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Article ; Online: The landscape of SETBP1 gene expression and transcription factor activity across human tissues.

Whitlock, Jordan H / Wilk, Elizabeth J / Howton, Timothy C / Clark, Amanda D / Lasseigne, Brittany N

2024 Volume 19, Issue 1, Page(s) e0296328

Abstract: The SET binding protein 1 (SETBP1) gene encodes a transcription factor (TF) involved in various cellular processes. Variants in SETBP1 can result in three different diseases determined by the introduction (germline vs. somatic) and location of the ... ...

Abstract	The SET binding protein 1 (SETBP1) gene encodes a transcription factor (TF) involved in various cellular processes. Variants in SETBP1 can result in three different diseases determined by the introduction (germline vs. somatic) and location of the variant. Germline variants cause the ultra-rare pediatric Schinzel Giedion Syndrome (SGS) and SETBP1 haploinsufficiency disorder (SETBP1-HD), characterized by severe multisystemic abnormalities with neurodegeneration or a less severe brain phenotype accompanied by hypotonia and strabismus, respectively. Somatic variants in SETBP1 are associated with hematological malignancies and cancer development in other tissues in adults. To better understand the tissue-specific mechanisms involving SETBP1, we analyzed publicly available RNA-sequencing (RNA-seq) data from the Genotype-Tissue Expression (GTEx) project. We found SETBP1 and its known target genes were widely expressed across 31 adult human tissues. K-means clustering identified three distinct expression patterns of SETBP1 targets across tissues. Functional enrichment analysis (FEA) of each cluster revealed gene sets related to transcriptional regulation, DNA binding, and mitochondrial function. TF activity analysis of SETBP1 and its target TFs revealed tissue-specific TF activity, underscoring the role of tissue context-driven regulation and suggesting its impact in SETBP1-associated disease. In addition to uncovering tissue-specific molecular signatures of SETBP1 expression and TF activity, we provide a Shiny web application to facilitate exploring TF activity across human tissues for 758 TFs. This study provides insight into the landscape of SETBP1 expression and TF activity across 31 non-diseased human tissues and reveals tissue-specific expression and activity of SETBP1 and its targets. In conjunction with the web application we constructed, our framework enables researchers to generate hypotheses related to the role tissue backgrounds play with respect to gene expression and TF activity in different disease contexts.
MeSH term(s)	Humans ; Abnormalities, Multiple/genetics ; Carrier Proteins/genetics ; Carrier Proteins/metabolism ; Craniofacial Abnormalities/genetics ; Gene Expression ; Intellectual Disability/genetics ; Nuclear Proteins/genetics ; Nuclear Proteins/metabolism ; Transcription Factors/genetics ; Transcription Factors/metabolism
Chemical Substances	Carrier Proteins ; Nuclear Proteins ; SETBP1 protein, human ; Transcription Factors
Language	English
Publishing date	2024-01-02
Publishing country	United States
Document type	Journal Article
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0296328
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Long-read RNA sequencing identifies region- and sex-specific C57BL/6J mouse brain mRNA isoform expression and usage.

Jones, Emma F / Howton, Timothy C / Flanary, Victoria L / Clark, Amanda D / Lasseigne, Brittany N

bioRxiv : the preprint server for biology

2024

Abstract: Alternative splicing (AS) contributes to the biological heterogeneity between species, sexes, tissues, and cell types. Many diseases are either caused by alterations in AS or by alterations to AS. Therefore, measuring AS accurately and efficiently is ... ...

Abstract	Alternative splicing (AS) contributes to the biological heterogeneity between species, sexes, tissues, and cell types. Many diseases are either caused by alterations in AS or by alterations to AS. Therefore, measuring AS accurately and efficiently is critical for assessing molecular phenotypes, including those associated with disease. Long-read sequencing enables more accurate quantification of differentially spliced isoform expression than short-read sequencing approaches, and third-generation platforms facilitate high-throughput experiments. To assess differences in AS across the cerebellum, cortex, hippocampus, and striatum by sex, we generated and analyzed Oxford Nanopore Technologies (ONT) long-read RNA sequencing (lrRNA-Seq) C57BL/6J mouse brain cDNA libraries. From >85 million reads that passed quality control metrics, we calculated differential gene expression (DGE), differential transcript expression (DTE), and differential transcript usage (DTU) across brain regions and by sex. We found significant DGE, DTE, and DTU across brain regions and that the cerebellum had the most differences compared to the other three regions. Additionally, we found region-specific differential splicing between sexes, with the most sex differences in DTU in the cortex and no DTU in the hippocampus. We also report on two distinct patterns of sex DTU we observed, sex-divergent and sex-specific, that could potentially help explain sex differences in the prevalence and prognosis of various neurological and psychiatric disorders in future studies. Finally, we built a Shiny web application for researchers to explore the data further. Our study provides a resource for the community; it underscores the importance of AS in biological heterogeneity and the utility of long-read sequencing to better understand AS in the brain.
Language	English
Publishing date	2024-01-11
Publishing country	United States
Document type	Preprint
DOI	10.1101/2024.01.11.575219
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Article: The landscape of

