scholarly journals A systems genetics approach reveals PbrNSC as a regulator of lignin and cellulose biosynthesis in stone cells of pear fruit

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Runze Wang ◽  
Yongsong Xue ◽  
Jing Fan ◽  
Jia-Long Yao ◽  
Mengfan Qin ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Target Genes ◽  
Cell Formation ◽  
Systems Genetics ◽  
Pyrus Pyrifolia ◽  
Rna Seq ◽  
Pear Fruit ◽  
Stone Cell ◽  
Wide Range ◽  
Gene Regulatory

Abstract Background Stone cells in fruits of pear (Pyrus pyrifolia) negatively influence fruit quality because their lignified cell walls impart a coarse and granular texture to the fruit flesh. Results We generate RNA-seq data from the developing fruits of 206 pear cultivars with a wide range of stone cell contents and use a systems genetics approach to integrate co-expression networks and expression quantitative trait loci (eQTLs) to characterize the regulatory mechanisms controlling lignocellulose formation in the stone cells of pear fruits. Our data with a total of 35,897 expressed genes and 974,404 SNPs support the identification of seven stone cell formation modules and the detection of 139,515 eQTLs for 3229 genes in these modules. Focusing on regulatory factors and using a co-expression network comprising 39 structural genes, we identify PbrNSC as a candidate regulator of stone cell formation. We then verify the function of PbrNSC in regulating lignocellulose formation using both pear fruit and Arabidopsis plants and further show that PbrNSC can transcriptionally activate multiple target genes involved in secondary cell wall formation. Conclusions This study generates a large resource for studying stone cell formation and provides insights into gene regulatory networks controlling the formation of stone cell and lignocellulose.

scholarly journals ISMARA: Completely automated inference of gene regulatory networks from high-throughput data

2017 ◽  
Author(s):  
Mikhail Pachkov ◽  
Piotr J Balwierz ◽  
Phil Arnold ◽  
Andreas J Gruber ◽  
Mihaela Zavolan ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Throughput ◽  
Regulatory Networks ◽  
Target Genes ◽  
Chromatin State ◽  
Response Analysis ◽  
Rna Seq ◽  
High Throughput Data ◽  
Micro Rnas ◽  
Gene Regulatory

As the costs of high-throughput measurement technologies continue to fall, experimental approaches in biomedicine are increasingly data intensive and the advent of big data is justifiably seen as holding the promise to transform medicine. However, as data volumes mount, researchers increasingly realize that extracting concrete, reliable, and actionable biological predictions from high-throughput data can be very challenging. Our laboratory has pioneered a number of methods for inferring key gene regulatory interactions from high-throughput data. For example, we developed motif activity response analysis (MARA)[, which models genome-wide gene expression (RNA-Seq, or microarray) and chromatin state (ChIP-Seq) data in terms of comprehensive predictions of regulatory sites for hundreds of mammalian regulators (TFs and micro-RNAs). Using these models, MARA identifies the key regulators driving gene expression and chromatin state changes, the activities of these regulators across the input samples, their target genes, and the sites on the genome through which these regulators act. We recently completely automated MARA in an integrated web-server (ismara.unibas.ch) that allows researchers to analyze their own data by simply uploading RNA-Seq or ChIP-Seq datasets, and provides results in an integrated web interface as well as in downloadable flat form.

scholarly journals ISMARA: Completely automated inference of gene regulatory networks from high-throughput data

2017 ◽  
Author(s):  
Mikhail Pachkov ◽  
Piotr J Balwierz ◽  
Phil Arnold ◽  
Andreas J Gruber ◽  
Mihaela Zavolan ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Throughput ◽  
Regulatory Networks ◽  
Target Genes ◽  
Chromatin State ◽  
Response Analysis ◽  
Rna Seq ◽  
High Throughput Data ◽  
Micro Rnas ◽  
Gene Regulatory

As the costs of high-throughput measurement technologies continue to fall, experimental approaches in biomedicine are increasingly data intensive and the advent of big data is justifiably seen as holding the promise to transform medicine. However, as data volumes mount, researchers increasingly realize that extracting concrete, reliable, and actionable biological predictions from high-throughput data can be very challenging. Our laboratory has pioneered a number of methods for inferring key gene regulatory interactions from high-throughput data. For example, we developed motif activity response analysis (MARA)[, which models genome-wide gene expression (RNA-Seq, or microarray) and chromatin state (ChIP-Seq) data in terms of comprehensive predictions of regulatory sites for hundreds of mammalian regulators (TFs and micro-RNAs). Using these models, MARA identifies the key regulators driving gene expression and chromatin state changes, the activities of these regulators across the input samples, their target genes, and the sites on the genome through which these regulators act. We recently completely automated MARA in an integrated web-server (ismara.unibas.ch) that allows researchers to analyze their own data by simply uploading RNA-Seq or ChIP-Seq datasets, and provides results in an integrated web interface as well as in downloadable flat form.

