Talk on the genetic and genomic evaluation system for US dairy cattle made to scientists at Embrapa Gado de Leite in Juiz de Fora, MG, Brasil, on September 10, 2014.
This document discusses feeding strategies for high-yielding dairy cows. It notes that milk is synthesized from nutrients absorbed from the bloodstream. High yielders are defined as cows producing over 20 kg/day or buffaloes over 15 kg/day. Feeding strategies for high yielders include providing extra rations of high-quality roughage and concentrates, gradually increasing concentrates, and maintaining 14% crude protein. Challenge feeding involves increasing concentrates before calving to prepare cows for high milk production. Minerals like calcium, phosphorus and magnesium are also important to meet requirements and prevent issues like milk fever. Buffers help maintain rumen pH for optimal fiber digestion and milk fat levels.
The document summarizes key aspects of pig reproduction including female and male anatomy, the estrous cycle, signs of heat, breeding, pregnancy diagnosis techniques, farrowing, and post-partum events. It describes the female reproductive tract including ovaries, oviducts, uterus, cervix, and vagina. It also outlines the male reproductive system including testes, epididymis, and penis. Key events of the estrous cycle, signs of heat in sows, breeding methods, and pregnancy diagnosis techniques are summarized.
This document discusses calf fattening in Pakistan. It notes the increasing demand for meat due to population growth, urbanization, and rising incomes. Per capita meat consumption in Pakistan has risen from 11 kg in 1983 to a projected 47 kg in 2020. The majority of beef production comes from traditional, inefficient systems involving young calves. The document advocates for commercial feedlot systems to finish calves on balanced diets to higher weights to produce quality beef. It provides details on feedlot design, selection of animals, feeding, and management. Feeding trials demonstrated growth rates of over 1 kg per day. Commercial feedlot systems can yield good profits but farmers must sell processed, high quality meat through organized markets.
This document summarizes the utilization of sex-sorted semen in cattle production. It discusses how sperm are sorted based on their X and Y chromosomes into sexed semen with 80-90% accuracy using flow cytometry. The sexed semen allows producers to limit offspring to a single sex. The document outlines the sex-sorting process and provides examples of its use in the dairy industry to produce more valuable female calves and in the beef industry to produce male calves. It also briefly discusses potential issues like calf welfare due to killing of excess male calves.
Priority areas of livestock sector for strengthening food and nutrition secur...ILRI
Presented by Tek B. Gurung and Bimal K. Nirmal at the Workshop on transforming livelihoods in South Asia through sustainable livestock research and development, Kathmandu, Nepal, 13-14 November 2018
This document discusses feeding strategies for high-yielding dairy cows. It notes that milk is synthesized from nutrients absorbed from the bloodstream. High yielders are defined as cows producing over 20 kg/day or buffaloes over 15 kg/day. Feeding strategies for high yielders include providing extra rations of high-quality roughage and concentrates, gradually increasing concentrates, and maintaining 14% crude protein. Challenge feeding involves increasing concentrates before calving to prepare cows for high milk production. Minerals like calcium, phosphorus and magnesium are also important to meet requirements and prevent issues like milk fever. Buffers help maintain rumen pH for optimal fiber digestion and milk fat levels.
The document summarizes key aspects of pig reproduction including female and male anatomy, the estrous cycle, signs of heat, breeding, pregnancy diagnosis techniques, farrowing, and post-partum events. It describes the female reproductive tract including ovaries, oviducts, uterus, cervix, and vagina. It also outlines the male reproductive system including testes, epididymis, and penis. Key events of the estrous cycle, signs of heat in sows, breeding methods, and pregnancy diagnosis techniques are summarized.
This document discusses calf fattening in Pakistan. It notes the increasing demand for meat due to population growth, urbanization, and rising incomes. Per capita meat consumption in Pakistan has risen from 11 kg in 1983 to a projected 47 kg in 2020. The majority of beef production comes from traditional, inefficient systems involving young calves. The document advocates for commercial feedlot systems to finish calves on balanced diets to higher weights to produce quality beef. It provides details on feedlot design, selection of animals, feeding, and management. Feeding trials demonstrated growth rates of over 1 kg per day. Commercial feedlot systems can yield good profits but farmers must sell processed, high quality meat through organized markets.
This document summarizes the utilization of sex-sorted semen in cattle production. It discusses how sperm are sorted based on their X and Y chromosomes into sexed semen with 80-90% accuracy using flow cytometry. The sexed semen allows producers to limit offspring to a single sex. The document outlines the sex-sorting process and provides examples of its use in the dairy industry to produce more valuable female calves and in the beef industry to produce male calves. It also briefly discusses potential issues like calf welfare due to killing of excess male calves.
Priority areas of livestock sector for strengthening food and nutrition secur...ILRI
Presented by Tek B. Gurung and Bimal K. Nirmal at the Workshop on transforming livelihoods in South Asia through sustainable livestock research and development, Kathmandu, Nepal, 13-14 November 2018
Feeding standards provide tables indicating nutrient quantities required by livestock for different physiological functions. There are two terms used - nutrient allowance and nutrient requirements. Nutrient requirements define the specific nutrients and amounts needed in a complete balanced diet for healthy animals. Feeding standards include comparative, digestible-nutrient, and production-value types. Nutrient requirements vary depending on factors like mature size, gestation stage, and milk production potential. Requirements also differ between dairy cattle and buffalo due to differences in feed utilization efficiency, rumen volume and motility, dry matter intake, and other digestive traits.
Record keeping in dairy farm management.pdfHari Om Pandey
Presentation tries to explain role of record keeping in sound planning of breeding, feeding and heeding and health management of dairy farm
in order to efficiently and effectively manage growth, production and reproduction. It assists in livestock management decisions and evaluates overall activities of the dairy farm.
This document discusses selection of high quality dairy animals and monitoring herd performance. It describes important points for selecting animals such as breed characteristics, production ability, and docility. Selection should be based on factors like body conformation, health, and past lactation performance. Methods of selection mentioned include mass selection, tandem selection, independent culling, and using a selection index. Monitoring herd performance allows for early problem detection. Methods discussed are tracking clinical disease, feed intake, milk production, and body condition scoring.
Heat treatment and chemical treatments can increase the bypass protein content of feed ingredients fed to ruminants. Heat treatment through processes like autoclaving can increase the rumen undegraded protein fraction by denaturing proteins and forming protein-carbohydrate complexes. Chemical treatments using formaldehyde or lignosulfonate can also increase rumen undegraded protein by forming cross-links between amino acids or precipitating protein respectively, making it less susceptible to microbial breakdown in the rumen. The level of treatment and feed ingredient impacts the effectiveness at increasing bypass protein for ruminant digestion and nutrition.
This document provides information on feeding cattle and buffalo, including:
1. Definitions of key terms like ration, balanced ration, concentrate, and roughage.
2. Guidelines for formulating balanced rations including determining nutrient requirements, understanding feed composition, and combining feeds to meet animal requirements.
3. Details on calculating nutrient requirements for maintenance, production, pregnancy, growth, and examples of such calculations.
