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Genomic adaptation to agricultural environments: cabbage white butterflies (Pieris rapae) as a case study

Overview of attention for article published in BMC Genomics, May 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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Title
Genomic adaptation to agricultural environments: cabbage white butterflies (Pieris rapae) as a case study
Published in
BMC Genomics, May 2017
DOI 10.1186/s12864-017-3787-2
Pubmed ID
Authors

Kristin L. Sikkink, Megan E. Kobiela, Emilie C. Snell-Rood

Abstract

Agricultural environments have long presented an opportunity to study evolution in action, and genomic approaches are opening doors for testing hypotheses about adaptation to crops, pesticides, and fertilizers. Here, we begin to develop the cabbage white butterfly (Pieris rapae) as a system to test questions about adaptation to novel, agricultural environments. We focus on a population in the north central United States as a unique case study: here, canola, a host plant, has been grown during the entire flight period of the butterfly over the last three decades. First, we show that the agricultural population has diverged phenotypically relative to a nonagricultural population: when reared on a host plant distantly related to canola, the agricultural population is smaller and more likely to go into diapause than the nonagricultural population. Second, drawing from deep sequencing runs from six individuals from the agricultural population, we assembled the gut transcriptome of this population. Then, we sequenced RNA transcripts from the midguts of 96 individuals from this canola agricultural population and the nonagricultural population in order to describe patterns of genomic divergence between the two. While population divergence is low, 235 genes show evidence of significant differentiation between populations. These genes are significantly enriched for cofactor and small molecule metabolic processes, and many genes also have transporter or catalytic activity. Analyses of population structure suggest the agricultural population contains a subset of the genetic variation in the nonagricultural population. Taken together, our results suggest that adaptation of cabbage whites to an agricultural environment occurred at least in part through selection on standing genetic variation. Both the phenotypic and genetic data are consistent with the idea that this pest has adapted to an abundant and predictable agricultural resource through a narrowing of niche breadth and loss of genetic variants rather than de novo gain of adaptive alleles. The present research develops genomic resources to pave the way for future studies using cabbage whites as a model contributing to our understanding of adaptation to agricultural environments.

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The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 2%
Unknown 44 98%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 8 18%
Student > Ph. D. Student 6 13%
Student > Master 5 11%
Researcher 4 9%
Student > Postgraduate 3 7%
Other 7 16%
Unknown 12 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 40%
Biochemistry, Genetics and Molecular Biology 6 13%
Environmental Science 2 4%
Mathematics 1 2%
Psychology 1 2%
Other 2 4%
Unknown 15 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 23 January 2018.
All research outputs
#4,614,525
of 23,605,418 outputs
Outputs from BMC Genomics
#1,849
of 10,773 outputs
Outputs of similar age
#78,919
of 314,265 outputs
Outputs of similar age from BMC Genomics
#51
of 220 outputs
Altmetric has tracked 23,605,418 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,773 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 82% 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 314,265 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 220 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.