sequence analysis - lärplattform moodle · sequence analysis part 1 • sequence analysis: general...

Sequence Analysis

Introduction to BioinformaticsBIMMS

December 2015

Gabriel TekuDepartment of Experimental Medical Science

Faculty of Medicine Lund University

Sequence analysis

Part 1

• Sequence analysis: general introduction

• Sequence features

• Motifs and Domains Part 2

• Galaxy

• EMBOSS

• Bioinformatics software for sequence analysis

Sequence analysis

Part 1

• Sequence analysis: general introduction

• Sequence features

• Motifs and Domains

Sequence analysis: definition

… refers to the process of subjecting a DNA, RNA or

peptide sequence to any of a wide range of analytical

methods to understand its features, function,

structure, or evolution...

[http://en.wikipedia.org/wiki/Sequence_analysis]

http://en.wikipedia.org/wiki/Sequence_analysis

Quick sequence analysis example

1. Obtain the protein sequence encoded by Human elastase gene from Uniprot, P08246

2. Obtain the CDS sequence for the protein.

http://www.ebi.ac.uk/Tools/st

1. Translate the CDS sequence obtained above




Quick sequence analysis example

4. Compare the translated CDS to the protein sequence obtained from 1 above.

http://www.ebi.ac.uk/Tools/msa/clustalo/

http://www.ebi.ac.uk/Tools/msa/clustalo/

Types of sequence analysis

Searching databases

Sequence alignments

Feature analyses

Feature analysis

Part 1

• General introduction

• Feature analyses


What is a feature

Sequence features are groups of nucleotides or amino

acids that confer certain characteristics upon a gene or

protein, and may be important for its overall function.



Protein features

Gene features

Exercise on features

1. Explore the features along the protein P08246

within UniProt

2. View the protein’s structure from pdb by following

the 3D structure link for 1h1b.

Quick exercise on motifs and domains

1. Identify the functional motif(s) of the protein P08246

Use PROSITE link from Uniprot Family & →Domains

2. What is the motif as represented by the database entry

Sequence analysis

Part 1

• General introduction

• Features


Motifs

• Short, conserved sequence patterns

• Associated to specific function(s)

Binding site

Active site

• ~ 10 - 30 amino acids

• Prosite

Motifs

Motifs: prosite

From CDS to protein sequence

Statistically significant motifs

Functional motifs

Protein family by virtue of similar functional sites

Quick exercise on scanning for motifs

1. Use the protein sequence of the gene ELANE to scan

prosite for motifs and domains.

2. Compare the results with that of the previous

exercise.

Motifs: prosite

Methodology

• Pattern development

Pattern from literature

Profiles

• Based on signature patterns

• Sensitivity

• Specificity

Pattern development

• Literature curated patterns

published

curated

tested against Swiss-Prot for specificity

Pattern development

• New patterns

start with review article

alignment of proteins from article

focus on biologically important regions

create core pattern

Pattern development

• New patterns (contd)

Search Swiss-Prot using core sites

Retain/discard core pattern

Refine core pattern and repeat search

Pattern development

Patterns

• Prosite syntax for patterns:

• one-letter codes for amino acids, e.g. G=Gly

• elements separated by a hyphen, “-”

• “X” used where any amino acid is accepted,

Patterns

Prosite syntax for patterns contd:• Ambiguities indicated by [ ],

e.g. [AG] means Ala or Gly,

• Amino acids that are not accepted at a given position are

listed between curly braces, “{ }”, e.g. {AG} means any amino acid except Ala and Gly,

Patterns

Prosite syntax for patterns contd:• repetitions are placed between braces,“( )”,

e.g. [AG](2,4) means Ala or Gly between 2 and 4 times,

• a pattern is anchored to the N-terminal or C-terminal by

“<“ and “>”, respectively.

G H E G V G K V V K L G A G A

G H E K K G Y F E D R G P S A

G H E G Y G G R S R G G G Y S

G H E F E G P K G C G A L Y I

G H E L R G T T F M P A L E C

G H E G V G K V V K L G A G A

K K Y F E D R A P S S

F Y G R S R G G Y I

L E P K G C P L E C

R T T F M

G-H-E-X(2)-G –X(5)-[GA]-X(3)

Quick exercise

Interpret the motif you obtained from the previous exercise.

