Low-complexity and Repetitive Regions

OraLee Branch John Wootton NCBI branch@ncbi.nlm.nih.gov

DNA Sequences–What would be the expected number of occurrences

of a particular sequence in a genome? • Size: human genome 6*109 considering both strands• Base frequency: equal• Sequence length: 20 nucleotides

–Bernouli Model: = 0.005

–But:• (GT)n with n>10 = 105

Sequence Composition

20

9

410*6

Low-complexity Regions

Simple Sequence Regions (SSR)– MICRO- or MINISATELLITES– Regions that have significant biases in AA or nucleotide composition :

repeats of simple motifs

– (GT)n

(AAC)n (P)

n (NANP)

n

Low-Complexity Regions/Segments– Complexity can be measured by Shannon’s Entropy

• Regarding an amino acid sequence

– For each composition of a complexity state, there exists a large number of possible sequences

20

1

)ln(i

ii ff

Low-Complexity Regions Locally abundant residues may be

– continuous or loosely clustered irregular or aperiodic

>25% of AA in currently sequenced genome is in LC regions– non-globular domains SSR

Examples: myosins, pilins, segments in antigens, short subsequences of 10-50 residues with unknown function– Beta-pleated sheets– Alpha helices– Coiled-coils

Low-Complexity Regions Locally abundant residues may be

– continuous or loosely clustered irregular or aperiodic

>25% of AA in currently sequenced genome is in LC regions– non-globular domains SSR

Examples: myosins, pilins, segments in antigens, short subsequences of 10-50 residues with unknown function– Beta-pleated sheets– Alpha helices– Coiled-coils

Detecting Low-Complexity

SEG and PSEG/NSEG algorithms–Wootton and Federhen

• Methods in Enzymology 266:33 (1996)• Computers and Chemistry 17:149 (1993)

SEG–UNIX Executable available on ncbi servers

• seg FASTAfile Window TriggerComplexity Extension K2(1) K2(2)

• Longer Window lengths define more sustained regions, but overlook short biased subsequences

clobber> seg hu.piron.fa 12 2.20 2.50>gi|730388|sp|P40250|PRIO_CERAE MAJOR PRION PROTEIN PRECURSOR (PRP)

1-49 MANLGCWMLVVFVATWSDLGLCKKRPKPGG WNTGGSRYPGQGSPGGNRYppqggggwgqphgggwgqphgggwgqphgg 50-86 gwgqggg 87-104 THNQWHKPSKPKTSMKHM agaaaagavvgglggymlgsams 105-127 128-179 RPLIHFGNDYEDRYYRENMYRYPNQVYYRP VDQYSNQNNFVHDCVNITIKQH tvttttkgenftet 180-193 194-228 DVKMMERVVEQMCITQYEKESQAYYQRGSS MVLFS sppvillisflifliv 229-244 245-245 G

clobber> seg hu.piron.fa 12 2.20 2.50 -l>gi|730388|sp|P40250|PRIO_CERAE(50-86) complexity=1.90 (12/2.20/2.50)ppqggggwgqphgggwgqphgggwgqphgggwgqggg

>gi|730388|sp|P40250|PRIO_CERAE(105-127) complexity=2.47 (12/2.20/2.50)agaaaagavvgglggymlgsams

>gi|730388|sp|P40250|PRIO_CERAE(180-193) complexity=2.26 (12/2.20/2.50)tvttttkgenftet

>gi|730388|sp|P40250|PRIO_CERAE(229-244) complexity=2.50 (12/2.20/2.50)sppvillisflifliv

SEG piron with different window lengthsquestion-based – exploratory tool – optimization step

– Intuitive explanation• Take a 20-residue long sequence

– (20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0)– ( 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 )– ( 3 3 3 3 3 2 2 2 2 1 1 0 0 0 0 0 0 0 0 0)

– Complexity can be described by Shannon’s Entropy (K2)• Regarding an amino acid sequence

– For each composition of a complexity state, there exists a large number of possible sequences (K1)

Detecting Low-Complexity

N

iii ffK

12 )ln(

N

iin

L

LK

1

1

!

!ln

1

How SEG works seg FASTAfile Window TriggerComplexity Extension

K2(1) K2(2)

Looks within window length: if complexity < K2(1) then extends until complexity < K2(2)

Uniform prior probabilities

– Protein sequence data base is a heterogeneous statistical mixture such that the initially-unknown AA frequencies in Low-complexity subsets need have no similarity to frequencies in total data base

– Unbiased view of low-complexity regions

– Gives equiprobable compositions for any complexity state

How SEG works, continued

How do you correct for the background AA/nuc composition bias?

– After randomly shuffling all the residues, determine the trigger complexity that results in 4% of the data base being within Low-complexity regions

– Then use this trigger complexity and subtract 4% from %AA in Low-complexity regions

Detecting Low-complexity with repetitive motif: SSR

PSEG or NSEG Repetition of residue types or k-grams Period 3

(n V E n K N n V D n K D n V N n K S n K)(n m i n m i n m i n m i n m i n m i n m)

(n m E n m N n m D n m D n m N n m S n m)

Sliding window along sequence in single residue steps

Evolutionary Mechanisms Evolution of sequences in general

– Evolution rate of 10-5 – 10-9

• Base pair substitution (10-9 )• Insertion/deletions• Recombination

In SSR, Low-complexity regions, mutations are in length – with steps typically +/- one repeat unit– Evolution rate 10-3

• Biased nucleotide substitution due to increased recombination in repetitive regions

• Unequal crossing over (recombination)• Replication slippage

Alignment of repeats does not imply relationships/ancestory

Low-Complexity and BLAST searches

Low-complexity regions results in BLAST searches being dominated by Low-complexity regions – biased AA/nuc composition

BLAST added “mask low-complexity” by default– Seg parameters: 12 2.2 2.5

BLAST now also uses a compositional bias filter on the whole database– Masks if composition bias using seg 10 1.8 2.1

YOU MAY WANT TO TURN THESE OPTIONS OFF and use your own organism-specific seg paramenters when doing protein homology searching

YOU WILL NEED TO TURN THESE OPTIONS OFF if you are interested in looking at sequence similarities of repetitive/low complexity regions.

Example: Plasmodium falciparum

Using whole genome sequences is important to limit pcr sequencing bias for antigens: hydrophilic proteins

Considering GC-content / AA bias–P. falciparum is approximately 28 % GC

Visualization of individual proteins

A helpful tool here and in general

SEALS: A system for Easy Analysis of Lots of Sequences, R. Walker and E. Koonin, NCBI

www.ncbi.nlm.nih.gov/ CBBresearch/Walker/SEALS/index.html

Demonstrate getting an appropriate data set– Taxnode2gi, gi2fasta– Daffy– Purge– Gref– Fanot

Use cleaned data set of P. falciparum proteins

Protein Analysis

Setting the trigger complexity:– Dbcomp– Shuffledb– Seg

Run SEG on P. falciparum MSP1, PfEMP2, Cg2– Options

• –p (tree form output) • -l (only report Low-C segs)• -h (don’t report Low-C segs)• -x (substitute Low-C with x)

Run PSEG on P. falciparum MSP1, PfEMP2, Cg2 with different –z (periodicity)

Usefulness of studying Low-Complexity

Within a proteinsecondary structure, homology searchers, protein locationgenetic disorders

Within taxamicrosatellite markerspolymorphism comparisons between proteins

Between taxaSynteny , orthologsdifferent selection pressures upon different organismsparasites: immunogenicity, rapid evolution of

antigens, recombination