Synaptic polarity and sign-balance prediction using gene expression data in the Caenorhabditis elegans chemical synapse neuronal connectome network

Graph theoretical analyses of nervous systems usually omit the aspect of connection polarity, due to data insufficiency. The chemical synapse network of Caenorhabditis elegans is a well-reconstructed directed network, but the signs of its connections are yet to be elucidated. Here, we present the gene expression-based sign prediction of the ionotropic chemical synapse connectome of C. elegans (3,638 connections and 20,589 synapses total), incorporating available presynaptic neurotransmitter and postsynaptic receptor gene expression data for three major neurotransmitter systems. We made predictions for more than two-thirds of these chemical synapses and observed an excitatory-inhibitory (E:I) ratio close to 4:1 which was found similar to that observed in many real-world networks. Our open source tool (http://EleganSign.linkgroup.hu) is simple but efficient in predicting polarities by integrating neuronal connectome and gene expression data.

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Synaptic polarity and sign-balance prediction using gene expression data in the Caenorhabditis elegans chemical synapse neuronal connectome network

10.1101/2020.05.22.110312 ◽

2020 ◽

Author(s):

Bánk G. Fenyves ◽

Gábor S. Szilágyi ◽

Zsolt Vassy ◽

Csaba Sőti ◽

Péter Csermely

Keyword(s):

Gene Expression ◽

Caenorhabditis Elegans ◽

Gene Expression Data ◽

Temporal Dynamics ◽

Receptor Gene ◽

Inhibitory Synapses ◽

Directed Network ◽

Chemical Synapse ◽

Expression Data ◽

C Elegans

AbstractGraph theoretical analyses of nervous systems usually omit the aspect of connection polarity, due to data insufficiency. The chemical synapse network of Caenorhabditis elegans is a well-reconstructed directed network, but the signs of its connections are yet to be elucidated. Here, we present the gene expression-based sign prediction of the C. elegans connectome, incorporating presynaptic neurotransmitter and postsynaptic receptor gene expression data (3,638 connections and 20,589 synapses total). We made successful predictions for more than two-thirds of all chemical synapses and determined a ratio of excitatory-inhibitory (E:I) interneuronal ionotropic chemical connections close to 4:1 which was found similar to that observed in many real-world networks. Our open source tool (http://EleganSign.linkgroup.hu) is simple but efficient in predicting polarities by integrating neuronal connectome and gene expression data.Author SummaryThe fundamental way neurons communicate is by activating or inhibiting each other via synapses. The balance between the two is crucial for the optimal functioning of a nervous system. However, whole-brain synaptic polarity information is unavailable for any species and experimental validation is challenging. The roundworm Caenorhabditis elegans possesses a fully mapped connectome with a comprehensive gene expression profile of its 302 neurons. Based on the consideration that the polarity of a synapse must be determined by the neurotransmitter(s) expressed in the presynaptic neuron and the receptors expressed in the postsynaptic neuron, we conceptualized and created a tool that predicts synaptic polarities based on connectivity and gene expression information. We were able to show for the first time that the ratio of excitatory and inhibitory synapses in C. elegans is around 4 to 1 which is in line with the balance observed in many natural systems. Our method opens a way to include spatial and temporal dynamics of synaptic polarity that would add a new dimension of plasticity in the excitatory:inhibitory balance. Our tool is freely available to be used on any network accompanied by any expression atlas.

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Sensory experience and sensory activity regulate chemosensory receptor gene expression in Caenorhabditis elegans

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.191352498 ◽

2001 ◽

Vol 98 (20) ◽

pp. 11032-11038 ◽

Cited By ~ 63

Author(s):

E. L. Peckol ◽

E. R. Troemel ◽

C. I. Bargmann

Keyword(s):

Gene Expression ◽

Caenorhabditis Elegans ◽

Receptor Gene ◽

Sensory Experience ◽

Chemosensory Receptor ◽

Sensory Activity ◽

Receptor Gene Expression

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Faculty Opinions recommendation of Sensory experience and sensory activity regulate chemosensory receptor gene expression in Caenorhabditis elegans.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1000879.14007 ◽

2001 ◽

Author(s):

Charles Zuker

Keyword(s):

Gene Expression ◽

Caenorhabditis Elegans ◽

Receptor Gene ◽

Sensory Experience ◽

Chemosensory Receptor ◽

Sensory Activity ◽

Receptor Gene Expression

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Faculty Opinions recommendation of Sensory experience and sensory activity regulate chemosensory receptor gene expression in Caenorhabditis elegans.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1000879.13112 ◽

2001 ◽

Author(s):

Oliver Hobert

Keyword(s):

Gene Expression ◽

Caenorhabditis Elegans ◽

Receptor Gene ◽

Sensory Experience ◽

Chemosensory Receptor ◽

Sensory Activity ◽

Receptor Gene Expression

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SPI: a tool for incorporating gene expression data into a four-dimensional database of Caenorhabditis elegans embryogenesis

Bioinformatics ◽

10.1093/bioinformatics/bth045 ◽

2004 ◽

Vol 20 (7) ◽

pp. 1097-1109 ◽

Cited By ~ 5

Author(s):

