SlideShare a Scribd company logo
ALMA  Alberta Livestock & Meat Agency Ltd.  Canadian Bovine Genomics Workshop September 14, 2009 Calgary, Alberta
International Beef Genomics:   United States Example    John Pollak Cornell University
Questions What is the international situation – U.S.? Is there an International Genomics Strategy?  How is Canada positioned to influence and/or align with this strategy?  What can we learn?
U.S. Example Discovery Tools  1 – Methodology 2 – Higher density panels Validation -------------------------------------- Demonstration
Discovery This period between BFI Canada and now has seen an amazing number of animals genotyped with the 50K panel. Applied to: Bull repositories – focus on traits with data collection infrastructure Animal phenotypes – focus on novel traits
Discovery ARS (beef and dairy) US MARC (phenotype and 2000 bulls) Beltsville (dairy bull repository)
Discovery NBCEC (field populations) Healthfulness (Iowa State) Feedlot Health (Colorado State) Reproduction and Stayability (Cornell) Industry partner: Pfizer Animal Genetics
Discovery University Programs Examples:  University of Missouri - Beef bull repository  University of Illinois – Genetic defects Texas A and M, UC Davis, Washington State….
Discovery USDA Competitive Grants  Examples with an NBCEC flavor (all interrelated): Milt Thomas, NMSU – Reproduction Alison Van Eenennaam, UCD – Integrated Dorian Garrick, ISU – Bioinformatics Van Tassell, Taylor and Pollak – Whole Genome Enabled Animal Selection
Discovery Industry Major DNA genetic service providers have R&D programs. Projects in collaboration with university researchers and independent projects
U.S. Example Discovery Tools  1 – Methodology 2 – Higher density panels Validation Demonstration
Tools Methodology The advent of large SNP panels presents a challenge to analysis of data. Software for the implementation of procedure like Bayes “B” (and derivates) is being developed. GenSel – Iowa State University (freeware)
Tools Methodology There are many advantages to universal software to include eliminating duplication of effort and having a system that is understood and tested by all.
Tools Methodology Integration of information for selection Optimal use of DNA-derived information and EPDs comes from appropriately indexing all sources of information.
Tools Blending of results: Indexing the MBVs and traditional genetic predictions.
Tools Using genotypes: Either fitting directly or through the  genomic relationship matrix   Misztal – University of Georgia
Tools Fitting MBVs: Using the molecular predictions as correlated information in genetic evaluation Kachman – University of Nebraska (American Angus Association application)
U.S. Example Discovery Tools  1 – Methodology 2 – Higher density panels Validation Demonstration
Tools Larger panel: Is 50K enough? In all of the discovery efforts, we are leaving a lot of unexplained genetic variation on the table. The proportion of the genetic variation explained by MBVs is typically quite good in the discovery populations but most often disappointing (< 20%) in validation populations. We also are seeing that the MBVs developed in one breed do not work as effectively in other breeds.
Tools Larger panel: Is 50K enough? Some Issues: Variation from rare minor alleles. LD issues leading to lack of “portability” of discovery from one breed to another.
Tools How will we apply the new “larger panel”? We have exhausted a lot of financial resources using the 50K. Will it be cost effective to consider redoing all animals genotyped with the 50K? I have not seen a strategic plan in academia for the most efficient, cost effective use of the new panel.
U.S. Example Discovery Tools  1 – Methodology 2 – Higher density panels Validation Demonstration
Validations Process of replicating discovery results in “ independent ” populations. Past validations are examples of joint efforts of the U.S., Australia and Canada.
Validations Running out of populations: We don’t have populations with phenotypes for all traits needing validation.  We are using populations we do have phenotyped for discovery. We also have problems with populations being disproportionately related to the discovery group.
Validation: Step Two We have not developed an in-depth strategy for “assessment” of DNA tools. We are looking across breeds. Not assessing differences across management schemes or environments.
ISSUE: Phenotypes From the process of discovery to broader assessment, the major issue is lack of phenotypic information. We simply do not have enough at this time, and efforts towards collaboration in pooling resources are necessary.
Is There a U.S. Genomics Strategy?  Positive: A large number of projects with a wide range of target traits and approaches. We also have projects in: Developing methodology for delivery. Developing extension materials. In validation.
Is There a U.S. Genomics Strategy?  Negative:  Disjointed.  We have not found efficient ways of combining our resources for discovery or for validation.  There is a strategy within ARS, within NBCEC, within USDA competitive grants and in the commercialization companies but not necessarily across organizations.
Questions Is there a U.S. Genomics Strategy? At the 30,000 foot level,,,,,,  =  kind of.
U.S. Example Discovery Tools  1 – Methodology 2 – Higher density panels Validation Demonstration
Demonstration There is still a lot of inertia impeding adoption and there is the need to develop consumer confidence in the process.  The EPD lesson: EPDs were eventually accepted as producers gained confidence that the predictions matched what they saw in their records. The Weight Trait Project
 
R & D Discovery Field study Analysis
Extension
Industry Infrastructure
2 Collaborators 4 Collaborators 6 Collaborators 7 Collaborators 1 Collaborator North Dakota Iowa South Dakota Nebraska Kansas 1 Collaborator Colorado 21 Ranches Collecting ~ 18,000 DNA samples
Demonstration Concept in this project is to force collaboration among the different organizations through the need to deliver the demonstration project.

