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ARS Home Plains Area Clay Center, Nebraska U.S. Meat Animal Research Center Genetics and Animal Breeding Research





- McDaneld, Tara
- Kuehn, Larry
- Harhay, Gregory
- Keele, John
- Smith, Timothy - Tim
- Snelling, Warren
- Thallman, Richard - Mark
- 2023
- Publications
- Food Animal Production (101)

Research Project: Genomes to Phenomes in Beef Cattle Research **Location:
                            Genetics and Animal Breeding** 2023 Annual Report **Objectives**
                                

Objective 1.  Improve genomic resource and annotation tools for beef cattle and sheep. 
Sub-objective 1A: Create pangenome resources for cattle. Improve accuracy of imputed cattle genotypes by using pangenome resources.
Sub-objective 1B: Improve annotation of assemblies through FAANG cooperation.

Objective 2.  Develop systems to improve performance through combined genetic and genomic characterization, heterosis, selection and analytical approaches.
Sub-objective 2A: Characterize genetic, genomic and phenotypic variance among and within diverse and influential beef cattle populations toward improved sustainable breeding and management decisions.
Sub-objective 2B: Estimate correlated responses to reducing an index of natural loss-of-function (LOF) alleles on reproduction, health, longevity, and traditional beef production traits.
Sub-objective 2C: Examine whether sequence changes that affect protein structure or expression (functional and structural variants) also effect traits important to beef cattle production efficiency and sustainability.
Sub-objective 2D: Develop strategies to incorporate commercial data into national genetic evaluations.
Sub-objective 2E: Investigate interactions of beef breeds with management systems in diverse environments.
Sub-objective 2F: Develop improved statistical methods for quantitative genetic and genomic analysis of beef cattle data.

Objective 3.  New methods for metagenome assembly, analysis, and characterization. New methods for characterizing genome function of microbes, protists and parasites.  
Sub-objective 3A: Develop methods for combined metagenomic assembly of complete microbial, protist, and parasite genomes from relevant microbiomes related to animals (rumen, gut, feces, environment).
Sub-objective 3B: Develop methods and computational models to characterize genome function of microbes, protists and parasites affecting animal health of sheep and cattle.
Sub-objective 3C: Profile bacterial populations (16S rRNA gene) in the respiratory tract of weaned beef calves after initiation of an inflammatory response.
Sub-objective 3D: Profile bacterial populations (16S rRNA gene) in the digestive tract (rumen) of cattle from source populations from USMARC and Colorado. **Approach**
                                

Challenges to sustainability of beef production include aspects of animal health and wellbeing, societal expectations of reduced antibiotic use and/or development of alternatives, and pressure to reduce the environmental impact of production. Advances in genomic and related technologies have opened new avenues to better understand the relationships between variants of animal genomes, production traits, and the microbes that are associated with animal production, health, and well-being. These technologies support and depend on 1) continued improvement in annotation of cattle and sheep genomes, 2) development of research populations with pertinent phenotypes that broadly represent industry genetics, 3) identification of genomic variants segregating in beef cattle populations and assessment of the interaction of variation with production phenotypes as influenced by environment and management, and 4) characterization of microbes and microbiomes relevant to beef production. The proposed Project Plan will modernize and improve the relevance of phenotyped populations in which the effects of variation can be estimated, enhance genome annotation to sharpen the focus for evaluation of effects of variation on phenotype, and extensively characterize the content and impact of microbiomes and key microbes on target traits. Population-independent and population-specific management strategies will be assessed in cooperation with the ARS Beef Grand Challenge and related programs, using advancements in statistical methodology and partnering with commercial producers and other ARS locations. This combination will enable broader understanding of the components contributing to production efficiency, environmental impact, and animal welfare, while developing specific technologies and estimates of across-breed expected progeny difference (EPD) and heterosis effects for release to beef cattle producers. **Progress Report**
                                

