2016
DOI: 10.1104/pp.16.00090
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Comparative Transcriptomic Approaches Exploring Contamination Stress Tolerance in Salix sp. Reveal the Importance for a Metaorganismal de Novo Assembly Approach for Nonmodel Plants

Abstract: Metatranscriptomic study of nonmodel organisms requires strategies that retain the highly resolved genetic information generated from model organisms while allowing for identification of the unexpected. A real-world biological application of phytoremediation, the field growth of 10 Salix cultivars on polluted soils, was used as an exemplar nonmodel and multifaceted crop response well-disposed to the study of gene expression. Sequence reads were assembled de novo to create 10 independent transcriptomes, a globa… Show more

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Cited by 19 publications
(24 citation statements)
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References 156 publications
(169 reference statements)
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“…ANCHOR is designed with utility for nonideal, uncharacterised biology in mind and, in particular, to provide flexibility to complex data sets and complement high uncertainty metatranscriptomics (Gonzalez et al ., ; Brereton et al ., ; Gonzalez et al ., ). While benchmarking against synthetic or simple (mock) communities is essential, an equally important test of the technology is its utility to contribute to unknown biology in complex real‐world systems.…”
Section: Resultsmentioning
confidence: 99%
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“…ANCHOR is designed with utility for nonideal, uncharacterised biology in mind and, in particular, to provide flexibility to complex data sets and complement high uncertainty metatranscriptomics (Gonzalez et al ., ; Brereton et al ., ; Gonzalez et al ., ). While benchmarking against synthetic or simple (mock) communities is essential, an equally important test of the technology is its utility to contribute to unknown biology in complex real‐world systems.…”
Section: Resultsmentioning
confidence: 99%
“…Default recommended annotation uses four sequence repositories with strict BLASTn criteria (>99% identity and coverage) providing each amplicon with up to four pools of labels from: NCBI‐curated bacterial and Archaea RefSeq, NCBI nr/nt, SILVA and Ribosomal Database Project (RDP). Annotation selection against the four databases is based on de novo metatranscriptomics strategy (Brereton et al ., ; Gonzalez et al ., ), where all potential annotation is retained to allow for informed annotation selection and downstream interpretation. BLASTn returns with a query identity and coverage <99% are discarded and the highest identity/coverage scores are selected per query.…”
Section: Methodsmentioning
confidence: 99%
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“…E values < 10 −4 (protein blast) and < 10 −6 (nucleotide blast) were used as cutoffs. A previously reported method for selecting annotation (based on the percentage of maximum potential bitscore) from blastx returns was used to help select the primary annotation given multiple high scoring alignments for a single sequence, all statistically characterised as non-random [ 2 ]. BLAST hits that were not selected but have a high comparable percentage of maximum potential bitscore (within 10%) were retained for each contig as (alternative) secondary annotation.…”
Section: Methodsmentioning
confidence: 99%
“…The observation of gene expression across multiple interacting organisms has the potential to better reflect the complex reality of biology than the observation of organisms in isolation [ 1 ]. By separating the assembly of RNA sequence data from annotation (identification) of assembled contigs, de novo metatranscriptome assembly allows for such observation without a prerequisite for, and therefore bias from, reference genome sequences from organisms expected to be present within any biological system [ 2 , 3 ]. A metatranscriptomic approach designed without constraint to any a priori defined organism, but open to annotation from any sequenced strata of life, should be powerful in biological systems already recognised as highly complex, such as the human digestive tract or rhizosphere microbiome (although such microbiome complexity could arguably be defined by the current extent of study in a biological field).…”
Section: Introductionmentioning
confidence: 99%