The genetic architecture of crop domestication: a meta-analysis

1
The genetic architecture of crop domestication a
meta-analysis

• María Chacón, Todd Vision, Zongli Xu
• Department of Biology
• University of North Carolina at Chapel Hill
• October 23, 2003

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Domestication

• Domestication involves genetic changes in
  populations tending to infer increased fitness
  for human-made habitats and away from fitness for
  wild habitats. (Harlan 1995)
• Domestication syndrome The stereotypical set of
  adaptations to human habitat seen in crops

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Quantitative trait locus (QTL) mapping in wild x
domesticated crosses

• Genetic architecture of domestication
• Number of QTL
• Effect sizes
• Mode of action
• Chromosomal locations
• Limitations
• Underestimate QTL
• Overestimation of effect size in small samples
• QTL are located to large chromosomal segments
• Difficult to distinguish linked vs. pleiotropic
  QTL
• Mapping populations differ in
• Statistical power
• Ability to measure dominance

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QTL mapping
X
Parents
F1
QTL
F2 genotype
QTL
F2 Phenotype
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QTL map in rice (Cai and Morishima, 2002)
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Received wisdom regarding domestication QTL (DQTL)

• Few loci of major effect
• Domestication alleles tend to be recessive
• DQTL tend to be clustered among and within
  linkage groups
• DQTL tend to be homologous among related crops
  (e.g. fruit weight QTL in the Solanaceae)

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Crop systems
Pulses Common bean Cowpea
Fruit crops Eggplant Pepper Tomato Watermelon
Vegetable crops Lettuce
Grain crops Maize Pearl millet Rice Sorghum Wheat Wild rice
Industrial crops Cotton Sunflower Sugarcane
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Questions

• What is the effect of study power on
• The DQTL per trait?
• The effect sizes of the DQTL?
• Do DQTL tend to be recessive even for polygenic
  traits?
• What is the effect of breeding system?
• What does the pattern suggest about the origin of
  the domestication alleles?
• Clustering of DQTL among and within linkage
  groups
• Is it an artifact of pleiotropy?
• Is the pattern of clustering consistent with the
  major hypothesis concerning its origin

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Questions

• What is the effect of study power on
• The DQTL per trait?
• The effect sizes of the DQTL?
• Do DQTL tend to be recessive even for polygenic
  traits?
• What is the effect of breeding system?
• What does the pattern suggest about the origin of
  the domesticated alleles?
• Clustering of DQTL among and within linkage
  groups
• Is it an artifact of pleiotropy?
• Is the pattern of clustering consistent with the
  major hypothesis concerning its origin

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Gene action
A2A2
Genotype
A1A2
A1A1
-a
a
0
d
Genotypic value
Additive
Dominant
Recessive
-1.00
-0.75
-0.25
0
0.25
0.75
1.00
1.25
-1.25
d/agene action of the A1 allele
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Expectations for gene action of domestication
alleles

• Domestication alleles are recessive (Lester,
  1989, Ladizinsky, 1998)
• If adaptation uses new mutations autogamous are
  expected to fix more recessive alleles than
  allogamous (Orr and Betancourt, 2001)
• If adaptation uses standing variation, the
  probability of fixation of alleles is independent
  of dominance (Orr and Betancourt, 2001)

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Gene action of domestication alleles
Average d/a 0.570 (autogamous), 0.015
(allogamous) Two-tailed paired t-test plt0.31
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Findings

• Domestication alleles are not always recessive
• Autogamous and allogamous crops have equal
  proportions of recessive and dominant
  domestication alleles
• Results are more compatible with the predictions
  of the standing variation model than the new
  mutation model

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Questions

• What is the effect of study power on
• The DQTL per trait?
• The effect sizes of the DQTL?
• Do DQTL tend to be recessive even for polygenic
  traits?
• What is the effect of breeding system?
• What does the pattern suggest about the origin of
  the domesticated alleles?
• Clustering of DQTL among and within linkage
  groups
• Is it an artifact of pleiotropy?
• Is the pattern of clustering consistent with the
  major hypothesis concerning its origin

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Why might DQTL be clustered?

