A BIOINFORMATIC GENE HUNTING

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Bioinformatics

When biology meets informatics

What is bioinformatics?

•Creation and maintenance of databases to store biological information

•Development of mathematical and statistical tools for analysis, interpretation and continuous updating of biological information

•Development of new tools to assess relationships among members of large data sets in order to obtain a comprehensive picture of normal cellular activities and their alterations

•Data sharing

Bioinformatics includes:

1. Databases collecting

experimental data generated in

research laboratories

2. Software for navigating

databases

Where does bioinformatics stem from?

Human Genome Project

Experimental efforts to determine structure

and function of biologicalmolecules

Production of large data sets

Molecular biology databases(genes and proteins)

Interpretation

Techniques, tools, algorithmsfor analysis, comparison, classification,interpretation

The global approach to the study of biological data refers to the possibility for analysis and

comparison of:

• Genomes ( the whole genetic information of a given organism)

• Transcriptomes ( the full set of RNAs of a given organism )

• Proteomes ( the full set of proteins of a given organism)

Applications of bioinformatics analysis

MEDICINE

AGRICULTUREPHARMACEUTICS

A database is a collection of information.

Databases are made of “entries”.

Databases

Biological databases •A biological database is a large collection of information and data derived from laboratory studies (in vitro and in vivo analysis), from bioinformatics (in silico analysis) and from the scientific literature.

•Data are structured so to enable efficient user access and management of different types of information.

Bioinformatics was essential to obtain the complete sequence of

the human genome

Genomic DNA

Random long (5-20 kb) and short (0.4-1.2 kb) fragments derived from mechanical breakage of DNA were cloned in

vectors and sequenced.

Bidirectional automated sequencing

Computerized reconstruction of genomic sequence

Whole genome shotgun

Primary and specialized

databases

Primary databases collect nucleotide sequences (DNA , RNA) or protein sequences containing general information for the retrieval of sequences, and to identify species of origin and function.

Specialized databases collect large sets of homogeneous records (taxonomic, functional, literature, etc. etc...), with additional annotations and specific information.

---ATGTTGAAGTTCAAGTATGGT---

--MLKFKYG--

Nucleotide sequence database

Amino acid sequence database

3D structures database

Genetic diseases database

Gene expression database

How to extract information from a

database

We can combine different criteria by means of Boolean operators to intersect (operator AND), add (operator OR) or exclude (operator BUT NOT) information. More Boolean operators are available for more sophisticated searches (IN, NEAR and WITH).

By entering a text in a box (like with a search engine, i.e. google) or filling in a given form

AND

OR

BUT NOT

Algorithms in bioinformatics

Algorithms to compare sequences:- to assess similarities - to study molecular evolution and phylogenesis

Algorithms to predict:- genes- regulatory elements (promoters, etc.)- RNA structures- protein structures

Some important results obtained by bioinformatics:

• Search for homologous genes in the same and in different species

• Identification of genes and genetic markers

• Identification of disease-associated genes

• Prediction of three-dimensional structures of proteins

• Design of new drugs

• Data sharing

Genetic-based differences in the response to drugs

Comparing two human genomes, single base differences are found, on average, every 1200-1500 base pairs

Each individual is unique

A new “omics” discipline: PHARMACOGENOMICS

What is pharmacogenomics for?

Patient with genetic defect

reduced dose of drug

standard drug

1/10 thiopurine

What do you need to know to “surf among the genomes”

without being submerged by the waves !!!

Chromosome structure and classification

metacentric acrocentricsubmetacentric

long arm

q

short arm

p

satellite

centromere

Human karyotype and chromosome map

Chromosome banding

Karyotype: Q banding

Karyotype: G banding

Each chromosomehas a specific

banding pattern

Chromosomes mutations

Fig.10.2.1 Mutazioni cromosomiche

delezione

traslocazione

inversione

Basi perse

GAC-AAA-GGA-TGA-CTG original sequence

GAC-AAA-CGA-TGA-CTG substitution

GAC-AAA-TGG-ATG-ACT-G insertion

GAC-AA~G-GAT-GAC-TG deletion

Gene mutations or point mutations

Identification of genes and genetic

markers

Identification of disorder-

associated genes

From gene to protein

Exon 1 Exon 2 Exon 3 Exon 4

Intron 1 Intron 2 Intron 3

Starttranscription

Endtranscription

H2N

Transcription

COOH

5’UTR

3'

5'3'

3'5'

Maturation

Translation

DNA

preRNA

mRNA

protein

5'

3’UTR

Prediction of genes within a genomic region

• Internal exons (---exon---gt---intron---ag---exon---)• First exon (5’ UTR sequence)• Last exon (3’ UTR sequence)• Unique exons• Alternative splicing sites• Promoters (TATA e CAAT boxes)• Polyadenylation signals (AAUAAA)• start codon ATG• STOP codon

splice sites

Splicing

Alternative splicing

Alternative splicing

Here is a comprehensive view of what you should find among the

genome waves .… enjoy your surfing!!

QuickTime™ and a TIFF (Uncompressed) decompressor are needed to see this picture.

Finding the Genes

Dr. Blat helping a gene find itself.

