TopicNet: a framework for measuring transcriptional regulatory network change

Reshaping the chromatin landscape in HUVECs from small-for-gestational-age newborns

Small for gestational age (SGA), with increased risk of adult-onset cardiovascular diseases and metabolic syndromes, is known to associate with endothelial dysfunction, but the pathogenic mechanisms remain unclear. In this study, the pathological state of human umbilical vein endothelial cells (HUVECs) from SGA individuals was characterized by presenting increased angiogenesis, migration, proliferation, and wound healing ability relative to their normal counterparts. Genome-wide mapping of transcriptomes and open chromatins unveiled global gene expression alterations and chromatin remodeling in SGA-HUVECs. Specifically, we revealed increased chromatin accessibility at active enhancers, along with dysregulation of genes associated with angiogenesis, and further identified CD44 as the key gene driving HUVECs' dysfunction by regulating pro-angiogenic genes' expression and activating phosphorylated ERK1/2 and phosphorylated endothelial NOS expression in SGA. In SGA-HUVECs, CD44 was abnormally upregulated by 3 active enhancers that displayed increased chromatin accessibility and interacted with CD44 promoter. Subsequent motif analysis uncovered activating protein-1 (AP-1) as a crucial transcription factor regulating CD44 expression by binding to CD44 promoter and associated enhancers. Enhancers CRISPR interference and AP-1 inhibition restored CD44 expression and alleviated the hyperangiogenesis of SGA-HUVECs. Together, our study provides a foundational understanding of the epigenetic alterations driving pathological angiogenesis and offers potential therapeutic insights into addressing endothelial dysfunction in SGA.

Inter3D: Capture of TAD Reorganization Endows Variant Patterns of Gene Transcription

Topologically associating domain (TAD) reorganization commonly occurs in the cell nucleus and contributes to gene activation and inhibition through the separation or fusion of adjacent TADs. However, functional genes impacted by TAD alteration and the underlying mechanism of TAD reorganization regulating gene transcription remain to be fully elucidated. Here, we first developed a novel approach termed Inter3D to specifically identify genes regulated by TAD reorganization. Our study revealed that the segregation of TADs led to the disruption of intrachromosomal looping at the myosin light chain 12B (MYL12B) locus, via the meticulous reorganization of TADs mediating epigenomic landscapes within tumor cells, thereby exhibiting a significant correlation with the down-regulation of its transcriptional activity. Conversely, the fusion of TADs facilitated intrachromosomal interactions, suggesting a potential association with the activation of cytochrome P450 family 27 subfamily B member 1 (CYP27B1). Our study provides comprehensive insight into the capture of TAD rearrangement-mediated gene loci and moves toward understanding the functional role of TAD reorganization in gene transcription. The Inter3D pipeline developed in this study is freely available at https://github.com/bm2-lab/inter3D and https://ngdc.cncb.ac.cn/biocode/tool/BT7399.

Time-course swRNA-seq uncovers a hierarchical gene regulatory network in controlling the response-repair-remodeling after wounding

Wounding initiates intricate responses crucial for tissue repair and regeneration. Yet, the gene regulatory networks governing wound healing remain poorly understood. Here, employing single-worm RNA sequencing (swRNA-seq) across 12 time-points, we delineated a three-stage wound repair process in C. elegans: response, repair, and remodeling. Integrating diverse datasets, we constructed a dynamic regulatory network comprising 241 transcription regulators and their inferred targets. We identified potentially seven autoregulatory TFs and five cross-autoregulatory loops involving pqm-1 and jun-1. We revealed that TFs might interact with chromatin factors and form TF-TF combinatory modules via intrinsically disordered regions to enhance response robustness. We experimentally validated six regulators functioning in transcriptional and translocation-dependent manners. Notably, nhr-76, daf-16, nhr-84, and oef-1 are potentially required for efficient repair, while elt-2 may act as an inhibitor. These findings elucidate transcriptional responses and hierarchical regulatory networks during C. elegans wound repair, shedding light on mechanisms underlying tissue repair and regeneration.

