Gene Search by use of MySQL Background – myself NsGene – DTU satellite Parkinson Disease (Affymetrix GeneChip) Analysis of fetal brain tissue Gene Discovery

Gene Search by use of MySQL

• Background – myself

• NsGene – DTU satellite

• Parkinson Disease (Affymetrix GeneChip)

• Analysis of fetal brain tissue

• Gene Discovery

• Use of MySQL

• Search for a new Growth Factor family

Background

• Thomas Nordahl Petersen

•Chemist, Ph.D protein Crystallography, University of Copenhagen

•Computational Scientist, SBI-AT

•Prediction of protein structure, secondary structure, fold recognition, homology modelling

•Bioinformatics - Gene discovery, NsGene

Devolop novel cell and gene based products for thetreatment of neurological diseases.

• Growth of cells in a capsule matrix

• The therapeutic protein be released directly in the relevant brain area

• Safe delivery across the blood-brain-barrier

ECT ProductsECT for Parkinson’s Disease

• Michael J. Fox foundation granted US $3 million to support a clinical “proof-of-concept” (May 2004)

• Identification of novel genes by use of bioinformatics

• Neublastin (GDNF family – potent neuroprotective effects)

Factor Products

• Scanning the human genome or assembled protein sets for different features of interest

Two case studies

• Parkinson related gene(s)

•Affymetrix GeneChip experiments

• Novel factor products

• Scanning an assembled protein set

• A new growth factor family

Parkinson DiseaseDegenerative central nervous system (CNS) disorder

Parkinson DiseaseLoss of dopamine producing brain cells

Parkinson’s Disease

• Dopamine from Substantia nigra activates neurons in Striatum/Basal ganglia

• Important for initiation of movement

Cure for Parkinson’s Disease ?

Parkinson disease may be cured provided that new dopamineproducing cells replace the dead ones.

Dopamin producing brain cells from aborted foetuses have beenoperated into the brain of parkinson patients and ín some casescured the disease. Brain tissue from approx 6 foetuses were needed.

Major ethical problems !

Search for a protein drug is the only valid option

Parkinson DiseaseDopamine producing cells

• Dopaminergic neurons can be found in the ventral part of the mesencephalon (VM) from approximately 6 weeks

• No dopaminergic neurons can be found in the neighbouring dorsal part (DM).

• Dopaminergic differentiation by use of GeneChips to compare the expression profiles of VM and DM

Fetal brain tissueMidbrain mesencephalon

Vm Dm+ Dopamine producingcells

- Dopamine producingcells

• Aborted feotus brain tissue – Karolinska hospital

• Feotus of age 6-10 weeks, 2 cases

Midbrain mesencephalon

Vm Dm

+ Dopamineproducingcells

- Dopamine producingcells

RNA purification + amplification

Affymetrix genechip analysis

Isolate the two samples (Vm/Dm)

Dopamine producing cells at the interface ?

GenePublisher(program by Steen Knudsen)

•Scale, normalize the Affymetrix GeneChip experiments

A1 A2 A2 B1 B2 B2 P-value

319 315 314 44 48 38 1.26e-07

314 334 327 443 434 444 6.55e-05

1980 1974 1973 1801 1785 1763 6.77e-05

123 123 126 87 88 93 8.01e-05

103 101 104 77 78 73 0.000112

107 107 111 79 77 82 0.000124

128 123 117 189 184 196 0.000142

179 179 186 145 147 149 0.000191

78 77 79 86 87 87 0.000202

96 90 93 136 129 138 0.000215

Vulcano plot

P-value

Log2 Fold change

Assigning Affymetrix GeneChip probes to a protein sequence

~20.000 probes on each of the A/B Affymetrix chips. Theprobes are normally not a part of a protein sequence.

Affymetrix probe

Blast

IPI protein sequence

Blast inferred

Unigene sequence (cDNA)5’ 3’

Internal database

Signal Peptide prediction

Conclusion – so far

• The most up-regulated genes include several ‘known’ genes like dopamine transporter (good positive control)

•The most interesting genes are the ‘unknowns’ that were up-regulated in Vm. Futher analysis is ongoing.