scholarly journals Transcriptional circuitry atlas of genetic diverse unstimulated murine and human macrophages define disparity in population-wide innate immunity

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bharat Mishra ◽  
Mohammad Athar ◽  
M. Shahid Mukhtar
Keyword(s):  
Immune Responses ◽  
Gene Regulatory Networks ◽  
Racial Disparity ◽  
Regulatory Networks ◽  
Target Genes ◽  
Decisive Role ◽  
Rna Seq ◽  
Comprehensive Understanding ◽  
Regulatory Behavior ◽  
Gene Regulatory

AbstractMacrophages are ubiquitous custodians of tissues, which play decisive role in maintaining cellular homeostasis through regulatory immune responses. Within tissues, macrophage exhibit extremely heterogeneous population with varying functions orchestrated through regulatory response, which can be further exacerbated in diverse genetic backgrounds. Gene regulatory networks (GRNs) offer comprehensive understanding of cellular regulatory behavior by unfolding the transcription factors (TFs) and regulated target genes. RNA-Seq coupled with ATAC-Seq has revolutionized the regulome landscape influenced by gene expression modeling. Here, we employ an integrative multi-omics systems biology-based analysis and generated GRNs derived from the unstimulated bone marrow-derived macrophages of five inbred genetically defined murine strains, which are reported to be linked with most of the population-wide human genetic variants. Our probabilistic modeling of a basal hemostasis pan regulatory repertoire in diverse macrophages discovered 96 TFs targeting 6279 genes representing 468,291 interactions across five inbred murine strains. Subsequently, we identify core and distinctive GRN sub-networks in unstimulated macrophages to describe the system-wide conservation and dissimilarities, respectively across five murine strains. Our study concludes that discrepancies in unstimulated macrophage-specific regulatory networks not only drives the basal functional plasticity within genetic backgrounds, additionally aid in understanding the complexity of racial disparity among the human population during stress.

scholarly journals EPEN-21. IMPAIRED NEURONAL-GLIAL FATE SPECIFICATION IN PEDIATRIC EPENDYMOMA REVEALED BY SINGLE-CELL RNA-SEQ

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii311-iii312
Author(s):  
Bernhard Englinger ◽  
Johannes Gojo ◽  
Li Jiang ◽  
Jens M Hübner ◽  
McKenzie L Shaw ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Single Cell ◽  
Regulatory Networks ◽  
Target Genes ◽  
Target Identification ◽  
Rna Seq ◽  
Cell Models ◽  
Pediatric Ependymoma ◽  
Glial Fate ◽  
Anatomic Locations

Abstract Ependymoma represents a heterogeneous disease affecting the entire neuraxis. Extensive molecular profiling efforts have identified molecular ependymoma subgroups based on DNA methylation. However, the intratumoral heterogeneity and developmental origins of these groups are only partially understood, and effective treatments are still lacking for about 50% of patients with high-risk tumors. We interrogated the cellular architecture of ependymoma using single cell/nucleus RNA-sequencing to analyze 24 tumor specimens across major molecular subgroups and anatomic locations. We additionally analyzed ten patient-derived ependymoma cell models and two patient-derived xenografts (PDXs). Interestingly, we identified an analogous cellular hierarchy across all ependymoma groups, originating from undifferentiated neural stem cell-like populations towards different degrees of impaired differentiation states comprising neuronal precursor-like, astro-glial-like, and ependymal-like tumor cells. While prognostically favorable ependymoma groups predominantly harbored differentiated cell populations, aggressive groups were enriched for undifferentiated subpopulations. Projection of transcriptomic signatures onto an independent bulk RNA-seq cohort stratified patient survival even within known molecular groups, thus refining the prognostic power of DNA methylation-based profiling. Furthermore, we identified novel potentially druggable targets including IGF- and FGF-signaling within poorly prognostic transcriptional programs. Ependymoma-derived cell models/PDXs widely recapitulated the transcriptional programs identified within fresh tumors and are leveraged to validate identified target genes in functional follow-up analyses. Taken together, our analyses reveal a developmental hierarchy and transcriptomic context underlying the biologically and clinically distinct behavior of ependymoma groups. The newly characterized cellular states and underlying regulatory networks could serve as basis for future therapeutic target identification and reveal biomarkers for clinical trials.