Recent advances in exploring transcriptional regulatory landscape of crops

Crop breeding entails developing and selecting plant varieties with improved agronomic traits. Modern molecular techniques, such as genome editing, enable more efficient manipulation of plant phenotype by altering the expression of particular regulatory or functional genes. Hence, it is essential to thoroughly comprehend the transcriptional regulatory mechanisms that underpin these traits. In the multi-omics era, a large amount of omics data has been generated for diverse crop species, including genomics, epigenomics, transcriptomics, proteomics, and single-cell omics. The abundant data resources and the emergence of advanced computational tools offer unprecedented opportunities for obtaining a holistic view and profound understanding of the regulatory processes linked to desirable traits. This review focuses on integrated network approaches that utilize multi-omics data to investigate gene expression regulation. Various types of regulatory networks and their inference methods are discussed, focusing on recent advancements in crop plants. The integration of multi-omics data has been proven to be crucial for the construction of high-confidence regulatory networks. With the refinement of these methodologies, they will significantly enhance crop breeding efforts and contribute to global food security.

Complex regulatory networks influence pluripotent cell state transitions in human iPSCs

Stem cells exist in vitro in a spectrum of interconvertible pluripotent states. Analyzing hundreds of hiPSCs derived from different individuals, we show the proportions of these pluripotent states vary considerably across lines. We discover 13 gene network modules (GNMs) and 13 regulatory network modules (RNMs), which are highly correlated with each other suggesting that the coordinated co-accessibility of regulatory elements in the RNMs likely underlie the coordinated expression of genes in the GNMs. Epigenetic analyses reveal that regulatory networks underlying self-renewal and pluripotency are more complex than previously realized. Genetic analyses identify thousands of regulatory variants that overlapped predicted transcription factor binding sites and are associated with chromatin accessibility in the hiPSCs. We show that the master regulator of pluripotency, the NANOG-OCT4 Complex, and its associated network are significantly enriched for regulatory variants with large effects, suggesting that they play a role in the varying cellular proportions of pluripotency states between hiPSCs. Our work bins tens of thousands of regulatory elements in hiPSCs into discrete regulatory networks, shows that pluripotency and self-renewal processes have a surprising level of regulatory complexity, and suggests that genetic factors may contribute to cell state transitions in human iPSC lines.

Gene regulatory network inference in the era of single-cell multi-omics

The interplay between chromatin, transcription factors and genes generates complex regulatory circuits that can be represented as gene regulatory networks (GRNs). The study of GRNs is useful to understand how cellular identity is established, maintained and disrupted in disease. GRNs can be inferred from experimental data - historically, bulk omics data - and/or from the literature. The advent of single-cell multi-omics technologies has led to the development of novel computational methods that leverage genomic, transcriptomic and chromatin accessibility information to infer GRNs at an unprecedented resolution. Here, we review the key principles of inferring GRNs that encompass transcription factor-gene interactions from transcriptomics and chromatin accessibility data. We focus on the comparison and classification of methods that use single-cell multimodal data. We highlight challenges in GRN inference, in particular with respect to benchmarking, and potential further developments using additional data modalities.

Analysis of regulatory network modules in hundreds of human stem cell lines reveals complex epigenetic and genetic factors contribute to pluripotency state differences between subpopulations

Stem cells exist in vitro in a spectrum of interconvertible pluripotent states. Analyzing hundreds of hiPSCs derived from different individuals, we show the proportions of these pluripotent states vary considerably across lines. We discovered 13 gene network modules (GNMs) and 13 regulatory network modules (RNMs), which were highly correlated with each other suggesting that the coordinated co-accessibility of regulatory elements in the RNMs likely underlied the coordinated expression of genes in the GNMs. Epigenetic analyses revealed that regulatory networks underlying self-renewal and pluripotency have a surprising level of complexity. Genetic analyses identified thousands of regulatory variants that overlapped predicted transcription factor binding sites and were associated with chromatin accessibility in the hiPSCs. We show that the master regulator of pluripotency, the NANOG-OCT4 Complex, and its associated network were significantly enriched for regulatory variants with large effects, suggesting that they may play a role in the varying cellular proportions of pluripotency states between hiPSCs. Our work captures the coordinated activity of tens of thousands of regulatory elements in hiPSCs and bins these elements into discrete functionally characterized regulatory networks, shows that regulatory elements in pluripotency networks harbor variants with large effects, and provides a rich resource for future pluripotent stem cell research.

