Genomic Selection as a Risk Management Tool for U.S. Dairies

Progress report for SW21-925

Project Type: Research and Education
Funds awarded in 2021: $349,876.00
Projected End Date: 03/31/2024
Host Institution Award ID: G369-21-W8612
Grant Recipients: Washington State University; University of Idaho
Region: Western
State: Washington
Principal Investigator:
Dr. Holly Neibergs
Washington State University
Co-Investigators:
Dr. Amber Adams-Progar
Washington State University
Dr. Joseph Dalton
University of Idaho
J. Shannon Neibergs
Washington State University
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Project Information

Abstract:

Washington and Idaho dairies, a leading commodity in the West, are experiencing difficult financial times, and need tools that can improve sustainability and profitability through enhanced production efficiency. After feed, the cost of raising replacement heifers (young female cattle to replace aging cows) is a dairy farm’s greatest expense. Genomic selection, the use of DNA technologies to make accurate predictions of the performance of crops, fruit and livestock, offers permanent improvement of agricultural yields. The improvement of yields with the same or even lower inputs improves environmental sustainability and results in higher profitability. Our proposal’s significance is that by undergoing the transformative change of using genomic selection to choose the “right” heifers, dairy farms will be more sustainable and profitable. Although this demonstration will be done in dairies, the benefits of genomic selection are also applicable to other agricultural enterprises.

Genomic selection is used predominantly in animals with high individual values, such as cattle, to offset the cost of DNA technology. This proposal is using demonstration dairies in Washington and Idaho to educate producers, veterinarians, allied health individuals, agricultural students and Extension agents about genomic selection and how it benefits dairies by: 1) reducing financial risk by predicting genetically superior females, thereby improving milk production while maintaining or reducing herd inventory; 2) resulting in a positive return on investment and increased profitability and; 3) reducing the dairy’s environmental impact through reduced manure production by improving herd efficiency. Traditional and genomic approaches have been used to predict performance to rank and select heifers. Heifers have been bred and will soon be calving and milking. Reproductive and health performance on each animal has been recorded. Predicted and actual reproductive, and health performance for the demonstration herds are beginning to be compared. Once the first lactation is complete, that information will be added to the reproductive and health information and serve as the basis for the analyses of profitability, financial risk, and return on investment for the six demonstration dairies.

The implementation of genomic selection has lagged on dairy farms due to a lack of education. This proposal focuses on educating producers, veterinarians and others about the financial benefits of genomic selection compared to traditional selection to overcome this hurdle. Producer and veterinarian Genomic Selection Workshops and university students will “select” replacement heifers using actual data from the demonstration farms based on genomic and traditional selection information. Educational outcomes have (and are) being measured for Workshops using pre- and post- workshop assessments to determine, if attendees have: 1) improved their knowledge of genomic selection and financial risk management; 2) plan to implement genomic selection to improve their (or their client’s) herd and their dairy's profitability; and 3) plan to share their knowledge with others. Outcomes for university classes regarding students' increased knowledge of genomic selection was measured by class testing. Profitability and production outcomes of the dairies will be measured through comparing cattle selected by genomic and traditional selection approaches. Environmental and sustainability outcomes will be measured by the reduction of cattle needed and the reduction in nutrients to meet the same level of production using genomic selection compared to traditional selection. Project information will be disseminated to agricultural stakeholders at state and national meetings, through Extension newsletters, and Extension and professional journal publications.

Project Objectives:

The research objectives are to:

Objective 1: Identify the profitability difference between replacement heifers chosen with genomic selection compared to those chosen with traditional selection on a per animal basis.

Objective 2: Identify return on investment for the cost of genomic selection on a per heifer, per dairy and across dairies basis.

Objective 3: Determine the reduction in financial risk (variability in profits) that results from an increased accuracy of prediction of replacement heifer performance through genomic selection on a per dairy and across all dairies basis.

Objective 4: Develop a model to project the one and ten-year difference in dairy farm profitability and nutrient (manure) load contributed to the environment between traditional versus genomic selection to determine the added sustainability of using genomic selection.