More Related Content

What's hot

sbv IMPROVER: an industry initiative to harness the wisdom of the crowd in sc...
sbv IMPROVER: an industry initiative to harness the wisdom of the crowd in sc...sbv IMPROVER: an industry initiative to harness the wisdom of the crowd in sc...
sbv IMPROVER: an industry initiative to harness the wisdom of the crowd in sc...
Crowdsourcing Week
 
150219 agbt giab_poster_marc
150219 agbt giab_poster_marc150219 agbt giab_poster_marc
150219 agbt giab_poster_marc
GenomeInABottle
 
2014 agbt giab data integration poster 140206
2014 agbt giab data integration poster 1402062014 agbt giab data integration poster 140206
2014 agbt giab data integration poster 140206
GenomeInABottle
 
Caulder - DIVOS BioITWorld 2015
Caulder - DIVOS BioITWorld 2015Caulder - DIVOS BioITWorld 2015
Caulder - DIVOS BioITWorld 2015
Dana Caulder
 
The use of BEDTools to analyze CNV regions
The use of BEDTools to analyze CNV regionsThe use of BEDTools to analyze CNV regions
The use of BEDTools to analyze CNV regions
Leandro Lima
 
Application of adverse outcome pathways in chemical risk assessment, Dan Vill...
Application of adverse outcome pathways in chemical risk assessment, Dan Vill...Application of adverse outcome pathways in chemical risk assessment, Dan Vill...
Application of adverse outcome pathways in chemical risk assessment, Dan Vill...
OECD Environment
 
Giab jan2016 analysis team breakout SNP indel update zook
Giab jan2016 analysis team breakout SNP indel update zookGiab jan2016 analysis team breakout SNP indel update zook
Giab jan2016 analysis team breakout SNP indel update zook
GenomeInABottle
 
CBGW David Chalack Panel
CBGW David Chalack PanelCBGW David Chalack Panel
CBGW David Chalack Panel
Genome Alberta
 
Validating microbiome claims – including the latest DNA techniques
Validating microbiome claims – including the latest DNA techniquesValidating microbiome claims – including the latest DNA techniques
Validating microbiome claims – including the latest DNA techniques
Eagle Genomics
 
Lesson 5.0: How Closely Related Are We?
Lesson 5.0: How Closely Related Are We?Lesson 5.0: How Closely Related Are We?
Lesson 5.0: How Closely Related Are We?
Big History Project
 
Challenges with implementing a new diagnostic platform in Post Entry Quarantine
Challenges with implementing a new diagnostic platform in Post Entry QuarantineChallenges with implementing a new diagnostic platform in Post Entry Quarantine
Challenges with implementing a new diagnostic platform in Post Entry Quarantine
Plant Biosecurity Cooperative Research Centre
 

What's hot (11)

sbv IMPROVER: an industry initiative to harness the wisdom of the crowd in sc...
sbv IMPROVER: an industry initiative to harness the wisdom of the crowd in sc...sbv IMPROVER: an industry initiative to harness the wisdom of the crowd in sc...
sbv IMPROVER: an industry initiative to harness the wisdom of the crowd in sc...
 
150219 agbt giab_poster_marc
150219 agbt giab_poster_marc150219 agbt giab_poster_marc
150219 agbt giab_poster_marc
 
2014 agbt giab data integration poster 140206
2014 agbt giab data integration poster 1402062014 agbt giab data integration poster 140206
2014 agbt giab data integration poster 140206
 
Caulder - DIVOS BioITWorld 2015
Caulder - DIVOS BioITWorld 2015Caulder - DIVOS BioITWorld 2015
Caulder - DIVOS BioITWorld 2015
 
The use of BEDTools to analyze CNV regions
The use of BEDTools to analyze CNV regionsThe use of BEDTools to analyze CNV regions
The use of BEDTools to analyze CNV regions
 
Application of adverse outcome pathways in chemical risk assessment, Dan Vill...
Application of adverse outcome pathways in chemical risk assessment, Dan Vill...Application of adverse outcome pathways in chemical risk assessment, Dan Vill...
Application of adverse outcome pathways in chemical risk assessment, Dan Vill...
 
Giab jan2016 analysis team breakout SNP indel update zook
Giab jan2016 analysis team breakout SNP indel update zookGiab jan2016 analysis team breakout SNP indel update zook
Giab jan2016 analysis team breakout SNP indel update zook
 
CBGW David Chalack Panel
CBGW David Chalack PanelCBGW David Chalack Panel
CBGW David Chalack Panel
 
Validating microbiome claims – including the latest DNA techniques
Validating microbiome claims – including the latest DNA techniquesValidating microbiome claims – including the latest DNA techniques
Validating microbiome claims – including the latest DNA techniques
 
Lesson 5.0: How Closely Related Are We?
Lesson 5.0: How Closely Related Are We?Lesson 5.0: How Closely Related Are We?
Lesson 5.0: How Closely Related Are We?
 
