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Earth's temperature is rising, and with this increase, fungal communities are responding and affecting soil carbon processes. At a long-term soil-warming experiment in a boreal forest in interior Alaska, warming and warming-associated drying alters the function of microbes, and thus, decomposition of carbon. But what genetic mechanisms and resource allocation strategies are behind these community shifts and soil carbon changes? Here, we evaluate fungal resource allocation efforts under long-term experimental warming (including associated drying) using soil metatranscriptomics. We profiled resource allocation efforts toward decomposition and cell metabolic maintenance, and we characterized community composition. We found that under the warming treatment, fungi allocate resources to cell metabolic maintenance at the expense of allocating resources to decomposition. In addition, we found that fungal orders that house taxa with stress-tolerant traits were more abundant under the warmed treatment compared to control conditions. Our results suggest that the warming treatment elicits an ecological tradeoff in resource allocation in the fungal communities, with potential to change ecosystem-scale carbon dynamics. Fungi preferentially invest in mechanisms that will ensure survival under warming and drying, such as cell metabolic maintenance, rather than in decomposition. Through metatranscriptomes, we provide mechanistic insight behind the response of fungi to climate change and consequences to soil carbon processes.
Pubmed ID: 31551941
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Original SAMTOOLS package has been split into three separate repositories including Samtools, BCFtools and HTSlib. Samtools for manipulating next generation sequencing data used for reading, writing, editing, indexing,viewing nucleotide alignments in SAM,BAM,CRAM format. BCFtools used for reading, writing BCF2,VCF, gVCF files and calling, filtering, summarising SNP and short indel sequence variants. HTSlib used for reading, writing high throughput sequencing data.
View all literature mentionsBioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.
View all literature mentionsSoftware for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data.
View all literature mentionsQuality control software that perform checks on raw sequence data coming from high throughput sequencing pipelines. This software also provides a modular set of analyses which can give a quick impression of the quality of the data prior to further analysis.
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