Constructing a full, multiple-layer interactome for SARS-CoV-2 in the context of lung disease: Linking the virus with human genes and microbes

The COVID-19 pandemic caused by the SARS-CoV-2 virus has resulted in millions of deaths worldwide. The disease presents with various manifestations that can vary in severity and long-term outcomes. Previous efforts have contributed to the development of effective strategies for treatment and prevention by uncovering the mechanism of viral infection. We now know all the direct protein-protein interactions that occur during the lifecycle of SARS-CoV-2 infection, but it is critical to move beyond these known interactions to a comprehensive understanding of the "full interactome" of SARS-CoV-2 infection, which incorporates human microRNAs (miRNAs), additional human protein-coding genes, and exogenous microbes. Potentially, this will help in developing new drugs to treat COVID-19, differentiating the nuances of long COVID, and identifying histopathological signatures in SARS-CoV-2-infected organs. To construct the full interactome, we developed a statistical modeling approach called MLCrosstalk (multiple-layer crosstalk) based on latent Dirichlet allocation. MLCrosstalk integrates data from multiple sources, including microbes, human protein-coding genes, miRNAs, and human protein-protein interactions. It constructs "topics" that group SARS-CoV-2 with genes and microbes based on similar patterns of co-occurrence across patient samples. We use these topics to infer linkages between SARS-CoV-2 and protein-coding genes, miRNAs, and microbes. We then refine these initial linkages using network propagation to contextualize them within a larger framework of network and pathway structures. Using MLCrosstalk, we identified genes in the IL1-processing and VEGFA-VEGFR2 pathways that are linked to SARS-CoV-2. We also found that Rothia mucilaginosa and Prevotella melaninogenica are positively and negatively correlated with SARS-CoV-2 abundance, a finding corroborated by analysis of single-cell sequencing data.

Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets

Cell type-specific gene expression patterns are outputs of transcriptional gene regulatory networks (GRNs) that connect transcription factors and signaling proteins to target genes. Single-cell technologies such as single cell RNA-sequencing (scRNA-seq) and single cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq), can examine cell-type specific gene regulation at unprecedented detail. However, current approaches to infer cell type-specific GRNs are limited in their ability to integrate scRNA-seq and scATAC-seq measurements and to model network dynamics on a cell lineage. To address this challenge, we have developed single-cell Multi-Task Network Inference (scMTNI), a multi-task learning framework to infer the GRN for each cell type on a lineage from scRNA-seq and scATAC-seq data. Using simulated and real datasets, we show that scMTNI is a broadly applicable framework for linear and branching lineages that accurately infers GRN dynamics and identifies key regulators of fate transitions for diverse processes such as cellular reprogramming and differentiation.

ZBTB12 is a molecular barrier to dedifferentiation in human pluripotent stem cells

Development is generally viewed as one-way traffic of cell state transition from primitive to developmentally advanced states. However, molecular mechanisms that ensure the unidirectional transition of cell fates remain largely unknown. Through exact transcription start site mapping, we report an evolutionarily conserved BTB domain-containing zinc finger protein, ZBTB12, as a molecular barrier for dedifferentiation of human pluripotent stem cells (hPSCs). Single-cell RNA sequencing reveals that ZBTB12 is essential for three germ layer differentiation by blocking hPSC dedifferentiation. Mechanistically, ZBTB12 fine-tunes the expression of human endogenous retrovirus H (HERVH), a primate-specific retrotransposon, and targets specific transcripts that utilize HERVH as a regulatory element. In particular, the downregulation of HERVH-overlapping long non-coding RNAs (lncRNAs) by ZBTB12 is necessary for a successful exit from a pluripotent state and lineage derivation. Overall, we identify ZBTB12 as a molecular barrier that safeguards the unidirectional transition of metastable stem cell fates toward developmentally advanced states.

Interplay Between the Histone Variant H2A.Z and the Epigenome in Pancreatic Cancer

BACKGROUND

The oncogenic process is orchestrated by a complex network of chromatin remodeling elements that shape the cancer epigenome. Histone variant H2A.Z regulates DNA control elements such as promoters and enhancers in different types of cancer; however, the interplay between H2A.Z and the pancreatic cancer epigenome is unknown.

OBJECTIVE

This study analyzed the role of H2A.Z in different DNA regulatory elements.

METHODS

We performed Chromatin Immunoprecipitation Sequencing assays (ChiP-seq) with total H2A.Z and acetylated H2A.Z (acH2A.Z) antibodies and analyzed published data from ChIP-seq, RNA-seq, bromouridine labeling-UV and sequencing (BruUV-seq), Hi-C and ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) in the pancreatic cancer cell line PANC-1.

