Uncategorized Archive


PhD and Postdoc opportunities to study genome architecture at the UNIZH, Zurich (CH)

Information on the Grob’s lab: https://www.botinst.uzh.ch/en/research/development/stefangrob.html


Genome Res.: co-auth.: S.Soyk

Genome Res. 2021 Apr 2;gr.264879.120. doi: 10.1101/gr.264879.120. Online ahead of print.

Optimized sample selection for cost-efficient long-read population sequencing

Timothy Rhyker Ranallo-Benavidez 1Zachary H Lemmon 2Sebastian Soyk 3Sergey Aganezov 4William J Salerno 5Rajiv C McCoy 6Zachary B Lippman 2Michael C Schatz 6Fritz J Sedlazeck 5


An increasingly important scenario in population genetics is when a large cohort has been genotyped using a low-resolution approach (e.g. microarrays, exome capture, short-read WGS), from which a few individuals are selected for resequencing using a more comprehensive approach, especially long-read sequencing. The subset of individuals selected should ensure that the captured genetic diversity is fully representative and includes variants across all subpopulations. For example, human variation has historically been focused on individuals with European ancestry, but this represents a small fraction of the overall diversity. To address this goal, SVCollector identifies the optimal subset of individuals for resequencing. SVCollector analyzes a population-level VCF file from a low resolution genotyping study. It then computes a ranked list of samples that maximizes the total number of variants present from a subset of a given size. To solve this optimization problem, SVCollector implements a fast greedy heuristic and an exact algorithm using integer linear programming. We apply SVCollector on simulated data, 2504 human genomes from the 1000 Genomes Project, and 3024 genomes from the 3K Rice Genomes Project and show the rankings it computes are more representative than other naive strategies. We show that when selecting an optimal subset of 100 samples in these two cohorts, SVCollector identifies individuals from every subpopulation while naive methods yield an unbalanced selection. Finally, we show the number of variants present in cohorts of different sizes selected using this approach follows a power-law distribution that is naturally related to the population genetic concept of the allele frequency spectrum, allowing us to estimate the diversity present with increasing numbers of samples.


Welcome to Adnane!

Adnane Ben Amor has joined in March 2021 the CIG central services. His main tasks include providing support for the zebrafish service and prepare new solutions. He will also be involved in strenghtning the existing services.

With a technical background, Adnane started his career in the Swiss army to help managing laboratories’ stocks.
His interest in technology and challenges then drove him to work for 7 years in a microbiological laboratory for quality control. He was in charge of the the preparation of culture media, sterilization and decontamination.
His path also led him to temporary work at the central sterilization service of a Swiss hospital.
In his words: it is a real pleasure for him to join the CIG team and make his humble contribution to the great science done at the UNIL.

Le sourire embellit la journée et si malgré tout il ne se montre pas, il y a toujours le chocolat !


A.Reymond was interviewed in UNIL “L’Actu” web magazine regarding rare diseases, their symptoms and genetic origins.

Maladies rares: à chaque syndrome sa classe de mutations

Les récents progrès en matière de séquençage du génome humain ont permis de découvrir la cause de nombreuses maladies rares. Le professeur Alexandre Reymond, directeur du Centre intégratif de génomique (CIG) de l’UNIL, en collaboration avec une équipe mondiale de généticiens, décrit dans l’édition du 28 janvier 2021 de l’«American Journal of Human Genetics» comment trois classes de mutations, situées sur un même gène, engendrent trois syndromes neurodéveloppementaux spécifiques.

Article complet: https://news.unil.ch/display/1611750683226

Publication de l'”American Journal of Human Genetics”: http://www.genomyx.ch/am-j-hum-genet-co-auth-group-reymond-2/


Welcome to Imen!

Imen Habibi is Tunisian, and molecular biologist and clinical molecular geneticist. Imen completed her MSc and PhD in genetics and immunology of kidney and ophthalmic diseases in the lab of Prof. Gorgi (Tunis El Manar University, Tunisia). Following her PhD, she was then awarded a Swiss Government Excellence Scholarship at EPFL-IRO in 2014, where she has joined Prof. Schorderet group. In this position she was responsible for the molecular diagnosis of patients with inherited retinal dystrophies, managing a number of research projects focusing on gene identification studies using NGS, their bioinformatics analysis and using in vivo animal models (CRISPR/Cas9). She has now joined on Feb. 1st Prof. Reymond group at the CIG for her Postdoc, where she will investigate the genetic profiles of patients with Autism Spectrum Disorder (ASD). 


Welcome to Shivali !

Shivali has done her bachelor’s and master’s in India. As a part of her Bachelor’s project, she worked on the DNA Binding and DNA cleavage properties of transition metal complexes in the lab of Dr. Anupa Kumbhar. She did her Master’s by research from the Tata Institute of Fundamental Research at Prof. Mahendra Sonawane’s lab, where she worked on the interplay between polarity and adhesion in the zebrafish epidermis. She has now joined the Vastenhouw Group at the CIG for her PhD!