Transposable Elements (TE) in genomic sequence

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Transposable Elements (TE) in genomic sequence

• Mina Rho

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Contents

• Definition
• De novo identification of repeat families in
  large genomes (RepeatScout)
• Alkes L. Price, Neil C. Jones and Pavel A.
  Pevzner
• Combined Evidence Annotation of Transposable
  Elements in Genome Sequences
• Hadi Quesneville, Casey M. Bergman, Olivier
  Andrieu, Delphine Autard, Danielle Nouaud,
  Michael Ashburner, Dominique Anxolabehere

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Mobile element/Transposable element

• Transposon
• - a segment of DNA that can move around to
  different positions in the genome of a single
  cell.
• - cut out of its location and inserted into a
  new location.
• - consisting of DNA.
• Retrotransposon
• - copy and paste into a new location.
• - the copy is made of RNA and transcribed back
  into DNA using reverse transcriptase.
• - long terminal repeats (LTRs) at its ends.
• gt expect to get information of evolution,
  mutation, changes of amount of DNA in the genome.

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RepeatScout
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Definition

• Repeat family a collection of similar sequences
  which appear many times in a genome.
• the Alu repeat family has over 1 million
  approximate occurrences in the human genome
• 50 Human genome
• l-mer substring whose length is l

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Backgroud

• The current status on identification method of
  repeat families
• Given an existing library of repeat families
  
• RepeatMasker
• De novo identification
• REPuter (Kurtz et al., 2000)
• RepeatFinder (Volfovsky et al., 2001)
• RECON (Bao and Eddy, 2002)
• RepeatGluer (Pevzner et al., 2004)
• PILER (Edgar and Myers, 2005)
• RepeatScout

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Overview of RepeatScout

• Method
• Builds a table of high frequency l-mers as seeds
• Extends each seed to a longer consensus sequence
• Main advantage
• an efficient method of similarity search which
  enables a rigorous definition of repeat
  boundaries.

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How to create l-mer table
Sequence
i
i1
i2
j
k
Hash table
l-mer1
l-mer2
l-mer3
l-mer4
l-mer5
l-mer6
frequency
Position of last occurrence
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Output of l-mer table

• AAAAAAAAAAAGATA 8 2920943
• AAAAAAAGGAAAGAA 5 2468525
• AGGCTTGAACAATGG 3 1425014
• AAAAAAAAGAAAGAA 62 3009663
• GTTGGTTTCAAAGAA 7 2855871
• AAAAAAAATTTTTTT 22 2992836
• ATTCAAGTTAAATGG 4 1473342
• ATTCAATGTAACCAC 3 1463008
• ATGCATGCAATGCAT 9 1788944
• ATGCATTTAAAAGAA 3 1464381
• AAAAAACTCACTCCA 5 1489159

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How to build all positions of repeats
Sequence
i
i1
i2
j
k
Hash table
l-mer1
l-mer2
l-mer3
l-mer4
l-mer5
l-mer6
j
i
k
i2
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Query sequence (with l-mer1)
S1
S2
S3
S4
S5
Extending Q maximizing objective function one
nucleotide at a time
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Objective Function

• Q the length of Q
• C minimum threshold on the number of repeat
  elements
• a(Q, Sk) a pairwise fit_preferred alignment
  score

p Incomplete-fit penalty
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Output of optimized Q

