Progress 07/01/22 to 02/28/23
Outputs
Target Audience:Our target audience is comprised of underserved livestock producers who work with breeds and species for whom genomic analysis is not currently available. These producers know the power of genetics and have a strong desire to add it to their program, but simply lack the resources and technical know-how to effectively use these resources. They are committed to the health and well-being of their herds, but may not have a large amount of money to spend per animal, so want to use their resources in a way which maximizes the benefits. This includes breeds and species such as Texas Longhorn cattle, dairy goats, sheep, yak and many more. In Phase I, we worked specifically with Texas Longhorn cattle, although we will be branching into work with dairy goats for Phase II, and hope to move into other underserved breeds and species as we enter Phase III and beyond. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?The investigators and service providers engaged in this project are all well versed in the domain of high throughput genetic analyses, and software infrastructure to support the storage and analyses of these data. However, we have had the opportunity to educate breed associations on the benefits and limitations of genetic testing, and helped them focus their direction moving forward. As such, both Dr. Kalbfleisch and Dr. Loux are currently serving as advisors for the Cattlemen's Texas Longhorn Registry. Moving forward, as our objectives turn to genotype phenotype association studies, we will have opportunities not only to improve the knowledge and skills set of our team members, but when working with breed associations, we will be able to create process and infrastructure informed by their needs, and results that they can use to demonstrate a greater value in their animals. How have the results been disseminated to communities of interest?Going forward, we will begin presenting at meetings for breed associations to educate producers on the value of our system, and how it will benefit them. We will also work on literature that producers and breed associations can use to inform themselves on us, and our capabilities. As such, one area where we requested TABA funding for our Phase II proposal was for assitance writing White Papers to help educate the community about the myriad benefits available to them through genetic testing. We are consistently communicating with the breed associations we are working with. Again, both Dr. Kalbfleisch and Dr. Loux are serving as advisors for the Cattlemen's Texas Longhorn Registry, while Dr. Kalbfleisch is also on the scientific advisory board for USYAK. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
We successfully collected genomic data from 52Texas Longhorn cattle during Phase I, including 22animals sequenced with 20X genomic coverage, and an additional 13trios (sire, dam, offspring) were skim sequenced. These data served as the basis for the development of genetic tests such as parentage verification, animal ID, and identification ofgenetic markers for breed-specific economically-importanttraits. The objective of the Phase I project was the creation of a data management system for the storage, maintenance and analysis of high throughput genetic data produced by smaller animal production operations. To accomplish this objective, we completed the following aims: Aim 1) Build rudimentary data analysis tools such as parentage confirmation, animal identity (verify meat came from an animal for which you already have genetic data, or parental data), estimation of coefficient of inbreeding for potential mating pair for use in AI bull selection. One of our technical objectives was demonstrating that the Neogen Geneseek Low Pass sequencing product would accurately genotype Longhorn cattle given that this breed was not part of the training dataset for the imputation panel. Weindependently submitted samples for both low pass sequencing, and traditional SNP discovery/genotyping via whole genome sequencing and compared the resulting genotypes. Here, we demonstrated that after our quality filters had been applied, there was a less than 1% discordance rate between the genotypes imputed by low pass sequencing, and the corresponding genotype called using the 20X coverage. An artifact that we identied and reported to GeneSeek was that in~1/3 of the records, showed more duplicate VCF records for the same position, and discordant genotypes across those records. We excluded any polymorphism for an animal if it had multiple genotype calls within the same VCF fileat thesame locus. Our second objective within Aim 1 was to demonstrate that these low pass genotypes could be used for both parent, and meat verification. This test was also successful in that for 10 sire/dam/calf trios we demonstrated a less than 1% discrepancy with a Mendelian inheritance pattern. A discrepancy was counted when a calf was heterozygous at a position, for two alleles, such as A/B, and both parents were homozygous for a single allele such as A/A. Another way a discrepancy would have occurred was if either or both parents had an opposing homozygote. A calf with an A/A genotype could not have either a sire or a dam who was homozygous B/B. We demonstrated that a properly identified trio had in nearly all cases, less than 0.1% (one outlier had 0.17%) genotypes exhibiting non-Mendelian inheritance. In one case, we identified an example of mis-attributed paternity where the trio demonstrated 1.5% genotypes with non-Mendelian inheritance. A subsequent analysis of that trio, a "Single Parent" analysis, designed to confirm either the sire or the dam of a calf using only opposing homozygotes between the parent and calf showed the dam was correctly attributed, but the sire was not. This Single Parent analysis was also used for Meat Verification, by comparing the DNA profile of the meat sample to the parents recorded in the animal's pedigree when genotype data was not available for the corresponding animal itself. Finally, it was our objective to provide an analysis of possible matings to identify the pairings that would result in the greatest probability of heterozygosity in the calf. The calculation was done by counting the number of opposing homozygotes in a proposed dam/sire pair; this would be the least number of heterozygotes in the calf. Then a binomial distribution was calculated based on the number of sites where at least one parent was heterozygous. In those cases, there was a 50% chance that the calf would be heterozygous at that site. The total number of heterozygotes in either parent were used in the calculation of a binomial distribution that was centered on half this number. As such, the position of the curve was right shifted by the number of guaranteed hets (opposing homozygotes in the parents), and the width of the curve was given by the count of sites where at least one parent was heterozygous. Aim 2) Build a cloud-based data management system with a user-friendly front end that will allow farmers to upload genetic data for their animals for storage and analysis. We have deployed a web-based data management system that is password protected, with accounts for the breed associations with which we are actively working; currently Cattlemen's Texas Longhorn Registry, and USYAK. The system allows breed associations to upload animal data for registry within the system, and will allow them to request analyses, currently parentage, and meat identification (i.e., did this piece of meat come from the animal I sent to slaughter) that can be done either by comparing to genetic data for that animal, or by verifying vs. one of the animal's parents. Other algorithms we have developed will generate the predicted heterozygosity for proposed dam/sire pairing as described above. From within the application, we provide a template for animal data entry, and test requests that can be downloaded and filled out locally, or completed fully online. We will also mail data entry sheets upon request. Certain fields are required (species, breed, sex, etc). We also have the option to download an excel template which is more convenient when adding large numbers of animals concurrently. We have developed software that will generate PDF reports based on genetic data.
Publications
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