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De novo assembly, functional annotation, and analysis of the giant reed (Arundo donax L.) leaf transcriptome provide tools for the development of a biofuel feedstock

Overview of attention for article published in Biotechnology for Biofuels, May 2017
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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 (72nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

Mentioned by

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6 tweeters

Citations

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30 Dimensions

Readers on

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58 Mendeley
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Title
De novo assembly, functional annotation, and analysis of the giant reed (Arundo donax L.) leaf transcriptome provide tools for the development of a biofuel feedstock
Published in
Biotechnology for Biofuels, May 2017
DOI 10.1186/s13068-017-0828-7
Pubmed ID
Authors

Chiara Evangelistella, Alessio Valentini, Riccardo Ludovisi, Andrea Firrincieli, Francesco Fabbrini, Simone Scalabrin, Federica Cattonaro, Michele Morgante, Giuseppe Scarascia Mugnozza, Joost J. B. Keurentjes, Antoine Harfouche

Abstract

Arundo donax has attracted renewed interest as a potential candidate energy crop for use in biomass-to-liquid fuel conversion processes and biorefineries. This is due to its high productivity, adaptability to marginal land conditions, and suitability for biofuel and biomaterial production. Despite its importance, the genomic resources currently available for supporting the improvement of this species are still limited. We used RNA sequencing (RNA-Seq) to de novo assemble and characterize the A. donax leaf transcriptome. The sequencing generated 1249 million clean reads that were assembled using single-k-mer and multi-k-mer approaches into 62,596 unique sequences (unitranscripts) with an N50 of 1134 bp. TransDecoder and Trinotate software suites were used to obtain putative coding sequences and annotate them by mapping to UniProtKB/Swiss-Prot and UniRef90 databases, searching for known transcripts, proteins, protein domains, and signal peptides. Furthermore, the unitranscripts were annotated by mapping them to the NCBI non-redundant, GO and KEGG pathway databases using Blast2GO. The transcriptome was also characterized by BLAST searches to investigate homologous transcripts of key genes involved in important metabolic pathways, such as lignin, cellulose, purine, and thiamine biosynthesis and carbon fixation. Moreover, a set of homologous transcripts of key genes involved in stomatal development and of genes coding for stress-associated proteins (SAPs) were identified. Additionally, 8364 simple sequence repeat (SSR) markers were identified and surveyed. SSRs appeared more abundant in non-coding regions (63.18%) than in coding regions (36.82%). This SSR dataset represents the first marker catalogue of A. donax. 53 SSRs (PolySSRs) were then predicted to be polymorphic between ecotype-specific assemblies, suggesting genetic variability in the studied ecotypes. This study provides the first publicly available leaf transcriptome for the A. donax bioenergy crop. The functional annotation and characterization of the transcriptome will be highly useful for providing insight into the molecular mechanisms underlying its extreme adaptability. The identification of homologous transcripts involved in key metabolic pathways offers a platform for directing future efforts in genetic improvement of this species. Finally, the identified SSRs will facilitate the harnessing of untapped genetic diversity. This transcriptome should be of value to ongoing functional genomics and genetic studies in this crop of paramount economic importance.

Twitter Demographics

The data shown below were collected from the profiles of 6 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 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 58 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 28%
Researcher 10 17%
Student > Master 8 14%
Student > Bachelor 6 10%
Other 2 3%
Other 6 10%
Unknown 10 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 34%
Biochemistry, Genetics and Molecular Biology 14 24%
Engineering 4 7%
Computer Science 3 5%
Neuroscience 1 2%
Other 1 2%
Unknown 15 26%

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 02 June 2017.
All research outputs
#3,939,339
of 16,120,171 outputs
Outputs from Biotechnology for Biofuels
#286
of 1,189 outputs
Outputs of similar age
#75,346
of 273,029 outputs
Outputs of similar age from Biotechnology for Biofuels
#3
of 7 outputs
Altmetric has tracked 16,120,171 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,189 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done well, scoring higher than 75% 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 273,029 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 72% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.