Biology subjects

Solovyov, A.

Publications and source records attributed to Solovyov, A..

6 recordsLinked to original sources

bioRxiv2026

From Genes to Brains: Molecular Evolution and Mammalian Brain Cellular Diversity

Mammalian brains exhibit extensive diversity in size, cellular composition, and organization, yet the molecular evolutionary changes associated with this phenotypic diversification remain incompletely understood. Here, we investigated whether protein-sequence evolution covaries with quantitative differences in brain phenotypes across mammals. We integrated 29 brain and body traits with orthologous protein sequences from 18 mammalian species and obtained gene-specific molecular evolutionary measures for 10,395 genes. To reduce redundancy among strongly correlated phenotypes, we selected five representative traits that explained 88.12% of the standardized trait variance under linear reconstruction. Using RERconverge, we tested for associations between gene-specific relative evolutionary rates and evolutionary changes in these five representative traits. The primary analysis, based on log-transformed phenotypes, identified 25 significant gene--trait associations involving 23 genes, 19 of which were also recovered using untransformed phenotypes, indicating that a substantial subset of the associations was robust to phenotype transformation. Expression profiling of these shared candidate genes across adult human GTEx brain tissues revealed heterogeneous patterns ranging from broad expression across the examined tissues to low adult brain expression. Functional enrichment analysis further showed that the gene set retained for comparative analysis was enriched for diverse biological processes, including metabolic, cellular, and neural pathways. These results identify gene-specific evolutionary-rate associations with quantitative mammalian phenotypes and provide functional context for the genes represented in the comparative analysis. Our study provides a comparative framework linking relative evolutionary rates of protein-coding genes to quantitative variation in mammalian brain cellular architecture while accounting for shared evolutionary history.

evolutionary biology↗

bioRxiv2023

Cancer cells co-evolve with retrotransposons to mitigate viral mimicry

Overexpression of repetitive elements is an emerging hallmark of human cancers1. Diverse repeats can mimic viruses by replicating within the cancer genome through retrotransposition, or presenting pathogen-associated molecular patterns (PAMPs) to the pattern recognition receptors (PRRs) of the innate immune system2-5. Yet, how specific repeats affect tumor evolution and shape the tumor immune microenvironment (TME) in a pro- or anti-tumorigenic manner remains poorly defined. Here, we integrate whole genome and total transcriptome data from a unique autopsy cohort of multiregional samples collected in pancreatic ductal adenocarcinoma (PDAC) patients, into a comprehensive evolutionary analysis. We find that more recently evolved Short Interspersed Nuclear Elements (SINE), a family of retrotransposable repeats, are more likely to form immunostimulatory double-strand RNAs (dsRNAs). Consequently, younger SINEs are strongly co-regulated with RIG-I like receptor associated type-I interferon genes but anti-correlated with pro-tumorigenic macrophage infiltration. We discover that immunostimulatory SINE expression in tumors is regulated by either Long Interspersed Nuclear Elements 1 (LINE1/L1) mobility or ADAR1 activity in a TP53 mutation dependent manner. Moreover, L1 retrotransposition activity tracks with tumor evolution and is associated with TP53 mutation status. Altogether, our results suggest pancreatic tumors actively evolve to modulate immunogenic SINE stress and induce pro-tumorigenic inflammation. Our integrative, evolutionary analysis therefore illustrates, for the first time, how dark matter genomic repeats enable tumors to co-evolve with the TME by actively regulating viral mimicry to their selective advantage.

cancer biology↗

bioRxiv2023

Mechanism-guided quantification of LINE-1 reveals p53 regulation of both retrotransposition and transcription

Somatic activity of LINE-1 (L1) mobile elements has been implicated in cancer etiology, which may be related to the loss of p53-mediated regulation as a result of TP53 mutations. Quantifying the mechanisms of L1 regulation in cancer has been challenging. Here, we build a statistical model of L1 regulation by simultaneously quantifying L1 retrotransposition, L1 expression, and the fitness costs of mutated TP53 with precision. We first developed Total ReCall, an algorithm specifically tailored to the mechanisms of L1 reintegration, to detect L1 insertions from short-read whole-genome sequencing. Applying Total ReCall to high-quality data consisting of >750 paired tumor and normal samples from The Cancer Genome Atlas (TCGA) shows high L1 insertion heterogeneity among tumor types, with increased retrotransposition burden in lung squamous cell carcinoma, head and neck, and colon cancers. We next assessed the active RNA expression of intact L1 in >9,000 TCGA tumor samples, establishing, for the first time, a clear correlation between L1 expression and retrotransposition. Finally, we integrated the number of L1 insertions, L1 expression and a mathematical model of TP53 fitness into a multi-modal model of p53- mediated mechanisms of L1 regulation. We show that TP53 mutations enable retrotransposition both by disinhibiting L1 expression and enabling its reintegration and quantify the relative weights of this dual regulatory role. We demonstrate how mechanism-based multi-modal modeling applied at scale can statistically disentangle the complex interplay between canonical driver events in tumor evolution and retrotransposon activity.

