Challenges and opportunities in understanding microbial communities with metagenome assembly (accompanied by IPython Notebook tutorial)
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Since 1905, the Department of Agricultural Engineering, now the Department of Agricultural and Biosystems Engineering (ABE), has been a leader in providing engineering solutions to agricultural problems in the United States and the world. The department’s original mission was to mechanize agriculture. That mission has evolved to encompass a global view of the entire food production system–the wise management of natural resources in the production, processing, storage, handling, and use of food fiber and other biological products.
History
In 1905 Agricultural Engineering was recognized as a subdivision of the Department of Agronomy, and in 1907 it was recognized as a unique department. It was renamed the Department of Agricultural and Biosystems Engineering in 1990. The department merged with the Department of Industrial Education and Technology in 2004.
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1905–present
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- Department of Agricultural Engineering (1907–1990)
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- College of Agriculture and Life Sciences (parent college)
- College of Engineering (parent college)
- Department of Industrial Education and Technology, (merged, 2004)
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Abstract
Metagenomic investigations hold great promise for informing the genetics, physiology, and ecology of environmental microorganisms. Current challenges for metagenomic analysis are related to our ability to connect the dots between sequencing reads, their population of origin, and their encoding functions. Assembly-based methods reduce dataset size by extending overlapping reads into larger contiguous sequences (contigs), providing contextual information for genetic sequences that does not rely on existing references. These methods, however, tend to be computationally intensive and are again challenged by sequencing errors as well as by genomic repeats While numerous tools have been developed based on these methodological concepts, they present confounding choices and training requirements to metagenomic investigators. To help with accessibility to assembly tools, this review also includes an IPython Notebook metagenomic assembly tutorial. This tutorial has instructions for execution any operating system using Amazon Elastic Cloud Compute and guides users through downloading, assembly, and mapping reads to contigs of a mock microbiome metagenome. Despite its challenges, metagenomic analysis has already revealed novel insights into many environments on Earth. As software, training, and data continue to emerge, metagenomic data access and its discoveries will to grow.
Comments
This article was published in Frontiers in Microbiology 6 (2015): 678, doi:10.3389/fmicb.2015.00678. Posted with permission.