Challenges with implementing a new diagnostic platform in Post Entry Quarantine
Challenges with implementing a new diagnostic platform in Post Entry QuarantineChallenges with implementing a new diagnostic platform in Post Entry Quarantine
Challenges with implementing a new diagnostic platform in Post Entry Quarantine
 

Viewers also liked

CBGW Diane Panrucker Panel
CBGW Diane Panrucker PanelCBGW Diane Panrucker Panel
CBGW Diane Panrucker Panel
Genome Alberta
 
CBGW Stephen Miller
CBGW Stephen MillerCBGW Stephen Miller
CBGW Stephen Miller
Genome Alberta
 
CBGW Brian Van Doormaal
CBGW Brian Van DoormaalCBGW Brian Van Doormaal
CBGW Brian Van Doormaal
Genome Alberta
 
CBGW Ted Bileya Panel
CBGW Ted Bileya PanelCBGW Ted Bileya Panel
CBGW Ted Bileya Panel
Genome Alberta
 
Application of molecular biology to conventional disease strategies ( M.Phil ...
Application of molecular biology to conventional disease strategies ( M.Phil ...Application of molecular biology to conventional disease strategies ( M.Phil ...
Application of molecular biology to conventional disease strategies ( M.Phil ...
Satya Prakash Chaurasia
 
Ali toronto november 2012 so me govt
Ali toronto november 2012 so me govtAli toronto november 2012 so me govt
Ali toronto november 2012 so me govt
Genome Alberta
 
CBGW Bob Church
CBGW Bob ChurchCBGW Bob Church
CBGW Bob Church
Genome Alberta
 
CBGW Julie Stitt Panel
CBGW Julie Stitt PanelCBGW Julie Stitt Panel
CBGW Julie Stitt Panel
Genome Alberta
 
12 Tweets for Using Digital Media for Internal Communication
12 Tweets for Using Digital Media for Internal Communication12 Tweets for Using Digital Media for Internal Communication
12 Tweets for Using Digital Media for Internal Communication
Genome Alberta
 

Viewers also liked (9)

CBGW Diane Panrucker Panel
CBGW Diane Panrucker PanelCBGW Diane Panrucker Panel
CBGW Diane Panrucker Panel
 
CBGW Stephen Miller
CBGW Stephen MillerCBGW Stephen Miller
CBGW Stephen Miller
 
CBGW Brian Van Doormaal
CBGW Brian Van DoormaalCBGW Brian Van Doormaal
CBGW Brian Van Doormaal
 
CBGW Ted Bileya Panel
CBGW Ted Bileya PanelCBGW Ted Bileya Panel
CBGW Ted Bileya Panel
 
Application of molecular biology to conventional disease strategies ( M.Phil ...
Application of molecular biology to conventional disease strategies ( M.Phil ...Application of molecular biology to conventional disease strategies ( M.Phil ...
Application of molecular biology to conventional disease strategies ( M.Phil ...
 
Ali toronto november 2012 so me govt
Ali toronto november 2012 so me govtAli toronto november 2012 so me govt
Ali toronto november 2012 so me govt
 
CBGW Bob Church
CBGW Bob ChurchCBGW Bob Church
CBGW Bob Church
 
CBGW Julie Stitt Panel
CBGW Julie Stitt PanelCBGW Julie Stitt Panel
CBGW Julie Stitt Panel
 
12 Tweets for Using Digital Media for Internal Communication
12 Tweets for Using Digital Media for Internal Communication12 Tweets for Using Digital Media for Internal Communication
12 Tweets for Using Digital Media for Internal Communication
 

Similar to CBGW John Pollak

Supporting researchers in the molecular life sciences Jeff Christiansen
Supporting researchers in the molecular life sciences Jeff Christiansen Supporting researchers in the molecular life sciences Jeff Christiansen
Supporting researchers in the molecular life sciences Jeff Christiansen
ARDC
 
Workshop finding and accessing data - fiona - lunteren april 18 2016
Workshop   finding and accessing data - fiona - lunteren april 18 2016Workshop   finding and accessing data - fiona - lunteren april 18 2016
Workshop finding and accessing data - fiona - lunteren april 18 2016
Fiona Nielsen
 
9 28-2012 surveys phenotypic drug discovery sig
9 28-2012 surveys phenotypic drug discovery sig9 28-2012 surveys phenotypic drug discovery sig
9 28-2012 surveys phenotypic drug discovery sig
Jonathan Lee
 
The Role of Libraries in Data Management and Curation
The Role of Libraries in Data Management and CurationThe Role of Libraries in Data Management and Curation
The Role of Libraries in Data Management and Curation
Nicole Vasilevsky
 
Genome sharing projects around the world nijmegen oct 29 - 2015
Genome sharing projects around the world   nijmegen oct 29 - 2015Genome sharing projects around the world   nijmegen oct 29 - 2015
Genome sharing projects around the world nijmegen oct 29 - 2015
Fiona Nielsen
 
