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>=Bioinformatics: from Sequence to Knowledge

Outline:• Introduction to bioinformatics• The TAU Bioinformatics unit • Useful bioinformatics issues and databases: the use of genome browsers, identifying gene splicing, pseudogenes, mutation severity prediction, PCR utilities, other useful tools• In brief: High-throughput technologies and experimental options• The protein space1

Dr. Metsada Pasmanik-Chor, Bioinformatics Unit, Tel Aviv University

The biotechnology revolution creates high-throughput data

http://chagall.med.cornell.edu/BioinfoCourse/presentations2010/Lecture1_2010.pdf

Late 60’s, early 70’s 1980s 21st century

2Dr. Metsada Pasmanik-Chor, Bioinformatics Unit, Tel Aviv University

http://chagall.med.cornell.edu/BioinfoCourse/presentations2010/Lecture1_2010.pdf

The human genome project (HGP)

Francis Collins (chairman of the international project from the NIH): “I think this is probably the most important scientific effort that mankind has ever mounted. That includes splitting the atom and going to the moon”.

1990-2003: Aim: to reveal the blueprint of human biology (3,000,000,000 letters).


Dr. Metsada Pasmanik-Chor, Bioinformatics Unit, Tel Aviv University4

The human genome project (HGP): sequencing strategies


Genomes for everyone

2014

+>=

>=

http://www.advances-in-genomics.org/presentations/Flicek.pdf

Huge amount of data

What do we do with all

this???


http://www.advances-in-genomics.org/presentations/Flicek.pdf

Goal: Make sense of bio-medical data using computer tools, and thereby bridge the gap between molecular biology and computer

science .

Data produced by Bio-Med labs &

stored in database

Analysis & better understanding

BioinformaticsBioinformaticsAlgorithmsAlgorithms and Toolsand Tools

Enables large scale analysis and interpretation of data. Provides computational methods for global understanding of biological data.

Why Bioinformatics?



Bioinformatics topics are all linked together

• – Bioinformatics helpdesk (phone or e-mail) for short and urgent questions

• - Extended consultation, usually sets of appointments and many discussions are required before analysis is complete

• - Research is done as part of collaboration with Bio-Med labs., resulting in joined papers or/and grant proposal submission

Consultation at TAU Bioinformatics Unit


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http://images.google.co.il/imgres?imgurl=https://neeis.gsfc.nasa.gov/Images/hotline.gif&imgrefurl=https://neeis.gsfc.nasa.gov/JDbGenie/vol1/htdocs/edcats/help_desk1.html&h=194&w=216&sz=4&hl=iw&start=10&tbnid=gkt1TlUxqCkJHM:&tbnh=96&tbnw=107&prev=/images%3Fq%3Dhot%2Bline%26svnum%3D10%26hl%3Diw%26lr%3D%26sa%3DG

http://images.google.co.il/imgres?imgurl=http://www.howard.edu/schoolcommunications/Journalism/hukc/hukcgraphics/grant.GIF&imgrefurl=http://www.howard.edu/schoolcommunications/Journalism/hukc/hukc%2520contents.htm&h=272&w=482&sz=11&hl=iw&start=85&tbnid=CLeaJCoQ7zFUsM:&tbnh=73&tbnw=129&prev=/images%3Fq%3Dgrant%2Bproposal%26start%3D80%26ndsp%3D20%26svnum%3D10%26hl%3Diw%26lr%3D%26sa%3DN

Why use consultation when many databases and tools are free and easy-to-use ?


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• Bioinformatics is a huge and dynamic field• New databases and tools are published every day, not all are good or even working, updates are crucial !• Choosing parameters for bioinformatics tools can be tricky and may change results dramatically !!!• Not always there ISIS a bioinformatics solution to every question, if not today, maybe tomorrow !

Rules of thumb !


• Use bioinformatics ! Google for new tools !