Objective 1 progress exceeded predictions of the project plan. The Bovine Pangenome Consortium led by ARS and founded by an ARS scientist at Clay Center, Nebraska, has assembled the genomes of 16 cattle breeds to “gold standard” level or better, including Angus, Brown Swiss, Charolais, Holstein, Jersey, N’Dama, Wagyu, Piedmontese, Brahman, Gyr, Guzerat, Nelore, Sahiwal, Tharparkar, Ankole, and Boran. Associate members of the consortium in China have assembled another 10 Chinese breed genomes. Another 14 breeds are in various stages of sequencing or assembly. A pangenome representation for cattle was created and revealed missing sequences and novel structural variations among cattle genomes, providing new insights into cattle genetic diversity and evolutionary history. Complete, “telomere-to-telomere” (T2T) assemblies for the Wagyu and Charolais breeds from a male F1 cross of these breeds were completed and are being curated, including the first complete assemblies of cattle sex chromosomes. Sheep T2T genomes were also assembled from a male F1 cross of Native Churro and East Friesian breeds, and comparison of the Y chromosomes of cattle and sheep has revealed unexpected differences between them and contrasts with the sex chromosomes of primates. Beyond the project plan milestones, we proposed a “Ruminant T2T” consortium to generate complete genome assemblies of as many ruminant species as possible to gain new insights into the differences between this sub-Order and non-ruminant species in the Order Cetartiodactyla. In support of this idea, a workshop grant to bring together experts from the human/primate T2T consortium effort and livestock researchers was submitted to and funded by the National Institutes of Food and Agriculture (NIFA). A highly successful workshop was held at Clay Center, Nebraska, in February 2023 with 41 in-person attendees and 61 remote participants, which produced a “white paper” describing the effort and resulted in formation of active working groups to pursue specific types of analyses that will inform the evolution of ruminants and provide insight into genome function that would not be possible without “complete” genome assemblies. At present T2T assemblies of goat, gaur, bison, and water buffalo have been created and are in curation, with assemblies of nine other ruminant species and four non-ruminant Cetartiodactlya species in progress. We also supported completion of Functional Annotation of Animal Genomes efforts for methylation and histone modification studies that expanded these efforts by applying emerging methods of analysis from the genome assembly pipeline to provide methylation data across the complete genome, not just the parts assembled in the reference genomes for cattle and sheep. 
For Objective 2, the Germplasm Evaluation Program (GPE) project is continuing from the previous project plan cycle with its evaluation of 18 different cattle breeds. With the loss of fall calving, recent drought mitigation, and the sale of breeding females to a collaborative location, the number of cows in the project has decreased to approximately 2,800 breeding females from a previous target of 3,600-4,000 females. However, the project remains on track for objectives to compare all breeds. Approximately 40% of these breeding females are nearly purebred which will facilitate new analyses to estimate breed specific heterosis for the large suite of traits measured in the project. We still have goals to produce over 1,000 animals via artificial insemination every year. This year (breeding season for 2024), that number had to be reduced dramatically due to drought conditions, so we are hoping for a rebound on these matings in 2024 for the 2025 calving season. We are now keeping a battery of approximately 150 bulls produced by the project to accommodate all our full season and clean-up breeding needs. 
Data collection in the Beef Grand Challenge Project competed last fall and analyses of the initial data on growth are now being conducted. This project evaluated GPE calves in stocker programs in different backgrounding systems with partner ARS locations (Clay Center, Nebraska; El Reno, Oklahoma; Miles City, Montana; Nunn, Colorado; Woodward, Oklahoma). We expect the genetics by environment by management interactions from this stocker program to help inform the need to account for genetic reranking potentials in National Cattle Evaluations and to inform breed choices in different regions of the country.
As an extension of the Beef Grand Challenge Project, we have now sent beef cows from our GPE program to partners in Beeville, Texas, and the ARS location in El Reno, Oklahoma. We expect that progeny from calves born to cows in these locations and in Clay Center, Nebraska, to further contribute to estimation of genetic by environment by management interactions that continue to impact breeding decisions and cattle evaluations for cow herd traits.
A pipeline to impute low-coverage sequence to phased haplotypes detected in a reference panel of 970 animals was finalized. The deeply sequenced panel includes natural service and artificial insemination sires of the GPE population, bulls used in each line of Selection for Functional Alleles project (SFA), and representatives of several cattle breeds whose sequence is publicly available. This pipeline has been applied to low-coverage sequence reads of SFA calves to make selections at weaning based on genotypes for loss-of-function variants, as well as to cattle from GPE and University of Nebraska-Lincoln populations. With new advancements in low-coverage sequencing, we are now able to impute sequence variants (up to 50 million) through the Grand Challenge Project. These imputations will allow us to perform genomic analyses on the over 40,000 animals genotyped for some platform throughout the GPE project. The processes were extended to call copy number variation from low-coverage sequence.   
