This document provides an overview and primer on 16S amplicon sequencing and analysis for metagenomics. It discusses how 16S is a ubiquitous gene that can be used to compare microbial communities across samples, outlines common analysis steps like preprocessing, OTU picking, taxonomy assignment, and diversity metrics, and introduces two analysis tools - MEGAN and Qiime. Key advantages and limitations of the 16S amplicon approach are highlighted.

1. 16S Amplicons
A primer on metagenomics
Andrea Telatin and Eleonora Sattin
BMR Genomics

2. De novo genome
Exome seq
16S Amplicons
Out of the
machine
Introduction to
bioinformatics
You are here

3. Today’s menu:!
• a biological perspective on 16S-seq
• a short primer on bioinformatic analysis
• introducing two tools:
• MEGAN (GUI)
• Qiime (pipeline)

4. Why?

5. – J. C. Venter
“whatever we look at,
we are barely scratching the
surface”

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

8. Key questions
• Who is out there?
• What are they doing?

9. How?

10. 16S Amplicon

11. 16S Amplicon
PROS!
• Ubiquitous gene
• Contains both conserved and variable regions
CONS!
• Copy number variations
• It’s only a (single) gene

12. metagenomics ≠ amplicon sequencing

13. 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?)

14. Sequence alignment

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

16. 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.
GapCost

17. 1) AGT
2) AT
3) ATC
1) AGT
2) A–T
3) ATC
1) AGT
2) AT–
3) ATC
1) AGT -
2) A - T -
3) A - TC
A B C A C B B C A
INPUT

18. Bioinformatics
analysis overview

19. Sequencing Reads
Pre-Processing
Denoising
OTU Picking
Taxonomical classification
Alpha/Beta Rarefaction
PCA

20. Sequencing output
(454, Illumina, Sanger)
fastq, fasta, qual, or sff/trace files
Metadata
mapping file
Pre-processing
e.g., remove primer(s), demultiplex,
quality filter
Denoise 454 Data
PyroNoise, Denoiser
Reference based
BLAST, UCLUST,
USEARCH
Pick OTUs and representative sequences
De novo
e.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 tree
e.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

21. Mapping File

22. (Processed) Sequences

23. Sequencing Reads
Pre-Processing
Denoising
OTU Picking
Taxonomical classification
Alpha/Beta Rarefaction
PCA

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

25. MEGANMaking pies since 2004

26. Any questions?