Somatic Activity Of Retrotransposons In Human

Hani Ben ShmuelProject advisor: Dr. Erez Levanon

Scientific Background

• Repetitive elements comprise 30–50% of mammalian genomes.

Transposable elements• Transposable elements are discrete pieces of DNA that can move

within genomes.

• TEs can be separated into two major classes:DNA transposons and retrotransposons.

• DNA Transposons can excise themselves from the genome, move as DNA and insert themselves into new genomic sites.

• Retrotransposons duplicate through RNA intermediates that are reverse transcribed and may integrate back to the genome.

Retrotransposons

• Retrotransposons can be subdivided into two groups distinguished by the presence or absence of long terminal repeats (LTRs):

• non-LTR retrotransposons - LINE-1 (L1), Alu and SVAelements.

• LTR retrotransposons - Human LTR elements are endogenous retroviruses (HERVs).

• L1, Alu and SVA non-LTR retrotransposons, collectively account for approximately one-third of the human genome, and are the only TEs currently active in humans.

• Previous methods for Identifying the Activity of Retrotransposons:

1. Comparison between Human and chimpanzee genomes.2. Genomic comparison between two different people.3. Insertions which cause diseases (Hemophilia).4. Inject element into bacteria and detect its expression.

Non-LTR Retrotransposons

The retrotransposition cycle

SVA element• non-LTR retrotransposon.

• ~3,000 copies in the human genome.

• A typical full length SVA element is ~2 kb.

• Made up of a short interspersed element (SINE) region, a variable number of tandem repeats (VNTR) region and an Alu-like region.

Effects on the human genome

• Generating insertion mutations and genomic instability.

• Altering gene expression.

• Contributing to genetic innovation.

• Increase genome size.

• Impact on the evolution of primate genomes in terms of both structure and function.

Impact of retrotransposons on human genome structure:

Impact of retrotransposons on human gene expression:

Project GoalExplore Retrotransposons’

somatic activity in the human genome.

Project Objectives• Building the infrastructure for the project (software, data,

formats, choosing parameters etc).

• Finding the most active element of each retrotransposon.

• Comparing expression level of retrotransposons from brain vs. cell line.

• Identifying recent insertion events of retrotransposons in human.

• Finding evidence for DNA editing in retrotransposons.

Project Importance

• Retrotransposons’ activity can cause dramatic changes in the human’s genome. Therefore,activity of those elements meaning risk in many somatic mutations.

• Insertion events in protein-coding or regulatory regions can alter genome function and influence genome evolution.

Next Generation Sequencing

• Revolutionary improvements in cost and speed of data generation.

• Shorter read length are produced.

• Increase data generation. Helicos

Illumina

Next Generation Sequencing

The Project input data

• RNAseq (transcriptome) from 12 people.

• 4 billion sequences (~0.5 terra).

• Sequenced with SOLiD, Illumina, 454 and helicos.

New data just arrived:• 5 billion sequences.• HiSeq2000, Illumina.• Better quality.

Tools

• BowTie - An ultrafast memory-efficient short read aligner.

• UCSC - Genome browser website.

• Perl - Scripting language.

Bowtie• Bowtie is an ultrafast, memory-efficient short read aligner

geared toward quickly aligning large sets of short DNA sequences (reads) to large genomes.

• Bowtie indexes the genome with a Burrows-Wheeler index.The idea: work hard to create a compact version of the reference(‘indexing’) that can be easily scanned by the short reads.

UCSC

• The site contains the reference sequence and working draft assemblies for a large collection of genomes.

• Tools for retrieving data associated with repeats.

Project steps (1)

1. Find the most active element of SVA: Reads alignment to SVA sequences using BowTie. Parameters adjustment . Relevant reads selection. Alignment to the human genome. Filter reads with more than 3,000 alignments. Find maximal number of hits for each

chromosome. Select the position with maximal hits.

Initial Results (1)

Initial Results (1)

Alignment to SVA dataset:• 24, 427 reads (total: 58,578,322).• 10, 969,837 alignments.

Alignment to Human Genome:• 24,388 reads (99.95%).• ~ 200 million alignments.• After filtering reads with alignments > 3000 ,

12,619,951 alignments.

Initial Results (1)

The most active element (1)

2. Compare expression level of retrotransposons from brain vs. cell line: Parameters selection. UHR (cell line) reads alignment to SVA sequences. Brain reads alignment to SVA sequences. Filter the results. Statistic calculations & Graphs.

Project steps (2)

Initial Results (2)• 100bp

• 50bp

Initial Results (2)

Summary

• Building infrastructure for the project.

• Using next generation sequencing as a research platform to identify the most active element of SVA in the human genome.

• Indication that there is no significant difference between the expression level of retrotransposons from brain and cell line.

What is next?

• Running the alignments and scripts on the new data.

• Getting results for other retrotransposons.

• Identifying recent insertion events of retrotransposons in human.

• Finding evidence for DNA editing in retrotransposons.

Thanks to:Dr. Erez Levanon