4. Information on feedstuff composition and examples of nutrient profiles of common feeds.
5. Overview of formulating balanced rations by partitioning feeds into roughages and concentrates.
The document discusses reproductive hormones and methods for inducing estrus and synchronizing ovulation in cattle. It describes the major reproductive hormones including GnRH, LH, FSH, progesterone, estrogen, hCG, and prostaglandins. It then explains several common methods for synchronizing estrus, including the use of prostaglandins, progestins like MGA and CIDR, and gonadotropin-releasing hormone in protocols like Ovsynch, Cosynch, and Heatsynch. The advantages, limitations, and costs of different synchronization methods are reviewed.
This document discusses various managemental strategies for reducing calving interval in farm animals. It covers factors that affect calving interval such as genetics, nutrition, year/season of calving, sex of calf. Management practices to improve calving interval include keeping accurate breeding records, detecting heat accurately, synchronizing estrus and breeding cycles, culling unhealthy animals, and providing proper nutrition and health programs. Hormonal treatments can also be used to reduce the postpartum anestrus period and tighten the calving interval.
Recording systems and their effect on animal breeding in EthiopiaNahom Ephrem
This document discusses the importance of record keeping for animal breeding in Ethiopia. It begins by explaining that reliable recording systems are needed to support cattle breeding programs and effective decision making. It then describes how livestock production in developing countries like Ethiopia is typically characterized by small herds without formal pedigree or performance recording. This limits the implementation of genetic improvement programs. The document outlines the types of records that should be kept, including breeding, production, health, feeding and financial records. It explains that record keeping benefits herd improvement and breeding programs by enabling selection, culling, and controlling inbreeding. However, lack of record keeping in Ethiopia has led to unplanned crossbreeding and increased inbreeding. The document concludes by identifying constraints that
Overview of Community Based Breeding Program and implementation procedureILRI
Presented by Tesfaye Getachew, ICARDA, at the SmaRT Ethiopia workshop and field day on Small Ruminant Community Based Breeding Program (CBBP), Hosaena, Ethiopia, 27–28 March 2018
Dry cow and heifer management is important for reducing calving problems and optimizing productivity. A farmer should select sires known for easy calving, especially for heifers, to avoid difficulties. Heifers are more vulnerable as their birth canals are stretching for the first time. Underfeeding dry cows and heifers does not result in smaller calves but impacts the health and productivity of the mother after calving. Proper feeding, management, and attention in the period before and after calving is crucial for health and performance.
Dr. Sushil Neupane's notes on "Introductory Genetics and Animal Breeding" for the 2nd year, 1st semester of the Diploma in Animal Science (latest syllabus of CTEVT) provide a comprehensive overview of key concepts and principles related to genetics and animal breeding. The notes cover fundamental topics in genetics and their practical applications in livestock production and breeding programs.
The document discusses cattle breeds found in India. It classifies them based on utility into milk, dual-purpose and draught breeds. It then describes the key physical characteristics and performance of popular breeds like Sahiwal, Gir, Hariana, Kankrej, Hallikar and Kangayam. These breeds are classified into 5 groups based on physical features. The document provides details of 19 native zebu cattle breeds of India, their origins, characteristics and status.
This document discusses feeding practices for small ruminants like sheep and goats. It provides information on meeting the nutritional requirements of sheep at different life stages through creep feeding and supplemental feeding. It also discusses feeding practices during pregnancy and lactation. Recommended ration compositions are provided for different physiological stages. Feeding behaviors and dietary preferences of goats are also covered.
Presented by Raphael Mrode, ILRI, at the workshop on Essential Knowledge for Effective Improvement and Dissemination of Genetics in Sheep and Goats, Addis Ababa, Ethiopia, 3–5 November 2020
Record keeping is a necessary element of good dairy management.
With no written records, farmers have to depend on their memory while making decisions regarding their farm practices.
Record keeping starts from Birth till death .
The document discusses ABS's dairy and beef sire selection processes. For dairy, most sires come from special matings of high-PTA cows and bulls. Progeny testing involves placing young bulls in limited service across many herds to evaluate daughters, with only 1 in 10 bulls graduating. For beef, ABS uses 8 criteria including EPDs and ultrasound data to select bulls with varied growth and maternal traits suited to different operations.
Economic Analysis Tools for Dairy Reproduction ProgramsDAIReXNET
This material was presented by Dr. Victor Cabrera for DAIReXNET on Monday, April 8, 2013. For more information, please see our archived webinars page at www.extension.org/pages/15830/archived-dairy-cattle-webinars.
Feeding standards provide tables indicating nutrient quantities required by livestock for different physiological functions. There are two terms used - nutrient allowance and nutrient requirements. Nutrient requirements define the specific nutrients and amounts needed in a complete balanced diet for healthy animals. Feeding standards include comparative, digestible-nutrient, and production-value types. Nutrient requirements vary depending on factors like mature size, gestation stage, and milk production potential. Requirements also differ between dairy cattle and buffalo due to differences in feed utilization efficiency, rumen volume and motility, dry matter intake, and other digestive traits.
Record keeping in dairy farm management.pdfHari Om Pandey
Presentation tries to explain role of record keeping in sound planning of breeding, feeding and heeding and health management of dairy farm
in order to efficiently and effectively manage growth, production and reproduction. It assists in livestock management decisions and evaluates overall activities of the dairy farm.
This document discusses selection of high quality dairy animals and monitoring herd performance. It describes important points for selecting animals such as breed characteristics, production ability, and docility. Selection should be based on factors like body conformation, health, and past lactation performance. Methods of selection mentioned include mass selection, tandem selection, independent culling, and using a selection index. Monitoring herd performance allows for early problem detection. Methods discussed are tracking clinical disease, feed intake, milk production, and body condition scoring.
Heat treatment and chemical treatments can increase the bypass protein content of feed ingredients fed to ruminants. Heat treatment through processes like autoclaving can increase the rumen undegraded protein fraction by denaturing proteins and forming protein-carbohydrate complexes. Chemical treatments using formaldehyde or lignosulfonate can also increase rumen undegraded protein by forming cross-links between amino acids or precipitating protein respectively, making it less susceptible to microbial breakdown in the rumen. The level of treatment and feed ingredient impacts the effectiveness at increasing bypass protein for ruminant digestion and nutrition.
This document provides information on feeding cattle and buffalo, including:
1. Definitions of key terms like ration, balanced ration, concentrate, and roughage.
2. Guidelines for formulating balanced rations including determining nutrient requirements, understanding feed composition, and combining feeds to meet animal requirements.
3. Details on calculating nutrient requirements for maintenance, production, pregnancy, growth, and examples of such calculations.
4. Information on feedstuff composition and examples of nutrient profiles of common feeds.
5. Overview of formulating balanced rations by partitioning feeds into roughages and concentrates.
The document discusses reproductive hormones and methods for inducing estrus and synchronizing ovulation in cattle. It describes the major reproductive hormones including GnRH, LH, FSH, progesterone, estrogen, hCG, and prostaglandins. It then explains several common methods for synchronizing estrus, including the use of prostaglandins, progestins like MGA and CIDR, and gonadotropin-releasing hormone in protocols like Ovsynch, Cosynch, and Heatsynch. The advantages, limitations, and costs of different synchronization methods are reviewed.
