Evidence map›Paper›PMID 24376660›Full record

ArticlePloS one2013

Ecological adaption analysis of the cotton aphid (Aphis gossypii) in different phenotypes by transcriptome comparison.

Zhao-Qun Li, Shuai Zhang, Jun-Yu Luo, Chun-Yi Wang, Li-Min Lv, Shuang-Lin Dong, Jin-Jie Cui

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Zhao-Qun LiState Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China ; Education Ministry Key Laboratory of Integrated Management of Crop Diseases and Pests, College of Plant Protection, Nanjing Agricultural University, Nanjing, China.
Shuai ZhangState Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China.
Jun-Yu LuoState Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China.
Chun-Yi WangState Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China.
Li-Min LvState Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China.
Shuang-Lin DongEducation Ministry Key Laboratory of Integrated Management of Crop Diseases and Pests, College of Plant Protection, Nanjing Agricultural University, Nanjing, China.
Jin-Jie CuiState Key Laboratory of Cotton Biology, Institute of Cotton Research of CAAS, Anyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe cotton aphid, Aphis gossypii Glover, is a destructive insect pest worldwide; it directly or indirectly damages (virus transmission) 300 species of host plants. Knowledge of their ecologically adaptive mechanisms at the molecular level may provide an essential and urgent method to effectively control this pest. However, no transcriptome information is available for the cotton aphid and sequence data are scarce. Therefore, we obtained transcriptome data.

resultsTo facilitate such a study, two cotton aphid transcriptomes at different growth stages of cotton, seedling and summer, were sequenced. A total of 161,396 and 66,668 contigs were obtained and assembled into 83,671 and 42,438 transcripts, respectively. After combining the raw date for both transcriptomes, the sequences were reassembled into 66,695 transcripts, and 52,160 were annotated based on BLASTX analyses. Comparison of the transcriptomes revealed that summer presented less challenges for the cotton aphids than the seedling stage of cotton. In total, 58 putative heat shock protein genes and 66 candidate cytochrome p450 genes were identified with BLASTX.

conclusionsOur results form a basis for exploring the molecular mechanisms of ecological adaption in the cotton aphid. Our study also provides a baseline for the exploration of abiotic stress responses. In addition, it provides large-scale sequence information for further studies on this species.

Indexed as

PhenotypePhylogenyTranscriptomeAdaptation, PhysiologicalAnimalsAphidsCytochrome P-450 Enzyme SystemEcosystemGossypiumHeat-Shock ProteinsInsect ProteinsIsoenzymesMolecular Sequence AnnotationSeedlingsCytochrome P-450 Enzyme SystemHeat-Shock ProteinsInsect ProteinsIsoenzymes

Identifiers

PMID24376660
PMCPMC3871566

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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.