Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1114932 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR29183073_1.fastq.gz | Fastqsanger.gz | |||
| SRR29183073_2.fastq.gz | Fastqsanger.gz | |||
| SRR29183074_1.fastq.gz | Fastqsanger.gz | |||
| SRR29183074_2.fastq.gz | Fastqsanger.gz | |||
| SRR29183075_1.fastq.gz | Fastqsanger.gz |
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Project description:Microarrays have become established tools for describing microbial systems, however the assessment of expression profiles for environmental microbial communities still presents unique challenges. Notably, the concentration of particular transcripts are likely very dilute relative to the pool of total RNA, and PCR-based amplification strategies are vulnerable to amplification biases and the appropriate primer selection. Thus, we apply a signal amplification approach, rather than template amplification, to analyze the expression of selected lignin-degrading enzymes in soil. Controls in the form of known amplicons and cDNA from Phanerochaete chrysosporium were included and mixed with the soil cDNA both before and after the signal amplification in order to assess the dynamic range of the microarray. We demonstrate that restored prairie soil expresses a diverse range of lignin-degrading enzymes following incubation with lignin substrate, while farmed agricultural soil does not. The mixed additions of control cDNA with soil cDNA indicate that the mixed biomass in the soil does interfere with low abundance transcript changes, nevertheless our microarray approach consistently reports the most robust signals. Keywords: comparative analysis, microbial ecology, soil microbial communities
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