Transcriptomics as a tool for functional characterization of the grapevine genome

Massimo Delledonne

University of Verona - Italy

Assembly Number N50 (Kb) Longest (Kb) Size (Mb) Percentage of the assembly

contigs All 19578 65.9 557 467.5 -

Supercontigs

All 3515 2 065 12 675 487.1 100

Anchored on chromosomes 191 3 189 12 675 335.6 68.9

Anchored on chromosomes and oriented

143 3 827 12 675 296.9 60.9

Annotation Number Median Size (bp) Total length (Mb) Percentage of the

genome %GC

Genes 30 434 3 399 225.6 46.3 36.2

Exons CDS 149 351 130 33.6 6.9 44.5

Introns CDS 118 917 213 178.6 36.7 34.7

Intergenic 30 434 3 544 261.5 34.7 33.0

tRNA* 600 73 0.04 NS 43.0

miRNA** 164 103.5 0.002 NS 35.9

Orthology Common to Eudicotyledons

Common to Magnoliophyta

(flowering plants)

Number of orthologous

proteins

Identity percent

Number of orthologous proteins

Number of orthologous proteins

Populus trichocarpa 12 996 72.7

10 5478 121Arabidopsis

thaliana 11 404 65.5

Oryza sativa 9 731 59.8

25 years of Arabidopsis molecular biology and genetics have now yielded experimental proof of function for 3,500 genes