• It is best to use bioinformatics tools at the planning stage of experiment, and

not after performing it

• Make sure you use at least 2-3 different algorithms, with different

parameters, rely mainly on results that agree using different analyses

• Stick to mainstream databases and tools, as databases vary in content,

reliability, updates and handiness

• When you compare experiments, you are comparing the combination of the

experiment and the analysis, which may vary

•Do not hesitate to contact us if you have questions, as experience may save

you time and efforts11

Name Tel.Activity

Dr. Metsada Pasmanik-Chor

x 6992Genomics, DNA and proteins sequence analysis, microarray and Next Generation design and analysis

Adva Yeheskelx 6840Proteomics and structural biologyDr. Orly Yaron and Dr. Shira Modai

x 5251Microarray and next generation sequencing design and experiments (wet lab)

Bioinformatics students, projects

Collaborations in student projects on various subjects

Goals: bioinformatics teaching, scientific research and grant proposal collaborations


TAU Bioinformatics UnitWeb-page :http://www.tau.ac.il/lifesci/bioinformatics.html

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http://www.tau.ac.il/lifesci/bioinformatics.html


TAU Bioinformatics UnitWeb-page :http://www.tau.ac.il/lifesci/bioinformatics.html

http://www.tau.ac.il/lifesci/bioinformatics.html


Sequence analysis: a multistep process

http://genome.cshlp.org/content/13/1/1.long

Homolog genes: derived from a common ancestral gene

Ortholog genes: rising from speciation

Paralog genes: duplication of a chromosomal segment

HomoloGene database:http://www.ncbi.nlm.nih.gov/homologene

http://genome.cshlp.org/content/13/1/1.long

http://www.ncbi.nlm.nih.gov/homologene

Homologues and Sequence Conservation = Functionality

http://www.pgaeducation.org/tutoria/WUSTL/BerkeleyPGACompGeno_Boffelli.2.ppt#325,4,Slide

AGTTGAAACCTATAAATGCGTGATGGAGCGGTGGGATAGTTGAAACCTATAAATGCGTGATGGAGCGGTGGGAT

TACATTTCGACTATAAATGCGTATCGCCTCGCAACCCAATACATTTCGACTATAAATGCGTATCGCCTCGCAACCCAA

Conservationscale

sequence

AA

AA

diverged

CTATAAATGCGTCTATAAATGCGT

CTATAAATGCGTCTATAAATGCGT

conserved

80 m

illio

n ye

ars

potential functional region

Metsada Pasmanik-Chor, Ph.D. TAU Bioinformatics Unit

15

http://www.pgaeducation.org/tutoria/WUSTL/BerkeleyPGACompGeno_Boffelli.2.ppt#Slide%2019


http://www.ncbi.nlm.nih.gov/homologene/47906

http://www.ncbi.nlm.nih.gov/homologene/47906


Working example: the human estrogen receptor alphaRefSeq Genes:

NM_001122742.1NM_001122741.1NM_001291230.1NM_001122740.1NM_000125.3

NM_001291230.1: [provided by RefSeq, Mar 2014].

UCSC: http://genome-euro.ucsc.edu/index.html http://genome-euro.ucsc.edu/cgi-bin/hgTracks?db=hg19&position=chr6%3A152128814-152424408&hgsid=197277749_7mr2oIF1falEKD09ZDOn6oa4DEl5

Splicingevents


The UCSC genome browser

Dec. 2013 (GRCh38/hg38) Assembly ?

http://genome-euro.ucsc.edu/index.html

http://genome-euro.ucsc.edu/cgi-bin/hgTracks?db=hg19&position=chr6%3A152128814-152424408&hgsid=197277749_7mr2oIF1falEKD09ZDOn6oa4DEl5

ESR1 [NM_001122742]chr6:152011631-152424408, strand +Genomic length: 412778 bps, 10 exons

Inetrgenic regionIntronic regionTransposons and repeatsCoding exons

http://ecrbrowser.dcode.org/ UTRUTR

* D538G


ECR Browser

http://ecrbrowser.dcode.org/


- An integrated database of human genes that includes automatically-mined genomic, proteomic and transcriptomic information, as well as orthologies, disease relationships, SNPs, gene expression, gene function, and service links for ordering assays and antibodies. A collection of useful information concerning all human genes.

http://www.genecards.org/cgi-bin/carddisp.pl?gene=ESR1&search=esr1

Dr. Metsada Pasmanik-Chor, Bioinformatics Unit, Tel Aviv University21GeneAtlas: http://genatlas.medecine.univ-paris5.fr/fiche.php?symbol=ESR1

UCSC Genome Browser on Human Mar. 2006 (NCBI36/hg18)


https://fenix.tecnico.ulisboa.pt/downloadFile/3779571263334/intro_bioinformatica_55.pdf

Today’s workshop

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