The educational objective is to:

Objective 1: Educate dairy producers, veterinarians, extension agents and undergraduate university students on the use of genomic selection to mitigate financial risk and enhance profitability while improving the genetics of the milking herd. This will be accomplished through:

    1. Producer Workshops and Veterinarian Workshops in central and northwestern Washington and southern Idaho. Pre- and post-Workshop assessments will determine the value of the educational sessions to the attendees. Online workshops will be held in addition to in-person workshops for those unable to attend the in-person events.
    2. Undergraduate courses in Animal and Veterinary Science at Washington State University. Students will be tested on the information provided in class to assess their understanding of genomic selection uses.
    3. Online course that provides information and demonstrations on genomic selection and a self-test for participants to gauge their understanding of genomic selection.
Timeline:

The timeline for the activities described in the Research Plan and Educational plan are outlined below.

Gantt Chart

ACTIVITY

Year 1

Year 2

Year 3

Choose 200 heifers/dairy as potential replacements

X

 

 

Graduate & Undergraduates take pictures of heifers

X

 

 

Obtain traditional predicted transmitting ability (PTA)

X

 

 

Graduate & Undergraduates collect tissue samples, extract DNA, to genotype heifers

X

 

 

Genotyping completed and genomic PTAs obtained

X

 

 

Develop and present Producer Genomic Selection Workshops

X

 

X

Develop and present Veterinary Genomic Selection Workshops

X

 

X

Collect economic data and perform Economic Analysis

X

X

 

Collect Health, Fertility and Milk Production Records

X

X

 

Develop Educational Materials for Web

X

X

X

Include Educational Material in WSU Undergraduate Classes

X

X

X

Web Education with Dairy Producers of Washington

 

X

X

Host Web Site

 

X

X

Present Results at Dairy Farmers of Washington Meeting

 

 X

Cooperators

Click linked name(s) to expand/collapse or show everyone's info
  • Austin Allred - Producer
  • Adam Doleson - Producer
  • Peter Kasper - Producer
  • Terry Lenssen - Producer
  • Derek Teunissen - Producer
  • Case VanderMeulen - Producer

Research

Hypothesis:

Genomic selection is a more accurate predictor of future animal performance than the use of visual or pedigree information.

Genomic selection will reduce adverse financial consequences of choosing animals to remain in the herd that perform poorly.

Materials and methods:

Introduction

Genomic selection is based on finding associations of a DNA variant (SNP, see Figure 1) and a trait such as milk production. Once the association is made, animals are genotyped (their DNA identified at the region associated with a trait) to predict the performance of that animal and its offspring. For example, one animal may have the “A” nucleotide at a DNA position, and another animal may have a “C”. Through previous research, the “A” has been identified to be associated with an increase of 100 pounds of milk production and the “C” is associated with no additional milk production (above the average). Heifers that are genotyped and have received an “A” from both their dam and sire will produce 200 pounds more milk (two A’s × 100 lbs = 200 lbs), while those that only receive one “A” from one of their parents will produce 100 pounds more milk and those that receive no “A’s” will produce no more milk than average (Figure 2). These differences in performance from the average are called predicted transmitting abilities or PTA. Genomic selection is the use of PTA based on genotypes to estimate the performance of the heifers. Her offspring’s performance is estimated in the same way. In this proposal, several thousand SNP will be used to predict the performance of the heifers based on previous research that has linked the genotypes to heifer performance. The genotypes of each heifer will also be compared to the predicted performance of all Holstein heifers in the U.S. to assist the dairy producers, workshop participants and students to make decisions on which heifers to keep or cull. 

Genomic selection is much more accurate than basing the prediction of a heifer’s performance on the performance of her dam or her sire14-16,19. The increased accuracy of the heifer’s future milk production allows the dairy to identify heifers that are likely to produce more milk and therefore be more profitable over their lifetime. As the heifers will also produce the next generation of milking animals through their calves, this increase (or decrease) in milk production carries forward generation after generation. This proposal will measure the actual difference in milk and revenue produced from heifers selected using DNA genotypes (genomic selection) compared to heifers chosen using parent information and visual inspection (traditional selection). This real-life comparison will be used to educate present and future dairy producers, and veterinarians.

