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DISCOVERY OFPEACH QTL'S BY USING PBAXIV EUCARPIA Symposium on Fruit Breeding and Genetics Bologna June 18th, 2015

José R. HERNÁ[email protected]

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WHAT DID WE HAVE?

Crossing pops. from 5 research centers:

→ CRA in Rome.

→ INRA in Avignon.

→ INRA in Bordeaux.

→ IRTA in Lleida.

→ UMIL in Milan.

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WHAT DID WE HAVE? - Crossing pops.

18 crossing populations: # pops. per center

→ 11 F1 progenies + 4 F2 + 2 BC1 + 1 special progeny.

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1,472 offsprings: # offsprings per pop. and center


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1,472 offsprings:


→ 13 intraspecific crosses + 5 interspecific crosses.

intraspecific

interspecific

# offsprings per pop. and center

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WHAT DID WE HAVE? - Markers

1,472 offsprings:

→ Genotyped with 9K SNP array.

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1,472 offsprings: # informative SNPs per population


→ Each population with different number of informative SNPs.

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1,472 offsprings: # informative SNPs per population


→ Each population with different number of informative SNPs.

→ Working with 222 haploblocks. (3-4 weeks → 2-3 days)

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WHAT DID WE HAVE? - Phenotypes

1,472 offsprings:

→ 24 traits. (6 quantitative, 18 qualitative)

→ measured during different years (historical data)

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WHAT DID WE HAVE? - Phenotypes

1,472 offsprings:

→ 24 traits. (6 quantitative, 18 qualitative)

→ measured during different years (historical data)

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WHAT ARE WE GETTING? - Ripening date

→ Market opportunities.

→ Improvement of the fruit quality at extremes of the harvest season. (size, sugar content, …)

→ Highly heritable trait.

(Scorza & Sherman 1996; Souza et al. 1998; Byrne et al. 2000)

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→ Completely linked to consumer acceptance.

→ Moderate to low heritable trait.

275

250

225

200

175

150

CRA.pop1 CRA.pop2 CRA.pop3 INRAav.pop1 INRAav.pop2 INRAav.pop3 INRAav.pop4 INRAav.pop5 INRAav.pop6 INRAbx.pop1 IRTA.pop1 IRTA.pop2 IRTA.pop3 IRTA.pop4 IRTA.pop5 UMIL.pop1 UMIL.pop2 UMIL.pop3

Boxplots for beginning of the ripening date (day of the year):


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Detected ripening QTLs (posterior probabilities):

22.7

Bayes Factors:

>10 decisive 5 to 10 strong 2 to 5 positive

(evidence of the QTL)

6.9

9.7 6.2


LG LG LG LG LG LG LG LG

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22.7

Bayes Factors:



6.9

9.7 6.2

most known



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22.7

Bayes Factors:



6.9

9.7 6.2

most known



+ 3 articles:

→ Eduard et al. 2010: LG4 during 2 years ('Contender' x 'Ambra').→ Pirona et al. 2013: LG4 during 2 years ('PI91459' x 'Bounty').→ Romeu et al. 2014: LG4 during 2 years ('V6' x 'Granada').

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Detected ripening QTLs (additive effects):

22.7

+ 3 articles:

→ Eduard et al. 2010: LG4 during 2 years ('Contender' x 'Ambra').→ Pirona et al. 2013: LG4 during 2 years ('PI91459' x 'Bounty').→ Romeu et al. 2014: LG4 during 2 years ('V6' x 'Granada').

6.9

9.7 6.2



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Origin of the ripening QTL in LG2:

QTL position QTL effect

Parent's genotypes (prob.)

‘Weeping Flower Peach’ (Qq) → INRAav.pop6

‘PIxPFer’(Qq) → CRA.pop1, CRA.pop2 & CRA.pop3

‘BC1.25’ (Qq) → CRA.pop2 & CRA.pop3

‘BC1.61’ (Qq) → CRA.pop2 & CRA.pop3

22.7


LG LG

LG

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WHAT ARE WE GETTING? - Sugar content

→ Completely associated to consumer acceptance.

→ Dependent on maturity stages.


(Hilaire et al. 2000; Crisosto & Crisosto 2005; Cantín et al. 2009)

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CRA.pop1 CRA.pop2 CRA.pop3 INRAav.pop1 INRAav.pop3 INRAav.pop4 INRAav.pop6 INRAbx.pop1 IRTA.pop1 IRTA.pop2 IRTA.pop3 IRTA.pop4 IRTA.pop5 UMIL.pop1 UMIL.pop3

20.0

17.5

15.0

12.5

10.0

7.5

Boxplots for fruit sugar content (brix):


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Detected sugar QTLs (posterior probabilities):

8.6

Bayes Factors:


(evidence of the QTL) 23.7 6.6 3.1



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Sugar & ripening QTLs (positions):

8.6

23.7 6.6 3.1

22.7 6.9

9.7 6.2

SUGAR

RIPEN.




