701-1676-01L  Genomics of Environmental Adaptation

SemesterAutumn Semester 2020
LecturersR. Holderegger, F. Gugerli, C. Rellstab
Periodicityyearly recurring course
Language of instructionEnglish
CommentNumber of participants limited to 14.

Prerequisites: good knowledge in population genetics and some experience in using GIS and R is required.


701-1676-01 GGenomics of Environmental Adaptation
Blockkurs: 8.2.2021 - 12.2.2021
Ort der Veranstaltung: EPD01 / WSL Birmensdorf
40s hrsR. Holderegger, F. Gugerli, C. Rellstab

Catalogue data

AbstractThis five-day winter school aims at teaching advanced Master students, PhD students and post-doctoral researchers on aspects of the genomics of environmental adaptation. It provides both theoretical background and hands-on exercises on major topics of contemporary environmental genomics such as signatures of selection, outlier analysis or environmental association analysis.
ObjectiveGenomics of environmental adaptation is an evolving scientific field of both basic and applied interest. Researchers make increasing use of diverse methodological approaches built on concepts from ecology, evolutionary biology and population genomics. This winter school introduces students to some major concepts and methods of environmental genomics, i.e., (i) how the environment and adaptive genetic variation relate and (ii) how signatures of local adaptation can be detected in natural populations using genomic data. The winter school focuses on currently used methods and hands-on exercises, emphasizing an understanding of the underlying concepts and a discussion of benefits, limitations and pitfalls of environmental genomics. It is specifically aimed at the needs of advanced Master students, PhD students and post-doctoral researchers.
(1) Genetic structure: how selection, drift, gene flow and isolation interact, affect neutral and adaptive genetic variation and influence the genetic structure of populations.

(2) Environmental data: which environmental data are available and used to identify signatures of adaptation; what are their limitations; collinearity; sampling design.

(3) Outlier analysis: types of next-generation-sequencing data; concept and methodology of outlier analysis; diverse types of outlier analyses.

(4) Environmental association analysis (landscape genomics): concept and methodology of environmental association analysis; diverse types of environmental association analysis.

(5) Phenotypes and genomic data; GWAS; mechanistic understanding of the environment–genotype–phenotype interaction; designing an own study.
Lecture notesHand-outs will be distributed.
LiteratureThe course requires 4 hours of preparatory reading of selected papers on the genomics of environmental adaptation. These papers will be distributed by e-mail.
Prerequisites / NoticeGrading will be according to a short written report (6-8 pages) on one of the topics of the course (workload: about 8 hours) and according to student contributions during the course.

Prerequisites: students should have good knowledge in population genetics and evolutionary biology and basic skills in R; experience in using GIS is advantageous.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits2 credits
ExaminersR. Holderegger, F. Gugerli, C. Rellstab
Typegraded semester performance
Language of examinationEnglish
RepetitionRepetition only possible after re-enrolling for the course unit.
Additional information on mode of examinationFull presence in the course is mandatory; grading will be according to a short, written report (6-8 pages) on one of the topics of the course (workload: about 8 hours) and according to student contributions during the course.

Learning materials

No public learning materials available.
Only public learning materials are listed.


No information on groups available.


Places14 at the most
Waiting listuntil 14.01.2021

Offered in

Doctoral Department of Environmental SciencesEcology and EvolutionWInformation
Environmental Sciences MasterAdvanced Concept ClassesWInformation