This document summarizes research that used pedigree-based analysis (PBA) to identify quantitative trait loci (QTLs) in peach using data from multiple research centers. PBA was applied to 1,472 offspring from 18 crossing populations genotyped with 9K SNP markers and phenotyped for 24 traits. Several significant QTLs were detected for ripening date, sugar content, blush percentage, and acidity. The QTLs identified new alleles and genomic regions associated with these economically important traits. Integrating data from diverse populations allowed for discovery of more QTLs than previous studies using single progenies.
Winter on kehittänyt uuden teroitustyökalujärjestelmän keraamisten sekä timantti- ja CBN-laikkojen teroitukseen. Uudessa valikoimassa on kaksi erityyppistä teroitustyökalua CNC-koneiden tarkkuushiontaan: DDS Plus ja DDS Cut.
Winter on kehittänyt uuden teroitustyökalujärjestelmän keraamisten sekä timantti- ja CBN-laikkojen teroitukseen. Uudessa valikoimassa on kaksi erityyppistä teroitustyökalua CNC-koneiden tarkkuushiontaan: DDS Plus ja DDS Cut.
Dr. Jenny Patterson - The Impact Of Litter Of Origin On Lifetime ProductivityJohn Blue
The Impact Of Litter Of Origin On Lifetime Productivity - Dr. Jenny Patterson, from the 2015 Allen D. Leman Swine Conference, September 19-22, 2015, St. Paul, Minnesota, USA.
More presentations at http://www.swinecast.com/2015-leman-swine-conference-material
Evento organizado pelo Instituto de Estudos Avançados Polo Ribeirão Preto - USP.
Tema: Produção de etanol celulósico empregando enzimas fúngicas.
Palestra do Prof. Dr. João Atílio Jorge
Realizada em 10/03/2011.
Dr. Jenny Patterson - The Impact Of Litter Of Origin On Lifetime ProductivityJohn Blue
The Impact Of Litter Of Origin On Lifetime Productivity - Dr. Jenny Patterson, from the 2015 Allen D. Leman Swine Conference, September 19-22, 2015, St. Paul, Minnesota, USA.
More presentations at http://www.swinecast.com/2015-leman-swine-conference-material
Evento organizado pelo Instituto de Estudos Avançados Polo Ribeirão Preto - USP.
Tema: Produção de etanol celulósico empregando enzimas fúngicas.
Palestra do Prof. Dr. João Atílio Jorge
Realizada em 10/03/2011.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
1. YOUR LOGO
DISCOVERY OF
PEACH QTL'S BY USING PBA
XIV EUCARPIA Symposium on Fruit Breeding and Genetics
Bologna June 18th, 2015
José R. HERNÁNDEZ
joseramon.hernandez@irta.cat
2. YOUR LOGO
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.
3. YOUR LOGO
WHAT DID WE HAVE? - Crossing pops.
18 crossing populations:
# pops. per center
→ 11 F1 progenies + 4 F2 +
2 BC1 + 1 special progeny.
4. YOUR LOGO
WHAT DID WE HAVE? - Crossing pops.
1,472 offsprings:
# offsprings per pop. and center
→ 11 F1 progenies + 4 F2 +
2 BC1 + 1 special progeny.
5. YOUR LOGO
WHAT DID WE HAVE? - Crossing pops.
1,472 offsprings:
→ 11 F1 progenies + 4 F2 +
2 BC1 + 1 special progeny.
→ 13 intraspecific crosses +
5 interspecific crosses.
intraspecific
interspecific
# offsprings per pop. and center
6. YOUR LOGO
WHAT DID WE HAVE? - Markers
1,472 offsprings:
→ Genotyped with 9K SNP array.
7. YOUR LOGO
WHAT DID WE HAVE? - Markers
1,472 offsprings:
# informative SNPs per population
→ Genotyped with 9K SNP array.
→ Each population with different
number of informative SNPs.
8. YOUR LOGO
WHAT DID WE HAVE? - Markers
1,472 offsprings:
# informative SNPs per population
→ Genotyped with 9K SNP array.
→ Each population with different
number of informative SNPs.
→ Working with 222 haploblocks.
(3-4 weeks → 2-3 days)
9. YOUR LOGO
WHAT DID WE HAVE? - Phenotypes
1,472 offsprings:
→ 24 traits.