RESULTS

The results indicate that total H2A.Z facilitates the recruitment of RNA polymerase II and transcription factors at promoters and enhancers allowing the expression of pro-oncogenic genes. Interestingly, we demonstrated that H2A.Z is enriched in super-enhancers (SEs) contributing to the transcriptional activation of key genes implicated in tumor development. Importantly, we established that H2A.Z contributes to the three-dimensional (3D) genome organization of pancreatic cancer and that it is a component of the Topological Associated Domains (TADs) boundaries in PANC-1 and that total H2A.Z and acH2A.Z are associated with A and B compartments, respectively.

CONCLUSIONS

H2A.Z participates in the biology and development of pancreatic cancer by generating a pro-oncogenic transcriptome through its posttranslational modifications, interactions with different partners, and regulatory elements, contributing to the oncogenic 3D genome organization. These data allow us to understand the molecular mechanisms that promote an oncogenic transcriptome in pancreatic cancer mediated by H2A.Z.

The role of progesterone receptor isoforms in the myometrium

Myometrial contraction is stringently controlled throughout pregnancy and parturition. Progesterone signaling, effecting through the progesterone receptor (PR), is pivotal in modulating uterine activity. Evidence has shown that two major PR isoforms, PR-A and PR-B, have distinct activities on gene regulation, and the ratio between these isoforms determines the contractility of the myometrium at different gestational stages. Herein, we focus on the regulation of PR activity in the myometrium, especially the differential actions of the two PR isoforms, which maintain uterine quiescence during pregnancy and regulate the switch to a contractile state at the onset of labor. To demonstrate the PR regulatory network and its mechanisms of actions on myometrial activity, we summarized the findings into three parts: Regulation of PR Expression and Isoform Levels, Progesterone Receptor Interacting Factors, and Biological Processes Regulated by Myometrial Progesterone Receptor Isoforms. Recent genomic and epigenomic data, from human specimens and mouse models, are recruited to support the existing knowledge and offer new insights and future directions in myometrial biology.

Integrated bioinformatics analysis reveals that EZH2-rich domains promote transcriptional repression in cervical cancer

Cervical cancer is the third female cancer most common worldwide. The carcinogenic process involves an alteration of the mechanisms associated with transcription. Several studies have reported an oncogenic role of the polycomb complex subunit, EZH2. However, the role of EZH2 in cervical cancer is unknown. Hence, the objective of this study was to determine the role of EZH2 in transcriptional regulation in cervical cancer. The EZH2 expression and the methylation status of its promoter were analyzed in The Cancer Genome Atlas. The EZH2 enrichment profile was analyzed using chromatin immunoprecipitation with massively parallel DNA sequencing data provided by ENCODE project. The chromatin compartments were identified in the 4D Nucleome Data Portal. The functional annotation was examined in Enrichr. We report that EZH2 expression is increased in cervical cancer which is associated with hypomethylation of its promoter. EZH2 is enriched at promoter and distal intergenic regions. We identified that EZH2 defines chromatin domains enriched with H3K27me3 within repressive compartments in the HeLa-S3 cell line. Additionally, high EZH2 expression is associated with the repression of the senescent phenotype in cervical cancer patients. Our results suggest the participation of EZH2 in the generation of domains with a silencer function in cervical cancer, which regulate the expression of genes associated with cellular senescence.

GABPA-activated TGFBR2 transcription inhibits aggressiveness but is epigenetically erased by oncometabolites in renal cell carcinoma

Background

The ETS transcription factor GABPA has long been thought of as an oncogenic factor and recently suggested as a target for cancer therapy due to its critical effect on telomerase activation, but the role of GABPA in clear cell renal cell carcinoma (ccRCC) is unclear. In addition, ccRCC is characterized by metabolic reprograming with aberrant accumulation of L-2-hydroxyglurate (L-2HG), an oncometabolite that has been shown to promote ccRCC development and progression by inducing DNA methylation, however, its downstream effectors remain poorly defined.

Methods

siRNAs and expression vectors were used to manipulate the expression of GABPA and other factors and to determine cellular/molecular and phenotypic alterations. RNA sequencing and ChIP assays were performed to identify GABPA target genes. A human ccRCC xenograft model in mice was used to evaluate the effect of GABPA overexpression on in vivo tumorigenesis and metastasis. ccRCC cells were incubated with L-2-HG to analyze GABPA expression and methylation. We carried out immunohistochemistry on patient specimens and TCGA dataset analyses to assess the effect of GABPA on ccRCC survival.

