Insilico Gene Analysis

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In silico Gene Analysis


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Outline

Introduction

Alignment

ORF searching

3D protein modeling

Case study


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INTRODUCTIONWhat is gene?

What are the essential components of a gene

Initiation codon

Intron and exons(in eukaryotes)

Stop codon

Regulatory sequences

A length of DNA which codes for a particular protein, or in certain

cases a functional or structural RNA molecule


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INTRODUCTION .

Essential feature of gene which are considered for in silico gene analysis

All proteins contains 20 amino acids (one letter code)

Stop codons are also fixed TAA, TAG and TGA

Intron boundaries- GU-AC

Codon usage differs from organism to organism

All nucleotide sequences essentially contains A, T,G and C

Initiation codon is fixed - ATG


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FILE FORMATS

FASTA format>XM_414949 | Gallus gallus |alpha 2 globinMVLSAADKNNVKGIFTKIAGHAEEYGAETLERMFTTYPPTKTYF

GI format

; comment;commentXM_414949

MVLSAADKNNVKGIFTKIAGHAEEYGAETLERMFTTYPPTKTYF1

GDE format

%XM_414949 | Gallus gallus |alpha 2 globinMVLSAADKNNVKGIFTKIAGHAEEYGAETLERMFTTYPPTKTYF

NBRF/PIR format

>P1; XM_414949 | Gallus gallus |alpha 2 globinMVLSAADKNNVKGIFTKIAGHAEEYGAETLERMFTTYPPTKTYF


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ALIGNMENTS

The result of a comparison of two or more gene or protein sequences in

order to determine their degree of base or amino acid similarity

ALIGNMENT

Pair wise Alignment Multiple Alignment

Local Alignment Global alignment


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>NG_000007 |chromosome 11| beta hemoglobin|Homo sapiens

>NG_000007 |chromosome 11| beta hemoglobin|Homo sapiens

REFERENCE SEQUENCE

atggtgcatctgactcctgaggagaagtctgccgttactgccctgtggggcaaggtgaacgtggatgaagttggtggtgaggccctgggcaggctgctggtggtctacccttggacccagag

gttctttgagtcctttggggatctgtccactcctgatgctgttatgggcaaccctaaggtgaaggctcatggcaagaaagtgctcggtgcctttagtgatggcctggctcacctggacaacctcaagggcacctttgccacactgagtgagctgcactgtgacaagctgcacgtggatcctgagaacttcaggctcctgggcaacgtgctggtctgtgtgctggcccatcactttggcaaagaattcaccccaccagtgcaggctgcctatcagaaagtggtggctggtgtggctaatgccctggcccacaagtatcactaa

MVHLTPEEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPK ZVKAHGKKVLGAFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFG KEFTPPVQAAYQKVVAGVANALAHKYH


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Sequences may be nucleotide-nucleotide or amino acid-amino acid

PAIRWISE ALIGNMENT

Two sequences are compared at a time

It may be gaped/ un-gaped alignment

Ex : BLAST and FASTA

Two algorithms Smith- Waterman algorithm (local alignment)

Needleman-Wunsch algorithm (global alignment)


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BLAST (Basic Local Alignment Search Tool)

Pair wise local alignment

Developed by Stephen Altschul, Warren Gish, David Lipman

BLAST searches for short matches of a fixed length W between the

query and sequences in the database

Stages in search

BLAST performs an ungapped alignment between the query and databasesequence on either sides , if they share a common word.

BLAST performs a gapped alignment between the query sequence and the

database sequence


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BLAST .

It consider whole database as one

sequence and align the query

sequence

high-scoring segment pairs


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BLAST ..

Low complexity region


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FASTA

Pairwise local alignment

Developed by David J. Lipman and William R. Pearson in 1985

It looks for identically matching word length called ktup

It identifies single high scoring region

It matches individual sequence of database with query sequence


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FASTA .

It aligns the individual database

sequence with Query sequence

E value is different from BLAST

E= Np


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PROTEIN MATRICES

C 1

S 0 1

T 0 0 1

P 0 0 0 1

A 0 0 0 0 1

G 0 0 0 0 0 1N 0 0 0 0 0 0 1

D 0 0 0 0 0 0 0 1

E 0 0 0 0 0 0 0 0 1

Q 0 0 0 0 0 0 0 0 0 1

H 0 0 0 0 0 0 0 0 0 0 1

R 0 0 0 0 0 0 0 0 0 0 0 1

K 0 0 0 0 0 0 0 0 0 0 0 0 1

M 0 0 0 0 0 0 0 0 0 0 0 0 0 1

I 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

L 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1V 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

