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Animal Genetics Course
From 4 to 360h of flexible workload

Animal Genetics Course

Master the science of animal genetics from Mendelian principles to cutting-edge genomic selection and CRISPR-based editing. This course equips you with the quantitative, molecular, and computational skills demanded by modern livestock breeding and conservation programmes. Whether you work in research, industry, or animal production, you will gain the expertise to drive measurable genetic improvement.

What you will learn:

This course covers the full spectrum of animal genetics, starting with foundational principles of inheritance and cell biology, then advancing through quantitative genetics, population genetics, and molecular tools. You will learn how to estimate breeding values, construct selection indices, and design genomic evaluation pipelines using SNP data. The curriculum also addresses genome-wide association studies, QTL mapping, and functional genomic annotation. Conservation genetics, disease resistance breeding, and reproductive biotechnologies are covered in depth. You will also explore emerging topics, including CRISPR genome editing, artificial intelligence in breeding, and the integration of precision livestock farming.

How you study in practice Animal Genetics Course

How you practise Animal Genetics Course

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Course content

8 Chapters40 LessonsDuration between 4 and 360 hours (you decide)

Chapter 1See details

Foundations of Animal Genetics

  • Lesson 1 • DNA Replication and Gene Expression

    Explains how DNA copies itself and how genes produce proteins. Links molecular processes to observable traits in animals.

  • Lesson 2 • Cell Biology and Genetic Material

    Covers cell structure, chromosomes, and DNA organisation in animal cells. Provides the cellular context needed for all subsequent genetic concepts.

  • Lesson 3 • Sex Determination and Linkage

    Covers sex chromosome systems and X-linked inheritance across animal species. Establishes linkage concepts critical for marker-assisted selection.

  • Lesson 4 • Extensions of Mendelian Genetics

    Addresses inheritance patterns that deviate from simple Mendelian ratios. Prepares students to interpret complex pedigrees and trait distributions.

  • Lesson 5 • Mendelian Inheritance Principles

    Introduces Mendel's laws using animal examples. Builds the probability framework used throughout quantitative and population genetics chapters.

Chapter 2See details

Population Genetics in Animal Breeding

  • Lesson 1 • Inbreeding and Its Consequences

    Quantifies inbreeding using the inbreeding coefficient and traces its effects on fitness. Prepares students to manage inbreeding in closed herds.

  • Lesson 2 • Forces Changing Allele Frequencies

    Examines mutation, migration, drift, and selection as drivers of frequency change. Connects each force to outcomes in closed breeding populations.

  • Lesson 3 • Effective Population Size

    Defines effective population size and its role in genetic diversity conservation. Students calculate Ne under various mating structures.

  • Lesson 4 • Hardy-Weinberg Equilibrium

    Establishes the null model for allele and genotype frequencies. Deviations from equilibrium signal evolutionary forces acting on populations.

  • Lesson 5 • Crossbreeding and Heterosis

    Analyses the genetic basis of heterosis and crossbreeding systems. Students design cross schemes to exploit complementarity and hybrid vigour.

Chapter 3See details

Quantitative Genetics and Trait Variation

  • Lesson 1 • Breeding Value Estimation

    Covers the concept of breeding value and its estimation from performance data. Provides the statistical foundation for genetic evaluation systems.

  • Lesson 2 • Continuous Trait Distributions

    Explains why many animal traits follow normal distributions. Connects polygenic inheritance to phenotypic variation observed in populations.

  • Lesson 3 • Genetic Correlations Between Traits

    Introduces genetic and phenotypic correlations and their breeding implications. Students learn to anticipate correlated responses to selection.

  • Lesson 4 • Variance Components and Heritability

    Teaches decomposition of phenotypic variance into genetic and environmental parts. Heritability estimates guide selection intensity decisions.

  • Lesson 5 • Response to Selection

    Models expected genetic gain from selection programmes. Students calculate selection differentials and predict multi-generation progress.

Chapter 4See details

Molecular Genetics Tools and Techniques

  • Lesson 1 • Bioinformatics for Genetic Data

    Introduces software pipelines for processing and interpreting large genetic datasets. Students run basic analyses using publicly available genomic tools.

  • Lesson 2 • PCR and Genotyping Methods

    Teaches polymerase chain reaction principles and genotyping platforms. Students select appropriate methods for specific genetic marker applications.

  • Lesson 3 • DNA Extraction and Quality Assessment

    Covers tissue sampling, extraction protocols, and quality metrics for animal DNA. Proper sample quality is a prerequisite for all downstream molecular analyses.

  • Lesson 4 • DNA Sequencing Technologies

    Compares Sanger and next-generation sequencing approaches for animal genomics. Students evaluate sequencing strategies based on cost, throughput, and resolution.