scholarly journals Inferring gene regulatory networks from single-cell RNA-seq temporal snapshot data requires higher-order moments

Patterns ◽  
2021 ◽  
Vol 2 (9) ◽  
pp. 100332
Author(s):  
N. Alexia Raharinirina ◽  
Felix Peppert ◽  
Max von Kleist ◽  
Christof Schütte ◽  
Vikram Sunkara
Keyword(s):  
Single Cell ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Higher Order ◽  
Rna Seq ◽  
Higher Order Moments ◽  
Gene Regulatory

scholarly journals Ultrabithorax Is a Micromanager of Hindwing Identity in Butterflies and Moths

2021 ◽  
Vol 9 ◽  
Author(s):  
Amruta Tendolkar ◽  
Aaron F. Pomerantz ◽  
Christa Heryanto ◽  
Paul D. Shirk ◽  
Nipam H. Patel ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Targeted Mutagenesis ◽  
Junonia Coenia ◽  
Wing Venation ◽  
Loss Of Function ◽  
Color Patterns ◽  
Wide Range ◽  
Range Of Functions ◽  
Gene Regulatory ◽  
Pyralid Moth

The forewings and hindwings of butterflies and moths (Lepidoptera) are differentiated from each other, with segment-specific morphologies and color patterns that mediate a wide range of functions in flight, signaling, and protection. The Hox gene Ultrabithorax (Ubx) is a master selector gene that differentiates metathoracic from mesothoracic identities across winged insects, and previous work has shown this role extends to at least some of the color patterns from the butterfly hindwing. Here we used CRISPR targeted mutagenesis to generate Ubx loss-of-function somatic mutations in two nymphalid butterflies (Junonia coenia, Vanessa cardui) and a pyralid moth (Plodia interpunctella). The resulting mosaic clones yielded hindwing-to-forewing transformations, showing Ubx is necessary for specifying many aspects of hindwing-specific identities, including scale morphologies, color patterns, and wing venation and structure. These homeotic phenotypes showed cell-autonomous, sharp transitions between mutant and non-mutant scales, except for clones that encroached into the border ocelli (eyespots) and resulted in composite and non-autonomous effects on eyespot ring determination. In the pyralid moth, homeotic clones converted the folding and depigmented hindwing into rigid and pigmented composites, affected the wing-coupling frenulum, and induced ectopic scent-scales in male androconia. These data confirm Ubx is a master selector of lepidopteran hindwing identity and suggest it acts on many gene regulatory networks involved in wing development and patterning.

scholarly journals Characterization of rare spindle and root cell transcriptional profiles in the stria vascularis of the adult mouse cochlea

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Shoujun Gu ◽  
Rafal Olszewski ◽  
Ian Taukulis ◽  
Zheng Wei ◽  
Daniel Martin ◽  
...  
Keyword(s):  
Hearing Loss ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Adult Mouse ◽  
Stria Vascularis ◽  
Cell Types ◽  
Rna Seq ◽  
Root Cells ◽  
Transcriptional Profiles ◽  
Gene Regulatory

Abstract The stria vascularis (SV) in the cochlea generates and maintains the endocochlear potential, thereby playing a pivotal role in normal hearing. Knowing transcriptional profiles and gene regulatory networks of SV cell types establishes a basis for studying the mechanism underlying SV-related hearing loss. While we have previously characterized the expression profiles of major SV cell types in the adult mouse, transcriptional profiles of rare SV cell types remained elusive due to the limitation of cell capture in single-cell RNA-Seq. The role of these rare cell types in the homeostatic function of the adult SV remain largely undefined. In this study, we performed single-nucleus RNA-Seq on the adult mouse SV in conjunction with sample preservation treatments during the isolation steps. We distinguish rare SV cell types, including spindle cells and root cells, from other cell types, and characterize their transcriptional profiles. Furthermore, we also identify and validate novel specific markers for these rare SV cell types. Finally, we identify homeostatic gene regulatory networks within spindle and root cells, establishing a basis for understanding the functional roles of these cells in hearing. These novel findings will provide new insights for future work in SV-related hearing loss and hearing fluctuation.

scholarly journals Identifying genetic modulators of the connectivity between transcription factors and their transcriptional targets