F 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

Y 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

W 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

C S T P A G N D E Q H R K M I L V F Y W

C 12

S 0 2

T -2 1 3

P -1 1 0 6

A -2 1 1 1 2

G -3 1 0 -1 1 5

N -4 1 0 -1 0 0 2

D -5 0 0 -1 0 1 2 4

E -5 0 0 -1 0 0 1 3 4

Q -5 -1 -1 0 0 -1 1 2 2 4

H -3 -1 -1 0 -1 -2 2 1 4 3 6

R -4 0 -1 0 -2 -3 0 -1 -1 1 2 6

K -5 0 0 -1 -1 -2 1 0 0 1 0 3 5

M -5 -1 -1 -2 -1 -3 -2 -3 -2 -1 -2 0 0 6

I -3 0 0 -2 -1 -3 -2 -2 -2 -2 -2 -2 -2 2 5

L -6 -2 -2 -3 -2 -4 -3 -4 -3 -2 -2 -3 -3 4 2 6V -2 0 0 -1 0 -1 -2 -2 -2 -2 -2 -2 -2 2 4 2 4

F -4 -3 -3 -5 -4 -5 -4 -6 -5 -5 -2 -4 -5 0 1 2 -1 9

Y 0 -3 -3 -5 -3 -5 -2 -4 -4 -4 0 -4 -4 -2 -1 -1 -2 7 10

W -8 -5 5 -6 -6 -7 4 7 7 5 3 2 -3 -4 -5 -2 -6 0 0 17

C S T P A G N D E Q H R K M I L V F Y W

Associated substitution matrix PAM250 matrix

S

UB

J

E

C

T

QUERY


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GAPS AND PENALTIES

Constant penalty : usually it is 1

Proportional penalty : depends on length of the gap

Affine : gap openig penalty + gap extension penalty

S = actual alignment score from matrix gap penalty


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RESTRICTION SITES


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MULTIPLE ALIGNMENT

More than two sequences

Gaps are frequent

Always global alignment


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WHY DO WE NEED MULTIPLE ALIGNMENT ???

Homology searching between the sequence

To characterize the protein families-conserved domains, promoters etc,

Designing special probes, degenerated primers etc,..

Required in Protein modeling

Helps in prediction of secondary and tertiary structure of new sequence

Input for constructing phylogenetic tree


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MULTIPLE ALIGNMENT ALGORITHMS

Hierarchical method (Clustal W) Divide and conquer method

AB

C

D

E


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MULTIPLE ALIGNMENT .

Gaps

Conserved

region


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CONSERVED DOMAIN SEARCH

Conserved domain

Some amount of sequence (20 %) missing in blastat C terminal end


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SOFTWARE AVAILABLE

Clustal W / X

Bioedit

Q align

CLC free work bench

Gene tool

Vector NTI

NCBI server

EMBL server


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PHYLOGENETIC ANALYSIS

Sequence should be correct and originated from specified source

Sequences should be homologous

Each position in a alignment should be homologous with every other

in that alignment

No contamination of sequence i.e., nuclear and organelle genomes


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PHYLOGENETIC ANALYSIS.

Distance method

Tree building methods

Character based method

UPGMA NJ

Maximum parsimony method Maximum likelihood method


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SP

G

At

LAo

H

L

S

P

G

AoAt

H

NEIGHBOUR JOINING METHOD


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ORF SEARCHING

Molecular biology background

ORF contains following features

Initiation codon

Stop codon

Intron boundaries

Defined codon usage


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ORF FINDING ALGORITHMS

Content-based method

Site based method

Comparative method


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ORF FINDING ALGORITHMS

Text information

Graphical view

-Hemoglobin gene


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GENSCAN

Gene tool

CLC free work bench

SOFTWARE AVAILABLE


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PROTEIN THREE DIMENSIONAL MODELING

Comparative modeling

Fold recognition

Ab initio prediction


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COMPARATIVE PROTEIN MODELING

start

Identify related structure

Select Template

Evaluate the model

Align target sequence withtemplate structure

Build model for target

ModelOK?

YESend

NO


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Bovine hemoglobin Human hemoglobin Beta chain

COMPARATIVE PROTEIN MODELING


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SOFTWARE AVAILABLE

Cn3D

Bioediter

Deep view / swiss-pdb viewer


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OTHER METHODS

Also called as protein threading

It uses the library of models

Based on library information model is constructed

Fold recognition

Ab initio prediction

Uses the the thermodynamics and quantum mechanism

Insilico Gene Analysis

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