Methodology

• Pattern development

Pattern from literature

New patterns

• Profiles

Motifs: prosite

Profiles

Popular approaches

• position weight matrix

• HMM

Position weight matrix

1 2 3 4 5 6

1 A T G T C G

2 A A G A C T

3 T A C T C A

4 C G G A G G

5 A A C C T G

Pos.1 2 3 4 5 6 Overall

freq.

A 0.6 0.6 - 0.4 - 0.2 0.30

T 0.2 0.2 - 0.4 0.2 0.2 0.20

G - 0.2 0.6 - 0.2 0.6 0.27

C 0.2 - 0.4 0.2 0.6 - 0.23


freq.

A 0.6 0.6 - 0.4 - 0.2 0.30

T 0.2 0.2 - 0.4 0.2 0.2 0.20

G - 0.2 0.6 - 0.2 0.6 0.27

C 0.2 - 0.4 0.2 0.6 - 0.23


freq.

A 2.0 2.0 - 1.33 - 0.67 0.30

T 1.0 1.0 - 2.0 1.0 1.0 0.20

G - 0.74 2.22 - 0.74 2.22 0.27

C 0.87 - 1.74 0.87 2.61 - 0.23


freq.

A 2.0 2.0 - 1.33 - 0.67 0.30

T 1.0 1.0 - 2.0 1.0 1.0 0.20

G - 0.74 2.22 - 0.74 2.22 0.27

C 0.87 - 1.74 0.87 2.61 - 0.23

Pos.1 2 3 4 5 6

A 1.0 1.0 - 0.41 - -0.58

T 0.0 0.0 - 1.0 0.0 0.0

G - -0.43 1.15 - -0.43 1.15

C -0.2 - 0.8 -0.2 1.38 -

Pos.1 2 3 4 5 6

A 1.0 1.0 - 0.41 - -0.58

T 0.0 0.0 - 1.0 0.0 0.0

G - -0.43 1.15 - -0.43 1.15

C -0.2 - 0.8 -0.2 1.38 -

Pos.1 2 3 4 5 6

A 1.0 1.0 - 0.41 - -0.58

T 0.0 0.0 - 1.0 0.0 0.0

G - -0.43 1.15 - -0.43 1.15

C -0.2 - 0.8 -0.2 1.38 -Sum of logs = 6.33 A A C T C G

Profile

• Multiple sequence alignments with gaps

• Gap penalties

• Profile = PSSM that includes gap penalties

• Fine tuning gap parameters to achieve good profiles

Building a profile: PSI-BLAST Query sequence

BLAST

MSA

Profile A C B E123...

BLAST

Additional homologs

Incorporated profile

New profile A C B E123...

Iterate process

MEME Suite Example

Quick exercise

1. BLAST the protein P08246 against the Uniprot proteins.2. Select the first 5 hits and download the sequences in

fasta format3. Launch the MEME program at http://meme-suite.org/

4. Using the downloaded sequence file above, search for possible motifs using the MEME program.

5. Compare the results to that from Prosite.6. Leave the results open for later.

http://meme-suite.org/

Profiles from Hidden Markov Models

• More efficient

• From speech recognition

• Based on Markov Models

• Statistical approach

Some motif resources

• PROSITE

• PRINTS

• SMART

• InterProhttp://www.ebi.ac.uk/interpro/about.html

http://www.ebi.ac.uk/interpro/about.html

Domains

• Longer than motifs

• conserved sequence patterns

• Independent structural and functional unit

• Average length, 100 aa

• May (not) include motifs along boundries

Domains

• HMM applied in domain identification due to its

robustness.

