MER41 repeat sequences contain inducible STAT1 binding sites

Chromatin immunoprecipitation combined with massively parallel sequencing methods (ChIP-seq) is becoming the standard approach to study interactions of transcription factors (TF) with genomic sequences. At the example of public STAT1 ChIP-seq data sets, we present novel approaches for the interpretation of ChIP-seq data.We compare recently developed approaches to determine STAT1 binding sites from ChIP-seq data. Assessing the content of the established consensus sequence for STAT1 binding sites, we find that the usage of "negative control" ChIP-seq data fails to provide substantial advantages. We derive a single refined probabilistic model of STAT1 binding sequences from these ChIP-seq data. Contrary to previous claims, we find no evidence that STAT1 binds to multiple distinct motifs upon interferon-gamma stimulation in vivo. While a large majority of genomic sites with high ChIP-seq signal is associated with a nucleotide sequence resembling a STAT1 binding site, only a very small subset of the over 5 million potential STAT1 binding sites in the human genome is covered by ChIP-seq data. Furthermore a surprisingly large fraction of the ChIP-seq signal (5%) is absorbed by a small family of repetitive sequences (MER41). The observation of the binding of activated STAT1 protein to a specific repetitive element bolsters similar reports concerning p53 and other TFs, and strengthens the notion of an involvement of repeats in gene regulation. Incidentally MER41 are specific to primates, consequently, regulatory mechanisms in the IFN-STAT pathway might fundamentally differ between primates and rodents. On a methodological aspect, the presence of large numbers of nearly identical binding sites in repetitive sequences may lead to wrong conclusions about intrinsic binding preferences of TF as illustrated by the spacing analysis STAT1 tandem motifs. Therefore, ChIP-seq data should be analyzed independently within repetitive and non-repetitive sequences.

KRAB zinc-finger proteins and their transposable element targets: between antagonism and cooperation

Jonas Caspar De Tribolet-Hardy

There are 377 Krüppel-associated box (KRAB) domain-containing zinc finger proteins (KZFPs) in the human genome, making them the largest family of transcription factors. KZFPs are defined by a N-terminal KRAB domain and several zinc-finger domains arranged in an array at the C-terminus of the proteins. The zinc-finger domains each form sequence specific interactions with double stranded DNA, allowing the zinc-finger array to target specific genomic sequences. The KRAB domain, through its interaction with the protein TRIM28 (also known as KAP1) allows for the stable silencing of transcription in a genomic region. Together these two domains allow KZFPs to bind specific regions of the genome and generally lead to the formation of heterochromatin and silencing of transcription allthough other functions for some KZFPs have been recently reported. KZFPs usually target transposable elements (TEs), mobile genomic elements that can move through the genome either by cut-and-paste or copy-paste mechanisms and make up almost half of the human genome. Different KZFPs bind to specific regions of TEs, limiting their expression and thus mitigating some of the threat they pose to human development, allowing both the TE and its host to survive. In recent years it became apparent that both certain TEs and KZFPs have roles beyond the previously described threat and mitigation of that threat. TEs harbor gene regulatory regions allowing, through their spread, for a dissemination of those regions through the genome and for new gene regulatory networks to form. KZFPs can affect the transcription of genes located in proximity to their binding sites leading to changes in gene regulation as well. A multitude of regulatory roles involving KZFPs and TEs have been described in recent years making them an exciting field of study. A major hurdle in understanding both KZFPs and TEs is to identify the binding sites of KZFPs, as they reveal both the targets of the KZFP and how, if at all, a TE is regulated by KZFPs. To do so, we expanded on previous efforts and aimed to perform chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-seq) on every member of the human KZFP family. Here we present ChIP-seq experiments for 110 new KZFPs, which together with previously published data, allow us to study the binding of almost all human KZFPs (95%). The entirety of the data was analysed together to generate a coherent dataset and results for each KZFP are made available to the public on our web portal (https://tronoapps.epfl.ch/web/krabopedia/). The identified binding sites allowed us to witness the adaptation of the KZFP family to new TEs and showed how targeted sequences shift after segmental gene duplication events. Furthermore, we could corroborate that several KZFPs target the same TE subfamilies in a seemingly redundant fashion and show that unexpectedly these KZFPs arose independently in different genomic locations. These results represent a valuable tool for anyone studying KZFPs and should aid in the pursuit of both understanding KZFPs and TEs.

