is that this technique does not require cloning the DNA before sequencing, removing one of the main biases and bottlenecks in environmental sampling. The first metagenomic studies conducted using high-throughput sequencing used massively parallel 454 pyrosequencing. Three other technologies commonly applied to environmental sampling are the Ion Torrent Personal Genome Machine, the Illumina MiSeq or HiSeq and the Applied Biosystems SOLiD system. These techniques for sequencing DNA generate shorter fragments than Sanger sequencing; Ion Torrent PGM System and 454 pyrosequencing typically produces ~400 bp reads, Illumina MiSeq produces 400-700bp reads (depending on whether paired end options are used), and SOLiD produce 25–75 bp reads. Historically, these read lengths were significantly shorter than the typical Sanger sequencing read length of ~750 bp, however the Illumina technology is quickly coming close to this benchmark. However, this limitation is compensated for by the much larger number of sequence reads. In 2009, pyrosequenced metagenomes generate 200–500 megabases, and Illumina platforms generate around 20–50 gigabases, but these outputs have increased by orders of magnitude in recent years. An emerging approach combines shotgun sequencing and chromosome conformation capture (Hi-C), which measures the proximity of any two DNA sequences within the same cell, to guide microbial genome assembly. Long read sequencing technologies, including PacBio RSII and PacBio Sequel by Pacific Biosciences, and Nanopore MinION, GridION, PromethION by Oxford Nanopore Technologies, is another choice to get long shotgun sequencing reads that should make ease in assembling process. Bioinformatics The data generated by metagenomics experiments are both enormous and inherently noisy, containing fragmented data representing as many as 10,000 species. The sequencing of the cow rumen metagenome generated 279 gigabases, or 279 billion base pairs of nucleotide sequence data, while the human gut microbiome gene catalog identified 3.3 million genes assembled from 567.7 gigabases of sequence data. Collecting, curating, and extracting useful biological information from datasets of this size represent significant computational challenges for researchers. Sequence pre-filtering The first step of metagenomic data analysis requires the execution of certain pre-filtering steps, including the removal of redundant, low-quality sequences and sequences of probable eukaryotic origin (especially in metagenomes of human origin). The methods available for the removal of contaminating eukaryotic genomic DNA sequences include Eu-Detect and DeConseq. Assembly DNA sequence data from genomic and metagenomic projects are essentially the same, but genomic sequence data offers higher coverage while metagenomic data is usually highly non-redundant. Furthermore, the increased use of second-generation