out of 25,000

1 GAATTCACGC TTTAAGGCTA TGGCCACCTT TAAATAAAGT ACAGCATTAC

TAAAAAAAAA

61 TAAATAAATA ACCAATACAA ATCTTTTCAG AGACAAATGC ATTCTCTGAC

ATCTGAGGTT

121 ACAGCAAATC TCTTCTTCAC CTGTTTGCTT GTTTAGAGTT GTAATATTTG

CTTTGGTGTA

181 GAGCTGAAGA CATAAATTGG TAACCAATGG AATTATCTGG CCTCAGACTT

TATTTATTTT

241 CATCATTTAT TTCACTGATG TGCAAATTTA TTCCGTACCA GCAAATGTCA

ATTTAATTAT

301 ATTCTACAGT ACACAGTGAA TCATGTATAC TTAGTCAAGT TGTAAATACA

CTAAACCATA

361 TAAACTCACA ACAGTATATC AGCTCATGAT GGGTAAATGA CTTTTCCCTG

AGAAAGAGTA

421 TCTGTTTAAC CTGCATGATC TCACTCTTTA GTATTTGCTT CTTTAGTCGA

CGTTTGTTTC

481 CTAGTTTTGA ATATAATCAT GATATGGAGA GACAAGTGAA ATCACCACAA

TTTTGTTTTC

541 CAAAATGGGA GACTATGCAA ATGCTGAAAT GAGAATTAAT ACATCCAAAA

TATCGAACCA

601 CAATTATGGC TTTGCTTTAC TTTTTGCCCG TAAGAGACAT GTGGCCTAGA

ATAGGTGGCA

661 GGTATTCCTA CCACAACCTT GCTTAGCATA GTGGTTGACT AAATATAAAT

TTTAGAGATG

721 AAGGTTGTTC TATACCCAGA TTTCAACGTG ATTGCTATGC CCACTTCACT

TTCTTTAAAA

781 TACATATTTT TCTTACTTCT CACTTTCTTT TTCTTCTTGG TTGACATTTT

TTGGCTCAGG

841 GATTTTTTTT TTCCTTATGA TCTCAAGAAA TTTTTCTCAT TGAAAAAGAC

ATAATCGTGC

901 TGGGAGTGGT GGCTCATGCT TGTAATCCCA GCACTTTGGG AGGCTGAGGC

TGGTGGATCA

961 CCTGAGGTCA GCAGTTACAG ATGAGCCCGG CCAAAATGGT GAAACCTCAT

CTCTACTAAA

1021 AATACAAAAA TTTGCCAGGT GTGGTGGCAG GCACTTGTAA TCCCAGCCAC

TCGGGAGGCT

1081 GAGGCAGGAG AATCGCTTGA ACCCAGGAGG CAGAGGTTGC AGTGAGCCAA

GATCATTCCA

1141 TTGGACTCTA GCAGGGTGAC AAGAGCAAAA CTCCATCTCA GGAAAAAAAA

AATCATAAAT

1201 TTTCCCATAT GAAAAAAATA ACACAAGATC CGGAATACAG AGAGGAGCAT

AATCCTTTGC

1261 AGGTCATAGA TGTAATCTTT CTTCCAGGAA AAATTTATTT CAGATAAGAC

CAGAATTGGA

1321 AACATATTCC ATGCCGTCAG ATAGCACTGG CTTAGGAGAC GAATGAGGAG

GAGCCTGCAG

1381 GCTACCTCAA GGATAAGAAG CAGGCAAAAG GCAAGCACAG GGGCGGCATG

CACTCACACT

1441 GGGGCTGCTC CTTCCTGGGC AAGTTTCAGA AACTCACTGA CAGAGCTAGC

AGCTCCCATA

1501 GAGATGAATG CCCATGTTTT CCCGAAGGGA GAACTGATGC TTAGAAAGGC

TGAATGACTT

Genome

Gene 2

Gene 1

Gene 4

Gene 3

Gene 5

Gene 6

Gene 7

Gene 8

Gene 9

Gene 10

Orchestration of gene expression is at the basis of the mistery of life

If we could monitor the expression of the whole set of genes that are present in a cell or tissue, we could:

• make a “genetic catalog” of the biological processes going on in those cells• understand the set of genes required for those processes

And by comparing such “gene expression profiles” from two different cell types, we could learn what makes those cells different from each other.

MicroarrayMicroarray market market keepskeeps evolvingevolving• Affymetrix dominates the market of whole

genome chips (reproducibility, platform diffusion, platform automation etc.), but it is NOT flexible and is EXPENSIVE. Customization nearly impossible ($$$!!!!).

• A number of competitors offer more advanced or flexible technologies (Nimblegen, Illumina, Agilent etc.). Customization possible. Expensive

CombiMatrix Microarray

ExceptionalExceptional qualityquality controlcontrol: : EachEach spot spot ofof eacheach microarraymicroarray isis 100% 100% functionallyfunctionally testedtested

High flexibilityHigh flexibility: Each array contains up to : Each array contains up to 90,000 different sequences. In house synthesis90,000 different sequences. In house synthesis

Arrays are reArrays are re--usableusable: cost of the analysis : cost of the analysis significantly reducedsignificantly reduced

stanza2_0001.wmv

Electrode 1 Electrode 2

CGTGTACGTCGATGTCTACTGTT

TTATTATCAAATGTACAACTGTT

• Software applies voltage to sets of specific electrodes

• Electrode activation controls chemical reactions at each individual electrode on the microarray

90K sensitivity

calculation

with dynamic

range

Very good signal of hybridization due to good hybridization and washing procedures

Scatter

plot with

pair‐wise

correlation coefficients determining

limit

of 

reproducibility

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Up to 5 hyb

After 5 hyb

Value of correlation coefficients

CentreCentre forfor plantplant functionalfunctional genomicsgenomics

Combimatrix

Sinthesiser

Grape

genome

project:The centre

is

in charge

for

the production of

the Vitis

vinifera

“complete gene chip”. Two

chip versions

released

so far. Collaboration

with

USA, Portugal, Spain, Germany

and

FRANCE

Other

microarrays

currently

sinthesised and analysed:

• Homo sapiens

(University

of Verona)• Sheep

(University

of Udine and University

of Viterbo)• Medicago truncatula

(University

of

Turin, CNR)• Barley

(CRA, Piacenza and Rome)• Lotus japonicus

(CNR Naple)• Arabidopsis

(University

of Verona)• Pomodoro

(University

of Verona, University

of Naple, CNR)• Tobacco

(University

di Verona)

Agilent

Bioanalyzer

Real-Time PCR

1st 1st grapegrape

probe design: EST probe design: EST basedbased•

Total Grape

database:–

19583 TCs

and ETs–

2394 singletons (on 14550)–

Total of 21977 Grape

sequences

•

Probe selection:–

In high

specificity

across

the total database

to avoid

cross-hybridization–

Without

secondary

structure–

With

same

range of melting

temperature

and GC content–

35-40 mers which

is

the limit

of the technology–

In the 3’end preferentially

•

OligoArray

design on Grape

sequences

(controls

not included):–

17454 oligo pairs–

1908 single oligos–

2615 sequences

rejected

•

Total number

of Grape

transcripts

represented: 19363

•

Negative

(QC, virus, bacteria) and positive controls

(spikes, housekeeping genes) added

2nd 2nd grapegrape

probe design: probe design: basedbased

on the on the 8.4X 8.4X assemblyassembly

•

Total Grape

database:–

19583 TCs

and ETs–

2394 singletons (on 14550)–

3494 gene

predicted

from

genomic

sequences–

Total of 25471 Grape

sequences

•

Probe selection:–

In high

specificity

across

the total database

to avoid

cross-hybridization–

Without

secondary

structure–

With

same

range of melting

temperature

and GC content–

35-40 mers which

is

the limit

of the technology–

In the 3’end preferentially

(after

exclusion of the last 30 bases)