For the SFA population, packers informed us that quality of the MARC I composite, one of the populations currently under selection for functional alleles, was too low for them to consider purchasing the cattle in the future. To improve the quality of the cattle while continuing functional allele selection, Red Angus bulls with marbling expected progeny differences in the top half of the breed were sourced for mating to MARC I females. Functional allele genotypes were imputed from low-coverage sequence from those bulls so they could be assigned to select and control lines. Red Angus bulls will continue to be sourced for mating to remaining MARC I cows, while Red Angus x MARC I (MARC IA) replacement bulls and females will be selected and mated to generate a higher quality, more marketable composite.
We have continued to examine consequences of DNA pooling designs on errors associated with genotyping groups of animals as a pool. We now have interest from a swine breeding company and multiple cattle breed associations to assist them with incorporation of data from these pools into their genetic evaluation program. Continuing steps in this area could provide a means to incorporate data from commercial operations into seedstock selection programs. 
Objective 3 progress included completion of a pilot metagenome assembly study of sheep fecal material infested with internal parasites from the Strongyloides and Coccidial classes. This relatively simple sample provided estimates for the amount of sequence that would be required to adequately describe the more complex microbial communities found in the rumen, which harbor on the order of 10-fold more microbial species than fecal material. Initial characterization of rumen samples indicates that the 10-fold estimate is likely quite understated, possibly by an order of magnitude or more, and that novel approaches to metagenome assembly will be required. Collaborations to advance these efforts have been established, new instrumentation to support a higher depth of sequencing coverage has been procured, and initial samples have been sequenced. A parallel effort to study the eukaryotic component of the microbial community, known as protists, was pursued, and revealed extreme complexity of DNA extracted from samples highly enriched for protist content. This is likely due to the biology of protists, as they ingest bacteria as a food source and thus individual protist cells will have DNA fragments from prey bacteria. Approaches to overcome this previously-reported complication have been devised and are being tested, including development of methods to reduce complexity by narrowing focus to single protist species by size-based fractionation of the protist population.
ARS scientists at Clay Center, Nebraska, evaluated the microbial communities in the upper respiratory tract of calves across multiple timepoints. This work is part of a NIFA grant with collaborators at Teagasc and Agri-food and Biosciences Institute (AFBI). Evaluation of the animal’s resident respiratory pathogens including microbial and viral agents in the upper nasal cavity will help us to understand the impact of these pathogens on disease incidence. This NIFA grant is entering into the fifth year (non-funded year extension) in which data for secondary viral and bacterial infection by monitoring experimentally virus infected animals in longitudinal studies at AFBI will be analyzed.
For the rumen microbiome, we are evaluating the rumen samples from the Grand Challenge as outlined in Objective 2. Extraction of DNA has been completed for rumen samples collected at Clay Center, Nebraska, and Miles City, Montana. Analysis of the sequence data of bacterial populations has been initiated and preliminary data has been evaluated. DNA extraction is underway for rumen samples from El Reno, Oklahoma. **Accomplishments**
                                

1. Creation of the first complete, ungapped sex chromosome assemblies for cattle, sheep, and goat. Sex chromosomes (X and Y in mammals) harbor important genes affecting sex-specific traits and lack of high-quality assemblies have hampered genetic and genomic research in livestock species. Sex chromosomes have been very difficult to assemble from DNA sequence due to the presence of highly repetitive sequence arrays that can extend for millions of base pairs. ARS scientists at Clay Center, Nebraska, and Beltsville, Maryland, collaborated with researchers at the University of Idaho, Utah State University, University of Missouri, and the National Institutes of Health, to create and analyze complete sex chromosomes from cattle, sheep, and goat. The group produced the first complete sex chromosomes for any livestock species and identified surprising differences between gene content and arrangement between the ruminant species and between ruminants and primates. This work opens the door for improved analysis of sex-specific trait expression in three important livestock species. Genetic improvement programs with sex-specific inheritance patterns will now have higher accuracy. Beef cattle producers will benefit through an increased rate of genetic progress for important traits in these livestock species. 