Identify Huntington’s disease associated genes based on restricted Boltzmann machine with RNA-seq data

ABSTRACTHuntington’s disease (HD) is a dominantly inherited neurodegenerative disorder caused by a trinucleotide expansion in exon 1 of the huntingtin (Htt) gene. Cell death in HD occurs primarily in striatal medium spiny neurons (MSNs), but the involvement of specific MSN subtypes and of other striatal cell types remains poorly understood. To gain insight into cell type-specific disease processes, we studied the nuclear transcriptomes of 4,524 cells from the striatum of a genetically precise knock-in mouse model of the HD mutation, HttQ175/+, and from wildtype controls. We used 14-15-month-old mice, a time point roughly equivalent to an early stage of symptomatic human disease. Cell type distributions indicated selective loss of D2 MSNs and increased microglia in aged HttQ175/+ mice. Thousands of differentially expressed genes were distributed across most striatal cell types, including transcriptional changes in glial populations that are not apparent from RNA-seq of bulk tissue. Reconstruction of cell typespecific transcriptional networks revealed a striking pattern of bidirectional dysregulation for many cell type-specific genes. Typically, these genes were repressed in their primary cell type, yet de-repressed in other striatal cell types. Integration with existing epigenomic and transcriptomic data suggest that partial loss-of-function of the Polycomb Repressive Complex 2 (PRC2) may underlie many of these transcriptional changes, leading to deficits in the maintenance of cell identity across virtually all cell types in the adult striatum.

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Investigating Antisense Transcription at the HTT Locus

KnE Life Sciences ◽

10.18502/kls.v7i1.10149 ◽

2022 ◽

Author(s):

Eugeny A. Elisaphenko ◽

Anastasia A. Malakhova

Keyword(s):

Huntington's Disease ◽

Huntington’S Disease ◽

Intracellular Trafficking ◽

Gene Expression Regulation ◽

Antisense Transcription ◽

Dependent Manner ◽

Rna Seq ◽

Antisense Transcripts ◽

Cell Processes ◽

Different Parts

Antisense transcription is an important mechanism of gene expression regulation. Antisense RNAs play a role in mRNA processing, translation and epigenetic modifications of DNA and histones in the locus of their origin, leading to gene silencing. HTT is a widely expressed gene, the mutation of which causes Huntington’s disease. The product of the gene plays an important role in many cell processes, such as intracellular trafficking, cell division, autophagy, and others. An antisense transcription has been found at the HTT 5’-region. The HTT-AS gene has been reported to affect HTT expression in a Dicer-dependent manner. In this study, we analyzed extensive data from RNA-seq experiments for antisense transcription at the HTT locus. Antisense transcripts corresponding to the HTT-AS gene were not found. However, we revealed a number of antisense transcripts in different parts of the locus that may take part in the regulation and functioning of the HTT gene. Keywords: antisense transcription, HTT-AS, HTTregulation, Huntington’s disease

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Mutant Huntingtin Affects Diabetes and Alzheimer’s Markers in Human and Cell Models of Huntington’s Disease

Cells ◽

10.3390/cells8090962 ◽

2019 ◽

Vol 8 (9) ◽

pp. 962 ◽

Cited By ~ 1

Author(s):

Gepoliano Chaves ◽

John Stanley ◽

Nader Pourmand

Keyword(s):

Huntington's Disease ◽

Huntington’S Disease ◽

Genome Wide Association Study ◽

Cell Model ◽

Statistical Significance ◽

Mutant Huntingtin ◽

Rna Seq ◽

Genome Wide ◽

A Genome ◽

Reliable Model

A higher incidence of diabetes was observed among family members of individuals affected by Huntington’s Disease with no follow-up studies investigating the genetic nature of the observation. Using a genome-wide association study (GWAS), RNA sequencing (RNA-Seq) analysis and western blotting of Rattus norvegicus and human, we were able to identify that the gene family of sortilin receptors was affected in Huntington’s Disease patients. We observed that less than 5% of SNPs were of statistical significance and that sortilins and HLA/MHC gene expression or SNPs were associated with mutant huntingtin (mHTT). These results suggest that ST14A cells derived from R. norvegicus are a reliable model of HD, since sortilins were identified through analysis of the transcriptome in these cells. These findings help highlight the genes involved in mechanisms targeted by diabetes drugs, such as glucose transporters as well as proteins controlling insulin release related to mHTT. To the best of our knowledge, this is the first GWAS using RNA-Seq data from both ST14A rat HD cell model and human Huntington’s Disease.

