| Title |
Identifying genetic diversity of avirulence genes in Leptosphaeria maculans using whole genome sequencing
|
|---|---|
| Published in |
Functional & Integrative Genomics, June 2013
|
| DOI | 10.1007/s10142-013-0324-5 |
| Pubmed ID | |
| Authors |
Manuel Zander, Dhwani A. Patel, Angela Van de Wouw, Kaitao Lai, Michal T. Lorenc, Emma Campbell, Alice Hayward, David Edwards, Harsh Raman, Jacqueline Batley |
| Abstract |
Next generation sequencing technology allows rapid re-sequencing of individuals, as well as the discovery of single nucleotide polymorphisms (SNPs), for genomic diversity and evolutionary analyses. By sequencing two isolates of the fungal plant pathogen Leptosphaeria maculans, the causal agent of blackleg disease in Brassica crops, we have generated a resource of over 76 million sequence reads aligned to the reference genome. We identified over 21,000 SNPs with an overall SNP frequency of one SNP every 2,065 bp. Sequence validation of a selection of these SNPs in additional isolates collected throughout Australia indicates a high degree of polymorphism in the Australian population. In preliminary phylogenetic analysis, isolates from Western Australia clustered together and those collected from Brassica juncea stubble were identical. These SNPs provide a novel marker resource to study the genetic diversity of this pathogen. We demonstrate that re-sequencing provides a method of validating previously characterised SNPs and analysing differences in important genes, such as the disease related avirulence genes of L. maculans. Understanding the genetic characteristics of this devastating pathogen is vital in developing long-term solutions to managing blackleg disease in Brassica crops. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
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 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 3% |
| Australia | 1 | 3% |
| Unknown | 28 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 27% |
| Researcher | 5 | 17% |
| Student > Postgraduate | 4 | 13% |
| Student > Bachelor | 2 | 7% |
| Student > Master | 2 | 7% |
| Other | 5 | 17% |
| Unknown | 4 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 16 | 53% |
| Biochemistry, Genetics and Molecular Biology | 3 | 10% |
| Immunology and Microbiology | 2 | 7% |
| Nursing and Health Professions | 1 | 3% |
| Veterinary Science and Veterinary Medicine | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 6 | 20% |
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 20 September 2013.
All research outputs
#19,015,492
of 23,577,654 outputs
Outputs from Functional & Integrative Genomics
#323
of 554 outputs
Outputs of similar age
#149,555
of 198,557 outputs
Outputs of similar age from Functional & Integrative Genomics
#3
of 4 outputs
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