Indications discovery and drug repurposing
Indications discovery and drug repurposingIndications discovery and drug repurposing
Indications discovery and drug repurposing
Sean Ekins
 
Grand round whsiao_may2015
Grand round whsiao_may2015Grand round whsiao_may2015
Grand round whsiao_may2015
IRIDA_community
 
How Can We Make Genomic Epidemiology a Widespread Reality? - William Hsiao
How Can We Make Genomic Epidemiology a Widespread Reality?  - William HsiaoHow Can We Make Genomic Epidemiology a Widespread Reality?  - William Hsiao
How Can We Make Genomic Epidemiology a Widespread Reality? - William Hsiao
William Hsiao
 
Reproducibility (and the R*) of Science: motivations, challenges and trends
Reproducibility (and the R*) of Science: motivations, challenges and trendsReproducibility (and the R*) of Science: motivations, challenges and trends
Reproducibility (and the R*) of Science: motivations, challenges and trends
Carole Goble
 
NIH Data Science Special Interest Group
NIH Data Science Special Interest GroupNIH Data Science Special Interest Group
NIH Data Science Special Interest Group
Yaffa Rubinstien
 
The australian experience issues and solutions-Dr.Daniel Catchpoole
The australian experience issues and solutions-Dr.Daniel CatchpooleThe australian experience issues and solutions-Dr.Daniel Catchpoole
The australian experience issues and solutions-Dr.Daniel Catchpoole
Data Science NIH
 
Biobanking: The Australian Experience
Biobanking: The Australian ExperienceBiobanking: The Australian Experience
Biobanking: The Australian Experience
DataSciSIG
 
ILRI program outline: Livestock Genetics
ILRI program outline: Livestock GeneticsILRI program outline: Livestock Genetics
ILRI program outline: Livestock Genetics
ILRI
 
The Continuous Update Project: Novel approach to reviewing mechanistic evide...
 The Continuous Update Project: Novel approach to reviewing mechanistic evide... The Continuous Update Project: Novel approach to reviewing mechanistic evide...
The Continuous Update Project: Novel approach to reviewing mechanistic evide...
World Cancer Research Fund International
 
2018 NF Conference Cutaneous Neurofibroma
2018 NF Conference Cutaneous Neurofibroma2018 NF Conference Cutaneous Neurofibroma
2018 NF Conference Cutaneous Neurofibroma
Robert Allaway
 
Wheat Data Interoperability (1) by Esther DZALE YEUMO KABORE and Richard FULSS
Wheat Data Interoperability (1) by Esther DZALE YEUMO KABORE and Richard FULSSWheat Data Interoperability (1) by Esther DZALE YEUMO KABORE and Richard FULSS
Wheat Data Interoperability (1) by Esther DZALE YEUMO KABORE and Richard FULSS
CIARD Movement
 
SLAS Screen Design and Assay Technology SIG: SLAS2013 Presentation
SLAS Screen Design and Assay Technology SIG: SLAS2013 PresentationSLAS Screen Design and Assay Technology SIG: SLAS2013 Presentation
SLAS Screen Design and Assay Technology SIG: SLAS2013 Presentation
SLAS (Society for Laboratory Automation and Screening)
 
DSRG report 2001
DSRG report 2001DSRG report 2001
DSRG report 2001
Laurence Dawkins-Hall
 
CLARITY BPA: a Novel Approach to study EDCs
CLARITY BPA: a Novel Approach to study EDCsCLARITY BPA: a Novel Approach to study EDCs
CLARITY BPA: a Novel Approach to study EDCs
DES Daughter
 
Slides for rare disorders meeting
Slides for rare disorders meetingSlides for rare disorders meeting
Slides for rare disorders meeting
Sean Ekins
 

Similar to CBGW John Pollak (20)

Supporting researchers in the molecular life sciences Jeff Christiansen
Supporting researchers in the molecular life sciences Jeff Christiansen Supporting researchers in the molecular life sciences Jeff Christiansen
Supporting researchers in the molecular life sciences Jeff Christiansen
 
Workshop finding and accessing data - fiona - lunteren april 18 2016
Workshop   finding and accessing data - fiona - lunteren april 18 2016Workshop   finding and accessing data - fiona - lunteren april 18 2016
Workshop finding and accessing data - fiona - lunteren april 18 2016
 
9 28-2012 surveys phenotypic drug discovery sig
9 28-2012 surveys phenotypic drug discovery sig9 28-2012 surveys phenotypic drug discovery sig
9 28-2012 surveys phenotypic drug discovery sig
 
The Role of Libraries in Data Management and Curation
The Role of Libraries in Data Management and CurationThe Role of Libraries in Data Management and Curation
The Role of Libraries in Data Management and Curation
 
Genome sharing projects around the world nijmegen oct 29 - 2015
Genome sharing projects around the world   nijmegen oct 29 - 2015Genome sharing projects around the world   nijmegen oct 29 - 2015
Genome sharing projects around the world nijmegen oct 29 - 2015
 