Material and Methods

For the educational workshops and financial analyses, we have collected pictures (front, side and rear views) of each of the 1200 heifers, a tissue sample, genotypes and reproductive and health records. As heifers finish their first lactation, milk yield and milk components will be collected and summarized from each animal. The following provides an overview of that collection process.

Animal Data Collection. Each dairy producer collaborator provided access to approximately 200 heifers between 6 and 10 months of age (Figure 3). The age of heifers when replacement decisions are made vary by dairy, but the decision to keep or cull heifers was made prior to breeding at approximately one year of age. Pictures were taken of all heifers for use in workshops and in the undergraduate agricultural courses and will be used for selection of heifers using traditional selection methods. Groups of heifers (10, 20 or 50) were given to participants/students and they ranked the heifers based on visual, pedigree information and individual information and compared how these rankings changed depending on how the animals were assessed. Participants/students were also given four bulls to evaluate and determine by using genomic information, which were to be used to mate to the heifers they chose to keep as replacements. Beef bulls will also be provided as an option for offspring that will not be kept in the breeding herd. 

Following the pictures, an ear tissue sample was taken from each heifer (see Animal Assurance; WSU IACUC #6370). DNA was extracted from the tissue sample and genotyping was conducted using the Neogen Igenity Prime assay that contains over 50,000 DNA variants (SNP). The genotypes were used to predict the performance of each heifer as described in Figure 2. A graduate Animal Sciences student was involved with the sample collection needed for genotyping and data analysis.

Analysis of genotypes. The genotypes of the heifers was determined at the Neogen laboratory for three reasons: 1) Neogen donated the cost of DNA extraction required for the genotyping (a $4800 savings); 2) Neogen genotyped the animals at lower cost than we could have genotyped the animals; and 3) Neogen has a contractual relationship with the Council on Dairy Cattle Breeding that allows them to compare and rank each heifer against all other Holstein heifers that have been genotyped in the US. Without this contractual agreement between Neogen and the Council on Dairy Cattle Breeding, we would not have the ability to compare and rank the demonstration herd heifers to all US Holstein heifers.

The genomic prediction information (PTA) was provided to us and to the dairy producers by Neogen for use in this project to choose replacement heifers using genomic selection. All heifers at each dairy were ranked by using pedigree information and genomic information. This will allow the comparison of the profitability of different percentiles (top 25% versus bottom 25%) using different sources of information. Replacement decisions to keep or cull heifers were made by the dairy producers prior to the heifers being bred. Replacement heifers will be followed through one lactation. 

Financial Analysis

Objective 1: Identify the profitability difference between replacement heifers chosen with genomic selection compared to those chosen with traditional selection on a per heifer basis.

Profitability analysis will include expenses (the cost of health events such as treatment costs, costs associated with the number of inseminations required to achieve pregnancy, and feed costs) and revenues (revenue from first lactation milk sales, revenue from calf sales or heifer cull value if it occurs before the end of the first lactation)(see Equation 1). Individual heifer production data will be collected through each participating farm’s records database, which maintains all dairy production records and is updated daily. Feed costs, milk price and milk component premiums will be determined through public reports and held constant across dairies to isolate and evaluate the net profitability attributed to selection. The total profit made for heifers ranked in the top 25% and bottom 25% based on Genomic Selection and Traditional Selection groups will then be compared.

Objective 2: Identify return on investment for the cost of genomic selection on a per heifer, per dairy and across dairies basis.

The return on investment will be calculated to determine the value of using genomic selection for each dairy and across all dairies (see Equation 2.1). The return on investment will compare the heifer profits (see Equation 1 for calculation of profit) from the Genomic Selection group and the Traditional Selection group. This will identify how much profit was gained for the money spent on genotyping. A second related analysis for return on investment, will evaluate the additional milk production gained through genomic selection (see Equation 2.2).