A new growth factor family

• Criteria

• ‘Unknown’ family of protein sequences

• Growth factor like (Cys-Cys, SigP)

• Data source

• Assembled protein set/genomic data

• Search criteria are dynamic

• Use of MySQL

MySQL – a relational database language• Data are stored in tables as a ’black box’

• Data physically separated from user

• Language is easy to read and understand

• Complex search queries

• Combine data in different tables/databases

• Result can be obtained in seconds

• Search criteria can be changed

Parsing Blast files(Preparing data for MySQL)

# Qname Dname Mlen Alen Qlen % a_id % q_id e-value Qfrom Qto Dlen Dfrom Dto

IPI00000001.1 STAU_HUMAN 577 577 577 100.0 100.0 0.0 1 577 577 1 577

IPI00000005.1 RASN_HUMAN 189 189 189 100.0 100.0 e-106 1 189 189 1 189

IPI00000006.1 RASH_HUMAN 189 189 189 100.0 100.0 e-106 1 189 189 1 189

IPI00000009.1 RASK_HUMAN 189 189 189 100.0 100.0 e-106 1 189 189 1 189

IPI00000010.1 RASL_HUMAN 188 188 188 100.0 100.0 e-105 1 188 188 1 188

IPI00000012.3 ZNT1_MOUSE 86 261 240 33.0 35.8 1e-32 1 230 503 248 500

IPI00000013.1 CSL2_HUMAN 334 334 334 100.0 100.0 0.0 1 334 334 1 334

IPI00000015.2 SFR4_HUMAN 494 494 494 100.0 100.0 0.0 1 494 494 1 494

IPI00000016.1 LMA3_MOUSE 114 145 145 78.6 78.6 9e-62 1 145 3333 1521 1665

Storing data from blast alignments

Field Type

query_db enum('hs_2_18','hs_2_23','affym','mm_1_11','affym_mouse')

query_acc varchar(20)

target_db enum('swissp','mm_1_11','sid','sid_mouse’)

target_acc varchar(20)

align_len smallint(6)

match_len smallint(6)

query_len smallint(6)

perc_align_len float(5,1)

perc_query_len float(5,1)

minus_ln_e float(6,2)

query_from smallint(6)

query_to smallint(6)

target_from smallint(6)

target_to smallint(6)

target_len int(11)

MySQl example

SELECT

a.query_db, a.query_acc,

a.target_db, a.target_acc,

a.perc_align_len, a.minus_ln_e,

b.target_db, b.target_acc,

c.cleavage_site

FROM

blastdb AS a, blastdb AS b, signalp AS c

WHERE

a.query_db='hs_2_23' AND a.target_db = 'mm_1_11' AND

a.target_acc != 'NULL' AND b.target_db='swissp' AND

a.query_acc=b.query_acc AND b.target_acc='NULL' AND

c.query_db='hs_2_23' AND c.query_acc = a.query_acc AND

c.cleavage_site >= 15 AND c.cleavage_site<=45;

Output from MySQL

query_db query_acc target_db target_acc perc_align_lenminus_ln_e target_db target_acc cleavage_site

hs_2_23 IPI00000111 mm_1_11 IPI00223686 48.6 999.00 swissp NULL 35









47306

Clustering of protein sequencesTribe-mcl

47306 sequences

13130 clusters

Store in MySQL1) Cluster size

ACPGICSKSCCPFLTPALCSRTCCPY

2) Cys-Cys230

2

16

(3)

Conserved Cys-Cys

• Many growth factor families have their own specific Cys-pattern,TGF- family.

•Transforming growth factor- is a multifunctional peptide that controls proliferation, differentiation and other functions in many cell types.

• Search for Cys-pattern without any a priori knowledge

Search criteria

• Family cluster size > 1

• No SwissProt homologues

• Cys count > 4

• Signal Peptide

• Mouse homologue/orthologue

• 48 Families

• Manual inspection of alignments (- isoforms)

• Upload remaining sequences to internal database

Internal database

Outcome from Gene Search

• Family including 5 sequences

• Predicted as growth factors/hormones

• Some of them expressed in the brain

cys10A

cys10B

cys10C

cys10E

cys10D

Outcome from Gene Search


• Predicted as growth factors/hormones

• Some of them expressed in the brain


• Labwork at NsGene

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Patent applications

• Existing patent claims ?

• Product claim

• Medical use

• Futher function analysis

• Knock-out mouse experiments

• Clinical tests

Gene discovery

Documents

Gene Search by use of MySQL Background – myself NsGene – DTU satellite Parkinson Disease (Affymetrix GeneChip) Analysis of fetal brain tissue Gene Discovery