2. DNA pooling technique to reveal genetic connections between seedstock and commercial sectors of the beef industry. Genetic evaluation of seedstock cattle could benefit from commercial data as there are hidden relationships between commercial and seedstock sectors because many commercial producers buy bulls from the seedstock sector. Single nucleotide polymorphism genotypes could reveal these hidden relationships; however, genotyping can be cost prohibitive. The cost of commercial data capture could be decreased by pooling DNA, which is a method to genotype groups of animals to use their data in genetic evaluation. ARS researchers in Clay Center, Nebraska, constructed DNA pools with portions of shared unrelated animals to determine whether it is possible to reveal genetic connections between seedstock and commercial sectors, thus enabling the beef industry to produce cattle that better fit commercial production systems, as genetic evaluation of seedstock cattle could benefit from commercial data. DNA pools were created to mimic the results of DNA pools sharing relatives with the same degree of shared genomes. For example, a DNA pool of progeny and a DNA pool of the dams of the pooled progeny would produce the same result as two DNA pools sharing 50% overlap of unrelated animals. Knowing the relationship between seedstock cattle and DNA pools of commercial cattle may allow commercial data to enhance genetic evaluation of seedstock animals ultimately resulting in beef cattle with superior performance and efficiencies. Cattle that fit optimally in their production system have better health, are more environmentally sustainable and are more efficient, leading to more sustainable beef production. 3. Birth weight and postweaning gain of cattle from the Germplasm Evaluation project. Birth weight and postweaning gain of cattle from the Germplasm Evaluation project, that had been sequenced at low coverage (~0.5x) and had sequence-level genotypes imputed, were examined by ARS researchers in Clay Center, Nebraska, to estimate the amount of variation explained by sequence variants. Genotypes for single nucleotide polymorphism (SNP), a common type of genomic marker, on commercial SNP chips as well as variants within and near protein-coding genes were extracted and divided into sets according to expected functional consequences. Genomic relationship matrices were constructed for each marker subset to estimate variance components to see which portions explain the most variation. Fitting all markers explained the most variation in both birth weight and postweaning gain, followed by the modifier variants which are close to genes but do not alter the protein-coding sequence. Little variation was attributable to high impact variants, which can cause loss of gene function. Further refinement of markers using similar methods will identify marker sets that are more robust across breeds and improve our ability to use genomic markers in genomic improvement programs for important industry traits. Beef cattle producers will benefit from faster rates of genetic improvement as a result. 4. Evaluation of breed differences and heterosis for mature cow body composition and weight. Body condition score (BCS) and mature weight are both important indicators of mature cow efficiency and, subsequently, feed requirements. While a higher-condition score may result in heavier mature weights, the relationship is not guaranteed across breeds or animals within breeds. ARS researchers at Clay Center, Nebraska, with collaborators at the University of Nebraska, estimated breed differences for 16 different breeds as well as heterosis and genetic relationships between BCS and mature weight. Both traits were moderately heritable across cow parities and genetic relationships between the parities ranged from 0.3 to 0.6 indicating that although the traits are moderately related, selection for one trait is possible without changing the other. These results will help producers select breeds or individuals with lower maintenance energy requirements and will enable decision support tools for producers seeking to reduce cow maintenance requirements, which contribute to feed costs. These results are already being utilized in one large multibreed evaluation program in the United States (International Genetic Solutions). **Review Publications**
