U.S. flagAn official website of the United States government
                    Here's how you know **Official websites use .gov**
                            
                            A **.gov** website belongs to an official government organization in the United States.
 **Secure .gov websites use HTTPS**
                            
                            A **lock** (                            
                              A locked padlock                                                      
                            
                            ) or **https://** means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.


Menu Agricultural Research Service
						
                    U.S. DEPARTMENT OF AGRICULTURE
 Animal Genomics and Improvement Laboratory: Beltsville, MD
 close



    Research

                    Research Projects
                                    Publications
                                    Collaborations
                                    News
                                    Software
                People

                    Staff Listing
                                    Careers


        


                    AIP
                        Home
                                    About
                                    Publications
                                    Software
                                    People
                                    Collaborations
                                    Careers
                                    Centennial
                                    Contact
                                    Dairy industry links
                    DirectionsSearch small
                    Search
            
            ARS Home
                                About ARS
                                Contact Us




ARS Home Northeast Area Beltsville, Maryland (BARC) Beltsville Agricultural Research Center Animal Genomics and Improvement Laboratory Research Publications at this Location





- ARS National Programs
- Search for a scientific manuscript
- Search for a research project
- ARS Software
- Programs and Projects
- Collaborations
- Subjects of Investigation
- Publications
- IACUC
- Home
- About
- Publications
- Software
- People
- Collaborations
- Careers
- Centennial
- Contact
- Dairy industry links
- Home
- Queries login
- News
- Animal Evaluation lists
- Genotype counts

Title:   Author  item
                                            Wiggans, Georgeitem
                                            Vanraden, Paulitem
                                            Bickhart, Derekitem
                                            Tooker, Melvin
  Submitted to: Journal of Dairy Science
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 4/21/2016
                                    Publication  Date: 7/9/2016
                                    Citation: Wiggans, G.R., Van Raden, P.M., Bickhart, D.M., Tooker, M.E. 2016. Strategy for incorporating newly discovered causative genetic variants into genomic evaluations. Journal of Dairy Science. 99(E–Suppl. 1)/Journal of Animal Science. 94(E–Suppl. 5):137(abstr. 296).Interpretive Summary:
                                Technical Abstract: With sequence data available for an increasing number of dairy cattle, discovery of causative genetic variants is expected to be frequent. Current genomic evaluation systems require genotypes for all markers that contribute to an evaluation. A minimum number of animals with an observation for a new marker is required for accurate imputation. The SNP calls derived from sequence data from the 1000 Bull Genomes Project for 444 Holsteins were combined with SNP genotypes from bulls in the predictor population for US national genetic evaluations to impute candidate variants from the full sequence. From this imputed data, the set of SNP used in genomic evaluation along with the newly discovered causative variants were selected and stored. Those genotypes replaced the original genotypes for the bulls when extracting genotypes for genomic evaluation. The time required for imputation is substantially reduced in routine evaluation by using the haplotype library and assignments from the previous evaluation. To create suitable prior information for the expanded SNP set, genotypes for approximately 100,000 animals (including the predictor bulls and many cows with genotyped progeny) were imputed without priors. This step took about 1 d; if the full set of animals had been used, it would have taken over a week. The accuracy of this approximation was tested using the December 2015 Holstein genomic evaluation of nearly 1 million animals. Genotypes from 978,987 bulls and cows were used to create the priors, which were used to impute the December 2015 Holstein genotypes. Of the nearly 60 billion comparisons, 97.7% were identical, 1% differed by 1 allele, and 1.2% differed by a missing allele. Efficient methods that result in higher concordance may be possible. Adding new highly informative markers to the evaluation process is expected to improve prediction accuracy. In addition, excluding other markers may further increase accuracy if they contribute more noise than value when highly informative markers are included. The procedure developed enables newly discovered causative variants to be added to genomic evaluation almost immediately, which saves the time previously required for a marker to be added to a new genotyping chip as well as the time required for sufficient animals to be genotyped with the new chip to achieve adequate imputation accuracy. With this strategy, the benefits from adding new markers to genomic evaluation can be realized sooner.


Return to top


Connect with ARS Sign up


ARS Home
                            USDA.gov
                            Plain Writing
                            Policies & Links
                            Civil Rights Statements
                            FOIA
                            Accessibility Statement
                            Privacy Policy
                            Non-Discrimination Statement
                            Quality of Information
                            USA.gov
                            WhiteHouse.gov