•

OligoArray

design on Grape

sequences

(controls

not included):–

21451 unique–

3111 with

cross-hybridization

•

Total number

of Grape

transcripts

represented: 24562

•

Negative

(QC, virus, bacteria) and positive controls

(spikes, housekeeping

genes) added

3rd 3rd grapegrape

probe design: probe design: basedbased

on 12X on 12X assemblyassembly

and and in in deepdeep sequencingsequencing of the of the grapegrape

transcriptometranscriptome

Predicted genes validated only by a 454 sequence

67Predicted genes validated only by an EST sequence

84

Predicted genes covered by 454 OR EST 609

2500 “orphan

genes”

estimated

to

be

identified

in the grape

genome

-> dedicated

microarray

for

further

validation

ExerciseExercise

on on chromosomechromosome

33

Sequencing MappingGenomic sequencing

Molecular polymorphismsPhysical map

High resolution genetic mapQTLs for resistance

LEVEL 1 Structural Genomics

Germplasmcharacterization

Berry maturation

LEVEL 3

Biotic stresses Abiotic stresses

APPLIED PROJECTS

Reproduction /Development

Transcriptomics BioinformaticsEST

Deep cDNA sequencingMicroarray

Web portalDatabase

Data analysis

LEVEL 2

Proteomics Metabolomics2D-EMS

Metabolites analysis

Functional Genomics

UniVR Platform for the analysis of gene expression

Samples quality control

hybridization Data analysis Validation of results

Exercise with the prototype microarray carrying 24.000 grape genes

The objectives that we intend to achieve are The objectives that we intend to achieve are the following:the following:

• Functional characterization of the genes involved in the process of berry ripening and withering

• Functional characterization of the genes involved in the mechanisms of plant resistance to diseases

• Application of a “genetical genomics” approach to grapeThrough extensive microarray analysis, quantitative trait loci (QTL) analysis is applied to gene expression levels to identify genomic loci that control the observed expression change (eQTL), thus establishing “genetic regulatory networks”. Exercise: in collaboration with the “Institut Des Sciences De la Vigne et Du Vin” in Bordeaux, analysis of a population of 130 individuals segregating for root resistance to iron chlorosis and grape quality.

Project:“MOLECULAR CARACTERIZATION OF RIPENING AND WITHERING IN

CORVINA BERRY, THE MAJOR COMPONENT OF AMARONE WINE”( BACCA)

Veneto regional wine district, 2005

1000.000 euro: ORVIT 600.000, Veneto region 400.000

To effectively improve a process, it is imperative to understand its fundamental mechanisms as well as their mechanisms of regulation.

The wine is the final product of the process of biological transformation of grape berries, which characteristics determine the quality of the wine.

OUR GOAL:

To study ripening and withering in grape berries in order to identify the genes (“the instructions”) involved in the process and in the accumulation of compounds characterizing high-quality wines

Vitis vinifera cv. Corvina clone 482005, 2006 and 2007

• 3 areas of Verona province:

•High and moderate altitude

•Mode of cultivation: pergola o spalliera

Bardolino zoneValpolicellaEast Verona zone

Masi Faettini Borghetti Pule

Boni Az.GIV Zeni Cinquetti VillaMedici

Caloini RamaSolfa Danzi Aldegheri

Pasqua

3-08-20058-08-2006

15-0918-09

18-1023-10

17-1113-11

15-1218-12

22-084-09

RIPENING WITHERING

•RNA and protein

extraction

from

skin

and pulp•Metabolites

extraction

from

berry

and wine

18-07-2007 8-08 29-08 10-10 30-10 25-11

wine making

Transcriptomics

Proteomics

MetabolomicsFigura C2

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600

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7/8/02

23/8/02

29/8/024/9/02

18/9/02

25/9/02Data

g/K

g

3-oxo-a-ionolo Vomifoliolo3-OH-b-damascone 3-OH-b-ionone • Correlation of gene expression results from

microarray analysis with those coming from metabolomics, proteomics and with data from wine making experiments

• “Phenotypic plasticity” study on the 3 areas of production