• Some domain databases include

• Pfam-A

• Pfam-B

• Prodom

• MEME suite

Quick exercise

1. Identify the domain(s) of the P08246 protein.

2. Explain how you accomplished the task.

PART 2

• Galaxy

• EMBOSS

• Bioinformatics software for sequence analysis

• Open source tools

• Commercial softwares

Galaxy

• https://usegalaxy.org/

• One-stop shop

• from single sequence to NGS

• Open source

Sequence Analysis Introduction

Introduction to galaxy

http://galaxy.bmc.lu.se/


Which coding exon has the highest number of single nucleotide polymorphisms (SNPs) on chromosome 22?

Galaxy tutorial

Register

Login

Familiarize

Galaxy tutorial

https://github.com/nekrut/galaxy/wiki/Galaxy101-1

Galaxy tutorial: demo and exercise

1. Complete the galaxy 101 tutorial.

2. Share the final workflow.

3. Briefly describe the workflow in your own words.

4. Re-use the workflow, but this time; choose All SNPs

dataset as feature.

Galaxy Demo&

Exercise

EMBOSS

The European Molecular Biology Open Software Suite

Large user community

Available on the web, for many OS, servers and stand-alone

If you know how to use one, then you know how to use all

Mature and stable


EMBOSS

What is it good for? Sequence alignment Database search with sequence patterns Motif identification and domain analysis Nucleotide sequence pattern analysis


http://emboss.sourceforge.net/

EMBOSS FROM SOURCEFORGE

EMBOSS programs within galaxy

Many other portals

http://www.ebi.ac.uk/Tools/emboss/

http://emboss.bioinformatics.nl/

http://imed.med.ucm.es/EMBOSS/

http://www.bioinformatics2.wsu.edu/emboss/

http://pro.genomics.purdue.edu/emboss/

Quick CpG islands background for next exercise

Region of high density CG dinucleotides along the DNA 200 – 500 nucleotides, enriched with CG Enriched CpG nucleotides

The p in CpG islands represent the phosphodiester bond between the C and G nucleotides

Mostly occur within the promoter of eukaryotic genes Lock gene in an inactive stateHelps identify the transcription start site of a gene

Exercise

From galaxy, emboss toolshed:

List all tools that analyze CpG islands

On the search field, type in “cpg”

Access the documentation for two of these tools,

Preferably cpgplot and newcpgreport

Exercise• Write down the expected result

• Run the tools on the human gene ELANE

• Interpret the results.

Software for sequence analysis

• Open source tools

• Commercial tools


• Websites with links to open source tools and services

http://www.ebi.ac.uk/services

http://www.ncbi.nlm.nih.gov/guide/sequence-analysis/

http://bioinformatics.ca/links_directory/

http://bioinformatics.ca/links_directory/category/dna/structure-and-sequence-

feature-detection


Open source GNU general public licenses (GNU GPL)

• Continuous evolution of code• Community supported

Examples• EMBOSS• mothur


Commercial tools Proprietary Expensive licenses Examples

• Geneious (Biomatters Ltd., Auckland, New Zealand)

• CLC Genomics Workbench (CLC bio, Aarhus, Denmark)

• Sequencher (Gene Codes Corporation, MI, USA)

Software Company Cost (USD)a NGS analysesc Evolutionary analysesd Database searchinge Workflows

Avadis NGS Strand Scientific Intelligence $4500 ✓ ✗ ✗ ✓

CLC Genomics Workbench ClC bio, Qiagen $5500 ✓ ✓ ✓ ✓

CodonCode Aligner CodonCode $720 ✓ ✓ ✗ ✗

Genamics Expression Genamics $295 ✗ ✓ ✓ ✗

Geneious Biomatters $795 ✓ ✓ ✓ ✓

Full Lasergene Suite DNASTAR $5950 ✓ ✓ ✓ ✓

MacVector & Assembler MacVector $300 ✓ ✓ ✓ ✗

NextGENe Softgenetics $4049 ✓ ✗ ✗ ✗

Sequencher Gene Codes $2500 ✓ ✓ ✓ ✗

VectorNTI Advance Life Technologies $600 ✗ ✓ ✓ ✓Smith DR, Brief Bioinform. 2014 Sep 1

Commercial software and feature offerings

sequence analysis - lärplattform moodle · sequence analysis part 1 • sequence analysis: general...

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