Results

GABPA depletion, although inhibiting telomerase expression, robustly enhanced proliferation, invasion and stemness of ccRCC cells, whereas GABPA overexpression exhibited opposite effects, strongly inhibiting in vivo metastasis and carcinogenesis. TGFBR2 was identified as the GABPA target gene through which GABPA governed the TGFβ signaling to dictate ccRCC phenotypes. GABPA and TGFBR2 phenocopies each other in ccRCC cells. Higher GABPA or TGFBR2 expression predicted longer survival in patients with ccRCC. Incubation of ccRCC cells with L-2-HG mimics GABPA-knockdown-mediated phenotypic alterations. L-2-HG silenced the expression of GABPA in ccRCC cells by increasing its methylation.

Conclusions

GABPA acts as a tumor suppressor by stimulating TGFBR2 expression and TGFβ signaling, while L-2-HG epigenetically inhibits GABPA expression, disrupting the GABPA-TGFβ loop to drive ccRCC aggressiveness. These results exemplify how oncometabolites erase tumor suppressive function for cancer development/progression. Restoring GABPA expression using DNA methylation inhibitors or other approaches, rather than targeting it, may be a novel strategy for ccRCC therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02382-6.

DnaJC7 in Amyotrophic Lateral Sclerosis

Protein misfolding is a common basis of many neurodegenerative diseases including amyotrophic lateral sclerosis (ALS). Misfolded proteins, such as TDP-43, FUS, Matrin3, and SOD1, mislocalize and form the hallmark cytoplasmic and nuclear inclusions in neurons of ALS patients. Cellular protein quality control prevents protein misfolding under normal conditions and, particularly, when cells experience protein folding stress due to the fact of increased levels of reactive oxygen species, genetic mutations, or aging. Molecular chaperones can prevent protein misfolding, refold misfolded proteins, or triage misfolded proteins for degradation by the ubiquitin–proteasome system or autophagy. DnaJC7 is an evolutionarily conserved molecular chaperone that contains both a J-domain for the interaction with Hsp70s and tetratricopeptide domains for interaction with Hsp90, thus joining these two major chaperones’ machines. Genetic analyses reveal that pathogenic variants in the gene encoding DnaJC7 cause familial and sporadic ALS. Yet, the underlying ALS-associated molecular pathophysiology and many basic features of DnaJC7 function remain largely unexplored. Here, we review aspects of DnaJC7 expression, interaction, and function to propose a loss-of-function mechanism by which pathogenic variants in DNAJC7 contribute to defects in DnaJC7-mediated chaperoning that might ultimately contribute to neurodegeneration in ALS.

Progesterone Inhibits the Establishment of Activation-Associated Chromatin During TH1 Differentiation

TH1-mediated diseases such as multiple sclerosis (MS) and rheumatoid arthritis (RA) improve during pregnancy, coinciding with increasing levels of the pregnancy hormone progesterone (P4), highlighting P4 as a potential mediator of this immunomodulation. Here, we performed detailed characterization of how P4 affects the chromatin and transcriptomic landscape during early human TH1 differentiation, utilizing both ATAC-seq and RNA-seq. Time series analysis of the earlier events (0.5-24 hrs) during TH1 differentiation revealed that P4 counteracted many of the changes induced during normal differentiation, mainly by downregulating key regulatory genes and their upstream transcription factors (TFs) involved in the initial T-cell activation. Members of the AP-1 complex such as FOSL1, FOSL2, JUN and JUNB were particularly affected, in both in promoters and in distal regulatory elements. Moreover, the changes induced by P4 were significantly enriched for disease-associated changes related to both MS and RA, revealing several shared upstream TFs, where again JUN was highlighted to be of central importance. Our findings support an immune regulatory role for P4 during pregnancy by impeding T-cell activation, a crucial checkpoint during pregnancy and in T-cell mediated diseases, and a central event prior to T-cell lineage commitment. Indeed, P4 is emerging as a likely candidate involved in disease modulation during pregnancy and further studies evaluating P4 as a potential treatment option are needed.

