Evidence map›Paper›PMID 24988207›Full record

ArticlePloS one2014

Transcriptome analysis reveals signature of adaptation to landscape fragmentation.

Panu Somervuo, Jouni Kvist, Suvi Ikonen, Petri Auvinen, Lars Paulin, Patrik Koskinen, Liisa Holm, Minna Taipale, Anne Duplouy, Annukka Ruokolainen and 7 more

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. The physiology of movement.Movement ecology · 2020
    Review
  3. Article
  4. Article
  5. Predictable allele frequency changes due to habitat fragmentation in the Glanville fritillary butterfly.Proceedings of the National Academy of Sciences of the United States of America · 2016
    Article
  6. Article
  7. Article
4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

17 authors.

Panu SomervuoDepartment of Biosciences, University of Helsinki, Helsinki, Finland; Institute of Biotechnology, Genome Biology Program, University of Helsinki, Helsinki, Finland.
Jouni KvistDepartment of Biosciences, University of Helsinki, Helsinki, Finland; Institute of Biotechnology, Genome Biology Program, University of Helsinki, Helsinki, Finland.
Suvi IkonenLammi Biological Station, University of Helsinki, Lammi, Finland.
Petri AuvinenInstitute of Biotechnology, Genome Biology Program, University of Helsinki, Helsinki, Finland.
Lars PaulinInstitute of Biotechnology, Genome Biology Program, University of Helsinki, Helsinki, Finland.
Patrik KoskinenDepartment of Biosciences, University of Helsinki, Helsinki, Finland.
Liisa HolmDepartment of Biosciences, University of Helsinki, Helsinki, Finland; Institute of Biotechnology, Genome Biology Program, University of Helsinki, Helsinki, Finland.
Minna TaipaleScience for Life Laboratory, Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden and Genome-Scale Biology Research Program & Institute of Biomedicine, University of Helsinki, Helsinki, Finland.
Anne DuplouyDepartment of Biosciences, University of Helsinki, Helsinki, Finland.
Annukka RuokolainenDepartment of Biosciences, University of Helsinki, Helsinki, Finland.
Suvi SaarnioDepartment of Biosciences, University of Helsinki, Helsinki, Finland.
Jukka SirénDepartment of Biosciences, University of Helsinki, Helsinki, Finland; Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland.
Jukka KohonenDepartment of Mathematics and Statistics, University of Helsinki, Helsinki, Finland.
Jukka CoranderDepartment of Mathematics and Statistics, University of Helsinki, Helsinki, Finland.
Mikko J FrilanderInstitute of Biotechnology, Genome Biology Program, University of Helsinki, Helsinki, Finland.
Virpi AholaDepartment of Biosciences, University of Helsinki, Helsinki, Finland.
Ilkka HanskiDepartment of Biosciences, University of Helsinki, Helsinki, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We characterize allelic and gene expression variation between populations of the Glanville fritillary butterfly (Melitaea cinxia) from two fragmented and two continuous landscapes in northern Europe. The populations exhibit significant differences in their life history traits, e.g. butterflies from fragmented landscapes have higher flight metabolic rate and dispersal rate in the field, and higher larval growth rate, than butterflies from continuous landscapes. In fragmented landscapes, local populations are small and have a high risk of local extinction, and hence the long-term persistence at the landscape level is based on frequent re-colonization of vacant habitat patches, which is predicted to select for increased dispersal rate. Using RNA-seq data and a common garden experiment, we found that a large number of genes (1,841) were differentially expressed between the landscape types. Hexamerin genes, the expression of which has previously been shown to have high heritability and which correlate strongly with larval development time in the Glanville fritillary, had higher expression in fragmented than continuous landscapes. Genes that were more highly expressed in butterflies from newly-established than old local populations within a fragmented landscape were also more highly expressed, at the landscape level, in fragmented than continuous landscapes. This result suggests that recurrent extinctions and re-colonizations in fragmented landscapes select a for specific expression profile. Genes that were significantly up-regulated following an experimental flight treatment had higher basal expression in fragmented landscapes, indicating that these butterflies are genetically primed for frequent flight. Active flight causes oxidative stress, but butterflies from fragmented landscapes were more tolerant of hypoxia. We conclude that differences in gene expression between the landscape types reflect genomic adaptations to landscape fragmentation.

Indexed as

Adaptation, PhysiologicalGene Expression ProfilingAnimalsButterfliesCarrier ProteinsCluster AnalysisEcosystemGene ExpressionGene FrequencyGenetic VariationGenomeInsect ProteinsPolymorphism, Single NucleotideUp-Regulationarylphorin-binding proteins, insectCarrier ProteinsInsect Proteins

Identifiers

PMID24988207
PMCPMC4079591

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.