Whitlock, Jordan H / Wilk, Elizabeth J / Howton, Timothy C / Clark, Amanda D / Lasseigne, Brittany N

bioRxiv : the preprint server for biology

2023

Abstract: Background: The SET binding protein 1 (: Results: To better understand the tissue-specific mechanisms involving : Conclusions: This study provides insight into the landscape ... ...

Abstract	Background: The SET binding protein 1 ( Results: To better understand the tissue-specific mechanisms involving Conclusions: This study provides insight into the landscape of
Language	English
Publishing date	2023-10-14
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.08.08.551337
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Article ; Online: Computational Advancements in Cancer Combination Therapy Prediction.

Flanary, Victoria L / Fisher, Jennifer L / Wilk, Elizabeth J / Howton, Timothy C / Lasseigne, Brittany N

JCO precision oncology

2023 Volume 7, Page(s) e2300261

Abstract: Given the high attrition rate of de novo drug discovery and limited efficacy of single-agent therapies in cancer treatment, combination therapy prediction through in silico drug repurposing has risen as a time- and cost-effective alternative for ... ...

Abstract	Given the high attrition rate of de novo drug discovery and limited efficacy of single-agent therapies in cancer treatment, combination therapy prediction through in silico drug repurposing has risen as a time- and cost-effective alternative for identifying novel and potentially efficacious therapies for cancer. The purpose of this review is to provide an introduction to computational methods for cancer combination therapy prediction and to summarize recent studies that implement each of these methods. A systematic search of the PubMed database was performed, focusing on studies published within the past 10 years. Our search included reviews and articles of ongoing and retrospective studies. We prioritized articles with findings that suggest considerations for improving combination therapy prediction methods over providing a meta-analysis of all currently available cancer combination therapy prediction methods. Computational methods used for drug combination therapy prediction in cancer research include networks, regression-based machine learning, classifier machine learning models, and deep learning approaches. Each method class has its own advantages and disadvantages, so careful consideration is needed to determine the most suitable class when designing a combination therapy prediction method. Future directions to improve current combination therapy prediction technology include incorporation of disease pathobiology, drug characteristics, patient multiomics data, and drug-drug interactions to determine maximally efficacious and tolerable drug regimens for cancer. As computational methods improve in their capability to integrate patient, drug, and disease data, more comprehensive models can be developed to more accurately predict safe and efficacious combination drug therapies for cancer and other complex diseases.
MeSH term(s)	Humans ; Drug Discovery ; Machine Learning ; Meta-Analysis as Topic ; Neoplasms/drug therapy ; Retrospective Studies
Language	English
Publishing date	2023-10-12
Publishing country	United States
Document type	Journal Article
ISSN	2473-4284
ISSN (online)	2473-4284
DOI	10.1200/PO.23.00261
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Article: Altered Glia-Neuron Communication in Alzheimer's Disease Affects WNT, p53, and NFkB Signaling Determined by snRNA-seq.

Soelter, Tabea M / Howton, Timothy C / Clark, Amanda D / Oza, Vishal H / Lasseigne, Brittany N

bioRxiv : the preprint server for biology

2023

Abstract: Background: Alzheimer's disease is the most common cause of dementia and is characterized by amyloid-β plaques, tau neurofibrillary tangles, and neuronal loss. Although neuronal loss is a primary hallmark of Alzheimer's disease, it is known that non- ... ...