Y. Minakuchi ◽

M. Ito ◽

Y. Kohara

Keyword(s):

Gene Expression ◽

Caenorhabditis Elegans ◽

Gene Expression Data ◽

Expression Data

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A regulatory network modeled from wild-type gene expression data guides functional predictions in Caenorhabditis elegans development

BMC Systems Biology ◽

10.1186/1752-0509-6-77 ◽

2012 ◽

Vol 6 (1) ◽

pp. 77 ◽

Cited By ~ 11

Author(s):

Brandilyn Stigler ◽

Helen M Chamberlin

Keyword(s):

Gene Expression ◽

Caenorhabditis Elegans ◽

Gene Expression Data ◽

Regulatory Network ◽

Expression Data ◽

Wild Type ◽

Type Gene

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The comprehensive transcriptional analysis in Caenorhabditis elegans by integrating ChIP-seq and gene expression data

Genetics Research ◽

10.1017/s0016672314000081 ◽

2014 ◽

Vol 96 ◽

Cited By ~ 2

Author(s):

KAN HE ◽

JIAOFANG SHAO ◽

ZHONGYING ZHAO ◽

DAHAI LIU

Keyword(s):

Gene Expression ◽

Transcriptional Regulation ◽

Caenorhabditis Elegans ◽

Gene Expression Data ◽

Target Genes ◽

Model Systems ◽

Transcriptional Analysis ◽

Expression Data ◽

Tissue Specific ◽

C Elegans

SummaryThe fundamental step of learning transcriptional regulation mechanism is to identify the target genes regulated by transcription factors (TFs). Despite numerous target genes identified by chromatin immunopre-cipitation followed by high-throughput sequencing technology (ChIP-seq) assays, it is not possible to infer function from binding alone in vivo. This is equally true in one of the best model systems, the nematode Caenorhabditis elegans (C. elegans), where regulation often occurs through diverse TF binding features of transcriptional networks identified in modENCODE. Here, we integrated ten ChIP-seq datasets with genome-wide expression data derived from tiling arrays, involved in six TFs (HLH-1, ELT-3, PQM-1, SKN-1, CEH-14 and LIN-11) with tissue-specific and four TFs (CEH-30, LIN-13, LIN-15B and MEP-1) with broad expression patterns. In common, TF bindings within 3 kb upstream of or within its target gene for these ten studies showed significantly elevated level of expression as opposed to that of non-target controls, indicated that these sites may be more likely to be functional through up-regulating its target genes. Intriguingly, expression of the target genes out of 5 kb upstream of their transcription start site also showed high levels, which was consistent with the results of following network component analysis. Our study has identified similar transcriptional regulation mechanisms of tissue-specific or broad expression TFs in C. elegans using ChIP-seq and gene expression data. It may also provide a novel insight into the mechanism of transcriptional regulation not only for simple organisms but also for more complex species.

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Systematic Identification of Housekeeping Genes Possibly Used as References in Caenorhabditis elegans by Large-Scale Data Integration

Cells ◽

10.3390/cells9030786 ◽

2020 ◽

Vol 9 (3) ◽

pp. 786 ◽

Cited By ~ 1

Author(s):

Jingxin Tao ◽

Youjin Hao ◽

Xudong Li ◽

Huachun Yin ◽

Xiner Nie ◽

...

Keyword(s):

Gene Expression ◽

Caenorhabditis Elegans ◽

Gene Expression Data ◽

Reference Genes ◽

Large Scale ◽

Gene Array ◽

Housekeeping Genes ◽

Functional Enrichment ◽

Expression Data ◽

Data Types

For accurate gene expression quantification, normalization of gene expression data against reliable reference genes is required. It is known that the expression levels of commonly used reference genes vary considerably under different experimental conditions, and therefore, their use for data normalization is limited. In this study, an unbiased identification of reference genes in Caenorhabditis elegans was performed based on 145 microarray datasets (2296 gene array samples) covering different developmental stages, different tissues, drug treatments, lifestyle, and various stresses. As a result, thirteen housekeeping genes (rps-23, rps-26, rps-27, rps-16, rps-2, rps-4, rps-17, rpl-24.1, rpl-27, rpl-33, rpl-36, rpl-35, and rpl-15) with enhanced stability were comprehensively identified by using six popular normalization algorithms and RankAggreg method. Functional enrichment analysis revealed that these genes were significantly overrepresented in GO terms or KEGG pathways related to ribosomes. Validation analysis using recently published datasets revealed that the expressions of newly identified candidate reference genes were more stable than the commonly used reference genes. Based on the results, we recommended using rpl-33 and rps-26 as the optimal reference genes for microarray and rps-2 and rps-4 for RNA-sequencing data validation. More importantly, the most stable rps-23 should be a promising reference gene for both data types. This study, for the first time, successfully displays a large-scale microarray data driven genome-wide identification of stable reference genes for normalizing gene expression data and provides a potential guideline on the selection of universal internal reference genes in C. elegans, for quantitative gene expression analysis.

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