Advancing Science with DNA Sequence
Finding the genes in
microbial genomes
Natalia Ivanova
MGM Workshop
January 31, 2012
Advancing Science with DNA Sequence
Outline
1. Introduction
2. Tools out there
3. Basic principles behind tools and
known problems
4. Metagenomes
Advancing Science with DNA Sequence
Finding the genes in microbial genomes
features
Well-annotated
bacterial
genome in Artemis
genome viewer:
Sequence
features
in prokaryotic
genomes:
 stable RNA-coding genes (rRNAs, tRNAs, RNA
component of RNaseP, tmRNA)
 protein-coding genes (CDSs)
 transcriptional features (mRNAs, operons, promoters,
terminators, protein-binding sites, DNA bends)
 translational features (RBS, regulatory antisense
RNAs, mRNA secondary structures, translational
recoding and programmed frameshifts, inteins)
 pseudogenes (tRNA and protein-coding genes)
…
Advancing Science with DNA Sequence
Outline
1. Introduction
2. Tools out there
(don’t bother to write down the names and links, all
presentations will be available on the web site)
3. Known problems
4. Metagenomes
Advancing Science with DNA Sequence
Publicly available genome
annotation services
IMG-ER
http://img.jgi.doe.gov/
RAST
http://rast.nmpdr.org/
JCVI Annotation Service
http://www.jcvi.org/cms/research/projects/annotationservice/
RefSeq
http://www.ncbi.nlm.nih.gov/genomes/static/Pipeline.h
tml
Advancing Science with DNA Sequence
What they provide and how they
do it - RNAs
• Large structural RNAs (23S and 16S rRNAs)
BLASTn
RNAmmer http://www.cbs.dtu.dk/services/RNAmmer/
• Small structural RNAs (5S rRNA, tRNAs,
tmRNA, RNaseP RNA component)
Rfam database, INFERNAL search tool
http://www.sanger.ac.uk/Software/Rfam/
http://rfam.janelia.org/
http://infernal.janelia.org/
tRNAScan-SE
http://lowelab.ucsc.edu/tRNAscan-SE/
Advancing Science with DNA Sequence
What they provide and how they do it –
protein-coding gens (CDSs - not ORFs!)
Reading frames: translations of the nucleotide sequence with an offset of 0, 1
and 2 nucleotides (three possible translations in each direction)
Open reading frame (ORF): reading frame between a start and stop codon
Advancing Science with DNA Sequence
Gene finders: ab initio tools;
evidence-based refinement
Ab initio tools used by the pipelines:
Glimmer family (Glimmer2, Glimmer3, RBS finder) ->NCBI,
RAST, JCVI
http://glimmer.sourceforge.net/
GeneMark family (GeneMark-hmm, GeneMarkS) ->NCBI
http://exon.gatech.edu/GeneMark/
PRODIGAL -> IMG-ER, NCBI
http://compbio.ornl.gov/prodigal/
Evidence-based refinement:
mostly undocumented in-house developed tools.
Types of corrections:
missed genes (RAST, JCVI, NCBI), frameshifts (JCVI, NCBI), start sites
(RAST)
Advancing Science with DNA Sequence
Outline
1. Introduction
2. Tools out there
3. Basic principles behind tools
4. Metagenomes
Advancing Science with DNA Sequence
What is ab initio gene finder?
Two major approaches to prediction of protein-coding genes:
• ab initio (ORFs with nucleotide composition
similar to CDSs are also CDSs)
Advantages: finds “unique” genes; high sensitivity; very fast!
Limitations: often misses “unusual” genes; high rate of false positives
“evidence-based” (ORFs with translations
homologous to the known proteins are CDSs)
Advantages: finds “unusual” genes (e. g. horizontally transferred);
relatively low rate of false positive predictions
Limitations: cannot find “unique” genes; low sensitivity on short genes;
prone to propagation of false positive results of ab initio annotation tools;
slow!