• Predicted from some population genetic models (Le
  Thierry DEnnequin et al. 1999)
• Assuming
• DQTL could arise throughout the genome
• Introgression from wild relatives
• Selection will prefer linked QTL in
  disequilibrium
• Clustering should be more apparent in allogamous
  than autogamous crops
• Potential for methodological artifact
• One pleiotropic QTL would be detected multiple
  times
• This would give the false appearance of
  clustering
• Conservative set of QTLs chosen to reduce
  problems of pleotropic QTL (one per trait
  category per locus)

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Classification of domestication traits
Earliness Growth habit Increase in yield Gigantism Seed dispersal
Days to flower Heading date Fruiting date Ripening date Plant height No. tillers/plant No. of branches Average length of nodes No. of nodes Kernel No./spikelet Kernel No./plant Kernel No./panicle Grain yield Spikelet No./ spike Spikelet No./panicle Spikelet density Spike No./panicle Cupules/rank No. of rows of cupules Fruit number Fruit yield Seed size/weight Panicle length/weight Spike length/weight Fruit diameter/weight /length Shattering rate Brittle rachis Awn length
Full data set
Reduced data set
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How to test for QTL clustering

• Clustering among linkage groups
• Measured by a X2 goodness of fit test
• Clustering within linkage groups
• Measured by simulation (randomly assigning same
  number of QTL and measuring distance between
  neighboring QTL)

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Clustering of DQTL among and within LGs
Crop Outcrossing rate Clustering among Clustering within
Rice lt1 yes no
Rice lt1 yes yes
Rice lt1 yes yes
Common bean 1-5 yes yes
Tomato 1-5 yes no
Tomato (r) 1-5 yes no
Wheat 1-5 yes yes
Wheat (r) 1-5 yes no
Pepper 12-15 yes yes
Pepper (r) 12-15 no yes
Cowpea 12-15 yes yes
Eggplant 12-15 yes yes
Eggplant (r) 12-15 no no
Sunflower 25-40 yes no
Sunflower (r) 25-40 yes no
Pearl millet 25-40 yes yes
Pearl millet 25-40 yes yes
Maize gt40 no no
Wild rice gt90 no yes
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Clustering of DQTL in common bean
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Non-clustering of DQTL in maize
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Clustering of non-domestication QTL
Crop Cross type Outcrossing rate Clustering among Clustering within
Rice D x D lt1 no yes
Sunflower D x D 25-40 no no
Maize D x D gt40 no yes
Rice W x D lt1 yes yes
Cowpea W x D 12-15 yes yes
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Alternative explanations

• Are QTL clustered because they map to gene dense
  regions?
• Suggested for wheat (Peng et al. 2003)
• Preliminary test in rice using high density
  transcript map (6591 ESTs, Wu et al. 2002)
• Counted number of QTLs and markers in 5cM windows
• Average of markers/windows 4.41
• Weighted avg. of markers/window for QTL 3.49

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QTL homology

• Observed for QTL in several systems
• Cereals (grain size, flowering time, shattering)
• Solanaceae (fruit size, shape)
• Beans (seed size)
• Not necessarily domestication trait specific
• If clusters reflect chromosomal regions that are
  particularly liable to contain QTL
• Some correspondence in the location of QTL among
  related species is to be expected
• So do homologous QTL really correspond to the
  same genes?

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Summary

• DQTL number and effect size
• Trend toward less DQTL and larger effect sizes in
  low power studies
• Some major DQTL detected in powerful studies
  (e.g. sugarcane)
• Mode of gene action and origin of DQTL alleles
• d/a is not significantly different between
  allogamous and autogamous crops
• Results consistent with standing variation
  model
• Clustering of DQTL
• Does not appear to be an artifact of pleiotropy
• Not consistent with introgression hypothesis
• Appears to reflect inherent differences among
  regions of the genome

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Acknowledgements

• All those who helped provide supplemental data
  from their QTL studies
• John Burke (sunflower)
• Lizhong Xiong (rice)
• Valerie Poncet (pearl millet)
• Raymie Porter and Ron Phillips (wildrice)

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Statistical power

• Power
• Probability of rejecting the null hypothesis
  (absence of QTL) when it is false probability
  of detecting a QTL when it is present
• Calculated by simulation
• Assumptions
• Single codominant QTL
• Constant small additive effect
• Constant environmental variance

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Power of study and DQTL detected
DQTL detected per trait
Power
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Power and effect size of DQTL