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A Systematic Review of Transcriptional Dysregulation in Huntington’s Disease Studied by RNA Sequencing

Frontiers in Genetics ◽

10.3389/fgene.2021.751033 ◽

2021 ◽

Vol 12 ◽

Author(s):

Bimala Malla ◽

Xuanzong Guo ◽

Gökçe Senger ◽

Zoi Chasapopoulou ◽

Ferah Yildirim

Keyword(s):

Gene Expression ◽

Systematic Review ◽

Huntington's Disease ◽

Huntington’S Disease ◽

Rna Sequencing ◽

Brain Regions ◽

Medium Spiny Neurons ◽

Rna Seq ◽

Transcriptional Dysregulation ◽

Spiny Neurons

Huntington’s disease (HD) is a chronic neurodegenerative disorder caused by an expansion of polyglutamine repeats in exon 1 of the Huntingtin gene. Transcriptional dysregulation accompanied by epigenetic alterations is an early and central disease mechanism in HD yet, the exact mechanisms and regulators, and their associated gene expression programs remain incompletely understood. This systematic review investigates genome-wide transcriptional studies that were conducted using RNA sequencing (RNA-seq) technology in HD patients and models. The review protocol was registered at the Open Science Framework (OSF). The biomedical literature and gene expression databases, PubMed and NCBI BioProject, Array Express, European Nucleotide Archive (ENA), European Genome-Phenome Archive (EGA), respectively, were searched using the defined terms specified in the protocol following the PRISMA guidelines. We conducted a complete literature and database search to retrieve all RNA-seq-based gene expression studies in HD published until August 2020, retrieving 288 articles and 237 datasets from PubMed and the databases, respectively. A total of 27 studies meeting the eligibility criteria were included in this review. Collectively, comparative analysis of the datasets revealed frequent genes that are consistently dysregulated in HD. In postmortem brains from HD patients, DNAJB1, HSPA1B and HSPB1 genes were commonly upregulated across all brain regions and cell types except for medium spiny neurons (MSNs) at symptomatic disease stage, and HSPH1 and SAT1 genes were altered in expression in all symptomatic brain datasets, indicating early and sustained changes in the expression of genes related to heat shock response as well as response to misfolded proteins. Specifically in indirect pathway medium spiny neurons (iMSNs), mitochondria related genes were among the top uniquely dysregulated genes. Interestingly, blood from HD patients showed commonly differentially expressed genes with a number of brain regions and cells, with the highest number of overlapping genes with MSNs and BA9 region at symptomatic stage. We also found the differential expression and predicted altered activity of a set of transcription factors and epigenetic regulators, including BCL6, EGR1, FOSL2 and CREBBP, HDAC1, KDM4C, respectively, which may underlie the observed transcriptional changes in HD. Altogether, our work provides a complete overview of the transcriptional studies in HD, and by data synthesis, reveals a number of common and unique gene expression and regulatory changes across different cell and tissue types in HD. These changes could elucidate new insights into molecular mechanisms of differential vulnerability in HD.Systematic Review Registration:https://osf.io/pm3wq

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Single-Nucleus RNA-Seq Reveals Dysregulation of Striatal Cell Identity Due to Huntington’s Disease Mutations

Journal of Neuroscience ◽

10.1523/jneurosci.2074-20.2021 ◽

2021 ◽

pp. JN-RM-2074-20

Author(s):

Sonia Malaiya ◽

Marcia Cortes-Gutierrez ◽

Brian R. Herb ◽

Sydney R. Coffey ◽

Samuel R. W. Legg ◽

...