Indications discovery and drug repurposing
Indications discovery and drug repurposingIndications discovery and drug repurposing
Indications discovery and drug repurposing
 
Grand round whsiao_may2015
Grand round whsiao_may2015Grand round whsiao_may2015
Grand round whsiao_may2015
 
How Can We Make Genomic Epidemiology a Widespread Reality? - William Hsiao
How Can We Make Genomic Epidemiology a Widespread Reality?  - William HsiaoHow Can We Make Genomic Epidemiology a Widespread Reality?  - William Hsiao
How Can We Make Genomic Epidemiology a Widespread Reality? - William Hsiao
 
Reproducibility (and the R*) of Science: motivations, challenges and trends
Reproducibility (and the R*) of Science: motivations, challenges and trendsReproducibility (and the R*) of Science: motivations, challenges and trends
Reproducibility (and the R*) of Science: motivations, challenges and trends
 
NIH Data Science Special Interest Group
NIH Data Science Special Interest GroupNIH Data Science Special Interest Group
NIH Data Science Special Interest Group
 
The australian experience issues and solutions-Dr.Daniel Catchpoole
The australian experience issues and solutions-Dr.Daniel CatchpooleThe australian experience issues and solutions-Dr.Daniel Catchpoole
The australian experience issues and solutions-Dr.Daniel Catchpoole
 
Biobanking: The Australian Experience
Biobanking: The Australian ExperienceBiobanking: The Australian Experience
Biobanking: The Australian Experience
 
ILRI program outline: Livestock Genetics
ILRI program outline: Livestock GeneticsILRI program outline: Livestock Genetics
ILRI program outline: Livestock Genetics
 
The Continuous Update Project: Novel approach to reviewing mechanistic evide...
 The Continuous Update Project: Novel approach to reviewing mechanistic evide... The Continuous Update Project: Novel approach to reviewing mechanistic evide...
The Continuous Update Project: Novel approach to reviewing mechanistic evide...
 
2018 NF Conference Cutaneous Neurofibroma
2018 NF Conference Cutaneous Neurofibroma2018 NF Conference Cutaneous Neurofibroma
2018 NF Conference Cutaneous Neurofibroma
 
Wheat Data Interoperability (1) by Esther DZALE YEUMO KABORE and Richard FULSS
Wheat Data Interoperability (1) by Esther DZALE YEUMO KABORE and Richard FULSSWheat Data Interoperability (1) by Esther DZALE YEUMO KABORE and Richard FULSS
Wheat Data Interoperability (1) by Esther DZALE YEUMO KABORE and Richard FULSS
 
SLAS Screen Design and Assay Technology SIG: SLAS2013 Presentation
SLAS Screen Design and Assay Technology SIG: SLAS2013 PresentationSLAS Screen Design and Assay Technology SIG: SLAS2013 Presentation
SLAS Screen Design and Assay Technology SIG: SLAS2013 Presentation
 
DSRG report 2001
DSRG report 2001DSRG report 2001
DSRG report 2001
 
CLARITY BPA: a Novel Approach to study EDCs
CLARITY BPA: a Novel Approach to study EDCsCLARITY BPA: a Novel Approach to study EDCs
CLARITY BPA: a Novel Approach to study EDCs
 
Slides for rare disorders meeting
Slides for rare disorders meetingSlides for rare disorders meeting
Slides for rare disorders meeting
 

More from Genome Alberta

Improving the ROI from Social Media
Improving the ROI from Social MediaImproving the ROI from Social Media
Improving the ROI from Social Media
Genome Alberta
 
Antimicrobial Resistance
Antimicrobial ResistanceAntimicrobial Resistance
Antimicrobial Resistance
Genome Alberta
 
Ali washington sept 2013 spear presentation
Ali washington sept 2013 spear presentationAli washington sept 2013 spear presentation
Ali washington sept 2013 spear presentation
Genome Alberta
 
The Tria Project: Genomics of the Mountain Pine Beetle System
The Tria Project: Genomics of the Mountain Pine Beetle SystemThe Tria Project: Genomics of the Mountain Pine Beetle System
The Tria Project: Genomics of the Mountain Pine Beetle System
Genome Alberta
 
Genomics 101 jun 15 2012
Genomics 101 jun 15 2012Genomics 101 jun 15 2012
Genomics 101 jun 15 2012
Genome Alberta
 
Fed press Ottawa December Presentation
Fed press Ottawa December PresentationFed press Ottawa December Presentation
Fed press Ottawa December Presentation
Genome Alberta
 
Social Media Strategy to Deliver Results
Social Media Strategy to Deliver ResultsSocial Media Strategy to Deliver Results
Social Media Strategy to Deliver Results
Genome Alberta
 
2010 science comp presentation
2010 science comp presentation2010 science comp presentation
2010 science comp presentation
Genome Alberta
 
Prion Social Media Presentation
Prion Social Media PresentationPrion Social Media Presentation
Prion Social Media Presentation
Genome Alberta
 
Media Kits & Kaboodles
Media Kits & KaboodlesMedia Kits & Kaboodles
Media Kits & Kaboodles
Genome Alberta
 
