Agricultural and environmental biotechnology
Study-unit Code
In all curricula
Luigi Russi
Course Regulation
Coorte 2023
Type of study-unit
Obbligatorio (Required)
Type of learning activities
Attività formativa integrata


Code A002225
Teacher Gianpiero Marconi
  • Gianpiero Marconi
  • 63 ore - Gianpiero Marconi
Learning activities Caratterizzante
Area Discipline biotecnologiche generali
Academic discipline AGR/07
Type of study-unit Obbligatorio (Required)
Language of instruction english
Contents Endonucleases Restriction enzymes and enzymes for DNA manipulation. Details on Polymerase chain reaction, electrophoresis and Southern hybridization. Morphological, Biochemical and Molecular Markers. Association and linkage mapping. Practical and theoretical preparation of genomic libraries (cDNA theory). Details on sequencing of genomic libraries (evaluation of parameters quality). Markers-assisted breeding and Next generation sequencing. Fundamentals of bioinformatics on management of NGS big datasets.
Reference texts - Weising, Nybom, Wolff, Kahl. DNA Fingerprinting in Plants Principles, Methods, and Applications. CRC Press - Haddock & Dunn, Practical computing for biologists. Sinauer Accociated Publishers
- Lorenzetti et al, Miglioramento genetico delle piante agrarie. Edagricole editore
- Citterich et al, Fondamenti di Bioinformatica. Zanichelli editore
- Barcaccia & Falcinelli - Genetica e genomica Vol. III. Liguori editore
– Study material provided by the teacher
Educational objectives The course supplies a detailed knowledge of molecular markers in order to use them in plant breeding
Prerequisites Not required
Teaching methods Class lectures and Laboratory practical training
Other information Class lectures: Optional but strongly advised; Laboratory practical training: Compulsory, at least 80% of presence
Learning verification modality Oral exam
Extended program Restriction enzymes. Enzymes for DNA manipulation. Details for preparing an efficient polymerase chain reaction (PCR). Electrophoresis and Southern Hybridization. Sanger sequencing and Next Generation Sequencing (NGS). Genomic and cDNA libraries construction. Prokaryotic and eukaryotic genome structure. Morphological, biochemical and molecular markers. Hybridization-based Molecular Markers (RFLP). PCR-based Molecular Markers (RAPD, AFLP, STS, SCAR, CAPS, SSR, SNP). Marker based on Next Generation Sequencing technologies: RAD-Seq, ddRAD-Seq and GBS. Fundamentals of bioinformatics on management of NGS big datasets (several tools in bash). Practical preparation of NGS libraries (ddRAD-Seq) and identification, validation and genotyping analysis of SNPs markers. Theory and practical analysis on fingerprinting, population genetics and association (GWAS) and linkage mapping. Marker assisted selection and Next generation sequencing technologies and their implications for crop genetics and breeding.