                            *Rosenblatt, E., Gieder, K., Donovan, T., Murdoch, J., Smith, T.P.L., Heaton, M.P., Kalbfleisch, T.S., Murdoch, B.M., Bhattarai, S., Pacht, E., Verbist, E., Basnayake, V., McKay, S. 2023. Genetic diversity and connectivity of moose (Alces americanus americanus) in eastern North America. Conservation Genetics. 24:235-248. https://doi.org/10.1007/s10592-022-01496-w.*
                                *Ren, Y., Tseng, E., Smith, T.P.L., Hiendleder, S., Williams, J.L., Low, W. 2023. Long read isoform sequencing reveals hidden transcriptional complexity between cattle subspecies. BMC Genomics. 24. Article 108. https://doi.org/10.1186/s12864-023-09212-9.*
                                *Keele, J.W., McDaneld, T.G., Kuehn, L.A. 2023. Use of overlapping DNA pools to discern genetic differences despite pooling error. Journal of Animal Science. 101. Article skad166. https://doi.org/10.1093/jas/skad166.*
                                *McDaneld, T.G., Workman, A.M., Chitko-McKown, C.G., Kuehn, L.A., Dickey, A.M., Bennett, G.L. 2022. Detection of Mycoplasma bovirhinis and bovine coronavirus in an outbreak of bovine respiratory disease in nursing beef calves. Frontiers in Microbiomes. 1. Article 1051241. https://doi.org/10.3389/frmbi.2022.1051241.*
                                *Sanglard, L.P., Snelling, W.M., Kuehn, L.A., Thallman, R.M., Freetly, H.C., Wheeler, T.L., Shackelford, S.D., King, D.A., Spangler, M.L. 2022. Genetic and phenotypic associations of mitochondrial DNA copy number, SNP, and haplogroups with growth and carcass traits in beef cattle. Journal of Animal Science. 101. Article skac415. https://doi.org/10.1093/jas/skac415.*
                                *Ault-Seay, T.B., Brandt, K.J., Henniger, M.T., Payton, R.R., Mathew, D.J., Moorey, S.E., Schrick, F.N., Pohler, K.G., Smith, T.P.L., Rhinehart, J.D., Schneider, L.G., McLean, K.J., Myer, P.R. 2022. Bacterial communities of the uterus and rumen during heifer development with protein supplementation. Frontiers in Animal Science. 3. Article 903909. https://doi.org/10.3389/fanim.2022.903909.*
                                *Baller, J.L., Kachman, S.D., Kuehn, L.A., Spangler, M.L. 2022. Using pooled data for genomic prediction in a bivariate framework with missing data. Journal of Animal Breeding and Genetics. Article 12727. https://doi.org/10.1111/jbg.12727.*
                                *Sanglard, L.P., Kuehn, L.A., Snelling, W.M., Spangler, M.L. 2022. Influence of environmental factors and genetic variation on mitochondrial DNA copy number. Journal of Animal Science. 100(5). Article skac059. https://doi.org/10.1093/jas/skac059.*
                                *Snelling, W.M., Thallman, R.M., Spangler, M.L., Kuehn, L.A. 2022. Breeding sustainable beef cows: Reducing weight and increasing productivity. Animals. 12(14). Article 1745. https://doi.org/10.3390/ani12141745.*
                                *Leonard, A.S., Crysnanto, D., Fang, Z., Heaton, M.P., Vander Ley, B.L., Herrera, C., Bollwein, H., Bickhart, D.M., Kuhn, K.L., Smith, T.P.L., Rosen, B.D., Pausch, H. 2022. Structural variant-based pangenome construction has low sensitivity to variability of haplotype-resolved bovine assemblies. Nature Communications. 13. Article 3012. https://doi.org/10.1038/s41467-022-30680-2.*
                                *Ribeiro, A.F., Sanglard, L.P., Snelling, W.M., Thallman, R.M., Kuehn, L.A., Spangler, M.L. 2022. Genetic parameters, heterosis, and breed effects for body condition score and mature cow weight in beef cattle. Journal of Animal Science. 100(2). Article skac017. https://doi.org/10.1093/jas/skac017.*
                                *Keele, J., McDaneld, T., Lawrence, T., Jennings, J., Kuehn, L. 2021. Estimation of pool construction and technical error. Agriculture. 11(11). Article 1091. https://doi.org/10.3390/agriculture11111091.*
                                *Harhay, G.P., Harhay, D.M., Brader, K.D., Smith, T.P.L. 2021. A conserved Histophilus somni 23S intervening sequence yields functional, fragmented 23S rRNA. Microbiology Spectrum. 9(3). Article e0143121. https://doi.org/10.1128/Spectrum.01431-21.*