EPFL2022

Computational study of transcription factor binding sites

Romain Fernand Pietro Groux

Any living organism contains a whole set of instructions encoded as genes on the DNA. This set of instructions contains all the necessary information that the organism will ever need, from its development to a mature individual to environment specific responses. Since all these instructions are not needed at the same time, the gene expression needs to be regulated. Eukaryotic genomes are stored inside nuclei as chromatin. The chromatin is the association of DNA with dedicated storage proteins - the histones - and the necessary machinery to regulate and express genes (RNA polymerases or RNAPs). In the nuclei, histones are assembled into octamers around which are wrapped ~148bp of DNA. This structure is known as the nucleosome. The repetition of nucleosomes along the genome allows to drastically compact the genome, eventually allowing to fit it inside the nucleus. However, this comes at the cost of rendering the DNA sequence inaccessible to DNA readers, such as the RNAPs and transcription factors (TFs). TFs are a class of proteins that have the remarkable property of recognizing and binding specific DNA sequences. More striking, each TF can recognize a multitude of different - but similar - DNA sequences providing TFs with a wide sequence specificity range. Eventually, this allows the cell to recruit TFs at dedicated locations in the genome called regulatory elements (REs). The action of TFs at REs is crucial to gene expression. Indeed, TFs are involved in many processes such as the opening of the chromatin structure or the recruitment of RNAPs. However if TFs can influence the chromatin structure, the opposite is also true as histones impede TF binding on DNA. Thus the regulation of genes relies on a subtle and complex crosstalk between the chromatin and TFs. To better understand how TFs and chromatin interact together to regulate gene expression, I lead several projects prospecting TF binding specificity and the chromatin structure at REs in human. First, I used ENCODE next generation sequencing (NGS) data to explore how TF binding influences the nearby nucleosome organization and the propensity of some TFs to bind together. The results suggest that regular nucleosome arrays are found near all TFs. They also point out two special cases. When CTCF binds with the cohesin complex, it seems to drive the nucleosome organization, which is a unique feature among all TFs investigated. Additionally I present evidence supporting that EBF1 is a pioneer factor - a special class of TFs able to bind nucleosome. Secondly, I developed several clustering algorithms and software to partition genomic regions according to NGS data and/or on their DNA sequences. These methods allow to discover important trends, for instance different nucleosome architectures . I illustrated the usefulness of these methods for the study of chromatin accessibility data and the identification of REs. Thirdly, I participated to the assessment of SMiLE-seq, a new microfluidic device that generates TF specificity data. The creation of TF specificity models and their comparison with other publicly available models demonstrated the value of SMiLE-seq to study TF specificity. Finally, I participated in the development of a software that predicts TF binding sites. A careful benchmarking suggested that this software is - at the time of writing - the best available software in terms of speed while showing other performances similar to its competitors.

EPFL2020

Long-range heterogeneity at the 3' ends of human mRNAs

Philipp Bucher

The publication of a draft of the human genome and of large collections of transcribed sequences has made it possible to study the complex relationship between the transcriptome and the genome. In the work presented here, we have focused on mapping mRNA 3' ends onto the genome by use of the raw data generated by the expressed sequence tag (EST) sequencing projects. We find that at least half of the human genes encode multiple transcripts whose polyadenylation is driven by multiple signals. The corresponding transcript 3' ends are spread over distances in the kilobase range. This finding has profound implications for our understanding of gene expression regulation and of the diversity of human transcripts, for the design of cDNA microarray probes, and for the interpretation of gene expression profiling experiments.