Code A002224
Teacher Luigi Russi
  • Luigi Russi
  • 54 ore - Luigi Russi
Learning activities Caratterizzante
Area Discipline biotecnologiche generali
Academic discipline AGR/07
Type of study-unit Obbligatorio (Required)
Language of instruction ENGLISH
Contents Hardy Weinberg equilibrium; changes of gene frequencies; inbreeding and Sewall Wright's equilibrium; F statistics; adaptive value; Changes of mean and variance due to changes in allele frequencies; variance components, heritability; response to selection; quantitative traits under artificial and natural selection.
Reference texts 1. Conner JK, Hartl DL 2004. A Primer of Ecological Genetics. Sinauer Ass., Inc. USA
2. Hartl DL, Clark AG, 2008. Principles of Population Genetics, 4th Edition. Sinauer Associates.
3. Falconer DS, MacKay TFC. 1996 - Introduction to Quantitative Genetics. 4th Edition. Longman.
4. Study materials provided by the lecturer.
Educational objectives Provide students with the necessary in-depth knowledge to understand evolutive factors (selection, mutation, migration, genetic drift) occurring in natural and in improved populations, as well as the knowledge necessary to handle conventional and advanced genetic improvement programs.
Prerequisites In order to understand and apply the techniques listed in the course program, in addition to basic knowledge of genetics, it is very important to know basic concepts of statistics, accompanied by practical application of the most common softwares.
Teaching methods The Module in Quantitative Genetics is organized as follows:
1. Lectures on all topics listed in the above program
2. Classrooms practicals with applications of population genetics and quantitative genetics models, also with the use of appropriate softwares. The course includes a joint practical between the two modules, during which the experimental data obtained by each student from the lab practicals will be analyzed and the results interpreted in the light of the theoretical part done during the lectures.
3. Seminars on topics assigned by the lecturers.
Other information 1. Period of lectures and exams: 18 September 2023 - 23 February 2024.
2. Attendance at class lectures and practicals is strongly advised.
3. The study material provided by the lecturer (slides, notes, scientific papers, etc.) is available to enrolled students on the UNISTUDIUM platform (www.unistudium.unipg.it)
Learning verification modality For students not regularly attending the lectures the overall assessment, in the dates listed in the calendar of exams, is based on a written test lasting 2 hours, to assess the problem-solving ability, followed by an oral examination, lasting about half an hour, to assess communication skills and theoretical aspects that are needed in problem-solving applications.
For students regularly attending the lessons there will be a progressive learning assessment based on: (a) written tests on topics covered during the previous weeks; (b) the presentation skills and ability to discuss a scientific paper, activity scheduled towards the end of the course and assigned by the lecturer. For the module Quantitative genetics the content of the written test will be based on practical problems of population and quantitative genetics. The oral test will complement the written part to ensure that in addition to the problem-solving ability the student is able to express himself orally by discussing theoretical aspects. A final oral examination is intended to complete or integrate the written parts, with the goal of connecting all the practical and theoretical aspects developed in the course.
Extended program LECTURES:
Part 1: Population genetics
Concepts of metapopulation and subpopulation. Measuring genetic variation. Organization of the genetic variation within populations. Deriving the Hardy-Weinberg equation. Uses of the Hardy-Weinberg equilibrium (HWE). Testing the departure from the HWE. The HWE in case of multiple alleles, X-linked alleles, in autopoliploids. HW for two loci: gametic phase equilibrium.
HWE and non-random mating: assortative e disassortative mating, outbreeding and inbreeding. Sewall Wright equilibrium. Effect of mutation on allele frequencies. HWE and rate of reversible and irreversible mutation. Migration: one-way migration, island model. Effect of migration on allele frequencies. Wahlund effect. Random genetic drift and its effect on metapopulation and subpopulations. F-statistics of Sewall Wright. Effective population size. Bottleneck and founder event. Gene flow in fragmented populations. Natural selection and adaptation: fitness and selection coefficients. General model of natural selection on HWE. Selection aganist the recessive and aganist the dominant. Overdominance and heterozygote advantage. Interactions between the evolutionary forces.

Part 2: Quantitative genetics
Cluster analysis: data matrix, coefficients of similarity distance and correlations; hierarchical (single linkage, complete linkage, UPGMA) and non hierarchical (k-means).
Mendelian basis of continuous variation. Phenotipic and genotipic value. Environmental deviation. Different types of gene actions. Population mean. Population variance, phenotipic, genotypic and environmental variance. Additive and non-additive genetic variance (dominance and epistatic variance). Breeding value. Heritability. Estimating additive variance and heritability: offspring-parent regression, sibling analyses. Estimating additive genetic variance in autogamous populations. Response to selection, realized heritability, asimmetrical response, correlated response.

Class exercises on factors disturbing the HWE. At the end of laboratory practicals, as scheduled in the Genomic analysis module: reading and preparing a data matrix in Excel, cluster analysis of data, genetic interpretation of the results.
Practicals on examples from the literature: statistical analyses of experimental data (one and two-way anova, correlation and regression between traits, multilocation trials, estimates of heritability, carried out by R statistical software.

Students, individually and/or in a group, are expected to prepare and present a seminar to the class. Topics assigned by the lecturer some weeks before.
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