Bas Rodenburg_The Role of Breeding and Genetics in Animal Welfare
Animal Breeding and Genetics 3... · 2017-11-01 · Animal Breeding and Genetics Big Data and Ag...
Transcript of Animal Breeding and Genetics 3... · 2017-11-01 · Animal Breeding and Genetics Big Data and Ag...
Animal Breeding and GeneticsBig Data and Ag Tech
John J. CrowleyCanadian Beef Breeds CouncilLivestock Gentec at University of Alberta
ABIC 2017, Winnipeg, MB
@Gentec_john
Canadian Beef Breeds Council
To provide a unified voice in support of
the purebred genetics provided within
the Canadian beef cattle industry
To ensure the continuity, growth and
prosperity of the Canadian purebred
cattle sector as an integral component
of the Canadian beef cattle industry
SUPPORT PROMOTE REPRESENT
Livestock Gentec- University of Alberta
• An Alberta Innovates Bio Solutions
Center
• Commercial benefits to the Canadian
livestock industry
• Dept. of Agriculture, Food & Nutritional
Science at University of Alberta
End Product
• Measures of genetic merit (breeding values/EPDs)
• Indexed measures
• Mate allocation, breed composition
Herd/Farm Specific
National
International
Analysis
• Mixed Model Equations
• Relationship matrix generated through pedigree
• Animal and maternal random (genetic) effects
• Solutions of genetic merit for a suite of traits
• Indexing based on economic relevance. Unit = $
Analysis with the Advent of Genomics
Animal Chr1- 1 Chr1-2 Chr1-3 . . . . . . . . Chr15-100 Chr15-101 . . . . . . . .
1 AA AA AB . . . . . . . . AB AB . . . . . . . .
2 AB AA AB . . . . . . . . AB AA . . . . . . . .
3 AA AB AA . . . . . . . . BB AA . . . . . . . .
4 AA AA AA . . . . . . . . BB AA . . . . . . . .
Data sets get bigger
- New variable (DNA), increase computational demand multi-fold
- Increased efforts for phenotypes
DNA information in the form of base pair; ~50k loci spread across the genome
Stats Methods, Software and Hardware
Methods
• Advances in matrix algebra, Bayesian statistics
Processing
• Large RAM, Multiple Cores, GPU
Storage
Movement
Whole Genome Sequencing
Whole Genome Sequencing
Meyer and Tier, CSIRO, 2015
Genotype
Sequence
Content Format Size Computation Time
Sequence reads FASTQ ~30 GB Two hours for transfer from seq provider
QC reports HTML ~300 KB Less than one hour using one core
Mapped sequence reads BAM ~30 GB One day using 12 cores
Mapping reports Text ~1 KB A few seconds using one core
Variant calls VCF ~10 GB for 30 animals One and a half days using 30 cores
Genotype reports Text ~80 MB One hour using one core
*P. Stothard, UofA
Utilizing GenomicsUse Seedstock Commercial Feedlot Packer
DNA Assisted Selection X X
Parentage X X
Recessive Allele Testing X X
Control of Inbreeding X X
Mate Selection X X
DNA-based Management X X X
DNA-based Purchasing X X
Product Differentiation X
Traceability XSource: Van Eenennaam, 2012
End Goal
Where;
ΔG is genetic gain
i is selection intensity
r is selection accuracy
L is generation interval
σa is genetic SD
• Profitability/Sustainability
• Product Quality
• Greenhouse gases
• Consumer Confidence (Social Licence)
• Anti-Microbial Resistance
Selection Goals
Challenges
• Difficult/expensive to measure traits
• Improving ease of data capture
• Speed of analysis
• Affordability
• Infrastructure for application in beef