Abstract	Background: Alzheimer's disease is the most common cause of dementia and is characterized by amyloid-β plaques, tau neurofibrillary tangles, and neuronal loss. Although neuronal loss is a primary hallmark of Alzheimer's disease, it is known that non-neuronal cell populations are ultimately responsible for maintaining brain homeostasis and neuronal health through neuron-glia and glial cell crosstalk. Many signaling pathways have been proposed to be dysregulated in Alzheimer's disease, including WNT, TGFβ, p53, mTOR, NFkB, and Pi3k/Akt signaling. Here, we predict altered cell-cell communication between glia and neurons. Methods: Using public snRNA-sequencing data generated from postmortem human prefrontal cortex, we predicted altered cell-cell communication between glia (astrocytes, microglia, oligodendrocytes, and oligodendrocyte progenitor cells) and neurons (excitatory and inhibitory). We confirmed interactions in an independent orthogonal dataset. We determined cell-type-specificity using Jaccard Similarity Index and investigated the downstream effects of altered interactions in inhibitory neurons through gene expression and transcription factor activity analyses of signaling mediators. Finally, we determined changes in pathway activity in inhibitory neurons. Results: Cell-cell communication between glia and neurons is altered in Alzheimer's disease in a cell-type-specific manner. As expected, ligands are more cell-type-specific than receptors and targets. We validated 51 ligand-receptor pairs in an independent dataset that included two known Alzheimer's disease risk genes: Conclusions: Cell-cell communication between glia and neurons in Alzheimer's disease is altered in a cell-type-specific manner involving Alzheimer's disease risk genes. Signaling mediators had altered transcription factor activity suggesting altered glia-neuron interactions may dysregulate signaling pathways including WNT, p53, and NFkB in inhibitory neurons.
Language	English
Publishing date	2023-12-01
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.11.29.569304
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Article ; Online: Cell-type-specific gene expression and regulation in the cerebral cortex and kidney of atypical Setbp1

Whitlock, Jordan H / Soelter, Tabea M / Howton, Timothy C / Wilk, Elizabeth J / Oza, Vishal H / Lasseigne, Brittany N

Journal of cellular and molecular medicine

2023 Volume 27, Issue 22, Page(s) 3565–3577

Abstract: Schinzel Giedion Syndrome (SGS) is an ultra-rare autosomal dominant Mendelian disease presenting with abnormalities spanning multiple organ systems. The most notable phenotypes involve severe developmental delay, progressive brain atrophy, and drug- ... ...

Abstract	Schinzel Giedion Syndrome (SGS) is an ultra-rare autosomal dominant Mendelian disease presenting with abnormalities spanning multiple organ systems. The most notable phenotypes involve severe developmental delay, progressive brain atrophy, and drug-resistant seizures. SGS is caused by spontaneous variants in SETBP1, which encodes for the epigenetic hub SETBP1 transcription factor (TF). SETBP1 variants causing classical SGS cluster at the degron, disrupting SETBP1 protein degradation and resulting in toxic accumulation, while those located outside cause milder atypical SGS. Due to the multisystem phenotype, we evaluated gene expression and regulatory programs altered in atypical SGS by snRNA-seq of the cerebral cortex and kidney of Setbp1
MeSH term(s)	Humans ; Animals ; Mice ; Abnormalities, Multiple/genetics ; Abnormalities, Multiple/pathology ; Kidney/pathology ; Cerebral Cortex/pathology ; Gene Expression
Language	English
Publishing date	2023-10-23
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2074559-X
ISSN	1582-4934 ; 1582-4934 ; 1582-1838
ISSN (online)	1582-4934
ISSN	1582-4934 ; 1582-1838
DOI	10.1111/jcmm.18001
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Signature reversion of three disease-associated gene signatures prioritizes cancer drug repurposing candidates.

Fisher, Jennifer L / Wilk, Elizabeth J / Oza, Vishal H / Gary, Sam E / Howton, Timothy C / Flanary, Victoria L / Clark, Amanda D / Hjelmeland, Anita B / Lasseigne, Brittany N

FEBS open bio

2024 Volume 14, Issue 5, Page(s) 803–830

Abstract: Drug repurposing is promising because approving a drug for a new indication requires fewer resources than approving a new drug. Signature reversion detects drug perturbations most inversely related to the disease-associated gene signature to identify ... ...

