Ecosystems can be compared based on their metagenomes. Highly biodiverse ecosystems are responsible for important development like drug discovery,food production and buffering climate change. Metagenomics experiments are generating enormous data.
Using next generation sequencing, the massive number of DNA fragments extracted from the water sample can be stitched together to produce an intact metagenome..
Using next generation sequencing, the massive number of DNA fragments extracted from the water sample can be stitched together to produce an intact metagenome..
Yes this is quite a good area and the most advanced we can say for analyzing microbial communities, phylogenetic analyis etc. Owing to certain disadvantages of the classical approaches for identifying microbes, several methods like DNA-DNA hybridization, 16S rRNA gene sequencing, PCR based methods, immunological techniques have been attracting to unravel the microbial communities in several eco-diversified systems. The use of genomic, proteomic, metagenomic and bioinformatic approaches are the current area of research.
There is an online resource in monitoring metagenome projects worldwide named Genome online Database(GOLD)(http://www.genomesonline.org/).As of september 2011,GOLD contains information of 340 metagenome projects associated with 1927 metagenomics samples.The year 2011 is an important landmark in the history of genome sequencing project with registration and tracking of 10k genome projects
Integrated analysis of metagenomes, metatranscriptomes, metaproteomes and meta-metabolomes will be needed to understand the microbial systems biology.. Achieving such integration necessitates interdisciplinary efforts and continuous development of appropriate bioinformatics tools to decipher the complex biological networks underlying molecular, functional and community structure. The in silico investigation of biological networks could be quite effective in identifying central connected components that could bring, at a later time, more insight on their functionality and dynamics within the system