                                *Bennett, G.L., Keele, J.W., Kuehn, L.A., Snelling, W.M., Dickey, A.M., Light, D.E., Cushman, R.A., McDaneld, T.G. 2021. Using genomics to measure phenomics: Repeatability of bull prolificacy in multiple-bull pastures. Agriculture. 11(7). Article 603. https://doi.org/10.3390/agriculture11070603.*
                                *Zimmermann, M.J., Kuehn, L.A., Spangler, M.L., Thallman, R.M., Snelling, W.M., Lewis, R.M. 2021. Breed and heterotic effects for mature weight in beef cattle. Journal of Animal Science. 99(8). Article skab209. https://doi.org/10.1093/jas/skab209.*
                                *Clemmons, B.A., Shin, S.B., Smith, T.P.L., Embree, M.M., Voy, B.H., Schneider, L.G., Donohoe, D.R., McLean, K.J., Myer, P. 2021. Ruminal protozoal populations of Angus steers differing in feed efficiency. Animals. 11(6). Article 1561. https://doi.org/10.3390/ani11061561.*
                                *Ren, Y., MacPhillamy, C., To, T., Smith, T.P.L., Williams, J.L., Low, W.Y. 2021. Adaptive selection signatures in river buffalo with emphasis on immune and major histocompatibility complex genes. Genomics. 113(6):3599-3609. https://doi.org/10.1016/j.ygeno.2021.08.021.*
                                *Gillespi, A., Yirsaw, A., Gunasekaran, K.P., Smith, T.P., Bickhart, D.M., Turley, M., Connelley, T., Telfer, J.C., Baldwin, C.L. 2021. Characterization of the domestic goat yd T cell receptor gene loci and gene usage. Immunogenetics. 73:187-201. https://doi.org/10.1007/s00251-021-01203-y.*
                                *Liu, R., Tearle, R., Low, W., Chen, T., Thomsen, D., Smith, T.P.L., Hiendleder, S., Williams, J.L. 2021. Distinctive gene expression patterns and imprinting signatures revealed in reciprocal crosses between cattle sub-species. Biomed Central (BMC) Genomics. 22. Article 410. https://doi.org/10.1186/s12864-021-07667-2.*
                                *Cuevas-Gomes, I., McGee, M., Sanchez, J., O'Riordan, E., Byrne, N., McDaneld, T.G., Earley, B. 2021. Association between clinical respiratory signs, lung lesions detected by thoracic ultrasonography and growth performance in pre-weaned dairy calves. Irish Veterinary Journal. 74. Article 7. https://doi.org/10.1186/s13620-021-00187-1.*
                                *Safonova, Y., Shin, S.B., Kramer, L., Reecy, J., Watson, C.T., Smith, T.P.L., Pevzner, P.A. 2022. Variations in antibody repertoires correlate with vaccine responses. Genome Research. 32:791-804. https://doi.org/10.1101/gr.276027.121.*
                                *Perkin, L.C., Smith, T.P., Oppert, B.S., Poelchau, M. 2021. Variants in the mitochondrial genome sequence of Rhyzopertha dominica (Fabricius)(Coleoptera: Bostrycidae). Insects. 12(5). Article 387. https://doi.org/10.3390/insects12050387. LOG NO. 378692*
                                *Chitko-McKown, C.G., Bennett, G.L., Kuehn, L.A., DeDonder, K.D., Apley, M.D., Harhay, G.P., Clawson, M.L., Workman, A.M., White, B.J., Larson, R.L., Capik, S.F., Lubbers, B.V. 2021. Cytokine and haptoglobin profiles from shipping through sickness and recovery in metaphylaxis- or un-treated cattle. Frontiers in Veterinary Science. 8. Article 611927. https://doi.org/10.3389/fvets.2021.611927.*
                                *Dobson, L.K., Zimin, A., Bayles, D., Fritz-Waters, E., Alt, D., Olsen, S., Blanchong, J., Reecy, J., Smith, T.P.L., Derr, J.N. 2021. De novo assembly and annotation of the North American bison (Bison bison) reference genome and subsequent variant identification. Animal Genetics. 52(3):263-274. https://doi.org/10.1111/age.13060.*
                                *Bennett, G.L., Thallman, R.M., Snelling, W.M., Keele, J.W., Freetly, H.C., Kuehn, L.A. 2021. Genetic changes in beef cow traits following selection for calving ease. Translational Animal Science. 5(1):1-10. https://doi.org/10.1093/tas/txab009.*
                                *Chitko-McKown, C.G., Bierman, S.L., Kuehn, L.A., Bennett, G.L., DeDonder, K.D., Apley, M.D., Harhay, G.P., Clawson, M.L., White, B.J., Larson, R.L., Capik, S.F., Lubbers, B.V. 2021. Detection of bovine inflammatory cytokines IL-1ß, IL-6, and TNF-a with a multiplex electrochemiluminescent assay platform. Veterinary Immunology and Immunopathology. 237. Article 110274. https://doi.org/10.1016/j.vetimm.2021.110274.*
                                *Psota, E.T., Luc, E.K., Pighetti, G.M., Schneider, L.G., Trout Fryxell, R.T., Keele, J.W., Kuehn, L.A. 2021. Development and validation of a neural network for the automated detection of horn flies on cattle. Computers and Electronics in Agriculture. 180. Article 105927. https://doi.org/10.1016/j.compag.2020.105927.*


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