Genetics | EPFL Graph Search

Genetics is the study of genes, genetic variation, and heredity in organisms. It is an important branch in biology because heredity is vital to organisms' evolution. Gregor Mendel, a Moravian Augustinian friar working in the 19th century in Brno, was the first to study genetics scientifically. Mendel studied "trait inheritance", patterns in the way traits are handed down from parents to offspring over time. He observed that organisms (pea plants) inherit traits by way of discrete "units of inheritance". This term, still used today, is a somewhat ambiguous definition of what is referred to as a gene. Trait inheritance and molecular inheritance mechanisms of genes are still primary principles of genetics in the 21st century, but modern genetics has expanded to study the function and behavior of genes. Gene structure and function, variation, and distribution are studied within the context of the cell, the organism (e.g. dominance), and within the context of a population. Genetics has giv

Statistical Applications of Random Matrix Theory: Comparison of Two Populations

Rémy Mariétan

During the last twenty years, Random matrix theory (RMT) has produced numerous results that allow a better understanding of large random matrices. These advances have enabled interesting applications in the domain of communication. Although this theory can contribute to many other domains such as brain imaging or genetic research, its has been rarely applied. The main barrier to the adoption of RMT may be the lack of concrete statistical results from probabilistic Random matrix theory. Indeed, direct generalisation of classical multivariate theory to high dimensional assumptions is often difficult and the proposed procedures often assume strong hypotheses on the data matrix such as normality or overly restrictive independence conditions on the data. This thesis proposes a statistical procedure for testing the equality of two independent estimated covariance matrices when the number of potentially dependent data vectors is large and proportional to the size of the vectors corresponding to the number of observed variables. Although the existing theory builds a very good intuition of the behaviour of these matrices, it does not provide enough results to build a satisfactory test for both the power and the robustness. Hence, inspired by spike models, we define the residual spikes and prove many theorems describing the behaviour of many statistics using eigenvectors and eigenvalues in very general cases. For example in the two central theorems of this thesis, the Invariant Angle Theorem and the Invariant Dot Product Theorem. Using numerous generalisations of the theory, this thesis finally proposes a description of the behaviour of a statistic under a null hypothesis. This statistic allows the user to test the equality of two populations, but also other null hypotheses such as the independence of two sets of variables. Finally, the robustness of the procedure is demonstrated for different classes of models and criteria for evaluating robustness are proposed to the reader. Therefore, the major contribution of this thesis is to propose a methodology both easy to apply and having good properties. Secondly, a large number of theoretical results are demonstrated and could be easily used to build other applications.

EPFL2019

Foxn1 Regulates Lineage Progression in Cortical and Medullary Thymic Epithelial Cells But Is Dispensable for Medullary Sublineage Divergence

Xin Jin, Craig Nowell

The forkhead transcription factor Foxn1 is indispensable for thymus development, but the mechanisms by which it mediates thymic epithelial cell (TEC) development are poorly understood. To examine the cellular and molecular basis of Foxn1 function, we generated a novel and revertible hypomorphic allele of Foxn1. By varying levels of its expression, we identified a number of features of the Foxn1 system. Here we show that Foxn1 is a powerful regulator of TEC differentiation that is required at multiple intermediate stages of TE lineage development in the fetal and adult thymus. We find no evidence for a role for Foxn1 in TEC fate-choice. Rather, we show it is required for stable entry into both the cortical and medullary TEC differentiation programmes and subsequently is needed at increasing dosage for progression through successive differentiation states in both cortical and medullary TEC. We further demonstrate regulation by Foxn1 of a suite of genes with diverse roles in thymus development and/or function, suggesting it acts as a master regulator of the core thymic epithelial programme rather than regulating a particular aspect of TEC biology. Overall, our data establish a genetics-based model of cellular hierarchies in the TE lineage and provide mechanistic insight relating titration of a single transcription factor to control of lineage progression. Our novel revertible hypomorph system may be similarly applied to analyzing other regulators of development.

Public Library of Science2011

A Tale of Two Tumors: Unraveling the Complexities of Epigenetic Dysregulation in Cancer

Maria Christine Donaldson

Epigenetics plays an important role in cancer development and progression. Cancer cells hijack the epigenome by modifying the histone protein units responsible for packaging DNA, or by modifying the DNA itself, resulting in changes to chromatin topology and transcriptional programming within the cell. In this thesis, I report our investigation to uncover the mechanisms of epigenetic regulation and how epigenetic control of transcriptional programming goes awry in cancer. We investigate these processes in two separate contexts. In our first study, we investigate the mechanisms by which EZH2 oncogenic mutations alter structure and function of topologically associating domains in non-Hodgkin lymphoma. The process of chromatin folding leads to a systematic arrangement of hierarchical structural and regulatory elements found within the nucleus. A topologically associating domain (TAD) is a regulatory unit of self interacting DNA, where the transcription of the genes within a TAD is usually dictated by the presence of active (H3K36me3) or inactive (H3K27me3) histone marks. In cancer, the somatic point mutation in EZH2Y646X leads to a genome wide increase in H3K27me3, associated with transcriptional repression. While this alteration leads to changes in the global epigenetic status of the cell, its impact on chromatin organization and TAD-related function remain unclear. By combining transcriptomics and epigenetics with analyses of chromatin structure, we demonstrate a functional interplay between TADs and the epigenetic and transcriptional program of the genes found within them. This balance is altered by EZH2Y646X, leading to the synergistic silencing of entire domains directly targeting cell differentiation and tumor suppressive programs. A closer look reveals that the silencing of tumor suppressive TADs are coupled with structural modifications and changes in promoter interactions within EZH2Y646X target TAD6.139. Impressively, the TADâs transcriptional and epigenetic programs are restored by pharmacological inhibition of EZH2Y646X. Our results indicate that EZH2Y646X alters the topology and function of chromatin domains to promote synergistic oncogenic programs. In our second study, we dissect the epigenetic, transcriptomic, and metabolic signaling dependencies using a novel model of central nervous system primitive neural ectodermal tumors (CNS-PNETs). Central nervous system (CNS) tumors are the leading cause of cancer-associated death in children. Primitive neural-ectodermal tumors (CNS-PNETs) are a particularly aggressive subtype of embryonal CNS-tumor, with a five-year overall survival rate in less than 50% of patients. Despite sharing a similar cell of origin of other CNS tumors, CNS-PNETs have a different anatomical location, unique genetic and epigenetic features, and significantly worse clinical outcome. In addition, a lack of in vivo models for studying CNS tumors challenges the opportunity to dissect the genetic variables that underlie the origin of these tumors. We developed a novel CNS-PNET mouse model, called CNS-NPCs, using neural progenitor cells derived from human-iPS cells. Through histological, DNA methylation, and RNA sequencing analyses, we find that the CNS-NPC model recapitulates the the morphologic, epigenetic, and transcriptomic features of primary CNS-PNETs. In addition, through in vivo metabolic analyses of CNS-NPCs and the patient derived cell line, PFSK-1, we identified dysregulation in the neurotransmitter...

EPFL2019

A Tale of Two Tumors: Unraveling the Complexities of Epigenetic Dysregulation in Cancer

Maria Christine Donaldson

EPFL2019

Statistical Applications of Random Matrix Theory: Comparison of Two Populations

Rémy Mariétan

EPFL2019