This document discusses various managemental strategies for reducing calving interval in farm animals. It covers factors that affect calving interval such as genetics, nutrition, year/season of calving, sex of calf. Management practices to improve calving interval include keeping accurate breeding records, detecting heat accurately, synchronizing estrus and breeding cycles, culling unhealthy animals, and providing proper nutrition and health programs. Hormonal treatments can also be used to reduce the postpartum anestrus period and tighten the calving interval.
Recording systems and their effect on animal breeding in EthiopiaNahom Ephrem
This document discusses the importance of record keeping for animal breeding in Ethiopia. It begins by explaining that reliable recording systems are needed to support cattle breeding programs and effective decision making. It then describes how livestock production in developing countries like Ethiopia is typically characterized by small herds without formal pedigree or performance recording. This limits the implementation of genetic improvement programs. The document outlines the types of records that should be kept, including breeding, production, health, feeding and financial records. It explains that record keeping benefits herd improvement and breeding programs by enabling selection, culling, and controlling inbreeding. However, lack of record keeping in Ethiopia has led to unplanned crossbreeding and increased inbreeding. The document concludes by identifying constraints that
Overview of Community Based Breeding Program and implementation procedureILRI
Presented by Tesfaye Getachew, ICARDA, at the SmaRT Ethiopia workshop and field day on Small Ruminant Community Based Breeding Program (CBBP), Hosaena, Ethiopia, 27–28 March 2018
Dry cow and heifer management is important for reducing calving problems and optimizing productivity. A farmer should select sires known for easy calving, especially for heifers, to avoid difficulties. Heifers are more vulnerable as their birth canals are stretching for the first time. Underfeeding dry cows and heifers does not result in smaller calves but impacts the health and productivity of the mother after calving. Proper feeding, management, and attention in the period before and after calving is crucial for health and performance.
Dr. Sushil Neupane's notes on "Introductory Genetics and Animal Breeding" for the 2nd year, 1st semester of the Diploma in Animal Science (latest syllabus of CTEVT) provide a comprehensive overview of key concepts and principles related to genetics and animal breeding. The notes cover fundamental topics in genetics and their practical applications in livestock production and breeding programs.
The document discusses cattle breeds found in India. It classifies them based on utility into milk, dual-purpose and draught breeds. It then describes the key physical characteristics and performance of popular breeds like Sahiwal, Gir, Hariana, Kankrej, Hallikar and Kangayam. These breeds are classified into 5 groups based on physical features. The document provides details of 19 native zebu cattle breeds of India, their origins, characteristics and status.
This document discusses feeding practices for small ruminants like sheep and goats. It provides information on meeting the nutritional requirements of sheep at different life stages through creep feeding and supplemental feeding. It also discusses feeding practices during pregnancy and lactation. Recommended ration compositions are provided for different physiological stages. Feeding behaviors and dietary preferences of goats are also covered.
Presented by Raphael Mrode, ILRI, at the workshop on Essential Knowledge for Effective Improvement and Dissemination of Genetics in Sheep and Goats, Addis Ababa, Ethiopia, 3–5 November 2020
Record keeping is a necessary element of good dairy management.
With no written records, farmers have to depend on their memory while making decisions regarding their farm practices.
Record keeping starts from Birth till death .
The document discusses ABS's dairy and beef sire selection processes. For dairy, most sires come from special matings of high-PTA cows and bulls. Progeny testing involves placing young bulls in limited service across many herds to evaluate daughters, with only 1 in 10 bulls graduating. For beef, ABS uses 8 criteria including EPDs and ultrasound data to select bulls with varied growth and maternal traits suited to different operations.
Economic Analysis Tools for Dairy Reproduction ProgramsDAIReXNET
This material was presented by Dr. Victor Cabrera for DAIReXNET on Monday, April 8, 2013. For more information, please see our archived webinars page at www.extension.org/pages/15830/archived-dairy-cattle-webinars.
The increasing availability of SNP (single nucleotide polymorphisms) genotype data in livestock is stimulating the development of new data analysis strategies, which can be applied in animal breeding. One possible application is the prediction of carriers of specific haplotypes, especially if they impact animal health. It is therefore convenient to have a practical and easy-to-implement statistical method for the accurate classification of individuals into carriers and non-carriers. In this paper, we present a procedure for the identification of carriers of the haplotype HH1 on BTA5 (Bos Taurus autosome 5), which is known to be associated with reduced cow fertility in Holstein-Friesian cattle. A population of 1104 Holstein bulls genotyped with the 54K SNP-chip was available for the analysis. There were 45 carriers (5.3%) and 1045 non-carriers (94.7%). Two complementary multivariate statistical techniques were used for the identification of haplotype carriers: Backward Stepwise Selection (BSS) to select the SNP that best fit the model, and Linear Discriminant Analysis (LDA) to classify observations, based on the selected SNP, into carriers and non-carriers. In order to explore the minimum-sized set of SNP that correctly identifies haplotype carriers, different proportions of SNP were tested: 2.5; 10; 15; 30; 50 and 100%. For each proportion of SNP, BSS and LDA were applied, and the classification error rate was estimated in a 10-fold cross-validation scheme. Data were split in 10 subsets. The first subset was treated as validation set, while the model was fit on the remaining nine subsets (the training set). The overall error rate for the prediction of haplotype carriers was on average very low (∼1%) both in the training and in the validation datasets. The error rate was found to depend on the number of SNPs in the model and their density around the region of the haplotype on BTA5. The minimum set of SNPs to achieve accurate predictions was 18, with a total test error rate of 1.27. This paper describes a procedure to accurately identify haplotype carriers from SNP genotypes in cattle populations. Very few misclassifications were observed, which indicates that this is a very reliable approach for potential applications in cattle breeding.
This document summarizes John Cole's presentation on new genomic tools for dairy cattle. Some key points:
1) Genomic selection works well in dairy cattle due to extensive historical data, genetic evaluation programs, widespread AI use, and high-value animals. Genomics can reduce generation intervals.
2) Different genotyping arrays like BovineSNP50 and BovineHD are used, with over 300,000 animals genotyped as of 2013.
3) Genomic predictions provide information equivalent to dozens of progeny, improving reliability of selection, especially for lowly heritable traits. This allows more rapid genetic improvement.
- ABS was founded in the 1930s and played a major role in developing the artificial insemination industry in the US and globally. It pioneered technologies like frozen semen storage and transport.
- ABS set high standards for bull health, disease control, and semen quality that became the mark for the industry. It developed early sire evaluation techniques adopted by the USDA.
- ABS has expanded globally with business units and partnerships on six continents. It remains a leader in technological advancements and new products while staying dedicated to improving cattle genetics through selection and use of top progeny tested sires.