Abstract	Drug repurposing is promising because approving a drug for a new indication requires fewer resources than approving a new drug. Signature reversion detects drug perturbations most inversely related to the disease-associated gene signature to identify drugs that may reverse that signature. We assessed the performance and biological relevance of three approaches for constructing disease-associated gene signatures (i.e., limma, DESeq2, and MultiPLIER) and prioritized the resulting drug repurposing candidates for four low-survival human cancers. Our results were enriched for candidates that had been used in clinical trials or performed well in the PRISM drug screen. Additionally, we found that pamidronate and nimodipine, drugs predicted to be efficacious against the brain tumor glioblastoma (GBM), inhibited the growth of a GBM cell line and cells isolated from a patient-derived xenograft (PDX). Our results demonstrate that by applying multiple disease-associated gene signature methods, we prioritized several drug repurposing candidates for low-survival cancers.
MeSH term(s)	Drug Repositioning/methods ; Humans ; Antineoplastic Agents/pharmacology ; Animals ; Cell Line, Tumor ; Mice ; Glioblastoma/genetics ; Glioblastoma/drug therapy ; Glioblastoma/pathology ; Gene Expression Profiling ; Xenograft Model Antitumor Assays ; Gene Expression Regulation, Neoplastic/drug effects ; Brain Neoplasms/genetics ; Brain Neoplasms/drug therapy ; Brain Neoplasms/pathology ; Neoplasms/genetics ; Neoplasms/drug therapy ; Transcriptome/genetics ; Transcriptome/drug effects
Chemical Substances	Antineoplastic Agents
Language	English
Publishing date	2024-03-26
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ZDB-ID	2651702-4
ISSN	2211-5463 ; 2211-5463
ISSN (online)	2211-5463
ISSN	2211-5463
DOI	10.1002/2211-5463.13796
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Ten simple rules for using public biological data for your research.

Oza, Vishal H / Whitlock, Jordan H / Wilk, Elizabeth J / Uno-Antonison, Angelina / Wilk, Brandon / Gajapathy, Manavalan / Howton, Timothy C / Trull, Austyn / Ianov, Lara / Worthey, Elizabeth A / Lasseigne, Brittany N

PLoS computational biology

2023 Volume 19, Issue 1, Page(s) e1010749

Abstract: With an increasing amount of biological data available publicly, there is a need for a guide on how to successfully download and use this data. The 10 simple rules for using public biological data are: (1) use public data purposefully in your research; ( ... ...

Abstract	With an increasing amount of biological data available publicly, there is a need for a guide on how to successfully download and use this data. The 10 simple rules for using public biological data are: (1) use public data purposefully in your research; (2) evaluate data for your use case; (3) check data reuse requirements and embargoes; (4) be aware of ethics for data reuse; (5) plan for data storage and compute requirements; (6) know what you are downloading; (7) download programmatically and verify integrity; (8) properly cite data; (9) make reprocessed data and models Findable, Accessible, Interoperable, and Reusable (FAIR) and share; and (10) make pipelines and code FAIR and share. These rules are intended as a guide for researchers wanting to make use of available data and to increase data reuse and reproducibility.
MeSH term(s)	Reproducibility of Results ; Information Storage and Retrieval
Language	English
Publishing date	2023-01-05
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1010749
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Article ; Online: Prioritized polycystic kidney disease drug targets and repurposing candidates from pre-cystic and cystic mouse Pkd2 model gene expression reversion.

Wilk, Elizabeth J / Howton, Timothy C / Fisher, Jennifer L / Oza, Vishal H / Brownlee, Ryan T / McPherson, Kasi C / Cleary, Hannah L / Yoder, Bradley K / George, James F / Mrug, Michal / Lasseigne, Brittany N

Molecular medicine (Cambridge, Mass.)

2023 Volume 29, Issue 1, Page(s) 67

Abstract: Background: Autosomal dominant polycystic kidney disease (ADPKD) is one of the most prevalent monogenic human diseases. It is mostly caused by pathogenic variants in PKD1 or PKD2 genes that encode interacting transmembrane proteins polycystin-1 (PC1) ... ...