(6 quantitative, 18 qualitative)
→ measured during different years
(historical data)
10. YOUR LOGO
WHAT DID WE HAVE? - Phenotypes
1,472 offsprings:
→ 24 traits.
(6 quantitative, 18 qualitative)
→ measured during different years
(historical data)
11. YOUR LOGO
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)
12. YOUR LOGO
→ 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):
WHAT ARE WE GETTING? - Ripening date
13. YOUR LOGO
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
WHAT ARE WE GETTING? - Ripening date
LG LG LG LG LG LG LG LG
14. YOUR LOGO
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
most known
WHAT ARE WE GETTING? - Ripening date
LG LG LG LG LG LG LG LG
15. YOUR LOGO
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
most known
WHAT ARE WE GETTING? - Ripening date
LG LG LG LG LG LG LG LG
+ 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').
16. YOUR LOGO
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
WHAT ARE WE GETTING? - Ripening date
LG LG LG LG LG LG LG LG
17. YOUR LOGO
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
WHAT ARE WE GETTING? - Ripening date
LG LG
LG
18. YOUR LOGO
WHAT ARE WE GETTING? - Sugar content
→ Completely associated to
consumer acceptance.
→ Dependent on maturity stages.
→ Moderate to low heritable trait.
(Hilaire et al. 2000; Crisosto & Crisosto 2005; Cantín et al. 2009)
19. YOUR LOGO
→ Completely linked to consumer
acceptance.
→ Moderate to low heritable trait.
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):
WHAT ARE WE GETTING? - Sugar content
20. YOUR LOGO
Detected sugar QTLs (posterior probabilities):
8.6
Bayes Factors:
>10 decisive
5 to 10 strong
2 to 5 positive
(evidence of the QTL)
23.7 6.6 3.1
WHAT ARE WE GETTING? - Sugar content
LG LG LG LG LG LG LG LG
21. YOUR LOGO
Sugar & ripening QTLs (positions):
8.6
23.7 6.6 3.1
22.7
6.9
9.7 6.2
SUGAR
RIPEN.
WHAT ARE WE GETTING? - Sugar content
LG LG LG LG LG LG LG LG
LG LG LG LG LG LG LG LG
22. YOUR LOGO
Sugar & ripening QTLs (positions):
8.6
23.7 6.6 3.1
22.7
6.9
9.7 6.2
SUGAR
RIPEN.
WHAT ARE WE GETTING? - Sugar content
LG LG LG LG LG LG LG LG
LG LG LG LG LG LG LG LG
specific QTL
23. YOUR LOGO
Detected sugar QTLs (additive effects):
WHAT ARE WE GETTING? - Sugar content
LG LG LG LG LG LG LG LG
specific QTL
24. YOUR LOGO
Origin of the last sugar QTL in LG5:
QTL effect
Parent's genotypes (prob.)
‘TxE’ (Qq) → IRTA.pop4 & IRTA.pop5
‘Belbinette’ (Qq) → IRTA.pop1
‘FJxFa’ (Qq) → INRAbx.pop1
22.7
QTL position
WHAT ARE WE GETTING? - Sugar content
LG LG
LG
25. YOUR LOGO
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)
26. YOUR LOGO
WHAT ARE WE GETTING? - Blush (%)
→ Completely linked to consumer
acceptance.
→ Moderate to low heritable trait.
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 (%):
27. YOUR LOGO
WHAT ARE WE GETTING? - Blush (%)
Detected blush QTLs (posterior probabilities):
14.2
8.2 11.0 26.6
Bayes Factors:
>10 decisive
5 to 10 strong
2 to 5 positive
(evidence of the QTL)26.3
5.1
LG LG LG LG LG LG LG LG
28. YOUR LOGO
WHAT ARE WE GETTING? - Blush (%)
Detected blush QTLs (posterior probabilities):
14.2
8.2 11.0 26.6
Bayes Factors:
>10 decisive
5 to 10 strong
2 to 5 positive
(evidence of the QTL)26.3
5.1
+ Possible pleiotropic effects with fruit ripening QTLs.
