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Category: Metagenomics

Metagenomics and metabarcoding

Python 3 for scientists course and other didactic materials at SixthResearcher

I want to share with you the new section of Didactic Materials at the Sixth Researcher website.

In this section I will include courses, presentations, workshops and other materials that I prepared and could be useful for other researchers.

At the moment you can download 10 lessons with the fundamentals of Python 3 for biologists and other scientists that I imparted at UAM.

Also is available a Metabarcoding workshop with the fundamentals of the technique and a practical example explaining the bioinformatics analysis of the data.

The didactic materials in this new section will be licensed as Creative Commons Attribution-NonCommercial.


Python for Scientists

Materials from the course Basic Python 3 Programming for Scientists imparted at Adam Mickiewicz University:


Metabarcoding Bioinformatics analysis

Materials from the workshop Introduction to Bioinformatics analysis of Metabarcoding data:


 

Amplicon sequencing and high-throughput genotyping – Metagenomics

In the previous post I explained the fundamentals about the Amplicon Sequencing  (AS) technique, today I will show some current and future applications in Metagenomics and Metabarcoding.

Metagenomics (also referred to as ‘environmental’ or ‘community’ genomics) is the study of genetic material recovered directly from environmental samples. This discipline applies a suite of genomic technologies and bioinformatics tools to directly access the genetic content of entire communities of organisms. Usually we use the term metabarcoding when we apply the amplicon sequencing approach in metagenomics studies, also metagenomics term if preferred when we study full genomes, not only few gene regions.

Metabarcoding workflow. Source: http://www.naturemetrics.co.uk

For metabarcoding, 16S rRNA gene is the most common universal DNA barcode (marker) used to identify with great accuracy species from across the Tree of Life, but other genes as: cytochrome c oxidase subunit 1 (CO1), rRNA (16S/18S/28S), plant specific ones (rbcL, matK, and trnH-psbA) and gene regions as: internal transcribed spacers (ITSs) (Kress et al. 2014; Joly et al. 2014). The previous genes have mutation rates fast enough to discriminate close species and at the same time they are stable enough to identify individuals of the same specie.

Prokaryotic and eukaryotic rRNA operons

A perfect metagenomics barcode/marker should…

  • be present in all the organisms, in all the cells
  • have variable sequence among different species
  • be conserved among individuals of the same species
  • be easy to amplify and not too long for sequencing

Recommended DNA barcodes for metagenomics

The pioneer metabarcoding study of Sogin et al. 2006 to decipher the microbial diversity in the deep sea used as barcode the V6 hypervariable region of the rRNA gene. Sogin et al. sequenced around 118,000 PCR amplicons from environmental DNA preparations and unveiled thousand of new species not known before.

Observe that in metabarcoding we cannot use DNA tags to pick out single individuals, but to identify different samples (of water, soil, air…).

Metagenomics workshop in Evora

I want to announce that on 19th October I’ll teach the workshop titled “Introduction to Bioinformatics applied to Metagenomics and Community Ecology” during the conference Community Ecology for the 21st Century (Évora, Portugal).

In this workshop I’ll introduce the new tool called AmpliTAXO that allows an online, easy and automated analysis of NGS data from ribosomal RNA and other genetic markers used in metagenomics.

If you are interested, you can contact here with the conference organizers to join the workshop or the full conference, there are still available places in the workshop.

The workshop will consist in two modules, in the first, will be exposed the metagenomics fundamentals, challenges, the technical advances of the high-throughput sequencing techniques and the analysis pipeline of the most used tools (UPARSE, QIIME, MOTHUR). The second part will be practical and we will perform an analysis of real metagenomic data from NGS experiments.

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