↓ Skip to main content

Comparative transcriptomics and proteomics of three different aphid species identifies core and diverse effector sets

Overview of attention for article published in BMC Genomics, March 2016
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

twitter
9 tweeters

Citations

dimensions_citation
60 Dimensions

Readers on

mendeley
77 Mendeley
citeulike
2 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Comparative transcriptomics and proteomics of three different aphid species identifies core and diverse effector sets
Published in
BMC Genomics, March 2016
DOI 10.1186/s12864-016-2496-6
Pubmed ID
Authors

Peter Thorpe, Peter J. A. Cock, Jorunn Bos

Abstract

Aphids are phloem-feeding insects that cause significant economic losses to agriculture worldwide. While feeding and probing these insects deliver molecules, called effectors, inside their host to enable infestation. The identification and characterization of these effectors from different species that vary in their host range is an important step in understanding the infestation success of aphids and aphid host range variation. This study employs a multi-disciplinary approach based on transcriptome sequencing and proteomics to identify and compare effector candidates from the broad host range aphid Myzus persicae (green peach aphid) (genotypes O, J and F), and narrow host range aphids Myzus cerasi (black cherry aphid) and Rhopalosiphum padi (bird-cherry oat aphid). Using a combination of aphid transcriptome sequencing on libraries derived from head versus body tissues as well as saliva proteomics we were able to predict candidate effectors repertoires from the different aphid species and genotypes. Among the identified conserved or core effector sets, we identified a significant number of previously identified aphid candidate effectors indicating these proteins may be involved in general infestation strategies. Moreover, we identified aphid candidate effector sequences that were specific to one species, which are interesting candidates for further validation and characterization with regards to species-specific functions during infestation. We assessed our candidate effector repertoires for evidence of positive selection, and identified 49 candidates with DN/DS ratios >1. We noted higher rates of DN/DS ratios in predicted aphid effectors than non-effectors. Whether this reflects positive selection due to co-evolution with host plants, or increased neofunctionalization upon gene duplication remains to be investigated. Our work provides a comprehensive overview of the candidate effector repertoires from three different aphid species with varying host ranges. Comparative analyses revealed candidate effectors that are most likely are involved in general aspects of infestation, whereas others, that are highly divergent, may be involved in specific processes important for certain aphid species. Insights into the overlap and differences in aphid effector repertoires are important in understanding how different species successfully infest different ranges of plant species.

Twitter Demographics

The data shown below were collected from the profiles of 9 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 1%
Poland 1 1%
Canada 1 1%
Unknown 74 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 23%
Student > Master 16 21%
Researcher 13 17%
Student > Bachelor 6 8%
Student > Postgraduate 4 5%
Other 11 14%
Unknown 9 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 50 65%
Biochemistry, Genetics and Molecular Biology 11 14%
Business, Management and Accounting 1 1%
Environmental Science 1 1%
Unknown 14 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 16 June 2016.
All research outputs
#1,340,897
of 7,907,411 outputs
Outputs from BMC Genomics
#928
of 5,672 outputs
Outputs of similar age
#64,707
of 285,319 outputs
Outputs of similar age from BMC Genomics
#44
of 217 outputs
Altmetric has tracked 7,907,411 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,672 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done well, scoring higher than 83% of its peers.
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 285,319 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 217 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.