LG LG LG LG LG LG LG LG
29. YOUR LOGO
WHAT ARE WE GETTING? - Blush (%)
Detected blush QTLs (posterior probabilities):
14.2
8.2 11.0 26.6
Bayes Factors:
>10 decisive
5 to 10 strong
2 to 5 positive
(evidence of the QTL)26.3
5.1
+ 1 article:
→ Frett et al. 2014: LG3 during 4 years ('Zin Dai' x 'Crimson Lady').
+ Possible pleiotropic effects with fruit ripening QTLs.
LG LG LG LG LG LG LG LG
30. YOUR LOGO
WHAT ARE WE GETTING? - Blush (%)
Detected blush QTLs (posterior probabilities):
14.2
8.2 11.0 26.6
Bayes Factors:
>10 decisive
5 to 10 strong
2 to 5 positive
(evidence of the QTL)26.3
5.1
+ 1 article:
→ Frett et al. 2014: LG3 during 4 years ('Zin Dai' x 'Crimson Lady').
+ Possible pleiotropic effects with fruit ripening QTLs.
LG LG LG LG LG LG LG LG
31. YOUR LOGO
WHAT ARE WE GETTING? - Blush (%)
Detected blush QTLs (additive effects):
LG LG LG LG LG LG LG LG
32. YOUR LOGO
WHAT ARE WE GETTING? - Blush (%)
Origin of the 2 new blush QTLs:
Parent's genotypes (prob.)
LG LG LG LG LG LG LG LG
33. YOUR LOGO
WHAT ARE WE GETTING? - Blush (%)
Origin of the 2 new blush QTLs:
Parent's genotypes (prob.)
‘Weeping Flower Peach’ (Qq) → INRAav.pop6
‘Rubira’ (QQ)
‘Pamirskij 5’ (qq) → INRAav.pop3
P. davidiana (qq) → INRAav.pop4
LG LG LG LG LG LG LG LG
34. YOUR LOGO
WHAT ARE WE GETTING? - Blush (%)
Origin of the 2 new blush QTLs:
Parent's genotypes (prob.)
‘Weeping Flower Peach’ (Qq)
→ INRAav.pop6
‘Pamirskij 5’ (Qq)
→ INRAav.pop3
LG LG LG LG LG LG LG LG
35. YOUR LOGO
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)
36. YOUR LOGO
WHAT ARE WE GETTING? - Acidity (TA)
→ Completely linked to consumer
acceptance.
→ Moderate to low heritable trait.
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):
37. YOUR LOGO
WHAT ARE WE GETTING? - Acidity (TA)
Detected acidity QTLs (posterior probabilities):
27.0
3.4 12.2 2.4 4.7
Bayes Factors:
>10 decisive
5 to 10 strong
2 to 5 positive
(evidence of the QTL)
LG LG LG LG LG LG LG LG
38. YOUR LOGO
WHAT ARE WE GETTING? - Acidity (TA)
Detected acidity QTLs (additive effects):
27.0
3.4 12.2 2.4 4.7
highest effect
LG LG LG LG LG LG LG LG
39. YOUR LOGO
WHAT ARE WE GETTING? - Acidity (TA)
Detected acidity QTLs (additive effects):
27.0
3.4 12.2 2.4 4.7
highest effect
LG LG LG LG LG LG LG LG
40. YOUR LOGO
WHAT ARE WE GETTING? - Acidity (TA)
Peach & Apple acidity QTLs:
PEACH
APPLE
(Illa et al. 2011)
LG LG LG LG LG LG LG LG
41. YOUR LOGO
WHAT ARE WE GETTING? - Acidity (TA)
Peach & Apple acidity QTLs:
PEACH
APPLE
(Illa et al. 2011)
LG LG LG LG LG LG LG LG
42. YOUR LOGO
WHAT ARE WE GETTING? - Acidity (TA)
Peach & Apple acidity QTLs:
PEACH
APPLE
(Illa et al. 2011)
LG LG LG LG LG LG LG LG
43. YOUR LOGO
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
44. YOUR LOGO
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
45. YOUR LOGO
DISCOVERY OF
PEACH QTL'S BY USING PBA
XIV EUCARPIA Symposium on
Fruit Breeding and Genetics
Bologna June 18th, 2015
José R. HERNÁNDEZ
joseramon.hernandez@irta.cat
Data from: Coordination:
- CRA - DLO
- INRA-Avignon - IRTA
- INRA-Bordeaux
- IRTA
- UMIL
THANKS!
