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Advancing Science with DNA Sequence
Metagenome analysis
Natalia Ivanova
MGM Workshop
May 17, 2012
Advancing Science with DNA Sequence
1. Metagenome definitions:
a refresher course
Advancing Science with DNA Sequence
Metagenome definitions
Metagenome is a collective genome of microbial community, AKA
microbiome (native, enriched, sorted, etc.).
Metagenomic library (or libraries) is constructed from isolated DNA
(native, enriched, etc.).
Metagenomic library can be single-end (AKA standard)
or paired-end
Advancing Science with DNA Sequence
Metagenome definitions
Single-end (standard) metagenomic library will produce
contigs upon assembly (i. e. longer sequences based on
overlap between reads)
Any Ns found in contigs correspond to low quality bases
ATGCAAAGGCCGCATCCAGCAGGTT
TACGTTTCCGGCGTAGGTCGTCCAA
Paired-end metagenomic library will produce scaffolds upon
assembly (non-contigous joining of reads based on read
pair information)
Ns found in scaffolds correspond either to low quality bases or
to gaps of unknown size
ATGCAAAGGCCGCATCC
AGCAGGTT
NNNNNN
TACGTTTCCGGCGTAGG
TCGTCCAA
Advancing Science with DNA Sequence
Amplified and Unamplified
Libraries
Amplified Library
Unamplified Library
Fragmentation (1ug)
Fragmentation (1ug)
Double SPRI
End repair / Phosphorylation
End repair / Phosphorylation
SPRI Clean
Double SPRI
A-tailing with Klenow exoSPRI Clean
A-tailing with Klenow exo-
DNA Chip
Adaptor Ligation
Heat Inactivation
DNA Chip
Adaptor Ligation
SPRI Clean
PCR 10-cycle Amplification
SPRI Clean
qPCR Quantification
DNA Chip
SPRI Clean
qPCR Quantification
DNA Chip
Advancing Science with DNA Sequence
Metagenome definitions (contd):
Unless the community has very low complexity (i. e.
dominated by one or a few clonal populations),
assembly at 100% nucleotide identity will be very
fragmented.
overlap = alignment of reads at x% identity
What to do with k-mer based assemblies?
Use multiple k-mer settings, combine assemblies
with an overlap-layout consensus assembler like
minimus2 using minimal % identity of 95%.
Tradeoff between overlap length and % identity.
Advancing Science with DNA Sequence
Reasoning behind combining multiple
assemblies
Advancing Science with DNA Sequence
Trimming does not
appear to be ideal for
this process
Assembly
Pipeline v.0.9
CPU time intensive, no known
metagenomic Kmer
prediction algorithm
A snapshot of older (454Illumina) metagenome
assembly pipeline
Picking best kmer – manual proces
8
Advancing Science with DNA Sequence
Metagenome definitions (contd):
overlap = alignment of reads at x% identity
Assembly of sequences at less than 100% identity =>
population contigs and scaffolds representing a
consensus sequence of species population
isolate contig
species population
contigs
Advancing Science with DNA Sequence
2 more important definitions
1.
Sequence coverage (AKA read depth)
How many times each base has been sequenced => needs to
be considered when calculated protein family abundance
Per-contig average coverage
Per-base coverage => per-gene coverage
2. Bins
Scaffolds, contigs and unassembled reads can be binned into
sets of sequences (bins) that likely originated from the
same species population or a population from a broader
taxonomic lineages
Advancing Science with DNA Sequence
What IMG does and doesn’t do
• Scaffolds and contigs are generated by assembly – not
provided in IMG/M
• Sequence coverage can be computed by the
assembler based on alignments it generates
(preferable) or can be added later by aligning reads
to contigs – the latter can be provided in IMG/M
• Bins are generated by binning software – not
provided in IMG/M
• Scaffolds, contigs and unassembled reads are
annotated with non-coding RNAs, repeats (CRISPRs),
and protein coding genes (CDSs); the latter are
assigned to protein families (COGs, Pfams, TIGRfams,
KEGG Orthology, EC numbers, internal clusters) – is
provided in IMG/M
Advancing Science with DNA Sequence
What’s the difference between IMG and
MG-RAST, IMG and CAMERA?
• We prefer to assemble the data

longer sequences -> better quality of gene prediction and functional
annotation

longer sequences -> chromosomal context and binning -> population-level
analysis
• But we don’t provide assembly services except for metagenomes
sequenced at the JGI