Ian Locke runs a 3,560 acre property in Holbrook, NSW, breeding 1,200 Poll Hereford cattle and 3,700 prime lambs. The property has highly variable soils and winter dominant rainfall of 708mm. Locke's Wirruna Poll Hereford stud has been operating since 1949, focusing on selecting cattle that perform well under commercial conditions. Locke runs a disciplined breeding program selecting for traits like calving ease, growth rates, and fertility. Bulls sold from the stud average in the top 10% of the breed for performance indexes.
Opportunities for genetic improvement of health and fitness traitsJohn B. Cole, Ph.D.
This document summarizes a presentation on opportunities for genetic improvement of health and fitness traits in dairy cattle. It discusses challenges such as low heritability of health traits and lack of standardized recording. It also provides examples of ways to increase genetic gain, such as improving reliability through genomics and increasing selection intensity. International efforts to develop guidelines for recording health traits are described. Overall, the presentation argues that improving health and fitness should be a priority for the dairy industry given economic impacts, and that genetic selection can help achieve improvements provided data recording is expanded and standardized.
The GMS genetic management system combines herd goals with each cow's phenotype and genotype to recommend matings to bulls that can improve weaknesses. Trained evaluators gather information on cows and work with producers to determine goals. The program gives 2-3 sire recommendations per cow based on genetics and allows producers to customize indexes and conformation formulas to their operation. Key features help control inbreeding and recessives through pedigree analysis and producer-set limits.
The document summarizes research detecting DNA regions associated with milk protein composition in dairy cattle. The study identified regions on chromosomes 6 and 11 that influence casein and beta-lactoglobulin levels. The chromosome 6 region affected all four casein fractions and explained some genetic variants in casein genes. The chromosome 11 region influenced beta-lactoglobulin levels and explained variants of the beta-lactoglobulin gene. Identifying these DNA regions provides opportunities to use genetic selection to improve milk quality and composition for cheese and other dairy products.
Genetic evaluation and best prediction of lactation persistencyJohn B. Cole, Ph.D.
At the same level of production cows with high persistency milk more at the end than the beginning of lactation. Best prediction of persistency is calculated as a function of trait-specific standard lactation curves and the linear regression of a cow’s test day deviations on days in milk.
This document outlines genetic programming, including an introduction describing it as emulating Darwinian evolution within computer programs. It describes the typical life cycle of genetic programming, including initializing a population, evaluating programs, selecting programs for reproduction, applying genetic operators like crossover and mutation, and repeating the process. It also discusses experimental setup parameters, genetic operators, fitness evaluation methods, and applications of genetic programming in areas like regression, classification, telecommunications, computer networks, finance, clinical domains, and more.
The document discusses using genetic programming to develop chess strategies. Genetic programming uses genetic algorithms and Darwinian principles of natural selection to evolve computer programs to solve complex problems. It proposes using genetic programming to evolve chess evaluation functions and strategies. This is done by generating an initial population of random strategies, having them play each other, and using the results to breed new strategies via crossover and mutation until high-performing strategies emerge. The approach shows promise but also faces challenges like increased computational requirements as strategy complexity grows. It also suggests starting with the simpler game of "Loser's Chess" to reduce branching factors before scaling up to full chess.
Performance recording and bull evaluation: Contrasting experiencesILRI
Presented by Enyew Negussie, Natural Resources Institute Finland (Luke), at the African Dairy Genetic Gains Program Annual Planning Meeting, 20-23 February 2017
This document provides definitions and information about key terms related to animal reproduction and genetics, including terminology for reproductive management, breeding systems, the anatomy and functions of the male and female reproductive systems in various livestock species, cell division, fertilization, chromosomes, genes, heredity, and genetic prediction using Punnett squares. It covers topics such as estrus, gestation, parturition, inbreeding, crossbreeding, the ovaries, testicles, sperm, eggs, dominant and recessive genes, homozygous and heterozygous, and using genetics to predict offspring traits.
FruitBreedomics 1st Stakeholder Day meeting 20120207 Most used founders in di...fruitbreedomics
The document evaluates the genetic diversity in European apple and peach breeding programs. It analyzes the pedigree and genome-wide inbreeding coefficients of current breeding germplasm to determine the genetic origin and founder contribution. Results show that the main programs have a narrow genetic framework contributed by a few founders, but this base is enriched by genetically distinct material incorporated for disease resistance or other traits. Comparing programs can provide insight into diversity and the effect of climatic zones and breeding program age.
Dr. Melaku Gedil presented on genotyping in breeding programs at the Implementation of Crop Improvement Strategy of IITA. The presentation discussed strategies for crop breeding including recombining genes among genotypes and selecting superior genotypes. It also discussed marker assisted selection (MAS) and its advantages such as enabling selection at the seedling stage and accelerating line development. Key issues in implementing MAS included the need for genomic resources, cost-effective genotyping systems, high-throughput phenotyping, and accurate marker-trait association methods.
Using genotyping and whole-genome sequencing to identify causal variants asso...John B. Cole, Ph.D.
Talk on identification of causal variants given to graduate students at the Universidade Federal de Viçosa in Viçosa, MG, Brasil, on September 9, 2014. It discusses work in my lab to identify causal variants associated with simple and complex modes of inheritance using SNP genotyping and next generation sequencing.
Current Research in Genomic Selection- Dr. Joe DaltonDAIReXNET
Dr. Dalton presented this material for a DAIReXNET webinar. You can view the recorded webinar on YouTube at https://www.youtube.com/watch?v=BL1jb8WY8lk
This presentation describes recent changes to the national genetic evaluation system, as well as new research undertaken by AGIL scientists. Topics covered include the 2014 genetic base change, updates to the lifetime net merit selection index, and introduction of the grazing merit index, and the redefinition of daughter pregnancy rate. New research on the use of gene content to predict polled status, and statistical models for accommodating genotype-by-environment interactions also are described.
Genetic Evaluation of Stillbirth in US Holsteins Using a Sire-maternal Grands...John B. Cole, Ph.D.
This document summarizes the genetic evaluation of stillbirth in US Holsteins using a sire-maternal grandsire threshold model. Over 6 million stillbirth records from 1980-2005 were analyzed. Heritability of direct and maternal stillbirth was estimated to be 3.0% and 6.5%, respectively. Genetic and phenotypic trends for stillbirth over time were small. Stillbirth EPDs were included in the US National Milk Progeny Test program starting in August 2006 and the US began participating in Interbull evaluations for calving traits in November 2006.
World Wide Sires has been offering high quality bovine genetics for over 40 years. They combine two large American bull studs with over 51,000 co-op members. They have delivered many successful sires that have contributed greatly to Irish herds and the global dairy industry. With over 600 bulls available, they offer genetics to suit all farming systems. Their focus on genomic selection and mating tools ensures profitable cows for the future.
This document discusses the value of estimated breeding values (EBVs) for genetic improvement in the US meat goat industry. It explains that EBVs quantify an animal's genetic merit for economically important traits based on their own performance data as well as data from relatives. The accuracy of EBVs depends on contemporary groups, genetic connections between animals, and the amount of data collected. The National Sheep Improvement Program (NSIP) currently provides EBVs for a few meat goat herds in the US through its Kidplan program. Producers can benefit from EBVs by selecting breeding stock with above average EBVs for important traits.
