Searching for a link between AID-mediated mutations and patterns of transcription initiation and pausing in activated B cells

Abstract

Activation-induced cytidine deaminase (AID) is an enzyme and key component of both 15 class-switch recombination and somatic hypermutation, two mechanisms used by activated B 16 cells to diversify their antigen repertoire, as it catalyzes the deamination of deoxycytidines turning 17 them into deoxyuridines, introducing mutations in immunoglobulin genes. AID, however, can also 18 target enhancer regions as well as non-immunoglobulin genes, called AID off-target genes, 19 sometimes leading to B cell malignancies. The exact mechanisms underlying AID’s promiscuous 20 activity have not yet been deciphered, but transcription is believed to be a prerequisite for AID-21 induced mutagenesis and RNA exosome has been suggested to enable AID’s accessibility to the 22 antisense strand. 23

Using a combination of precision run-on sequencing (PRO-seq for RNA Pol II occupancy 24 and PRO-cap for transcription initiation sites), RNA exosome, and mutation data from Mus 25 musculus and Homo sapiens activated B cells, we compared the transcriptional profiles between 26 AID off-target and non AID off-target genes with similar expression levels and the concurrence of 27 the mutation patterns with the transcriptional patterns in the AID off-target genes. Our results 28 suggest that in general, no major differences in the promoter-proximal and the gene body regions 29 were found in terms of different positions of transcription initiation and RNA Pol II occupancy and 30 general transcription levels. On the other hand, the region upstream of the annotated start of the 31 gene was found to be transcriptionally more active in both the sense and antisense strands in the 32 AID off-target genes, despite the similar expression levels between the AID off-targets and the 33 non AID off-targets in the genes themselves. Furthermore, enhancers linked to AID off-target 34 genes had increased transcriptional activity compared to enhancers linked to non AID off-target 35 genes. The PRO-seq and PRO-cap techniques offer base-pair resolution, thus, we were able to 36 investigate very localized transcriptional profiles around mutated and non-mutated cytosines; in 37 general, the mutated cytosines tend to be fewer at the lowest range of transcription activity values 38 than the non-mutated cytosines, with this tendency being more evident in the sense strand. Then, 39 pairing the mutation frequency of each cytosine with the transcriptional activity around it, we 40 detected an initial gradual increase in the transcriptional activity from the category with the lowest 41 mutation frequencies to the categories with higher mutation frequencies. This initial increase was 42 eventually restrained and no significant differences in the transcriptional activity were observed 43 with further increase of mutation frequency. Last, gene-specific (in mice) and region-specific (in 44 humans) plots of the transcriptional activity, RNA exosome sensitivity, and mutational activity 45 were generated and in many cases a faithful co-location of transcriptional and mutational patterns 46 was observed. At the same time, though, predictability is not guaranteed, as there are also cases 47 in which the mutation and transcription patterns do not match, suggestive of other as yet 48 undetermined mechanisms.

Popular Abstract

Why do the mechanisms that create the diversity of our antibodies attack non-antibody-producing genes?

Our body’s immune system responds to certain foreign molecules (called antigens) by producing and secreting antibodies through our B cells. Upon encountering such foreign molecules, B cells undergo a massive expansion of their antibody repertoire by mutating the genes that produce the antibodies. This expansion increases the chance to produce antibodies that bind more efficiently to the antigens and compromise their potentially harmful effect on our organisms. However, some genes unrelated to antibody production can also be targeted by the mechanisms that mutate the antibody-producing genes, sometimes causing diseases, such as cancer. The exact mechanisms that lead to the mutation of certain genes while leaving others unharmed have yet to be deciphered. One factor that has been shown to affect this promiscuous targeting of genes is how active a gene is, defined by its transcriptional output.

In this project, we are examining whether the targeted genes’ transcriptional activity is more concentrated in specific subregions of the genes and, more locally, whether around the mutated positions of the genes we observe higher activity rates than around non-mutated positions. For this, we established a workflow that utilizes custom scripts, as well as external bioinformatics tools.

To address our questions, we used B cells from mice and humans that were immunologically activated and we extracted the transcriptional activity rates across the whole genome of these cells. Then, we divided the genes in two categories according to whether or not they were often targeted by the mutagenic mechanisms that normally produce the antibody diversity (we called these genes “target genes” and “non-target genes” respectively). This categorization was based on the mutation profiles of the genes; the target genes were the genes that were found to be mutated and the non-target genes were the non-mutated genes. For the first part (region scale), we separated each gene into a gene start and a gene body region, and we included an upstream region (a region just before the gene) as well as other regions that are known to affect gene activity (called enhancers) in our analyses. Then, we compared how active these regions were in the target and non-target genes. For the second part (position-specific scale), we split all positions which could potentially be targeted by the mutagenic mechanisms into three groups: the mutated positions in the target genes, the non-mutated positions in the target genes, and the non-mutated positions in the non-target genes. These three groups were compared in terms of gene activity in a small region around each position.

From the results of the comparisons performed, we found no difference on how active the gene start and gene body regions are between the target and non-target genes. However, the upstream regions and the enhancers of the target genes were found to be significantly more active. Furthermore, we found that the gene activity around the mutated positions is generally higher than in the non-mutated positions. Last, by examining the mutation and gene activity profiles of each gene, we identified many cases of faithful matching of mutation frequency and gene activity, although this pattern is not a universal trait of the target genes as there were a lot of cases without any evident connection between the two aforementioned variables.

In conclusion, among the factors that affect the targeting of non-antibody-producing genes by the mutagenic mechanisms responsible for antibody diversification is not only how active a gene is, but also how active other regions outside of the gene (upstream and enhancer regions) are. Within the mutated genes, there is a tendency that the mutations are more frequent in more active subregions of the genes. Nevertheless, this tendency alone is not strong enough to allow us to predict positions that will be affected by the mutagenic mechanisms, suggesting that there are also other factors other than how active a region is that are involved in the process. Deciphering the mechanisms behind the promiscuous mutagenesis of genes in B cells can help us understand how certain diseases develop and aim for more specialized therapeutic approaches.

Master’s Degree Project in Bioinformatics 60 credits 2020
Department of Biology, Lund University

Advisors: Rushad Pavri, Ursula Schöberl
Research Institute of Molecular Pathology (IMP), Vienna, Austria

• author: Ourailidis, Iordanis
• supervisor: Rushad Pavri; Ursula Schöberl
• organization: Degree Projects in Bioinformatics
• course: BINP52 20191
• year: 2020
• type: H2 - Master's Degree (Two Years)
• subject: Biology and Life Sciences
• language: English
• id: 9012073
• date added to LUP: 2020-06-02 09:35:41
• date last changed: 2020-06-02 09:35:41