Advancing Science with DNA Sequence
How ab initio tools work – very
briefly
Ribosome
binding site
open reading frame
Start codon:
ATG, GTG, TTG
Stop codon:
TAG, TAA, TGA
Prokaryotic gene model used
by all ab initio gene finders
Ribosome-binding site within
certain distance of the start codon;
One of 3 start codons;
One of 3 stop codons;
No frame interruptions
• Statistical model of
coding and non-coding
regions (codon or dicodon
frequencies, hidden
Markov models of
different lengths)
• Statistical model
architecture
• Additional algorithms for
refinement of
predictions (RBS finder,
overlap resolution, etc.)
Advancing Science with DNA Sequence
Known problems of all annotation
pipelines
• RNAs
– Incomplete rRNAs
– Trans-spliced tRNA
in archaeal genomes
– Small structural RNAs
not predicted at all
Genome
Sequencing
center
16S rRNA,
nt
Synechococcus sp. CC9311
UCSD, TIGR
1477
Synechococcus sp. CC9605
JGI
1440
Synechococcus elongatus PCC 7942
JGI
1490
Synechococcus sp. JA-2-3BA(2-13)
TIGR
1323
Synechococcus sp. JA-3-3Ab
TIGR
1324
Synechococcus sp. RCC307
Genoscope
1498
Synechococcus sp. WH7803
Genoscope
1497, 1464
• Protein-coding genes that don’t fit into prokaryotic gene model
used by ab initio gene finders
Ribosome
– no RBS (leaderless transcripts)
– interrupted translation frame
sequencing errors or
translational exceptions
– non-canonical start
binding
site
open reading frame
Start codon:
ATG, GTG, TTG
Stop codon:
TAG, TAA, TGA
Advancing Science with DNA Sequence
Symptoms of gene finding
problems
• Some type of mandatory features (rRNAs, tRNAs,
CDSs) is missing
• “Truncated” genes (shorter than homologs) =>
funky translation initiation features (non-canonical
start codons, leaderless transcripts)
• Many “unique” genes without protein family
assignment or BLASTp hit => sequencing errors
(frameshifts)
• Undetected selenocysteines, programmed
frameshifts in ~50 well-conserved protein families
Advancing Science with DNA Sequence
Supplemental tools
 TIS (translation initiation site) prediction/correction
TICO http://tico.gobics.de/
TriTISA http://mech.ctb.pku.edu.cn/protisa/TriTISA
 Two tools often disagree about the best TIS, especially in high
GC genomes
 Operon prediction
JPOP http://csbl.bmb.uga.edu/downloads/#jpop
http://www.cse.wustl.edu/~jbuhler/research/operons/
http://www.sph.umich.edu/~qin/hmm/
 Proteins with unusual translational features –
selenocysteine-containing genes
bSECISearch http://genomics.unl.edu/bSECISearch/
Advancing Science with DNA Sequence
Metagenomes sequenced with new
technologies: low-coverage problems
• Both 454 and Illumina require high sequence coverage in order to
achieve high sequence quality (25x to >100x)
• High sequence coverage cannot be achieved for
metagenome data
coverage
sequence
metagenome
coverage
genome
sequence
How does this affect metagenome annotation?
~70% of 454 Titanium reads have at least 1 sequencing artifact
(basecalls in homopolymeric runs), there is no clear pattern
of error distribution
>100 bp Illumina reads have ~3% error rate, error rate is higher
towards the end of the read, the majority of errors are
substitutions
Advancing Science with DNA Sequence
Just one example…
4-read contig, 1476 nt, no misassembly
3 frameshifts
Contig has 27 homopolymers (3 nt and more), 3 of them have errors
No correlation with homopolymer type or error type
Reads
weregene
quality trimmed prior to assembly
predicted
Advancing Science with DNA Sequence
Metagenome annotation tools
(more details will be given)
GeneMark (GeneMark-hmm for reads, GeneMarkS for
longer contigs)
http://exon.gatech.edu/GeneMark/
• MetaGene
http://metagene.cb.k.u-tokyo.ac.jp/metagene/
• FragGeneScan
http://omics.informatics.indiana.edu/FragGeneScan/
Full-service annotation pipelines
• IMG/M-ER – “metagenome gene calling” + other
options
http://img.jgi.doe.gov/submit
• MG-RAST
http://metagenomics.nmpdr.org/
• CAMERA annotation pipeline
http://camera.calit2.net/