  • Lesson 5 • Genetic Marker Systems

    Surveys marker types from RFLPs to SNP arrays used in animal genetics. Marker choice affects resolution, cost, and applicability in breeding programmes.

Chapter 5See details

Genomic Selection and Evaluation

  • Lesson 1 • Validation and Accuracy of Genomic EBVs

    Teaches cross-validation methods and accuracy metrics for genomic predictions. Students assess reliability before deploying genomic selection in practice.

  • Lesson 2 • Reference Population Design

    Addresses size, composition, and updating of reference populations for genomic evaluation. Reference population quality directly determines prediction reliability.

  • Lesson 3 • Linkage Disequilibrium and Haplotypes

    Explains LD structure and haplotype blocks as the basis for genomic prediction. LD decay patterns determine the required marker density for accurate predictions.

  • Lesson 4 • Genomic Relationship Matrices

    Constructs genomic relationship matrices from SNP data and compares them to pedigree-based matrices. Genomic relationships improve the accuracy of genetic evaluations.

  • Lesson 5 • Statistical Models for Genomic Prediction

    Covers GBLUP, Bayesian, and machine learning models for genomic estimated breeding values. Model choice affects prediction accuracy for different trait architectures.

Chapter 6See details

Genetic Improvement Programme Design

  • Lesson 1 • Mating System Design

    Evaluates assortative, disassortative, and optimum contribution mating strategies. Mating design balances genetic gain against inbreeding accumulation.

  • Lesson 2 • Reproductive Technologies in Breeding

    Integrates AI, ET, and MOET into genetic improvement schemes. Reproductive technologies amplify selection intensity and reduce generation intervals.

  • Lesson 3 • Genetic Gain Monitoring and Evaluation

    Establishes metrics and feedback loops to track realised genetic progress. Monitoring identifies programme deviations and guides corrective adjustments.

  • Lesson 4 • Defining Breeding Objectives

    Guides construction of economically weighted breeding goals for animal populations. Clear objectives align genetic improvement with production system requirements.

  • Lesson 5 • Selection Index Construction

    Builds multi-trait selection indices that optimise genetic gain across objectives. Index theory translates breeding goals into practical selection decisions.

Chapter 7See details

Animal Genomics and Functional Annotation

  • Lesson 1 • QTL Mapping and Fine Mapping

    Explains interval mapping and fine-mapping strategies to localise quantitative trait loci. Fine mapping narrows candidate regions for functional investigation.

  • Lesson 2 • Functional Genomics Approaches

    Introduces transcriptomics, proteomics, and metabolomics as tools for trait dissection. Functional data bridges statistical associations and biological pathways.

  • Lesson 3 • Candidate Gene Analysis

    Guides prioritisation and functional validation of candidate genes from association studies. Validated candidates become targets for marker-assisted and genomic selection.

  • Lesson 4 • Epigenetics in Animal Populations

    Covers DNA methylation, histone modification, and their heritable effects on animal phenotypes. Epigenetic variation adds complexity to classical genetic models.

  • Lesson 5 • Genome-Wide Association Studies

    Covers GWAS design, statistical testing, and result interpretation for animal traits. GWAS findings inform candidate gene identification and genomic selection models.

Chapter 8See details

Genetic Diversity and Conservation Genetics

  • Lesson 1 • Population Structure and Differentiation

    Analyses the genetic structure within and among animal populations. Structure analysis reveals breed relationships and guides conservation prioritisation.

  • Lesson 2 • Measuring Genetic Diversity

    Quantifies diversity using molecular markers and genomic data. Diversity metrics guide decisions in both conservation and commercial breeding programmes.

  • Lesson 3 • Genomic Tools for Wildlife Management

    Extends animal genetics methods to wild population monitoring and management. Non-invasive sampling and genomic tools enable conservation without capture.

  • Lesson 4 • Breed Characterisation and Traceability

    Uses molecular markers to characterise breeds and verify individual ancestry. Traceability supports breed registry integrity and product authentication.

  • Lesson 5 • Conservation of Endangered Breeds

    Applies genetic principles to cryopreservation and recovery of at-risk animal breeds. Conservation strategies balance genetic diversity with demographic viability.

Certification
Certification

Your valid completion certificate

This course is for you:

  • Animal science students: ready to move beyond textbook theory into practice.

  • Livestock producers: wanting data-driven decisions to improve herd performance.

  • Veterinarians: seeking deeper genetic knowledge to advise breeding clients better.

  • Conservation biologists: managing genetic diversity in wild or endangered animal populations.

  • Agronomists transitioning: shifting focus toward animal production and genetic improvement.

  • Lab technicians: aiming to contextualise molecular work within broader breeding programmes.

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