2016 ◽  
Vol 113 (13) ◽  
pp. E1835-E1843 ◽  
Author(s):  
Mina Fazlollahi ◽  
Ivor Muroff ◽  
Eunjee Lee ◽  
Helen C. Causton ◽  
Harmen J. Bussemaker
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Nonsynonymous Mutation ◽  
Gene Regulatory ◽  
Genetic Modulators

Regulation of gene expression by transcription factors (TFs) is highly dependent on genetic background and interactions with cofactors. Identifying specific context factors is a major challenge that requires new approaches. Here we show that exploiting natural variation is a potent strategy for probing functional interactions within gene regulatory networks. We developed an algorithm to identify genetic polymorphisms that modulate the regulatory connectivity between specific transcription factors and their target genes in vivo. As a proof of principle, we mapped connectivity quantitative trait loci (cQTLs) using parallel genotype and gene expression data for segregants from a cross between two strains of the yeast Saccharomyces cerevisiae. We identified a nonsynonymous mutation in the DIG2 gene as a cQTL for the transcription factor Ste12p and confirmed this prediction empirically. We also identified three polymorphisms in TAF13 as putative modulators of regulation by Gcn4p. Our method has potential for revealing how genetic differences among individuals influence gene regulatory networks in any organism for which gene expression and genotype data are available along with information on binding preferences for transcription factors.

scholarly journals NKX2-5 mutations causative for congenital heart disease retain functionality and are directed to hundreds of targets

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Romaric Bouveret ◽  
Ashley J Waardenberg ◽  
Nicole Schonrock ◽  
Mirana Ramialison ◽  
Tram Doan ◽  
...  
Keyword(s):  
Congenital Heart Disease ◽  
Heart Disease ◽  
Regulatory Networks ◽  
Congenital Heart ◽  
Target Genes ◽  
Loss Of Function ◽  
Wild Type ◽  
Interaction Domain ◽  
Ets Proteins ◽  
Gene Regulatory

We take a functional genomics approach to congenital heart disease mechanism. We used DamID to establish a robust set of target genes for NKX2-5 wild type and disease associated NKX2-5 mutations to model loss-of-function in gene regulatory networks. NKX2-5 mutants, including those with a crippled homeodomain, bound hundreds of targets including NKX2-5 wild type targets and a unique set of "off-targets", and retained partial functionality. NKXΔHD, which lacks the homeodomain completely, could heterodimerize with NKX2-5 wild type and its cofactors, including E26 transformation-specific (ETS) family members, through a tyrosine-rich homophilic interaction domain (YRD). Off-targets of NKX2-5 mutants, but not those of an NKX2-5 YRD mutant, showed overrepresentation of ETS binding sites and were occupied by ETS proteins, as determined by DamID. Analysis of kernel transcription factor and ETS targets show that ETS proteins are highly embedded within the cardiac gene regulatory network. Our study reveals binding and activities of NKX2-5 mutations on WT target and off-targets, guided by interactions with their normal cardiac and general cofactors, and suggest a novel type of gain-of-function in congenital heart disease.

scholarly journals AGENT: the Arabidopsis Gene Regulatory Network Tool for Exploring and Analyzing GRNs

2021 ◽  
Author(s):  
Vincent Lau ◽  
Rachel Woo ◽  
Bruno Pereira ◽  
Asher Pasha ◽  
Eddi Esteban ◽  
...  
Keyword(s):  
Gene Regulatory Networks ◽  
Gene Network ◽  
Regulatory Networks ◽  
Target Genes ◽  
Ad Hoc ◽  
Arabidopsis Gene ◽  
Nitrate Signaling ◽  
Multi Level ◽  
Gene Regulatory

AbstractGene regulatory networks (GRNs) are complex networks that capture multi-level regulatory events between one or more regulatory macromolecules, such as transcription factors (TFs), and their target genes. Advancements in screening technologies such as enhanced yeast-one-hybrid screens have allowed for high throughput determination of GRNs. However, visualization of GRNs in Arabidopsis has been limited to ad hoc networks and are not interactive. Here, we describe the Arabidopsis GEne Network Tool (AGENT) that houses curated GRNs and provides tools to visualize and explore them. AGENT features include expression overlays, subnetwork motif scanning, and network analysis. We show how to use AGENT’s multiple built-in tools to identify key genes that are involved in flowering and seed development along with identifying temporal multi-TF control of a key transporter in nitrate signaling. AGENT can be accessed at https://bar.utoronto.ca/AGENT.

Sign in / Sign up

Export Citation Format

Share Document