New paradigms in breeder seed production include molecular marker techniques, phenomics, and controlled environments. DNA marker fingerprinting and barcoding can verify variety identification and genetic purity. Molecular grow-out tests (GOT) using nested markers allow testing of genetic purity at different generations. Phenomics facilities enable high-throughput field and greenhouse phenotyping for selection and uniformity testing. Controlled environments are useful for seedling phenotyping and screening under precise environmental conditions. Together these new approaches can help strengthen maintenance breeding and quality assurance of breeder seed.
The use and economic value of genomic testing for calves on dairy farmsJohn B. Cole, Ph.D.
This document discusses the use and economic value of genomic testing for calves on dairy farms. It provides information on how genomic selection works and how it can increase genetic gain. Genomic testing can be used for animal identification and parentage verification, early culling decisions, mate selection to produce better calves, and identifying elite cows. The document examines studies that show dairy farms could make improved mating decisions using genomic testing data to pair cows and bulls. Genomic testing provides reliable estimates of animals' genetic merit and can help farmers make better long-term breeding and management decisions.
The national genetic evaluation program
for dairy cattle in the United States is described. Topics include an historical overview of traits and statistical methodology, the structure of the contemporary dairy genetics industry, and the implementation of genomic selection.
New applications of genomic technology in the US dairy industryJohn B. Cole, Ph.D.
John B. Cole presented on new applications of genomic technology in the US dairy industry. Some key points include: genomic selection has been successful due to extensive historical data and widespread use of AI; over 300,000 animals have been genotyped across several dairy breeds; the percentage of genomically tested young bulls marketed has increased significantly since 2007; non-additive effects, novel recessives, and whole genome sequencing can further improve selection; and new phenotypes like health traits and methane production are being studied but require large datasets for accurate evaluation.
This document summarizes dairy cattle breeding in the United States. It provides statistics on the US dairy population and yield trends over time. The US has over 9 million dairy cows in 67,000 herds, with average production of 19,000 lbs per cow. Breeding is predominantly Holstein and Jersey breeds using artificial insemination. The document outlines the national dairy genetic evaluation program and traits evaluated, including yield, longevity, mastitis resistance, and calving traits. Genetic trends show substantial increases in yield over time but stability or decreases for health and fitness traits.
This is the second presentation from a six part webinar series on the National Sheep Improvement Program (NSIP). The presenter is Dr. Ken Andries from Kentucky State University. The date of the presentation was May 8, 2014.
Genomic selection has been successful in the dairy cattle industry by increasing genetic progress. Several challenges remain, including pre-selection bias when young genotyped bulls are selected for further breeding before progeny testing, and developing across-breed genomic evaluations. While genomic selection is widely used and has increased the rate of genetic improvement, continuing work is needed to address these challenges to ensure the most accurate genomic evaluations.
An updated version of lifetime net merit incorporating additional fertility t...John B. Cole, Ph.D.
The slides for my upcoming talk on the 2014 revision of the lifetime net merit selection index to be presented at the 2014 ASAS-ADSA-CSAS Joint Annual Meeting in Kansas City, MO.
Breed Composition Codes for Crossbred Dairy Cattle with an Application to Cal...John B. Cole, Ph.D.
This document describes a study that developed a system to store breed composition data in a national database. The study also investigated using crossbred daughter records in breed-of-sire genetic evaluations for calving ease in Brown Swiss and Jersey bulls. Crossbred records from over 338,000 animals were analyzed. Threshold models were used to evaluate calving ease. Results showed it is feasible to use crossbred daughter records in genetic evaluations and that there is no genetic trend for calving ease in Brown Swiss or Jersey bulls.
Dr. Jason Ross - Improving Sow SurvivabilityJohn Blue
Improving Sow Survivability - Dr. Jason Ross, Iowa State University, From the 2018 World Pork Expo, June 6 - 8, 2018, Des Moines, IA, USA.
More presentations at http://www.swinecast.com/2018-world-pork-expo
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Using genotypes to construct phenotypes for dairy cattle breeding programs an...John B. Cole, Ph.D.
Modern dairying uses sophisticated data collection systems to maximize farm profitability. This has traditionally included information on cows and their environments, and now commonly includes genotype information from high-density single nucleotide polymorphism (SNP) panels. The US national database alone contains genotypes for 924,543 bulls and cows as of March 23, 2015, and many other countries are also genotyping animals. As the data continue to grow, the prospect of using genotypes to construct phenotypes directly, instead of measuring phenotypes on animals, becomes more attractive. There are many applications for this genomic information other than the prediction of breeding values. A notable recent application is the use of haplotypes in combination with next-generation sequencing data to identify causal variants associated with recessives. The methodology for identifying recessive haplotypes by searching for a deficit of homozygotes was first used in combination with sequence data to identify the causal variant (APAF1) associated with the HH1 haplotype. The US currently tracks 24 recessive haplotypes in four cattle breeds, and thanks to the work of several teams around the world the causal variants for 17 of them are known. The haplotypes include lethal recessive conditions, such as brachyspina, as well as hair coat color and polledness. There is growing interest in the latter to improve animal welfare and increase economic efficiency, but the polled haplotype has a very low frequency (0.41%, 0.93%, and 2.22% in Brown Swiss, Holstein, and Jersey, respectively). Increasing haplotype frequency by index selection requires known status for all animals. Gene content (GC) for non-genotyped animals was computed using records from genotyped relatives. Prediction accuracy was checked by comparing polled status from recessive codes and animal names to GC for 1,615 non-genotyped Jerseys with known status. 97% (n = 675) of horned animals were correctly assigned GC near 0, and 3% (n = 19) were assigned GC near 1. Heterozygous polled animals had GC near 0 (52%, n = 474) and near 1 (47%; n = 433), although 3 animals were assigned a GC near 2. All homozygous polled animals (n = 11) were assigned GC near 2. Genotype information can also be combined with other data, such as milk spectral data, to predict phenotypes for traits that are expensive or difficult to measure directly. These data can be used for precision farm management, including early culling decisions, monitoring of animals at risk for health problems, and identification of efficient and inefficient cows. The most substantial challenge faced by many dairy managers will be the effective use of the new phenotypes that now are available.
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The document discusses the use of technology on dairy farms. It notes that technology provides benefits like making work faster, cheaper, and easier. It then discusses several technologies used on dairy farms today like automated systems for measuring feed and water intake, monitoring cows, and milking systems. The document also looks at challenges like the need for more frequent milk sampling and how collected on-farm data is not always put in a central database. It concludes that sensor technology is producing large amounts of data that could improve management if combined across farms.
The hunt for a functional mutation affecting conformation and calving traits ...John B. Cole, Ph.D.
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Genomic selection and systems biology – lessons from dairy cattle breedingJohn B. Cole, Ph.D.
Presentation made to the staff of Keygene, NV, in Wageningen, The Netherlands.
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Use of NGS to identify the causal variant associated with a complex phenotypeJohn B. Cole, Ph.D.