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Sugar & ripening QTLs (positions):

8.6

23.7 6.6 3.1

22.7 6.9

9.7 6.2

SUGAR

RIPEN.




specific QTL

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Detected sugar QTLs (additive effects):



specific QTL

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Origin of the last sugar QTL in LG5:

QTL effect


‘TxE’ (Qq) → IRTA.pop4 & IRTA.pop5

‘Belbinette’ (Qq) → IRTA.pop1

‘FJxFa’ (Qq) → INRAbx.pop1

22.7

QTL position


LG LG

LG

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WHAT ARE WE GETTING? - Blush (%)

→ Consumer acceptance in fresh market.

→ Not as dependent of maturity indexes as sugar, firmness …

→ Highly influenced by environment interactions (not only light exposure but also nutrition).

→ Low heritable trait.(Luchsinger et al. 2001 Carbó & Iglesias 2002; Trevisan et al. 2008)

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100%

75%

50%

25%

0%

CRA.pop1 CRA.pop2 CRA.pop3 INRAav.pop1 INRAav.pop2 INRAav.pop3 INRAav.pop4 INRAbx.pop1 UMIL.pop1 UMIL.pop3

Boxplots for percentage of red fruit surface, or blush (%):

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Detected blush QTLs (posterior probabilities):

14.2

8.2 11.0 26.6

Bayes Factors:


(evidence of the QTL)26.35.1


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14.2

8.2 11.0 26.6

Bayes Factors:



+ Possible pleiotropic effects with fruit ripening QTLs.


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14.2

8.2 11.0 26.6

Bayes Factors:



+ 1 article:

→ Frett et al. 2014: LG3 during 4 years ('Zin Dai' x 'Crimson Lady').



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14.2

8.2 11.0 26.6

Bayes Factors:



+ 1 article:

→ Frett et al. 2014: LG3 during 4 years ('Zin Dai' x 'Crimson Lady').



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Detected blush QTLs (additive effects):


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Origin of the 2 new blush QTLs:



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‘Rubira’ (QQ)‘Pamirskij 5’ (qq) → INRAav.pop3P. davidiana (qq) → INRAav.pop4


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‘Pamirskij 5’ (Qq) → INRAav.pop3


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WHAT ARE WE GETTING? - Acidity (TA)

→ Consumer acceptance.

→ Interesting for fruits with low sugar content.

→ Interesting also for early harvest of melting fruits.

(Souza et al. 1998; Crisosto et al. 2001; Crisosto et al. 2006)

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CRA.pop1 CRA.pop2 CRA.pop3 INRAav.pop1 INRAav.pop3 INRAav.pop6 INRAbx.pop1 IRTA.pop1 IRTA.pop2 IRTA.pop3 IRTA.pop4 IRTA.pop5 UMIL.pop1 UMIL.pop3

30

20

10

Boxplots for fruit titratable acidity (meq/100ml):

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Detected acidity QTLs (posterior probabilities):

27.0

3.4 12.2 2.4 4.7

Bayes Factors:




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Detected acidity QTLs (additive effects):

27.0

3.4 12.2 2.4 4.7

highest effect


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Detected acidity QTLs (additive effects):

27.0

3.4 12.2 2.4 4.7

highest effect


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Peach & Apple acidity QTLs:

PEACH

APPLE

(Illa et al. 2011)


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PEACH

APPLE

(Illa et al. 2011)


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PEACH

APPLE

(Illa et al. 2011)


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Previous state of the arte:

→ Low number of molecular markers for QTLs used in

Peach breeding programs.

→ Limited genetic variability used for QTL detection on

crossing populations (single progeny?):

* detection of small proportion of the involved QTLs.

* missing of useful alleles (not present or segregating).

* unknown robustness and magnitude in different genetic backgrounds.

CONCLUSIONS / PROSPECTS

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Pedigree-Based Analysis :

→ Integrating crossing pops., detection of new QTLs and alleles.

→ After QTLs, associate favorable alleles with haplotypes and

founder/parental individuals.

→ To finish with new markers for these quantitative traits (that

could be incorporated in breeding programs).

CONCLUSIONS / PROSPECTS

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DISCOVERY OFPEACH QTL'S BY USING PBA

XIV EUCARPIA Symposium onFruit Breeding and Genetics

Bologna June 18th, 2015

José R. HERNÁ[email protected]

Data from: Coordination:

- CRA - DLO

- INRA-Avignon - IRTA

- INRA-Bordeaux

- IRTA

- UMIL

THANKS!

Science

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