we may be able to help with assembly of 454
we’re not equipped to assemble massive amounts of Illumina data
http://galaxy.jgi-psf.org
Contact person: Ed Kirton, [email protected]
• IMG does not provide tools for analysis of 16S data from the
metagenome itself



we do assembly -> assembled 16S sequences are generally not very reliable
BLASTn of reads matching conserved regions is misleading
we do pyrotags or i-tags for every metagenome sequenced at the JGI
http://pyrotagger.jgi-psf.org
Advancing Science with DNA Sequence
2. IMG/M features:
divide and conquer
(see also IMG/M -> Using IMG/M -> Using IMG/M -> IMG User
Guide and IMG/M Addendum)
http://img.jgi.doe.gov/m
http://img.jgi.doe.gov/mer
username: public
password: public
Advancing Science with DNA Sequence
IMG/M User Interface Map
About IMG/M -> Using IMG/M -> User
Interface Map
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Dividing the contigs by GC content
or length
• Statistics
Microbiome Details ->
Genome Statistics -> DNA
Scaffolds
• Search
Microbiome Details ->
Scaffold Search
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Dividing the genes phylogenetically:
Phylogenetic Distribution
Phylogenetic Distribution of Genes
Microbiome Details -> Phylogenetic Distribution of
Genes
gene lists
gene counts
histogram
Components:
(phylum/class)
summary statistics
 histograms
counts, lists,
 Protein Recruitment Plots histogram
statistics
(family)
 summary statistics tables
counts, lists
histogram
 lists of genes
(species)
recruitment plots
Advancing Science with DNA Sequence
Dividing the contigs: Scaffold Cart
• Lists of contigs
or genes in
Gene Cart
E. g. Microbiome Details ->
Genome Statistics -> DNA
Scaffolds -> scaffold
counts
Scaffold Cart
Features:
 Scaffold Export
 Adding all genes to Gene
Cart
 Function Profile (against
functions in Function
Cart)
 Histograms by GC
content, length and gene
count
 Phylogenetic Distribution
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All Carts in IMG are
interconnected
Gene Cart
Scaffold Cart
Function Cart
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Dividing the genes by abundance/
by function
• Abundance Profiles
Compare Genomes -> Abundance Profiles Tools
Components:
Common parameters:
 Normalization (none/scale for size)
 Type of count (raw counts/estimated gene copies)
 Type of protein family (COG, Pfam, Enzyme, TIGRfam)
Advancing Science with DNA Sequence
Other tools
• Phylogenetic Marker COGs
Find Functions -> Phylogenetic Marker COGs
• SNP BLAST and SNP Vista
Gene Page -> SNP BLAST -> SNP VISTA
IMG/M exercises:
http://genomebiology.jgi-psf.org/Content/MGM-11.Feb2012/agenda.html
The first 3 pages are questions without answers; the rest is a cheat sheet
Advancing Science with DNA Sequence
Life outside IMG: binning tools
Alignment-based tools
• MEGAN – BLAST+LCA
http://www-ab.informatik.uni-tuebingen.de/software/megan
• MTR – BLAST+ MTR
http://cs.ru.nl/gori/software/MTR.tar.gz
• SOrt-ITEMS – processed BLAST best hit
http://metagenomics.atc.tcs.com/binning/SOrt-ITEMS
• CARMA and Web-CARMA – MSA + neighbor-joining tree
http://webcarma.cebitec.uni-bielefeld.de
Compositional tools
• PhyloPythia – 6-mers, SVM
http://cbcsrv.watson.ibm.com/phylopythia.html
• TACOA – 2-6 mers, k-nearest neighbor classifier
http://www.cebitec.uni-bielefeld.de/brf/tacoa/tacoa.html
• Phymm and PhymmBL – Interpolated Markov models (IMMs)
http://www.cbcb.umd.edu/software/phymm/
• ClaMS – DOR, DBC
http://clams.jgi-psf.org
Advancing Science with DNA Sequence
Life outside IMG: statistical
analysis tools
Comparison of 2 samples
• MEGAN - http://www-ab.informatik.uni-tuebingen.de/software/megan
• STAMP - http://kiwi.cs.dal.ca/Software/STAMP
Comparison of sets of samples
• ShotgunFunctionalizeR – R package for statistical analysis http://shotgun.zool.gu.se
• METAREP – package from JCVI, includes multidimensional
scaling, hierarchical clustering, etc - http://www.jcvi.org/metarep
• METASTATS – package for analysis of paired samples with
replicates - http://metastats.cbcb.umd.edu/
• LEfSE – package for comparison of multiple classes of samples
with replicates - http://huttenhower.sph.harvard.edu/lefse/