This document summarizes a presentation on using next generation sequencing to identify the causal variant associated with a complex phenotype like dystocia in cattle. It discusses selecting animals to sequence, the sequencing and analysis process, challenges in annotation and validation, and recent successes in identifying causal mutations for other traits in cattle. The presentation outlines using sequencing to investigate a quantitative trait locus for dystocia on chromosome 18 in cattle that affects traits like birth weight and gestation length. It describes analyzing sequence data to identify variants associated with predicted birth weight and discusses ongoing challenges in sequencing, analysis, and validating causal variants.
This document summarizes research on genomic evaluation of dairy cattle health traits. It discusses challenges in evaluating health traits including low heritability and inconsistent definitions. The researchers conducted single and multiple trait genetic and genomic analyses on health event data from over 1 million US dairy cow records. Heritability estimates for various health events ranged from 0.03 to 0.20. Genomic evaluation allowed more accurate prediction of sires' daughters' probabilities of different health events compared to traditional genetic evaluation. The multiple trait genomic analysis found moderate to strong genetic correlations between some health events.
Genomic evaluation of low-heritability traits: dairy cattle health as a modelJohn B. Cole, Ph.D.
Genetic selection has been very successful when applied to traits of moderate to high heritability, but progress has been slow for traits with low heritabilities. The problem is further compounded when novel traits are considered because data needed to calculate high-reliability PTA generally are not available. A combination of producer-recorded health event data and SNP genotypes may permit the routine calculation of PTA with reasonable reliabilities for health traits.
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PyPedal, an open source software package for pedigree analysisJohn B. Cole, Ph.D.
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This document summarizes research using high-density SNP genotypes to fine-map quantitative trait loci (QTL) in cattle. It describes Illumina genotyping arrays with varying numbers of SNPs, from 54k to 778k. Two examples are given of identifying causal variants for haplotypes related to fertility. For HH1 in Holsteins, sequencing identified a missense mutation in APAF1 associated with embryonic lethality. For JH1 in Jerseys, a stopgain mutation was found in CWC15. Preliminary fine-mapping of the Weaver locus using HD genotypes identified a region on BTA4 for further study by next-generation sequencing.
What can we do with dairy cattle genomics other than predict more accurate br...John B. Cole, Ph.D.
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Validation of Producer-Recorded Health Event Data and Use in Genetic Improvem...John B. Cole, Ph.D.
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1. 2014
Genetic improvement
programs for US dairy
cattle
John B. Cole
Animal Genomics and Improvement Laboratory
Agricultural Research Service, USDA
Beltsville, MD
john.cole@ars.usda.gov
2. U.S. dairy population and milk yield
10,000
8,000
6,000
4,000
2,000
0
30
25
20
15
10
5
0
40 50 60 70 80 90 00 10
Milk yield (kg/cow)
Cows (millions)
Year
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (2) Cole
3. U.S. DHI dairy statistics (2011)
l 9.1 million U.S. cows
l ~75% bred AI
l 47% milk recorded through Dairy Herd Information (DHI)
w 4.4 million cows
− 86% Holstein
− 8% crossbred
− 5% Jersey
− <1% Ayrshire, Brown Swiss, Guernsey, Milking
Shorthorn, Red & White
w 20,000 herds
w 220 cows/herd
w 10,300 kg/cow
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (3) Cole
4. Collaboration with industry
l Council on Dairy Cattle Breeding (CDCB)
responsible for receiving data and for
computing and delivering US genetic
evaluations for dairy cattle
l AIP responsible for research and
development to improve the evaluation
system
l CDCB and AIP employees co-located in
Beltsville
l Dr. João Dürr is CDCB CEO
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (4) Cole
5. Council on Dairy Cattle Breeding
CDCB
PDCA NAAB DRPC DHIA
Purebred Dairy
Cattle Association
National Association of
Animal Breeders
Dairy Records
Processing Centers
Information Association
l 3 board members from each
organization
l Total of 12 voting members
l 2 nonvoting industry members
Dairy Herd
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (5) Cole
6. Genetic evaluation advances
Year Advance Gain,
%
1862 USDA established
1895 USDA begins collecting dairy records
1926 Daughter-dam comparison 100
1962 Herdmate comparison 50
1973 Records in progress 10
1974 Modified contemporary comparison 5
1977 Protein evaluated 4
1989 Animal model 4
1994 Net merit, productive life, and somatic cell
score
50
2008 Genomic selection >50
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (6) Cole
7. Animal model
1989 to present
Introduced by Wiggans and VanRaden
Advantages
Information from all relatives
Adjustment for genetic merit of mates
Uniform procedures for males and females
Best prediction (BLUP)
Crossbreds included (2007)
Genomic information added (2008)
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (7) Cole
8. Traits evaluated
Year Trait Year Trait
1926 Milk & fat yields 2000 Calving ease1
1978 Conformation (type) 2003 Daughter pregnancy rate
1978 Protein yield 2006 Stillbirth rate
1994 Productive life 2006 Bull conception rate2
1994 Somatic cell score
(mastitis)
2009 Cow and heifer
conception rates
1Sire calving ease evaluated by Iowa State University (1978–99)
2Estimated relative conception rate evaluated by DRMS in Raleigh,
NC (1986–2005)
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (8) Cole
9. Evaluation methods for traits
Heritability
Animal model (linear)
Yield (milk, fat, protein)
Type (AY, BS, GU, JE)
Productive life
Somatic cell score
Daughter pregnancy rate
Heifer conception rate
Cow conception rate
Sire–maternal grandsire model (threshold)
Service sire calving ease
Daughter calving ease
Service sire stillbirth rate
Daughter stillbirth rate
25 – 40%
7 – 54%
8.5%
12%
4%
1%
1.6%
8.6%
3.6%
3.0%
6.5%
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (9) Cole
10. Type traits
Stature
Strength
Body depth
Dairy form
Rump angle
Thurl width
Rear legs (side)
Rear legs (rear)
Foot angle
Feet and legs
score
Fore udder
attachment
Rear udder height
Rear udder width
Udder cleft
Udder depth
Front teat placement
Rear teat placement
Teat length
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (10) Cole