Objective 3: Determine the reduction in financial risk (variability in profits) on a per dairy and across dairies basis that results from an increased accuracy of prediction of replacement heifer performance through genomic selection. Objectives 1 and 2 keep milk price constant to isolate the effects of genomic and traditional selection. The primary factor affecting dairy financial risk is variation in milk price. Equation 3 evaluates the effect of selection profit when milk prices vary. The range of milk prices producers have received over the past five years ranges from $13.00 to $20.70. Profits for each selection group will be calculated iteratively for the range of milk prices received over the past five years.

Objective 4: Develop a model to project the one and ten-year difference in dairy farm profitability and nutrient (manure) load contributed to the environment between traditional versus genomic selection to determine the added sustainability of using genomic selection.

Predicted dairy farm profitability. A model will be developed to predict the ten-year difference in dairy farm profitability and nutrient (manure) load contributed to the environment between traditional versus genomic selection to determine the added sustainability of using genomic selection. This model will be based on data collected on the first lactation. The hypothesis is that production efficiency gains from Genomic Selection heifers will result in less animals needed to meet a constant level of production, therefore, resulting in significantly less manure, thus improving economic sustainability while increasing profitability. This hypothesis is based on studies conducted and USDA statistics over the past 10 years that has shown that genomic selection has improved milk production with fewer cows8.

The model will simulate milk production gain for each selection method and the projected milk production gains of the offspring over the ten-year period. Total milk production for each dairy will be held constant and herd inventory number will be adjusted to maintain this level of production. The net present value for genomic and traditional selection profits will be calculated to account for the time value of money. Total manure and nutrients produced over the 10-year period will be estimated using USDA NRCS manure characteristics21,22. For example, the average US Holstein cow produces 25,946 pounds of milk per lactation so 100 cows would produce 2.5 million pounds of milk in one lactation23. This analysis will identify how many heifers will be required to meet the average milk yield for 100 US Holstein cows in the Genomic Selection and Traditional Selection groups and how that number would impact the environment through the amount of nutrients (manure) in pounds that would be produced17,21,22,24.

 

 

 

Research results and discussion:

Hypothesis 1: Genomic selection is a more accurate predictor of future animal performance than the use of visual or pedigree information.

Predictions (PTAs) of the animals' performance for health, fertility and milk quality and yield has been determined by the genotypes performed by Neogen and evaluated by the Council on Dairy Cattle Breeding. Actual heifer performance for health and fertility is now being collected and will be compared to the predicted performance of these animals. Milking performance will also be collected as the heifers calve and begin milking. This information will be utilized in the profitability analyses along with the milking performance (when available) of each animal.

Hypothesis 2: Genomic selection will reduce adverse financial consequences of choosing animals to remain in the herd that perform poorly.

The profitability analyses will begin once the milk production data for each of the heifers is available.

Participation Summary
6 Farmers participating in research

Education

Educational approach:

The educational approach is to provide background information on genomics and selection of animals based on visual, pedigree or individual information to form a foundation for the hands-on exercise in the second step. The second step is to allow the students/participants to learn experientially by utilizing real cattle data to experience the differences these different approaches can have on accurately predicting the best animals, improving overall herd performance and reducing financial risk. Below are the populations we have served this year:

Future Animal Scientists and Pre-Veterinary Students

In three WSU courses (Animal Breeding and Genetics (120 students), Dairy Production (45 students) and Agricultural Animal Health (90 students)) undergraduates were taught about genomic selection and then provided real data to choose replacement females. First they chose Holstein animals (from the data collected this summer) based on appearance, then on sire information, sire and maternal grandsire information and finally the heifer's own genomic information. Comparisons were made on the heifers chosen based on the different selection criteria. A second data set from the Jersey Association was then evaluated based on pedigree and individual genomic information and lactation performance. Comparisons were made on the differences in the accuracy of predicted and actual performance using the different approaches and how this affected revenue received from milk sales. Undergraduate students were tested over this information in each class.