cancer biology↗

bioRxiv2021

Repeats Mimic Immunostimulatory Viral Features Across a Vast Evolutionary Landscape

An emerging hallmark across human diseases - such as cancer, autoimmune and neurodegenerative disorders - is the aberrant transcription of typically silenced repetitive elements. Once active, a subset of repeats may be capable of "viral mimicry": the display of pathogen-associated molecular patterns (PAMPs) that can, in principle, bind pattern recognition receptors (PRRs) of the innate immune system and trigger inflammation. Yet how to quantify the landscape of viral mimicry and how it is shaped by natural selection remains a critical gap in our understanding of both genome evolution and the immunological basis of disease. We propose a theoretical framework to quantify selective forces on virus-like features as the entropic cost a sequence pays to hold a non-self PAMP and show our approach can predict classes of viral-mimicry within the human genome and across eukaryotes. We quantify the breadth and conservation of viral mimicry across multiple species for the first time and integrate selective forces into predictive evolutionary models. We show HSATII and intact LINE-1 (L1) are under selection to maintain CpG motifs, and specific Alu families likewise maintain the proximal presence of inverted copies to form double-stranded RNA (dsRNA). We validate our approach by predicting high CpG L1 ligands of L1 proteins and the innate receptor ZCCHC3, and dsRNA present both intracellularly and as MDA5 ligands. We conclude viral mimicry is a general evolutionary mechanism whereby genomes co-opt pathogen-associated features generated by prone repetitive sequences, likely offering an advantage as a quality control system against transcriptional dysregulation.

systems biology↗

bioRxiv2019

Y-RNAs Lead an Endogenous Program of RIG-I Agonism Mobilized upon RNA Virus Infection and Targeted by HIV

Pattern recognition receptors (PRRs) protect against host invasion by detecting specific molecular patterns found in pathogens and initiating an immune response. While microbial-derived PRR ligands have been extensively characterized, the contribution and relevance of endogenous ligands to PRR activation during viral infection remain overlooked. In this work, we characterize the landscape of endogenous ligands that engage RIG-I-like receptors (RLRs) upon infection by a positive-sense RNA virus, a negative-sense RNA virus or a retrovirus. We found that several endogenous RNAs transcribed by RNA polymerase 3 (Pol3) specifically engage RLRs, and in particular the family of small non-coding repeats Y-RNAs, which presents the highest affinity as RIG-I ligands. We show that this recognition is dependent on Y-RNA mimicking viral secondary structure and its 5-triphosphate extremity. Further, we found that HIV-1 infection triggers a VPR-dependent downregulation of RNA triphosphatase DUSP11 in vitro and in vivo, leading to an increase of Y-RNA 5-triphosphorylation that enables their immunogenicity. Importantly, we show that altering DUSP11 expression is sufficient to induce a type-I interferon and T cell activation transcriptional program associated with HIV-1 infection. Overall, our work uncovers the critical contribution of endogenous repeat RNAs ligands to antiviral immunity and demonstrates the role of this pathway in HIV-1 infection.

immunology↗

bioRxiv2017

Global Cancer Transcriptome Quantifies Repeat Element Polarization Between Immunotherapy Responsive and T cell Suppressive Classes

Growing evidence indicates that innate immune pathway activation is critical for responses to immunotherapy and overall cancer prognosis. It has been posited that innate immunity in the tumor microenvironment can be driven by derepression of endogenous repetitive element RNA. The ability to characterize these species can potentially provide novel predictive biomarkers for tumor immune responses and a mechanistic basis for elements of innate activation by tumors. We first compared total RNA and poly(A)-capture protocols applied to tumor RNA-sequencing to detect non-RNA coding transcriptomes in the TCGA. While the poly(A) protocol efficiently detects coding, most non-coding genes, and much of the LINE/SINE/ERV repeat repertoire, we found that it fails to capture overall repeat expression and co-expression. The probing of total RNA expression reveals distinct repetitive co-expression subgroups. Secondly, we found that total repeat element expression delivers the most dynamic changes in samples, which may serve as more robust biomarkers of clinical outcomes. Finally, we show that while expression of ERVs, but not other immunostimulatory repeats such as HSATII, is associated with response to immunotherapy in a cohort of patients with urothelial cancer treated with anti-PD-L1 therapy, global repeat derepression strongly correlates with an immunosuppressive phenotype in the microenvironment of colorectal and pancreatic tumors. We validate in situ in human primary tumors, associating the immunosuppressive phenotype with HSATII expression. In conclusion, we demonstrate the importance of analyzing repetitive element RNAs as potential biomarkers of response to immunotherapy and the need to better characterize these features in next generation sequencing protocols.

cancer biology↗