11. Holstein milk (kg)
1,000
0
-1,000
-2,000
-3,000
-4,000
Phenotypic base = 11,828 kg
Cows
Sires
1960 1970 1980 1990 2000 2010
Breeding value (kg)
Birth year
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (11) Cole
12. Holstein productive life (mo)
2
0
-2
-4
-6
-8
-10
Phenotypic base = 27.2 mo
Sires
Cows
1960 1970 1980 1990 2000 2010
Breeding value (mo)
Birth year
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (12) Cole
13. Holstein somatic cell score (log2)
3.10
3.00
2.90
2.80
2.70
Sires
Cows
Phenotypic base = 3.0
1984 1988 1992 1996 2000 2004 2008
Breeding value (log2)
Birth year
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (13) Cole
14. Holstein daughter pregnancy rate (%)
8.0
6.0
4.0
2.0
0.0
-2.0
Sires
Cows
Phenotypic base = 22.6%
1960 1970 1980 1990 2000 2010
Breeding value (%)
Birth year
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (14) Cole
15. Holstein calving ease (%)
11.0
10.0
9.0
8.0
7.0
6.0
Daughte
r
Service-sire
phenotypic base = 7.9%
Daughter
phenotypic base = 7.5%
Service
sire
0.01%/yr
1980 1985 1990 1995 2000 2005 2010
PTA
(% difficult births in heifers)
Birth year
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (15) Cole
16. Genetic-economic indices (2010)
Trait
Relative value (%)
Net
Cheese
merit
merit
Fluid
merit
Milk (lb) 0 –15 19
Fat (lb) 19 13 20
Protein (lb) 16 25 0
Productive life (PL, mo) 22 15 22
Somatic cell score (SCS, log2) –10 –9 –5
Udder composite (UC) 7 5 7
Feet/legs composite (FLC) 4 3 4
Body size composite (BSC) –6 –4 –6
Daughter pregnancy rate (DPR, %) 11 8 12
Calving ability (CA$, $) 5 3 5
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (16) Cole
18. Traditional evaluation summary
Evaluation procedures have improved
Fitness traits have been added
Effective selection has produced substantial
annual genetic improvement
Indices enable selection for overall economic
merit
Fertility evaluations prevent continued decline
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (18) Cole
19. Genomic evaluation system
Provides timely evaluations of young
bulls for purchasing decisions
Increases accuracy of evaluations of bull
dams
Assists in selection of service sires,
particularly for low-reliability traits
High demand for semen from
genomically evaluated 2-year-old bulls
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (19) Cole
20. Genomic data flow
Dairy Herd Improvement
(DHI) producer
DNA samples
genotypes
Council on Dairy Cattle
Breeding (CDCB)
DNA laboratory
AI organization,
breed association
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (20) Cole
21. Progression of chips
Bovine3K
BeadChip
(3K)
Jul
BovineHD
BeadChip
(777K)
Jan
2008 2009 2010
Dec
Official 3K
evaluations
Sep
Unofficial 3K
evaluations
Aug
Official 50K
Brown Swiss
evaluations
Jan
Official 50K
Holstein & Jersey
evaluations
BovineSNP50
BeadChip
Apr
(50K)
Jan
Unofficial 50K
evaluations
Zoetis LD
BeadChip
(12K)
Sep
GGP HD
BeadChip
(77K)
GGP v2 BeadChip
(19K)
May
Dec
GeneSeek Genomic
Profiler (GGP)
BeadChip (8K)
Feb
BovineLD
BeadChip
(7K)
Sep
2011 2012 2013
Oct
Official 12K
evaluations
May
Official 19K
evaluations
Jan
Official 77K
evaluations
Mar
Official 8K
evaluations
Dec
Official
7K & 648K
evaluations
Aug
Affymetrix BOS 1
Official 777K
evaluations
Plate Array
(648K)
Jan
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (21) Cole
22. Evaluation flow
Animal nominated for genomic evaluation
by breed association or AI organization
Hair or other DNA source sent to
genotyping lab
DNA extracted and placed on chip for 3-day
genotyping process
Genotypes sent from genotyping lab to AIPL
for accuracy review
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (22) Cole
23. Laboratory quality control
Each SNP evaluated for
Call rate
Portion heterozygous
Parent-progeny conflicts
Clustering investigated if SNP exceeds limits
Number of failing SNPs indicates genotype
quality
Target of <10 SNPs in each category
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (23) Cole
24. Evaluation flow (continued)
Genotype calls modified as necessary
Genotypes loaded into database
Nominators receive reports of parentage
and other conflicts
Pedigree or animal assignments corrected
Genotypes extracted and imputed to 45K
SNP effects estimated
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (24) Cole
25. Imputation
Based on splitting genotype into individual
chromosomes (maternal and paternal
contributions)
Missing SNPs assigned by tracking inheritance
from ancestors and descendants
Imputed dams increase predictor population
Genotypes from all chips merged by imputing
SNPs not present
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (25) Cole
26. findhap
Developed by Dr. Paul VanRaden, ARS, USDA
Divides chromosomes into segments
Allows for successively shorter segments (usually 3
runs)
Long segments lock in identical by descent
Shorter segments fill in missing SNPs
Separates genotype into maternal and paternal
contribution, haplotypes (phasing)
Builds haplotype library sequenced by frequency
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (26) Cole
27. Evaluation flow (continued)
Final evaluations calculated
Evaluations released to dairy industry
Download from CDCB FTP site with
separate files for each nominator
Monthly release for new animals
All genomic evaluations updated 3 times
each year with traditional evaluations
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (27) Cole
28. Genomic evaluation results
Source: https://www.cdcb.us/Report_Data/Marker_Effects/marker_effects.cfm?Breed=HO&Trait=Net_Merit
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (28) Cole
29. Information sources for evaluations
Traditional evaluations of genotyped bulls
and cows used to estimate SNP effects
Combined final evaluation
Sum of SNP effects for an animal’s alleles
Polygenetic effect
Traditional evaluation
Pedigree data used and validated by
genotypes
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (29) Cole
30. Genotypes received since July 2013
Breed Female Male
All
animals
%
female
Ayrshire 1,359 229 1,588 86
Brown Swiss* 892 6,253 7,145 12
Holstein 172,956 31,657 204,613 85
Jersey** 26,434 4,804 31,238 85
All 201,641 42,943 244,584 82
*Includes >5,000 bulls added from Interbull in June 2014
**Includes 1,068 Danish bulls added in November 2013
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (30) Cole
31. Genotypes evaluated
400,000
350,000
300,000
250,000
200,000
150,000
100,000
50,000
0
Jun
A
O
Jan
Young imputed
Old imputed
Female Young <50K
Male Young <50K
Female Old <50K
Male Old <50K
Female Young >=50K
Male Young >=50K
Female Old >=50K
Male Old >=50K
F
A
M
J
J
A
S
O
N
D
Jan
F
M
A
M
J
J
A
S
O
N
D
Jan
F
M
A
M
J
J
A
S
O
N
D
Jan
F
M
A
M
J
J
A
S
Animals genotyped (no.)