Keyword(s):

Huntington's Disease ◽

Huntington’S Disease ◽

Rna Seq ◽

Cell Identity ◽

Disease Mutations ◽

Single Nucleus

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Ensemble Consensus-Guided Unsupervised Feature Selection to Identify Huntington’s Disease-Associated Genes

Genes ◽

10.3390/genes9070350 ◽

2018 ◽

Vol 9 (7) ◽

pp. 350 ◽

Cited By ~ 1

Author(s):

Xia Guo ◽

Xue Jiang ◽

Jing Xu ◽

Xiongwen Quan ◽

Min Wu ◽

...

Keyword(s):

Feature Selection ◽

Huntington's Disease ◽

Huntington’S Disease ◽

Differentially Expressed Gene ◽

Cell Junction ◽

Support Vector ◽

Unsupervised Feature Selection ◽

Gene Set ◽

Disease Associated Genes ◽

The Stability

Due to the complexity of the pathological mechanisms of neurodegenerative diseases, traditional differentially-expressed gene selection methods cannot detect disease-associated genes accurately. Recent studies have shown that consensus-guided unsupervised feature selection (CGUFS) performs well in feature selection for identifying disease-associated genes. Since the random initialization of the feature selection matrix in CGUFS results in instability of the final disease-associated gene set, for the purposes of this study we proposed an ensemble method based on CGUFS—namely, ensemble consensus-guided unsupervised feature selection (ECGUFS) in order to further improve the accuracy of disease-associated genes and the stability of feature gene sets. We also proposed a bagging integration strategy to integrate the results of CGUFS. Lastly, we conducted experiments with Huntington’s disease RNA sequencing (RNA-Seq) data and obtained the final feature gene set, where we detected 287 disease-associated genes. Enrichment analysis on these genes has shown that postsynaptic density and the postsynaptic membrane, synapse, and cell junction are all affected during the disease’s progression. However, ECGUFS greatly improved the accuracy of disease-associated gene prediction and the stability of the disease-associated gene set. We conducted a classification of samples with labels based on the linear support vector machine with 10-fold cross-validation. The average accuracy is 0.9, which suggests the effectiveness of the feature gene set.

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Huntington’s disease-specific mis-splicing captured by human-mouse intersect-RNA-seq unveils pathogenic effectors and reduced splicing factors

10.1101/2020.05.11.086017 ◽

2020 ◽

Author(s):

Ainara Elorza ◽

Yamile Márquez ◽

Jorge R. Cabrera ◽

José Luis Sánchez-Trincado ◽

María Santos-Galindo ◽

...

Keyword(s):

Neurodegenerative Diseases ◽

Huntington's Disease ◽

Huntington’S Disease ◽

Neuronal Loss ◽

Splicing Factors ◽

Post Mortem ◽

Rna Seq ◽

Protein Levels ◽

Wide Range ◽

Bona Fide

AbstractDeregulated alternative splicing has been implicated in a wide range of pathologies. Deep RNA-sequencing has revealed global mis-splicing signatures in multiple human diseases; however, for neurodegenerative diseases, these analyses are intrinsically hampered by neuronal loss and neuroinflammation in post-mortem brains. To infer splicing alterations relevant to Huntington’s disease (HD) pathogenesis, here we performed intersect-RNA-seq analyses of human post-mortem striatal tissue and of an early symptomatic mouse model in which neuronal loss and gliosis are not yet present. Together with a human/mouse parallel motif scan analysis, this approach allowed us to identify the shared mis-splicing signature triggered by the HD-causing mutation in both species and to infer upstream deregulated splicing factors. Moreover, we identified a plethora of downstream neurodegeneration-linked effector genes, whose aberrant splicing is associated with decreased protein levels in HD patients and mice. In summary, our intersect-RNA-seq approach unveiled the pathogenic contribution of mis-splicing to HD and could be readily applied to other neurodegenerative diseases for which bona fide animal models are available.

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