Chromosomes mutations

Fig.10.2.1 Mutazioni cromosomiche

delezione

traslocazione

inversione

Basi perse

GAC-AAA-GGA-TGA-CTG original sequence

GAC-AAA-CGA-TGA-CTG substitution

GAC-AAA-TGG-ATG-ACT-G insertion

GAC-AA~G-GAT-GAC-TG deletion

Gene mutations or point mutations

Bioinformatics uses algorithms

Algorithms to compare sequences:- to assess similarities - to study molecular evolution and phylogenesis

Algorithms to predict:- genes- regulatory elements (promoters, etc.)- RNA structures- protein structures

Genome sequence

Sequence Similarity Searches

Genome sequerce

Ganome sequence

Genome spequence

Genetic variability

Genme sequence

mutations

•Evolution implies the generation of morphological

and molecular variants.•At the molecular level, variants are created by

errors (mutations) during DNA replication not

corrected by DNA repair systems. •Introduction of mutations (single aa substitutions,

deletions, insertions) imply that DNA segments

with the same function in different organisms don’t

share exactly the same sequence.

Sequences conservation and

evolution

Sequence alignment programs to study variability

Sequence alignment establishes a biunivocal relationship between two sequences (or parts of them) so minimizing the number of operations necessary to transform one sequence into the other.

Alignment is obtained by comparing

sequences in a pairwise fashion

Each comparison is given a score which is

a measure of the degree of similarity

E V D Q K I S - - K W D| | | | | | |E V - K K I T R P K W D

SA= E V D Q K I S K W D

SB= E V K K I T R P K W D

gap mismatchmatch

Alignment:

When sequences are not identical, the alignment must contain gaps and mismatches

Identity, Similarity and HomologyIdentityThe extent to which two sequences are invariant

SimilarityQuantitative parameter defined by the alignment score

HomologyOrigin from a common ancestor sequence

Homologous Sequences

ATA GAAKAVALVLPNLKGKLNGIALRVPTPNVSVVDLVVQVSKK-TFAEEVNAAFRDSAEK-- 328ATB GAAKAVSLVLPQLKGKLNGIALRVPTPNVSVVDLVINVEKKGLTAEDVNEAFRKAANG-- 351HS GAAKAVGKVIPELNGKLTGMAFRVPTANVSVVDLTCRLEKP-AKYDDIKKVVKQASEG-- 268MM GAAKAVGKVIPELNGKLTGMAFRVPTPNVSVVDLTCRLEKP-AKYDDIKKVVKQASEG-- 266XL GAAKAVGKVIPELNGKITGMAFRVPTPNVSVVDLTCRLQKP-AKYDDIKAAIKTASEG-- 266DM GAAKAVGKVIPALNGKLTGMAFRVPTPNVSVVDLTVRLGKG-ASYDEIKAKVQEAANG-- 265CE GAAKAVGKVIPELNGKLTGMAFRVPTPDVSVVDLTVRLEKP-ASMDDIKKVVKAAADG-- 274SP GAAKAVGKVIPALNGKLTGMAFRVPTPDVSVVDLTVKLAKP-TNYEDIKAAIKAASEG-- 268ATC GAAKAVGKVLPALNGKLTGMSFRVPTVDVSVVDLTVRLEKA-ATYEEIKKAIKEESEG-- 272OS GAAKAVGKVLPDLNGKLTGMSFRVPTVDVSVVDLTVRIEKA-ASYDAIKSAIKSASEG-- 270SC GAAKAVGKVLPELQGKLTGMAFRVPTVDVSVVDLTVKLNKE-TTYDEIKKVVKAAAEG-- 266ECA GAAKAVGKVLPELNGKLTGMAFRVPTPNVSVVDLTVRLEKA-ATYEQIKAAVKAAAEG-- 266HI GAAKAVGKVLPALNGKLTGMAFRVPTPNVSVVDLTVNLEKP-ASYDAIKQAIKDAAEGKT 268ECC GAAKAIGLVIPELSGKLKGHAQRVPVKTGSVTELVSILGKK-VTAEEVNNALKQATTN-- 266

Homologous sequence comparison helps in:

•identifying important structural and functional domains of a given protein•identifying aa residues responsible for common features and those responsible for different features of a given protein

Degree of Sequences Conservation • In sequence alignment both sequence identity

and degree of conservation of different aa residues in positions where the two sequences differ are taken into consideration.

• Molecules with similar primary aa sequence tend to have similar secondary and tertiary structures

• If two proteins share 50% of their sequence, the probability that they have superimposable 3D structures is very, very high

Conservative (two aa with similar chemical properties) substitutionsSemi-conservative substitutionsNon-conservative substitutions

Genes in evolutionHomologous genes are those evolved from a common ancestral precursor gene:

•orthologous genes: genes in different species that have evolved directly from an ancestral gene, generally maintaining the same function.

•paralogous genes: two genes or clusters of genes at different chromosomal locations in the same organism that have structural similarities and have diverged from the parent copy by duplication. In general, their function is different although correlated with that of the ancestral precursor gene.

The three-letter and one-letter amino acid code

Amino acid polarity

polar aanon polar aa

+ -

Sequence conservation during evolution

• Evolution doesn’t work on DNA sequences or on primary structures of proteins, but only on 3D structures of proteins

• As a consequence of this and of the degeneration of the genetic code, 3D structure of proteins is more conserved than primary structure, which in turn is more conserved than the nucleotide coding sequence

-ATGTTGAAGTTT-- M L K F -

-ATGTTGAAGTTT-- M L K F -

-ATGTTGAAGTTT-- M L K F -

-ATGTTGAAGTTC-- M L K F -aa sequence identity

-ATGTTGAAGTAT-- M L K Y -

Different aa sequence, conserved

structure

-ATGTTGAAGGTT-- M L K V -

Different aa sequence, altered 3D

structure

Model organismsModel organisms

Zebrafish Danio rerio

Mouse Mus musculus30.000 geni19.000 geni

Nematode Caenorhabditis elegans

Fruit flyDrosophila melanogaster

30,000 genes

13.600 geni

Unknown Function

The specific function of the major part of the human genome is unknown