistance gene Rph20 to provide stable leaf rust resistance across environments. Stable resistance to barley leaf rust (BLR, caused by Puccinia hordei) was evaluated across environments in barley breeding populations (BPs). To identify genomic regions that can be combined with Rph20 to improve adult plant resistance (APR), two BPs genotyped with the Diversity Arrays Technology genotyping-by-sequencing platform (DArT-seq) were examined for reaction to BLR at both seedling and adult growth stages in Australian environments. An integrated consensus map comprising both first- and second-generation DArT platforms was used to integrate QTL information across two additional BPs, providing a total of four interrelated BPs and 15 phenotypic data sets. This enabled identification of key loci underpinning BLR resistance. The APR gene Rph20 was the only active resistance region consistently detected across BPs. Of the QTL identified, RphQ27 on chromosome 6HL was considered the best candidate for pairing with Rph20. RphQ27 did not align or share proximity with known genes and was detected in three of the four BPs. The combination of RphQ27 and Rph20 was of low frequency in the breeding material; however, strong resistance responses were observed for the lines carrying this pairing. This suggests that the candidate minor gene RphQ27 can interact additively with Rph20 to provide stable resistance to BLR across diverse environments. |
X Demographics
The data shown below were collected from the profiles of 38 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 10 | 26% |
| United States | 6 | 16% |
| United Kingdom | 2 | 5% |
| Germany | 2 | 5% |
| India | 1 | 3% |
| Italy | 1 | 3% |
| Canada | 1 | 3% |
| Pakistan | 1 | 3% |
| Switzerland | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 12 | 32% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 23 | 61% |
| Scientists | 13 | 34% |
| Science communicators (journalists, bloggers, editors) | 2 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 25% |
| Professor | 2 | 17% |
| Other | 1 | 8% |
| Student > Master | 1 | 8% |
| Unknown | 5 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 50% |
| Biochemistry, Genetics and Molecular Biology | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Unknown | 4 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 23. 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 12 December 2019.
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#1,482,605
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Outputs from Theoretical and Applied Genetics
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Outputs of similar age from Theoretical and Applied Genetics
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