CBGW Heather Burrow
CBGW Heather BurrowCBGW Heather Burrow
CBGW Heather Burrow
Genome Alberta
 
CBGW Identigen Ronan Loftus
CBGW Identigen Ronan LoftusCBGW Identigen Ronan Loftus
CBGW Identigen Ronan Loftus
Genome Alberta
 
CBGW Steve Moore
CBGW Steve MooreCBGW Steve Moore
CBGW Steve Moore
Genome Alberta
 
CBGW Stewart Bauck Panel
CBGW Stewart Bauck PanelCBGW Stewart Bauck Panel
CBGW Stewart Bauck Panel
Genome Alberta
 
CBGW Tom Holm Panel
CBGW Tom Holm PanelCBGW Tom Holm Panel
CBGW Tom Holm Panel
Genome Alberta
 

More from Genome Alberta (15)

Improving the ROI from Social Media
Improving the ROI from Social MediaImproving the ROI from Social Media
Improving the ROI from Social Media
 
Antimicrobial Resistance
Antimicrobial ResistanceAntimicrobial Resistance
Antimicrobial Resistance
 
Ali washington sept 2013 spear presentation
Ali washington sept 2013 spear presentationAli washington sept 2013 spear presentation
Ali washington sept 2013 spear presentation
 
The Tria Project: Genomics of the Mountain Pine Beetle System
The Tria Project: Genomics of the Mountain Pine Beetle SystemThe Tria Project: Genomics of the Mountain Pine Beetle System
The Tria Project: Genomics of the Mountain Pine Beetle System
 
Genomics 101 jun 15 2012
Genomics 101 jun 15 2012Genomics 101 jun 15 2012
Genomics 101 jun 15 2012
 
Fed press Ottawa December Presentation
Fed press Ottawa December PresentationFed press Ottawa December Presentation
Fed press Ottawa December Presentation
 
Social Media Strategy to Deliver Results
Social Media Strategy to Deliver ResultsSocial Media Strategy to Deliver Results
Social Media Strategy to Deliver Results
 
2010 science comp presentation
2010 science comp presentation2010 science comp presentation
2010 science comp presentation
 
Prion Social Media Presentation
Prion Social Media PresentationPrion Social Media Presentation
Prion Social Media Presentation
 
Media Kits & Kaboodles
Media Kits & KaboodlesMedia Kits & Kaboodles
Media Kits & Kaboodles
 
CBGW Heather Burrow
CBGW Heather BurrowCBGW Heather Burrow
CBGW Heather Burrow
 
CBGW Identigen Ronan Loftus
CBGW Identigen Ronan LoftusCBGW Identigen Ronan Loftus
CBGW Identigen Ronan Loftus
 
CBGW Steve Moore
CBGW Steve MooreCBGW Steve Moore
CBGW Steve Moore
 
CBGW Stewart Bauck Panel
CBGW Stewart Bauck PanelCBGW Stewart Bauck Panel
CBGW Stewart Bauck Panel
 
CBGW Tom Holm Panel
CBGW Tom Holm PanelCBGW Tom Holm Panel
CBGW Tom Holm Panel
 

Recently uploaded

Mutation Testing for Task-Oriented Chatbots
Mutation Testing for Task-Oriented ChatbotsMutation Testing for Task-Oriented Chatbots
Mutation Testing for Task-Oriented Chatbots
Pablo Gómez Abajo
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
Jason Packer
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
akankshawande
 
Northern Engraving | Modern Metal Trim, Nameplates and Appliance Panels
Northern Engraving | Modern Metal Trim, Nameplates and Appliance PanelsNorthern Engraving | Modern Metal Trim, Nameplates and Appliance Panels
Northern Engraving | Modern Metal Trim, Nameplates and Appliance Panels
Northern Engraving
 
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Pitangent Analytics & Technology Solutions Pvt. Ltd
 
5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides
DanBrown980551
 
Essentials of Automations: Exploring Attributes & Automation Parameters
Essentials of Automations: Exploring Attributes & Automation ParametersEssentials of Automations: Exploring Attributes & Automation Parameters
Essentials of Automations: Exploring Attributes & Automation Parameters
Safe Software
 
High performance Serverless Java on AWS- GoTo Amsterdam 2024
High performance Serverless Java on AWS- GoTo Amsterdam 2024High performance Serverless Java on AWS- GoTo Amsterdam 2024
High performance Serverless Java on AWS- GoTo Amsterdam 2024
Vadym Kazulkin
 
A Deep Dive into ScyllaDB's Architecture
A Deep Dive into ScyllaDB's ArchitectureA Deep Dive into ScyllaDB's Architecture
A Deep Dive into ScyllaDB's Architecture
ScyllaDB
 
Session 1 - Intro to Robotic Process Automation.pdf
Session 1 - Intro to Robotic Process Automation.pdfSession 1 - Intro to Robotic Process Automation.pdf
Session 1 - Intro to Robotic Process Automation.pdf
UiPathCommunity
 