Veterinary students

The Agricultural Animal Club is a club of veterinary students interested in caring for agricultural animals upon graduation. We presented a review of genomic selection and then followed it with the second data set used with the undergraduate students. Nine veterinary students participated in this activity.

Educational Workshops for Dairy Producers and Dairy Veterinarians

With Covid-19 restrictions and the required used of masks indoors, there was a hesitancy from producers to attend in-person workshops, particularly in the fall. We waited until March to increase participation, hoping that the incidence of disease and the restrictions would lessen. We combined the producer and veterinary workshops as we anticipated that there would still be fewer participants than we had originally planned with the current restrictions. We have recently (Sunnyside, March 1) held a workshop in central Washington with 7 participants (3 were veterinarians) and in northwestern Washington (Lynden, March 3) with 15 participants. The next workshop will be in southern Idaho on April 5 and then we will hold two online workshops for those that could not or do not want to attend an in-person workshop. These workshops consisted of a dinner (partly sponsored by Neogen), a review of genetics/genomics and then an exercise where the participants selected and mated heifers based on the pictures and data from the heifers in the demonstration herds we collected this year.

Pre- and post- workshop surveys were collected from participants. Of the participants, 52.6% reported using genomic selection previously and 78% reported that they would like additional information (post workshop). Altogether, participants represented 21,300 cows and 7990 replacement heifers. From the WSARE survey, 100% responded that their awareness of genomics was improved and that they obtained new knowledge. Eighty-nine percent of participants obtained new skills, 75% modified their opinions or attitude toward genomic selection and 75% said that they would adopt new practices. The participants reported that they would likely share this information with a total of 39 others.

Education survey results

  Knowledge Questions Correct (average) Interested in genomics for choosing replacement heifers - yes (maybe yes) Interested in genomics for choosing sires - yes (maybe yes)

 Workshop helpful?

yes definitely (a little)

I am likely to discuss this with peers; as a resource; to give advice
Pre-workshop 86% 41% (53%) 53% (41%) 79% (21%)  
Post-workshop 93% 47% (42%) 78% (21%)   50%; 25%; 25% 
           

Educational & Outreach Activities

55 Curricula, factsheets or educational tools
7 Webinars / talks / presentations
2 Workshop field days

Participation Summary:

25 Farmers
9 Ag professionals participated
Education/outreach description:

Undergraduate courses:

  1. Animal Breeding & Genetics - 3 new lectures, 20 new educational group exercise packets (120 in course)
  2. Dairy Production - 1 new lecture (45 students)
  3. Agricultural Animal Health - 2 new lectures, 1 new educational group exercise (90 in course)

Veterinary students:

  1. Agricultural club - 1 new presentation, 5 new educational exercise materials (10 students)

Educational workshops: 2 new presentations and 20 new group exercise packets

  1. Central Washington (3 veterinarians, 6 producers)
  2. Northwestern Washington (15 producers)
  3. Southern Idaho

Demonstration dairies - 6 dairies and 6 veterinarians

Ranking Spreadsheet - For Use In Educational Settings

Learning Outcomes

19 Farmers reported changes in knowledge, attitudes, skills and/or awareness as a result of their participation
Key areas taught:
  • Concepts of DNA and inheritance of DNA material from parents to offspring
  • Selection (choosing animals in breeding population) can be done visually, through pedigree-based information or an individual's own DNA (genomic selection).
  • Predicted transmitting abilities (PTAs) are predictions of the average performance of an animal's offspring and are available for individual traits and multiple traits (selection indexes).
  • Performance predictions are more accurate using the information from the individual's own DNA. This reduces the risk that the individual animal will be a bad investment.
  • Mating decisions can also be informed through the individual's predicted transmitting abilities.
  • Management decision can be informed through the individual's predicted transmitting abilities.
  • Genomic selection reduces financial risk and increases long-term profitability
  • When and which animals to genotype will depend on breeding goals and when females are sorted that will be culled or bred differently.

Project Outcomes

14 Farmers intend/plan to change their practice(s)

Information Products

    Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.