Abstract	Background: Autosomal dominant polycystic kidney disease (ADPKD) is one of the most prevalent monogenic human diseases. It is mostly caused by pathogenic variants in PKD1 or PKD2 genes that encode interacting transmembrane proteins polycystin-1 (PC1) and polycystin-2 (PC2). Among many pathogenic processes described in ADPKD, those associated with cAMP signaling, inflammation, and metabolic reprogramming appear to regulate the disease manifestations. Tolvaptan, a vasopressin receptor-2 antagonist that regulates cAMP pathway, is the only FDA-approved ADPKD therapeutic. Tolvaptan reduces renal cyst growth and kidney function loss, but it is not tolerated by many patients and is associated with idiosyncratic liver toxicity. Therefore, additional therapeutic options for ADPKD treatment are needed. Methods: As drug repurposing of FDA-approved drug candidates can significantly decrease the time and cost associated with traditional drug discovery, we used the computational approach signature reversion to detect inversely related drug response gene expression signatures from the Library of Integrated Network-Based Cellular Signatures (LINCS) database and identified compounds predicted to reverse disease-associated transcriptomic signatures in three publicly available Pkd2 kidney transcriptomic data sets of mouse ADPKD models. We focused on a pre-cystic model for signature reversion, as it was less impacted by confounding secondary disease mechanisms in ADPKD, and then compared the resulting candidates' target differential expression in the two cystic mouse models. We further prioritized these drug candidates based on their known mechanism of action, FDA status, targets, and by functional enrichment analysis. Results: With this in-silico approach, we prioritized 29 unique drug targets differentially expressed in Pkd2 ADPKD cystic models and 16 prioritized drug repurposing candidates that target them, including bromocriptine and mirtazapine, which can be further tested in-vitro and in-vivo. Conclusion: Collectively, these results indicate drug targets and repurposing candidates that may effectively treat pre-cystic as well as cystic ADPKD.
MeSH term(s)	Animals ; Humans ; Mice ; Drug Repositioning ; Gene Expression ; Kidney/metabolism ; Polycystic Kidney Diseases/drug therapy ; Polycystic Kidney Diseases/genetics ; Polycystic Kidney Diseases/complications ; Polycystic Kidney, Autosomal Dominant/drug therapy ; Polycystic Kidney, Autosomal Dominant/genetics ; Tolvaptan/pharmacology ; Tolvaptan/therapeutic use ; TRPP Cation Channels/genetics ; TRPP Cation Channels/metabolism
Chemical Substances	Tolvaptan (21G72T1950) ; TRPP Cation Channels
Language	English
Publishing date	2023-05-22
Publishing country	England
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	1283676-x
ISSN	1528-3658 ; 1076-1551
ISSN (online)	1528-3658
ISSN	1076-1551
DOI	10.1186/s10020-023-00664-z
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Zs.A 4456: Show issues

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Jg. 1995 - 2021: Lesesall (2.OG)
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Article ; Online: Map of physical interactions between extracellular domains of Arabidopsis leucine-rich repeat receptor kinases.

Mott, G Adam / Smakowska-Luzan, Elwira / Pasha, Asher / Parys, Katarzyna / Howton, Timothy C / Neuhold, Jana / Lehner, Anita / Grünwald, Karin / Stolt-Bergner, Peggy / Provart, Nicholas J / Mukhtar, M Shahid / Desveaux, Darrell / Guttman, David S / Belkhadir, Youssef

Scientific data

2019 Volume 6, Page(s) 190025

Abstract: Plants use surface receptors to perceive information about many aspects of their local environment. These receptors physically interact to form both steady state and signalling competent complexes. The signalling events downstream of receptor activation ... ...

Abstract	Plants use surface receptors to perceive information about many aspects of their local environment. These receptors physically interact to form both steady state and signalling competent complexes. The signalling events downstream of receptor activation impact both plant developmental and immune responses. Here, we present a comprehensive study of the physical interactions between the extracellular domains of leucine-rich repeat receptor kinases (LRR-RKs) in Arabidopsis. Using a sensitized assay, we tested reciprocal interactions among 200 of the 225 Arabidopsis LRR-RKs for a total search space of 40,000 interactions. Applying a stringent statistical cut-off and requiring that interactions performed well in both bait-prey and prey-bait orientations resulted in a high-confidence set of 567 bidirectional interactions. Additionally, we identified a total of 2,586 unidirectional interactions, which passed our stringent statistical cut-off in only one orientation. These datasets will guide further investigation into the regulatory roles of LRR-RKs in plant developmental and immune signalling decisions.
MeSH term(s)	Arabidopsis Proteins/chemistry ; Protein Domains ; Protein Interaction Mapping/methods ; Protein Kinases/chemistry ; Protein Kinases/physiology ; Proteins
Chemical Substances	Arabidopsis Proteins ; Proteins ; leucine-rich repeat proteins ; Protein Kinases (EC 2.7.-)
Language	English
Publishing date	2019-02-26
Publishing country	England
Document type	Dataset ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2775191-0
ISSN	2052-4463 ; 2052-4463
ISSN (online)	2052-4463
ISSN	2052-4463
DOI	10.1038/sdata.2019.25
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