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
saastr
 
What is an RPA CoE? Session 1 – CoE Vision
What is an RPA CoE?  Session 1 – CoE VisionWhat is an RPA CoE?  Session 1 – CoE Vision
What is an RPA CoE? Session 1 – CoE Vision
DianaGray10
 
Christine's Product Research Presentation.pptx
Christine's Product Research Presentation.pptxChristine's Product Research Presentation.pptx
Christine's Product Research Presentation.pptx
christinelarrosa
 
Taking AI to the Next Level in Manufacturing.pdf
Taking AI to the Next Level in Manufacturing.pdfTaking AI to the Next Level in Manufacturing.pdf
Taking AI to the Next Level in Manufacturing.pdf
ssuserfac0301
 
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsConnector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
DianaGray10
 
Northern Engraving | Nameplate Manufacturing Process - 2024
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving | Nameplate Manufacturing Process - 2024
Northern Engraving | Nameplate Manufacturing Process - 2024
Northern Engraving
 
Y-Combinator seed pitch deck template PP
Y-Combinator seed pitch deck template PPY-Combinator seed pitch deck template PP
Y-Combinator seed pitch deck template PP
c5vrf27qcz
 
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptxNordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
MichaelKnudsen27
 
Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptxChoosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
Brandon Minnick, MBA
 
AppSec PNW: Android and iOS Application Security with MobSF
AppSec PNW: Android and iOS Application Security with MobSFAppSec PNW: Android and iOS Application Security with MobSF
AppSec PNW: Android and iOS Application Security with MobSF
Ajin Abraham
 

Recently uploaded (20)

Mutation Testing for Task-Oriented Chatbots
Mutation Testing for Task-Oriented ChatbotsMutation Testing for Task-Oriented Chatbots
Mutation Testing for Task-Oriented Chatbots
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
 
Northern Engraving | Modern Metal Trim, Nameplates and Appliance Panels
Northern Engraving | Modern Metal Trim, Nameplates and Appliance PanelsNorthern Engraving | Modern Metal Trim, Nameplates and Appliance Panels
Northern Engraving | Modern Metal Trim, Nameplates and Appliance Panels
 
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
 
5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides
 
Essentials of Automations: Exploring Attributes & Automation Parameters
Essentials of Automations: Exploring Attributes & Automation ParametersEssentials of Automations: Exploring Attributes & Automation Parameters
Essentials of Automations: Exploring Attributes & Automation Parameters
 
High performance Serverless Java on AWS- GoTo Amsterdam 2024
High performance Serverless Java on AWS- GoTo Amsterdam 2024High performance Serverless Java on AWS- GoTo Amsterdam 2024
High performance Serverless Java on AWS- GoTo Amsterdam 2024
 
A Deep Dive into ScyllaDB's Architecture
A Deep Dive into ScyllaDB's ArchitectureA Deep Dive into ScyllaDB's Architecture
A Deep Dive into ScyllaDB's Architecture
 
Session 1 - Intro to Robotic Process Automation.pdf
Session 1 - Intro to Robotic Process Automation.pdfSession 1 - Intro to Robotic Process Automation.pdf
Session 1 - Intro to Robotic Process Automation.pdf
 
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
 
What is an RPA CoE? Session 1 – CoE Vision
What is an RPA CoE?  Session 1 – CoE VisionWhat is an RPA CoE?  Session 1 – CoE Vision
What is an RPA CoE? Session 1 – CoE Vision
 
Christine's Product Research Presentation.pptx
Christine's Product Research Presentation.pptxChristine's Product Research Presentation.pptx
Christine's Product Research Presentation.pptx
 
Taking AI to the Next Level in Manufacturing.pdf
Taking AI to the Next Level in Manufacturing.pdfTaking AI to the Next Level in Manufacturing.pdf
Taking AI to the Next Level in Manufacturing.pdf
 
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsConnector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
 
Northern Engraving | Nameplate Manufacturing Process - 2024
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving | Nameplate Manufacturing Process - 2024
Northern Engraving | Nameplate Manufacturing Process - 2024
 
Y-Combinator seed pitch deck template PP
Y-Combinator seed pitch deck template PPY-Combinator seed pitch deck template PP
Y-Combinator seed pitch deck template PP
 
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptxNordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
 
Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptxChoosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
 
AppSec PNW: Android and iOS Application Security with MobSF
AppSec PNW: Android and iOS Application Security with MobSFAppSec PNW: Android and iOS Application Security with MobSF
AppSec PNW: Android and iOS Application Security with MobSF
 

