eco-fce: integrative genomic models for fce in monogastrics

ECO-FCE: Integrative genomic models for FCE in monogastrics

Pernille SarupJ. Jensen, M. Shirali, T. Ostersen, K. Wimmers, H. Reyer, P. Varley and P.

Sørensen

Center for Quantitative Genetics and Genomics (QGG)Aarhus University

From sequence ... ...to consequence


The ECO-FCE project is funded by the European Union Seventh Framework Programme (FP7 2007/2013) under grant agreement No. 311794.

• Selective Breeding• Models• Simulation study• Real data

outlineFrom sequence ... ...to consequence


The ECO-FCE project is funded by the European Union Seventh Framework Programme (FP7 2007/2013) under grant agreement No. 311794. 3

Selective breeding

Phenotypic variation in the population


The ECO-FCE project is funded by the European Union Seventh Framework Programme (FP7 2007/2013) under grant agreement No. 311794. 4

Heritability

Some of this variation is heritable: Related individuals have more similar phenotypes than unrelated individuals

Selective breeding



Variation and heredity is the basis for all selective breeding. The key is to select the animals with greatest genetic potential.Can be tricky for highly polygenic traits



• Selection• Models• Simulation study• Real data




7

BLUP model

Breeding values Genetic relationship

Additive genetic variance



8

BLUP model

Breeding values Genetic relationship

1

½

½

¼

¼ ¼



9

GBLUP model

Genomic breeding value Genomic relationship



All markers are from the same distribution - have same chance of being informative

10

GBLUP model



11

GBLUP model

Genomic BV Genomic relationshipCausal variation



Some markers are more equalthan others

12

GFBLUP model

Causal variation



14

Simulation study

0 5 10 15 20 25 30

0.22

0.24

0.26

0.28

0.30

Cluster

Dilution (x100)

Pred

ictiv

e ab

ility

h2f

0.10.20.30.5

Proportion of genetic variation in genomic feature

Cor

rela

tion

betw

een

GBV

s an

d ph

enot

ype

Dilution by non causal markers in feature

Sarup et al. 2016, BMC genetics

GBLUP

GFBLUP



16

Real data

Genotypes for 2213 Hermitage MaxGro pigs from ~55K SNPs.

Corrected phenotypes for genotyped individuals EBVs + residuals from BLUP on ~14K individuals

Total Feed Intake TFIResidual Feed Intake RFI

50 random 10 fold validation sets.



Get information fromThe study population

GWAS, Gene expression, proteomic, or metabolomicexperiments

Literature/databasesQTL databaseGene OntologyKegg pathways

Defining genomic features

17



Some of the SNPs was linked to genes that differ in gene expression between high RFI and low RFI pigs

Defining genomic features

18



19

results

GBLUP

p< 0.001

Total Feed IntakeResidual Feed Intake



20

Conclusions

Prediction accuracies improved by ~10%.

Genes that are differential expressed in liver and duodenum most informative.

GFBLUP models can increase prediction ability and contribute knowledge on the biological background of complex traits


The ECO-FCE project is funded by the European Union Seventh Framework Programme (FP7 2007/2013) under grant agreement No. 311794.The ECO-FCE project is funded by the European Union Seventh Framework Programme (FP7 2007/2013) under grant agreement No. 311794.

Genotype and phenotype data provided by:

P. Varley T. Ostersen

Gene expression experiments:K. Wimmers, H. Reyer

Model development and genomic prediction:P. Sarup, J. Jensen, M. Shirali, P. Sørensen

More on models and analysis in session 55 Thursday 11.15 in Audiotorium

Thank you for your attention


The ECO-FCE project is funded by the European Union Seventh Framework Programme (FP7 2007/2013) under grant agreement No. 311794.The ECO-FCE project is funded by the European Union Seventh Framework Programme (FP7 2007/2013) under grant agreement No. 311794.

Modeling of the phenotype

EBVs + residuals for genotyped individuals from BLUP on 13572 Hermitage tested animals

TFI = CPG + SEX + LITTER + A + SBW + EBW + eD110 = CPG + SEX + LITTER + A + eLMP= CPG + SEX + LITTER + A + e RFI = ATFI – bD110 AD110 - bLMP ALMP +

eTFI – bD110 eD110 - bLMP eLMP

Real data

eco-fce: integrative genomic models for fce in monogastrics

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