Introduction to 16S Analysis with NGS - BMR Genomics

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16S Amplicons A primer on metagenomics Andrea Telatin and Eleonora Sattin BMR Genomics

description

Introduction to the bioinformatics of 16S Amplicon Sequencing.

Transcript of Introduction to 16S Analysis with NGS - BMR Genomics

Page 1: Introduction to 16S Analysis with NGS - BMR Genomics

16S AmpliconsA primer on metagenomics

Andrea Telatin and Eleonora Sattin BMR Genomics

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De novo genome

Exome seq

16S Amplicons

Out of the machine

Introduction to bioinformatics

You are here

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Today’s menu:!

• a biological perspective on 16S-seq

• a short primer on bioinformatic analysis

• introducing two tools:

• MEGAN (GUI)

• Qiime (pipeline)

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Why?

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– J. C. Venter

“whatever we look at, we are barely scratching the

surface”

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Flores G. E. et al., 2011 (PLoS One)Microbial Biogeography of Public Restroom Surfaces

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Key questions• Who is out there?

• What are they doing?

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How?

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16S Amplicon

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16S AmpliconPROS!

• Ubiquitous gene

• Contains both conserved and variable regions

CONS!

• Copy number variations

• It’s only a (single) gene

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metagenomics ≠ amplicon sequencing

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Driving idea• Well established method

that can be used to compare different samples

• At any step we introduce bias, that have to be taken into account • Sampling (replicate or lie) • Cell breakage (are you strong enough?) • Amplification (where do your primers come from?) • Sequencing (how good is your machine?) • Analysis (database annotation?)

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Sequence alignment

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This is a hard example. !That is another easy example.

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This is a --hard---- example. || ||||| | | ||||||||| That is another easy example.

This is a-- h-ard---- example. || ||||| | | ||||||||| That is anothe-r easy example.

This is a hard example.------ || ||||| | | That is another easy example.

Gap C

ost

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1) AGT 2) AT 3) ATC

1) AGT 2) A – T 3) A TC

1) AGT 2) A T – 3) A TC

1) AGT - 2) A - T - 3) A - TC

A B C A C B B C A

INPUT

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Bioinformatics analysis overview

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Sequencing Reads

Pre-Processing

Denoising

OTU Picking

Taxonomical classification

Alpha/Beta Rarefaction

PCA

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Sequencing output (454, Illumina, Sanger)

fastq, fasta, qual, or sff/trace files

Metadata

mapping file

Pre-processinge.g., remove primer(s), demultiplex,

quality filter

Denoise 454 Data

PyroNoise, Denoiser

Reference basedBLAST, UCLUST,

USEARCH

Pick OTUs and representative sequences

De novoe.g., UCLUST, CD-HIT, MOTHUR, USEARCH

Assign taxonomy

BLAST, RDP Classifier

Align sequences

e.g., PyNAST, INFERNAL, MUSCLE,

MAFFT

Build 'OTU table'i.e., sample by observation

matrix

Build phylogenetic treee.g., FastTree, RAxML,

ClearCut

Database Submission

(In development)

OTU (or other sample by observation) table

Phylogenetic Tree

Evolutionary relationship between OTUs

α-diversity and rarefaction

e.g., Phylogenetic Diversity, Chao1,

Observed Species

β-diversity and rarefaction

e.g., Weighted and unweighted UniFrac, Bray-

Curtis, Jaccard

Interactive visualizations

e.g., PCoA plots, distance histograms, taxonomy charts, rarefaction plots, network visualization, jackknifed hierarchical clustering.

Legend

Required step or input Optional step or input

Currently supported for marker-gene data only

(i.e., 'upstream' step)

Currently supported for general sample by observation data

(i.e., 'downstream' step)

www.QIIME.orgwww.QIIME.org

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Mapping File

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(Processed) Sequences

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Sequencing Reads

Pre-Processing

Denoising

OTU Picking

Taxonomical classification

Alpha/Beta Rarefaction

PCA

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Qiime Output Demo!http://www.bmr-genomics.it/~telatin/16S

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MEGANMaking pies since 2004

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Any questions?