CBGW John Pollak

  • 1. ALMA Alberta Livestock & Meat Agency Ltd. Canadian Bovine Genomics Workshop September 14, 2009 Calgary, Alberta
  • 2. International Beef Genomics: United States Example   John Pollak Cornell University
  • 3. Questions What is the international situation – U.S.? Is there an International Genomics Strategy? How is Canada positioned to influence and/or align with this strategy? What can we learn?
  • 4. U.S. Example Discovery Tools 1 – Methodology 2 – Higher density panels Validation -------------------------------------- Demonstration
  • 5. Discovery This period between BFI Canada and now has seen an amazing number of animals genotyped with the 50K panel. Applied to: Bull repositories – focus on traits with data collection infrastructure Animal phenotypes – focus on novel traits
  • 6. Discovery ARS (beef and dairy) US MARC (phenotype and 2000 bulls) Beltsville (dairy bull repository)
  • 7. Discovery NBCEC (field populations) Healthfulness (Iowa State) Feedlot Health (Colorado State) Reproduction and Stayability (Cornell) Industry partner: Pfizer Animal Genetics
  • 8. Discovery University Programs Examples: University of Missouri - Beef bull repository University of Illinois – Genetic defects Texas A and M, UC Davis, Washington State….
  • 9. Discovery USDA Competitive Grants Examples with an NBCEC flavor (all interrelated): Milt Thomas, NMSU – Reproduction Alison Van Eenennaam, UCD – Integrated Dorian Garrick, ISU – Bioinformatics Van Tassell, Taylor and Pollak – Whole Genome Enabled Animal Selection
  • 10. Discovery Industry Major DNA genetic service providers have R&D programs. Projects in collaboration with university researchers and independent projects
  • 11. U.S. Example Discovery Tools 1 – Methodology 2 – Higher density panels Validation Demonstration
  • 12. Tools Methodology The advent of large SNP panels presents a challenge to analysis of data. Software for the implementation of procedure like Bayes “B” (and derivates) is being developed. GenSel – Iowa State University (freeware)
  • 13. Tools Methodology There are many advantages to universal software to include eliminating duplication of effort and having a system that is understood and tested by all.
  • 14. Tools Methodology Integration of information for selection Optimal use of DNA-derived information and EPDs comes from appropriately indexing all sources of information.
  • 15. Tools Blending of results: Indexing the MBVs and traditional genetic predictions.
  • 16. Tools Using genotypes: Either fitting directly or through the genomic relationship matrix Misztal – University of Georgia
  • 17. Tools Fitting MBVs: Using the molecular predictions as correlated information in genetic evaluation Kachman – University of Nebraska (American Angus Association application)
  • 18. U.S. Example Discovery Tools 1 – Methodology 2 – Higher density panels Validation Demonstration
  • 19. Tools Larger panel: Is 50K enough? In all of the discovery efforts, we are leaving a lot of unexplained genetic variation on the table. The proportion of the genetic variation explained by MBVs is typically quite good in the discovery populations but most often disappointing (< 20%) in validation populations. We also are seeing that the MBVs developed in one breed do not work as effectively in other breeds.
  • 20. Tools Larger panel: Is 50K enough? Some Issues: Variation from rare minor alleles. LD issues leading to lack of “portability” of discovery from one breed to another.
  • 21. Tools How will we apply the new “larger panel”? We have exhausted a lot of financial resources using the 50K. Will it be cost effective to consider redoing all animals genotyped with the 50K? I have not seen a strategic plan in academia for the most efficient, cost effective use of the new panel.
  • 22. U.S. Example Discovery Tools 1 – Methodology 2 – Higher density panels Validation Demonstration
  • 23. Validations Process of replicating discovery results in “ independent ” populations. Past validations are examples of joint efforts of the U.S., Australia and Canada.
  • 24. Validations Running out of populations: We don’t have populations with phenotypes for all traits needing validation. We are using populations we do have phenotyped for discovery. We also have problems with populations being disproportionately related to the discovery group.
  • 25. Validation: Step Two We have not developed an in-depth strategy for “assessment” of DNA tools. We are looking across breeds. Not assessing differences across management schemes or environments.
  • 26. ISSUE: Phenotypes From the process of discovery to broader assessment, the major issue is lack of phenotypic information. We simply do not have enough at this time, and efforts towards collaboration in pooling resources are necessary.
  • 27. Is There a U.S. Genomics Strategy? Positive: A large number of projects with a wide range of target traits and approaches. We also have projects in: Developing methodology for delivery. Developing extension materials. In validation.
  • 28. Is There a U.S. Genomics Strategy? Negative: Disjointed. We have not found efficient ways of combining our resources for discovery or for validation. There is a strategy within ARS, within NBCEC, within USDA competitive grants and in the commercialization companies but not necessarily across organizations.
  • 29. Questions Is there a U.S. Genomics Strategy? At the 30,000 foot level,,,,,, = kind of.
  • 30. U.S. Example Discovery Tools 1 – Methodology 2 – Higher density panels Validation Demonstration
  • 31. Demonstration There is still a lot of inertia impeding adoption and there is the need to develop consumer confidence in the process. The EPD lesson: EPDs were eventually accepted as producers gained confidence that the predictions matched what they saw in their records. The Weight Trait Project
  • 32.  
  • 33. R & D Discovery Field study Analysis
  • 36. 2 Collaborators 4 Collaborators 6 Collaborators 7 Collaborators 1 Collaborator North Dakota Iowa South Dakota Nebraska Kansas 1 Collaborator Colorado 21 Ranches Collecting ~ 18,000 DNA samples
  • 37. Demonstration Concept in this project is to force collaboration among the different organizations through the need to deliver the demonstration project.