Lecture 7: Quantitative Genetics and Breeding Notes

Genetic Diversity: An important concept that influences agricultural and horticultural practices, particularly in breeding.
Historical Context: Plant and animal breeding dates back thousands of years, long before genetics was understood, with verbal or pictorial records rather than written; reliable documentation has only emerged recently.
Motivation for Breeding: Primarily aimed at food production (meat, milk, fiber) to enable settled agricultural practices over hunting and gathering.

Advancements in Genetics: Recent understandings of DNA have illuminated the genetic basis of diversity, though many traits remain poorly understood regarding their underlying genes.
Quantitative Traits: Traits such as milk production in cows serve as examples of quantitative traits within breeding programs.
- E.g., average milk production in NZ dairy cows is $4,370$ liters per cow (2013 data).
Difference in Breeding Systems: US cows can produce significantly more milk due to factors such as hormonal injections and more frequent milking.

Alleles in Breeding: Improvement often hinges on assembling favorable combinations of existing alleles rather than relying on new mutations.
Estimations of Mutations: Only about $16$ significant mutations occur from one generation to the next, suggesting improvements are due to better allele combinations.
Milk Composition: Focus on producing milk solids rather than just volume, emphasizing the importance of fat content in milk.

Diversity in Breeds: Different sheep breeds such as Merino, Romney, and Corriedale showcase variations in wool characteristics (fiber diameter) and production goals.
- Merino: Fine wool, $12-24$ microns.
- Romney: Dual purpose for meat and stronger wool, $33-37$ microns.
- Corriedale: Mid micron wool, $26-31$ microns.
Genetic Identification Challenges: Different breeds share similar DNA sequences, making it hard to distinguish them without looking at specific allelic variations.
Genomic Tools: The Ensemble genome browser assists in exploring genetic variations across breeds and understanding their phenotypic implications.

Genetic Variation Across Genes: Variants exist not only in coding regions (exons) but also in introns and untranslated regions (UTRs), which can affect gene expression and protein synthesis.
- UTRs: Control stability and regulation of genes, and mutations here can influence phenotypic outcomes.
Specific Gene Example: The ovine cap6.1 gene (also known as krtap6.1) located on sheep chromosome one has several allelic variations affecting different traits such as wool diameter.

Cattle and Dog Breeds: Genetic diversity arises from combinations of alleles rather than mutations.
- Cattle: Originate from a common ancestor (Aurochs) but exhibit various traits due to selective breeding.
- Dogs: Descended from wolves with significant diversity resulting from selective breeding practices.
Phylogenetic Trees: Use genetic similarity to visualize relationships among various breeds, emphasizing common ancestry and selective breeding patterns.

Meiosis and Diversity: Genetic variation is mainly a result of meiosis processes such as crossing over and segregation of chromosomes, not mutations.
Stable Results Through Breeding: While mutations occur rarely over evolutionary timescales, selective breeding can achieve quicker changes within species through choosing desirable alleles.

Genotypic Combinations: The number of possible genotypes for multiple alleles can be calculated using the formula: $n \times (n + 1) / 2$ , where n is the number of alleles.
- Example: For $3$ alleles, it results in $6$ genotypes, and for $32$ alleles, it gives $496$ genotypes.
Impact on Phenotypes: A high number of alleles and their combinations contribute to phenotypical variations observed in livestock.

Ongoing Research: The field is evolving, and continued study into allelic variations and breeding strategies is vital to improve agricultural practices.
Takeaway Messages: Understanding genetic diversity and breeding strategies involves factorial combinations of alleles rather than assuming mutations; insights into DNA can aid in improving crops and livestock.