ordination of marker trait association profiles from long term international wheat trials
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Ordination of marker-trait association profiles from long-term international wheat trials. Vivi Arief, Pieter Kroonenberg, Ian Delacy, Mark Dieters, Jose Crossa and Kaye Basford. Outline. Motivation Construction of the Wheat Phenome Atlas

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ordination of marker trait association profiles from long term international wheat trials

Ordination of marker-trait association profiles from long-term international wheat trials

Vivi Arief, Pieter Kroonenberg, Ian Delacy, Mark Dieters, Jose Crossa and Kaye Basford

outline
Outline
  • Motivation
  • Construction of the Wheat Phenome Atlas
  • Three-way Principal Component Analysis of marker-trait association profiles
the challenge
The Challenge
  • To develop a detailed understanding of the heritable variation in the wheat genome
  • To directly translate this knowledge into gains in wheat breeding
cimmyt s wheat program
CIMMYT’s Wheat Program
  • Targets wheat breeding in 6 agro-ecological regions around the world
  • Contains a vast accumulation of knowledge, data and genetic resources
  • Is publicly available
wheat trials
Wheat Trials
  • 40 years of trials
  • With 10 or more international nurseries per year
  • And 50 to 400 entries per nursery
  • At 50 or more locations around the world

→ 17m phenotypic data points on >80 traits across 13k lines evaluated in >10k field trials (data worth >US$500m)

pedigree
Pedigree
  • Pedigree information tracing the history of all 13k lines in the breeding programs
seed available
Seed Available
  • Retained seed in storage from all trials available for low-cost high throughput genotyping (can give 26m marker data points)
unique resource
Unique resource
  • No other crop (to our knowledge) has this resource publicly available
enabling technologies
Enabling Technologies
  • ASREML (in the last 10 years)
    • An analysis program that can deal with the 17m unbalanced data points
  • ICIS (in the last 5 years)
    • Database to capture the pedigree, phenotype and marker data
  • DArTs (since 2006)
    • The first of high through-put affordable marker systems
    • US$45 a DNA sample gives ~1,500 data points
phenome map
Phenome Map
  • Diagrammatic representation of the regions of a genome that influence heritable phenotypic variation for a trait
phenome atlas
Phenome Atlas
  • The integration of all phenome maps and a description of the methodologies that were used to produce the maps
producing the wheat phenome atlas
Producing theWheat Phenome Atlas
  • Focus on the ESWYTs

Elite Spring Wheat Yield Trials

phenotypic data
Phenotypic data

Advanced lines with high yield potential

  • 25 cycles from 1979/80 to 2004/05
  • 685 unique lines
  • 1445 trials across 400 locations
  • Phenotypic data for 20 traits
    • 8 agronomic traits (including grain yield)
    • 3 rusts (leaf, stripe and stem)
    • 9 other foliar diseases
the analysis
The Analysis
  • Obtained BLUPs using ASREML
  • Fitted a separate residual and design for each trial
    • ESWYT 1 to 13: RCB
    • ESWYT 14 to 25: -lattice
  • Fitted separate models for combined association analysis and structured association analysis
    • Combined association analysis: G model
    • Family structure: G model
    • Spatial structure: GGL model
    • Temporal structure: GGY model
genotypic data
Genotypic data

DArTs (Diversity Arrays Technology)

  • Dominant markers 1; 0; X
  • 1447 markers
  • ~1.4 million data points
  • 645 genotypes  599 unique genotypes (some are replicated)
the analysis1
The Analysis

Association analyses

  • Simple t-test
    • for each trait
    • for each marker
    • for each structure

Marker order

  • ESWYT disequilibrium map
    • No existing map shared more than 50% common markers with ESWYT
    • Obtained using ESWYT dataset
wheat phenome atlas version 1 0
Wheat Phenome Atlas Version 1.0
  • 10 Phenome maps:
    • Overall
  • Population structures

Pedigree data

Phenotypic data

Marker data

x 2 analytical methods

  • Environmental structures
    • Mega-environment
    • Phenotypic data
  • Combination of population and environmental structures
    • ESWYT cycle
a wheat phenome atlas

A wheat phenome atlas

  • Phenome map: dense QTL map for a trait
  • Phenome atlas: collection and description of phenome maps
slide19

9 Other foliar diseases

Stripe rust on the spike (YS)

Septoria tritici blotch (ST)

Septoria nodurum blotch (SN)

Spot blotch (SB)

Powdery mildew (PM)

Barley yellow dwarf (BYD)

Fusarium leaf blotch (FN)

Tan spot (TS)

Xanthomonas (XT)

8 Agronomic traits

Grain Yield (GY)

Kernel Size (KS)

Plant Height (PH)

Days to Heading (DH)

Test Weight (TW)

Grain Protein (GP)

Lodging (LG)

Shattering (SH)

3 Rusts

Stem (SR)

Leaf (LR)

Stripe (YR)

Increasing blue colour = increasing significance of positive association

Increasing red colour = increasing significance of negative association

what did we find
What did we find?
  • Many Trait Associated Markers (TAMs) for a trait
  • Multiple traits for a TAM
  • Association identified depend on:
    • what germplasm included
    • where tested
    • when examined
slide22

Phenome maps:

markers  traits

For selection:

genotypes  markers  traits

Three-way principal component analysis

slide23

A TAM block

    • Markers in a linkage disequilibrium block showed significant association 
      • log score  4
slide24

Association: positive

Marker : present

Association: negative

Marker : absent

slide31

ME2

ME1

summary
Summary

Three-way ordination:

  • Summarizes genotype  TAM block  trait data
  • Reveals pattern in genotype  TAM block  trait data
    • Parental selection
    • Genotype screening
    • Prediction of selection outcome
  • Observed patterns depend on the genotype  TAM block  trait arrays used
our team
Our Team

Vivi Arief

Ian DeLacy

Hailemichael Desmae

Christopher Lambrides

Jacqueline Batley

David Edwards

Mark Dieters

Ian Godwin

Kaye Basford

Jose Crossa

Susanne Dreisigacker

Tom Payne

Ravi Singh

Etienne Duveiller

Guy Davenport

Yann Manes

Marilyn Warburton

Graham McLaren

Hans-Joachim Braun

Jonathan Crouch

Rodomiro Ortiz

Peter Wenzel

Eric Huttner

Andrzej Kilian

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