1. Chicken QTL Phenotype Ontology
Wilfrid Carré, Jan Aerts, Dave Burt, Andy Law
Roslin Institute, Genetics and Genomics

2. ENSEMBL Project What are we trying to achieve :
Add function over the genome sequence.
Integrate the QTL data to the Chicken Genome.
How are we going to that?
Get and organise all the QTL data.
Make it easily available (via cMap, ArkDB, ENSEMBL, UCSC…).
Work out where it maps on the genome.
Allow cross species comparison with synteny comparison.

3. Mapping QTL data Use Cases :
Map the QTL on Consensus linkage Map, Genome assembly, RH Map, Cytogentic Map.
based on position on common flanking markers.
 Browse by chromosome numbers or animal trait ontology tree
 Retrieve all available information for each QTL.
 Search by chromosomes, trait names and/or key-words in the publication.

4. Chicken Genome assembly
Mapping QTL data
Chicken QTL data in ArkDB :
Chicken Genome assembly
QTL study
QTL
QTL map
Linkage Map 90
Statistical test
Suggestive
Significant
Map Position (cM) 10 20 30 40 50 60 70 80

5. Chicken QTL data QTL data collected for Chicken : - 111 Publications
- 227 different traits
chicken QTL/Associations found
Different kind of data : - Association study (439 Associations, 40 studies)
- QTL analysis (1058 QTLs, 60 studies)
- Causative genes (11 genes, 11 studies)
Data : - QTL description (Trait, Age, Chromosome, Position, Flanking markers, Significance, Genome / Chromosome wise, QTL effect on the trait, …)
- Parameters of the study (Type of Cross, Number of animals in the study, Breed, Description, Statistic / Software used ….)
- References (Title of the publication, Authors, Journal, PubMed ID, Laboratory, Contact )

6. Classification of Traits
Trait Ontology :
- Mammalian Phenotype Ontology (MGI website) not suitable for production traits.
- Define a 3 level Ontology based on the different publications :
 Body traits
 Behavior
 Immune response
 Reproduction
- Define a 3 level Ontology based on the different publications :
 Body traits
 Fat  % Abdominal fat weight
 Abdominal fat weight
 Abdominal fat weight / BW
 Abdominal fat width
 Fat distribution
 Skin fat weight
 Skin fatness
- Define a 3 level Ontology based on the different publications :
 Body traits  Carcass traits
 Fat
 Growth traits
 Meat quality
 Metabolic traits
 Muscular system
 Nervous system
 Organs
 Plumage
 Skeletal system

7. Classification of Traits
Chicken Chr1
BWt
%AF GR
%CARCASS
%SF
Body trait
MD_R
Infectious disease
EN_to
AFE
EWt_to
Reproduction female

8. Issues with Traits
Interactions between traits / Traits belonging to different group :
 Thigh meat / bone ratio.
 Meat colour adjusted for body weight.
 Weights of heart, liver and gizzard (g).
Trait given at a specific age or stage:
Body weight at 5 weeks of age under Ascites Condition (g).
Feed intake in a fixed weight interval.
Environmental conditions :
Same trait in different environmental condition not necessary the same meaning.
Body weight at 5 weeks of age (g)
Body weight at 5 weeks of age under Ascites Condition (g)
Body weight post transport to the processing factory

9. Egg Quality Production traits
Issues with Traits
Different way to look at and to classify traits :
ROSLIN
Body traits Skeletal system
Body traits Skeletal system
Body traits Carcass traits
Body traits Muscular system
Tibia width
Tibia length
Thigh bone
Thigh weight
Thigh muscle
ATO
Egg Quality Production traits
Growth Production traits
Growth Production traits
ROSLIN
Reproduction fem Egg prod
Reproduction fem Egg shell
Reproduction fem Egg comp
Body traits Growth
Egg weight
Total Egg Number
Shell weight
Albumen weight
Test end Body weight
ATO
Egg production Production traits
Egg Quality Production traits

10. Other phenotype databases
Several other databases oriented on trait : OMIM, for human, or MGI for mouse.
Online Mendelian Inheritance in Animals (OMIA) is a database of genes, inherited disorders and traits in more than 135 animal species (other than human and mouse, which have their own resources).
The database of Genotype and Phenotype (dbGaP) was developed to archive and distribute the results of studies that have investigated the interaction of genotype and phenotype.

11. Conclusion
QTL identified in Human, Mouse and Rat are disease or physiology oriented. Same trait defined differently in farm animals.
How to make the connection between different traits?
How to integrate OMIA and OMIM data to the trait ontology?
 In order to do some comparative mapping necessity to have a similar ontology from one species to an other one.
Common trait should be in the same super classe and have almost the same subcategories even if they reflect different production in different species.
 Necessity to standardize abbreviations of traits.

12. Example of Comparative Mapping
Chicken chr 7
QTL for Body weight
Mouse
Chr 1
Chr 2
Chr 10
Chr 16
Human
Chr 2
Chr 3
Chr 21