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

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.

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.

Chicken Genome assembly Mapping QTL data Chicken QTL data in ArkDB : http://www.thearkdb.org/ 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

Chicken QTL data QTL data collected for Chicken : - 111 Publications - 227 different traits - 1508 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 e-mail)

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

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

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

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

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.

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.

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