• gtR0
• GGCCGGGCGCGGTGGCTCACGCCTGTAATCCCAGCACTTTGGGAGGCCGA
  GGCGGGCGGATCACTTGAGGTCAGGAGTTC
• GAGACCAGCCTGGCCAACATGGTGAAACCCCGTCTCTACTAAAAATACAA
  AAATTAGCCGGGCGTGGTGGCGCGCGCCTG
• TAATCCCAGCTACTCGGGAGGCTGAGGCAGGAGAATCGCTTGAACCCGGG
  AGGCGGAGGTTGCAGTGAGCCGAGATCGCG
• CCACTGCACTCCAGCCTGGGCGACAGAGCGAGACTCCGTCTCAAAAAAAA
  AAAAAAAAAAAAAAAAAAA
• gtR1
• AAAAGGCAGCAGAAACCTCTGCAGACTTAAATGTCCCTGTCTGACAGCTT
  TGAAGAGAGTAGTGGTTCTCCCAGCACGCA
• GCTGGAGATCTGAGAACGGACAGACTGCCTCCTCAAGTGGATCCCTGACC
  CCCGAGTAGCCTAACTGGGAGGCACCCCCC
• AGTAGGGGCAGACTGACACCTCACACGGCCAGGTACTCCTCTGAGAAAAA
  ACTTCCAGAGGAACAATCAGGCAGCAACAT
• TTGCTGCTCACCAATATCCACTGTTCTGCAGCCTCTGCTGCTGATACCCA
  GGCAAACAGGGTCTGGAGTGGACCTCCAGC
• AAACTCCAACAGACCTGCAGCTGAGGGTCCTGTCTGTTAGAAGGAAAACT
  AACAAACAGAAAGGACATCCACACCAAAAA
• CCCATCTGTACGTCACCATCATCAAAGACCAAAAGTAGATAAAACCACAA
  AGATGGGGAAAAAACAGAGCAGAAAAACTG
• GAAACTCTAAAAAGCAGAGCGCCTCTCCTCCTCCAAAGGAACGCAGCTCC
  TCACCAGCAACGGAACAAAGCTGGACGGAG
• AATGACTTTGATGAGTTGAGAGAAGAAGGCTTCAGATGATCAAACTACTC
  CAAGCTAAAGGAGGAAATTCAAACCCATGG
• CAAAGAAGTTAAAAACCTTGAAAAAAAATTAGACGAATGGATAACTAGAA
  TAACCAATGCAGAGAAGTCCTTAAAGGAGC
• TGATGGAGCTGAAAACCAAGGCTCGAGAACTACGTGAAGAATGCACAAGC
  CTCAGGAGCCGATGCGATCAACTGGAAGAA
• AGGGTATCAGTGATGGAAGATCAAATGAATGAAATGAAGTGAGAAGAGAA
  GTTTAGAGAAAAAAGAATAAAAAGAAATGA
• gtR2
• TTTTTTTTTTTTTTTAGATGCGGGGTGTCACTGTGTTGCTCAGGCTGGTC
  TCAAACTCCTGGGCTCAAGTGATCCTCCCA

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Parameter setting and post processing

• Parameter setting
• Recommend the smallest l 15
• For the arbitrary length L,
• The length of Q up to 10,000bp on each side
• Remove repeat families with Q lt 50
• Postprocessing
• Tandem Repeat finder, Nseg
• Remove repeat families with gt50 of their length
  annotated as low-complexity and tandem repeats
• RepeatMasker
• Mask the repeat families based on the library

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Benchmark

• C.briggsae genome (108Mb)
• 7h on a single 0.5 GHz DEC Alpha processor

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Combined evidence model of TE
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Overview

• Query Sequences Drosophila melanogaster (Fruit
  fly) Release 3, 4
• Combined evidence model pipeline of
  RepeatMasker, BLASTER, TBLASTX, all-by-all
  BLASTN, RECON, and TE-HMM
• - Methods for the annotation of known TE
  families
• - Methods for the annotation of anonymous TE
  families
• Benchmark FlyBase Release 3.1 annotation
• Sensitivity and specificity,
  characteristics of boundary

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Tools

• Blaster
• compares a query sequences against a subject
  databank.
• Launches one of the BLAST (BLASTN, TBLASTN,
  BLASTX, TBLASTX).
• Cut long sequences before launching BLAST and
  reassembles the results.
• MATCHER
• Maps match results onto query sequences by
  filtering overlapping hits.
• Keeps the match results with E-value lt 10-10 and
  length gt20
• Chains the remaining matches by dynamic
  programming.
• GROUPER
• Gather similar sequences into groups

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Measures

• For each nucleotide,
• TP correctly annotated as belonging to a TE
• FP falsely predicted as belonging to a TE
• TN correctly annotated as not belonging to a TE
• FN falsely predicted as not belonging to a TE

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Method for the Annotation of known TE families

• BLASTER using BLASTN and MATCHER (BLRn)
• RepeatMasker (RM)
• RepeatMasker with MATCHER (RMm)

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Method for the Annotation of known TE families

• BLASTER using BLASTN and MATCHER (BLRn)
• RepeatMasker (RM)
• RepeatMasker with MATCHER (RMm)
• RepeatMasker-BLASTER (RMBLR) combined hits from
  both BLRn and RM and give them to MATCHER

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Method for the Annotation of anonymous TE
families

• all-by-all comparison with BLASTER using BLASTN,
  MATCHER, and GROUPER
• RECON
• BLASTER using TBLASTX and MATCHER
• HMM

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What they (we) learned

• Overall, BLRn outperforms RM with respect to the
  precise determination of TE boundaries.
• RM is more sensitive for the detection of small
  and divergent TE.
• The difference between BLRn and RM make them
  complementary for TE annotation.
• A combined-evidence framework can improve the
  quality and confidence of TE annotation.

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Pipeline structure

• TE detection software BLASTER, RepeatMasker,
  TE-HMM, and RECON
• Tandem repeat detection software RepeatMasker,
  Tandem Repeat Finder (TRF), Mreps
• Database MySQL
• Open Portable Batch System
• Whole genomic sequence was segmented into chucks
  of 200kb overlapping by 10kb.
• The results from different tool were stored in
  the database.
• XML file is generated from the stored results and
  loaded into the Apollo genome annotation tool.

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The Annotation Pipeline
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