Dynamic regulatory networks of T cell trajectory dissect transcriptional control of T cell state transition

T cells exhibit heterogeneous functional states, which correlate with responsiveness to immune checkpoint blockade and prognosis of tumor patients. However, the molecular regulatory mechanisms underlying the dynamic process of T cell state transition remain largely unknown. Based on single-cell transcriptome data of T cells in non-small cell lung cancer, we combined cell states and pseudo-times to propose a pipeline to construct dynamic regulatory networks for dissecting the process of T cell dysfunction. Candidate regulators at different stages were revealed in the process of tumor-infiltrating T cell dysfunction. Through comparing dynamic networks across the T cell state transition, we revealed frequent regulatory interaction rewiring and further refined critical regulators mediating each state transition. Several known regulators were identified, including TCF7, EOMES, ID2, and TOX. Notably, one of the critical regulators, TSC22D3, was frequently identified in the state transitions from the intermediate state to the pre-dysfunction and dysfunction state, exerting diverse roles in each state transition by regulatory interaction rewiring. Moreover, higher expression of TSC22D3 was associated with the clinical outcome of tumor patients. Our study embedded transcription factors (TFs) within the temporal dynamic networks, providing a comprehensive view of dynamic regulatory mechanisms controlling the process of T cell state transition.

Unraveling the hCoV-19 Informational Architecture

The hCoV-19 virus is continuously evolving to highly infectious and lethal variants. There is a latent risk that current vaccines will not be effective over these novel variants. This entails comprehending the genome-wide viral information to unveil mutagenic mechanisms of hCoV-19. To date, this virus is studied as a collection of non-related variants, making it challenging to forecast hotspots and their upcoming effects. In this work, we explore genome-wide information to disentangle informational mechanisms that lead to insights into viral mutagenicity. Towards this aim, we modeled informational compartments based on a topic-free-alignment workflow. These compartments illustrate that hCoV-19 has a complex informational architecture that addresses high-level virus phenomena, i.e., mutagenicity. This new framework represents the first step towards identifying the virus mutagenicity leading to the development of all-variants-effective vaccines.

Co-evolution of tumor and immune cells during progression of multiple myeloma

Multiple myeloma (MM) is characterized by the uncontrolled proliferation of plasma cells. Despite recent treatment advances, it is still incurable as disease progression is not fully understood. To investigate MM and its immune environment, we apply single cell RNA and linked-read whole genome sequencing to profile 29 longitudinal samples at different disease stages from 14 patients. Here, we collect 17,267 plasma cells and 57,719 immune cells, discovering patient-specific plasma cell profiles and immune cell expression changes. Patients with the same genetic alterations tend to have both plasma cells and immune cells clustered together. By integrating bulk genomics and single cell mapping, we track plasma cell subpopulations across disease stages and find three patterns: stability (from precancer to diagnosis), and gain or loss (from diagnosis to relapse). In multiple patients, we detect “B cell-featured” plasma cell subpopulations that cluster closely with B cells, implicating their cell of origin. We validate AP-1 complex differential expression (JUN and FOS) in plasma cell subpopulations using CyTOF-based protein assays, and integrated analysis of single-cell RNA and CyTOF data reveals AP-1 downstream targets (IL6 and IL1B) potentially leading to inflammation regulation. Our work represents a longitudinal investigation for tumor and microenvironment during MM progression and paves the way for expanding treatment options.

Clonal evolution in multiple myeloma (MM) needs to be understood in both the tumor and its microenvironment. Here the authors perform single-cell multi-omics profiling of samples from MM patients at different stages, finding transitions in the immune cell composition throughout progression.

Aging and pathological aging signatures of the brain: through the focusing lens of SIRT6

Brain-specific SIRT6-KO mice present increased DNA damage, learning impairments, and neurodegenerative phenotypes, placing SIRT6 as a key protein in preventing neurodegeneration. In the aging brain, SIRT6 levels/activity decline, which is accentuated in Alzheimer's patients. To understand SIRT6 roles in transcript pattern changes, we analyzed transcriptomes of young WT, old WT and young SIRT6-KO mice brains, and found changes in gene expression related to healthy and pathological aging. In addition, we traced these differences in human and mouse samples of Alzheimer's and Parkinson's diseases, healthy aging and calorie restriction (CR). Our results define four gene expression categories that change with age in a pathological or non-pathological manner, which are either reversed or not by CR. We found that each of these gene expression categories is associated with specific transcription factors, thus serving as potential candidates for their category-specific regulation. One of these candidates is YY1, which we found to act together with SIRT6 regulating specific processes. We thus argue that SIRT6 has a pivotal role in preventing age-related transcriptional changes in brains. Therefore, reduced SIRT6 activity may drive pathological age-related gene expression signatures in the brain.