2009 2010 2011 2012 2013
Evaluation date
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (31) Cole
32. Growth in bull predictor population
Breed May 2014
12-mo
gain
Ayrshire 678 30
Brown Swiss 5,862 366
Holstein 25,276 2,361
Jersey 4,262 1,391
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (32) Cole
33. Reliabilities for young Holsteins*
50K genotypes
3K genotypes
40 45 50 55 60 65 70 75 80
Reliability for PTA protein (%)
*Animals with no traditional PTA in April 2011
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
Number of animals
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (33) Cole
34. Holstein prediction accuracy
Trait Bias*
Final score 0.1 58.8 22.7
Stature −0.2 68.5 30.6
Dairy form −0.2 71.8 34.5
Rump angle 0.0 70.2 34.7
Rump width −0.2 65.0 28.1
Feed and legs 0.2 44.0 12.8
Fore udder attachment −0.2 70.4 33.1
Rear udder height −0.1 59.4 22.2
Udder depth −0.3 75.3 37.7
Udder cleft −0.2 62.1 25.1
Front teat placement −0.2 69.9 32.6
Teat length −0.1 66.7 29.4
*2013 deregressed value – 2009 genomic evaluation
Reliability
(%)
Reliability
gain (%
points)
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (34) Cole
35. Parent ages of marketed Holstein bulls
140
120
100
80
60
40
20
0
Sire
Dam
2007 2008 2009 2010 2011 2012 2013
Parent age (mo)
Bull birth year
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (35) Cole
36. Marketed Holstein bulls
Year
entered
AI
Traditional
progeny-tested
Young
genotyped All bulls
2008 1,798 0 1,798
2009 1,909 337 2,246
2010 1,827 376 2,203
2011 1,441 467 1,908
2012 1,376 555 1,931
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (36) Cole
37. Genetic merit of marketed Holstein bulls
800
700
600
500
400
300
200
100
0
-100
Average gain:
$19.77/year
Average gain:
$52.00/year
Average gain:
$85.60/year
00 01 02 03 04 05 06 07 08 09 10 11 12 13 14
Average net merit ($)
Year entered AI
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (37) Cole
38. Genomic prediction of progeny test
0 1 2 3 4 5
Select parents,
transfer embryos
to recipients
Calves
born and
DNA
tested
Calves born
from DNA-selected
parents
Bull
receives
progeny
test
Reduce generation interval from 5 to 2 years
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (38) Cole
39. Genetic choices
Before genomics:
Proven bulls with daughter records
(PTA)
Young bulls with parent average (PA)
After genomics:
Young animals with DNA test (GPTA)
Reliability of GPTA ~70% compared to
PA ~35% and PTA ~85% for Holstein NM$
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (39) Cole
40. Young bulls: 2013 NM$ vs. 2010 PA
900
700
500
300
100
-100
-300
-500
-500 -300 -100 100 300 500 700 900
Net Merit, Dec. 2013
PA Net Merit, April 2010
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (40) Cole
41. Proven bulls: 2013 vs. 2010 NM$
900
700
500
300
100
-100
-300
-500
-500 -300 -100 100 300 500 700 900
Net Merit, Dec. 2013
Net Merit, April 2010
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (41) Cole
42. Young bulls: 2013 vs. 2010 NM$
900
700
500
300
100
-100
-300
-500
-500 -300 -100 100 300 500 700 900
Net Merit, Dec. 2013
Net Merit, April 2010
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (42) Cole
43. % genotyped mates of top young bulls
100
90
80
70
60
50
40
30
20
10
0
Numero Uno
Mogul
Maurice
Elvis ISY Altatrust
Garrold
Fernand
Supersire
S S I Robust Topaz
700 725 750 775 800 825 850 875 900 925
Net Merit (Aug 2013)
Percentage of mates genotyped
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (43) Cole
44. Why genomics works for dairy
cattle
Extensive historical data available
Well-developed genetic evaluation program
Widespread use of AI sires
Progeny-test programs
High-value animals worth the cost of
genotyping
Long generation interval that can be
reduced substantially by genomics
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (44) Cole
45. Key issues for the dairy industry
Inbreeding and genetic diversity
(including across breeds)
Sequencing, new genes, and mutations
Novel traits, resource populations
(feed efficiency, health, milk properties)
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (45) Cole
46. Application to more traits
Animal’s genotype good for all traits
Traditional evaluations required for accurate
estimates of SNP effects
Traditional evaluations not currently available
for heat tolerance or feed efficiency
Research populations could provide data for
traits that are expensive to measure
Will resulting evaluations work in target
population?
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (46) Cole
47. Parentage validation and discovery
Parent-progeny conflicts detected
Animal checked against all other genotypes
Reported to breeds and requesters
Correct sire usually detected
Maternal grandsire (MGS) checking
SNP at a time checking
Haplotype checking more accurate
Breeds moving to accept SNPs
in place of microsatellites
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (47) Cole
48. Haplotypes affecting fertility
Rapid discovery of new recessive defects
Large numbers of genotyped animals
Affordable DNA sequencing
Determination of haplotype location
Significant number of homozygous
animals expected, but none observed
Narrow suspect region with fine mapping
Use sequence data to find causative
mutation
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (48) Cole
49. Haplotypes affecting fertility
frequency (%) Earliest known ancestor
HH1 5 63.2* 4.5 Pawnee Farm Arlinda Chief
HH2 1 94.9–96.6 4.6 Willowholme Mark Anthony
HH3 8 95.4* 4.7 Glendell Arlinda Chief,
Gray View Skyliner
HH4 1 1.3* 0.7 Besne Buck
HH5 9 92.4–93.9 4.4 Thornlea Texal Supreme
JH1 15 15.7* 23.4 Observer Chocolate Soldier
BH1 7 42.8–47.0 14.0 West Lawn Stretch
BH2 19 10.6–11.7 15.4 Rancho Rustic My Design
AH1 17 65.9–66.2 23.6 Selwood Betty’s
*Causative mutation known
Name
Chromo-some
Location
(Mbp)
Carrier
Improver
Commander
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (49) Cole
50. Haplotypes to track known recessives
Concord-ance
(%)
New
carriers
(no.)
BLAD HHB 1* 11,782 99.9 314
CVM HHC 3* 13,226 — 2,716
DUMPS HHD 1* 3,242 100.0 3
Mule foot HHM 15* 87 97.7 120
Horned HHP 1 345 — 2,050
Red coat
HHR 18* 4,137 — 5,927
color
SDM BHD 11* 108 94.4 108
SMA BHM 24* 568 98.1 111
Weaver BHW 4 163 96.3 32
*Causative mutation known
Recessive Haplotype
Chromo-some
Tested
animals
(no.)
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (50) Cole
51. International dairy breeding
Genotype alliances
North America (US, Canada, UK, Italy)
Ireland, New Zealand
Netherlands, Australia
Eurogenomics (Denmark/Sweden/Finland,
France, Germany, Netherlands/Belgium,
Spain, Poland)
Interbull genomic multitrait across-country
evaluation (GMACE)
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (51) Cole
52. Impact on breeders
Haplotype and gene tests in selection and
mating programs
Trend towards a small number of elite
breeders that are investing heavily in
genomics
About 30% of young males genotyped
directly by breeders since April 2013
Prices for top genomic heifers can be
very high (e.g., $265,000 )
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (52) Cole
53. Impact on dairy producers
General
Reduced generation interval
Increased rate of genetic gain
More inbreeding/homozygosity?
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (53) Cole
54. Impact on dairy producers (continued)
Sires
Higher average genetic merit of available
bulls
More rapid increase in genetic merit for
all traits
Larger choice of bulls in terms of traits
and semen price
Greater use of young bulls
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (54) Cole
55. Conclusions
Genomic evaluation has dramatically changed
dairy cattle breeding
Rate of gain is increasing primarily because of
a large reduction in generation interval
Genomic research is ongoing
Detect causative genetic variants
Find more haplotypes affecting fertility
Improve accuracy through more SNPs, more
predictor animals, and more traits
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (55) Cole
56. U.S. genomic evaluation team
Embrapa Gado de Leite, Juiz de Fora, MG, Brasil 10 September 2014 (56) Cole