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Whole transcriptome analysis of Penicillium digitatum strains treatmented with prochloraz reveals their drug-resistant mechanisms

Overview of attention for article published in BMC Genomics, October 2015
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  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

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Title
Whole transcriptome analysis of Penicillium digitatum strains treatmented with prochloraz reveals their drug-resistant mechanisms
Published in
BMC Genomics, October 2015
DOI 10.1186/s12864-015-2043-x
Pubmed ID
Authors

Jing Liu, Shengqiang Wang, Tingting Qin, Na Li, Yuhui Niu, Dandan Li, Yongze Yuan, Hui Geng, Li Xiong, Deli Liu

Abstract

Penicillium digitatum is one of the most destructive postharvest pathogen of citrus fruits, causing fruit decay and economic loss. The emergence of fungicide-resistant strains made the control of P. digitatum more difficult. While the genome of P. digitatum is available, there has been few reports about its resistant mechanism from the transcriptome perspective and there has been no large-scale functional annotation of the genome using expressed genes derived from transcriptomes. Total RNA of P. digitatum strain HS-F6 (prochloraz-resistant strain) and HS-E3 (prochloraz-susceptible strain) before and after prochloraz-treatment were extracted and sequenced on an Illumina Hiseq 2000 platform. The transcriptome data of four samples were compared and analyzed using differential expression analysis, novel transcripts prediction and alternative splicing analysis, SNP analysis and quantitative real-time PCR. We present a large scale analysis about the transcriptome data of P. digitatum. The whole RNA was extracted from a prochloraz-resistant strain (HS-F6) and a prochloraz-susceptible strain (HS-E3) before and after prochloraz-treatment and sequenced by Illumina technology. A total of more than 100 million reads were generated and de novo assembled into 9760 transcripts that contained annotated genes after quality control and sequence assembling. 6625 single nucleotide variations (SNVs) were identified from the sequences aligned against the reference genome. Gene expression profiling analysis was performed upon prochloraz treatment in HS-F6 and HS-E3, and differential expression analysis was used to identify genes related to prochloraz-response and drug-resistance: there are 224 differentially expressed genes in HS-E3 and 1100 differentially expressed genes in HS-F6 after prochloraz-treatment. Moreover, gene expression profile in prochloraz-resistant strain HS-F6 is quite different from that in HS-E3 before prochloraz-treatment, 1520 differential expression genes were identified between the two strains. Gene ontology (GO) term enrichment and KEGG enrichment were then performed to classify the differential expression genes. Among these genes, there are a lot of transporter encoding genes including 14 MFS (Major Facilitator Superfamily) transporters, 8 ABC (ATP-binding cassette transporter) and 3 MATE (multidrug and toxic compound extrusion family) transporters. Meanwhile, the roles of typical MFS, ABC and MATE proteins in prochloraz resistance were investigated using real-time quantitative PCR. The sequencing-based transcriptome data of P. digitatum demonstrate differences between prochloraz-resistant and prochloraz-susceptible strains with prochloraz-treatment. The differences existed in expressed transcripts, splice isoforms and GO categories, which would contribute to our knowledge on the molecular mechanisms involved in drug resistance of P. digitatum.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 21%
Student > Ph. D. Student 7 16%
Student > Master 7 16%
Student > Bachelor 4 9%
Professor 2 5%
Other 5 12%
Unknown 9 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 47%
Biochemistry, Genetics and Molecular Biology 6 14%
Medicine and Dentistry 2 5%
Business, Management and Accounting 1 2%
Economics, Econometrics and Finance 1 2%
Other 3 7%
Unknown 10 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 01 July 2016.
All research outputs
#13,140,583
of 23,498,099 outputs
Outputs from BMC Genomics
#4,523
of 10,787 outputs
Outputs of similar age
#125,939
of 285,301 outputs
Outputs of similar age from BMC Genomics
#140
of 354 outputs
Altmetric has tracked 23,498,099 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,787 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 57% 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 285,301 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 55% of its contemporaries.
We're also able to compare this research output to 354 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.