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Cited by 50RNA Research and SplicingGenomics and Phylogenetic StudiesSingle-cell and spatial transcriptomics

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Isoform Diversity and Regulation in Peripheral and Central Neurons Revealed through RNA-Seq

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Lerch, Jessica K., Kuo, Frank, Motti, Dario, Morris, Richard, Bixby, John L., Lemmon, Vance P.·2012·PLoS ONE
DOI 10.1371/journal.pone.0030417PMC PMC3260295
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Abstract

To fully understand cell type identity and function in the nervous system there is a need to understand neuronal gene expression at the level of isoform diversity. Here we applied Next Generation Sequencing of the transcriptome (RNA-Seq) to purified sensory neurons and cerebellar granular neurons (CGNs) grown on an axonal growth permissive substrate. The goal of the analysis was to uncover neuronal type specific isoforms as a prelude to understanding patterns of gene expression underlying their intrinsic growth abilities. Global gene expression patterns were comparable to those found for other cell types, in that a vast majority of genes were expressed at low abundance. Nearly 18% of gene loci produced more than one transcript. More than 8000 isoforms were differentially expressed, either to different degrees in different neuronal types or uniquely expressed in one or the other. Sensory neurons expressed a larger number of genes and gene isoforms than did CGNs. To begin to understand the mechanisms responsible for the differential gene/isoform expression we identified transcription factor binding sites present specifically in the upstream genomic sequences of differentially expressed isoforms, and analyzed the 3' untranslated regions (3' UTRs) for microRNA (miRNA) target sites. Our analysis defines isoform diversity for two neuronal types with diverse axon growth capabilities and begins to elucidate the complex transcriptional landscape in two neuronal populations.

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Figure 1 Patterns of transcript expression and determination of reliably expressed transcripts. A, Transcripts that occur at low abundances are more frequent than transcripts that occur at high abundances. Power-law distribution states that the probability of gene expression k, will decay as a power-law P(k) ∞ k−r. This expression pattern occurs in both neuronal types. DRG R2 = 0.927. CGN R2 = 0.902. Axis in log scale. B, Logistic regression relationships between ‘reliability’ of isoform expression, measured by isoform FPKM having a lower confidence limit exceeding 0, and log (FPKM), for DRG neurons (left) and CGNs (right).
Figure 1 Patterns of transcript expression and determination of reliably expressed transcripts. A, Transcripts that occur at low abundances are more frequent than transcripts that occur at high abundances. Power-law distribution states that the probability of gene expression k, will decay as a power-law P(k) ∞ k−r. This expression pattern occurs in both neuronal types. DRG R2 = 0.927. CGN R2 = 0.902. Axis in log scale. B, Logistic regression relationships between ‘reliability’ of isoform expression, measured by isoform FPKM having a lower confidence limit exceeding 0, and log (FPKM), for DRG neurons (left) and CGNs (right).CC BY · PubMed Central
Figure 2 Differential isoform expression between DRGs and CGNs. A, Normalized abundances (FPKM) of isoforms in DRG neurons plotted against abundances in CGNs. Differentially expressed isoforms are in red. The criteria for differential expression are: | ln(FPKMCGN / FPKMDRG) | >1; p<0.05, the statistical test was deemed acceptable by Cuffdiff and FPKM >50. B, Same plot as in A except differentially expressed isoforms falling within gene families of particular importance in neurons are indicated by different colored dots. The lines mark the efold changes of +1 and -1. C, The number of differentially expressed isoforms is represented for each group of genes. DRG neuron isoforms are in green and CGN isoforms are in purple. D, The number of isoforms found in common in DRG neurons and CGNs in each category. See Table 2.
Figure 2 Differential isoform expression between DRGs and CGNs. A, Normalized abundances (FPKM) of isoforms in DRG neurons plotted against abundances in CGNs. Differentially expressed isoforms are in red. The criteria for differential expression are: | ln(FPKMCGN / FPKMDRG) | >1; p<0.05, the statistical test was deemed acceptable by Cuffdiff and FPKM >50. B, Same plot as in A except differentially expressed isoforms falling within gene families of particular importance in neurons are indicated by different colored dots. The lines mark the efold changes of +1 and -1. C, The number of differentially expressed isoforms is represented for each group of genes. DRG neuron isoforms are in green and CGN isoforms are in purple. D, The number of isoforms found in common in DRG neurons and CGNs in each category. See Table 2.CC BY · PubMed Central
Figure 3 Validation and functional testing of novel isoforms. A, Expression of 15 isoforms was assessed by qPCR in DRG neurons and CGNs. Isoform expression was compared to the fold change in FPKM. (Relative expression and FPKM ratios in Table 3). B, C, Atf3 and Pten isoform specific primers (bottom panels) were used on DRG cDNA and produced PCR products of the predicted sizes. B, Lane2: Atf3 cDNA (Open BioSystems); Lane3: conventional Atf3; Lane4: Atf3 J1; Lane5: Atf2 J2; Lane 6: Atf3 J3; Lane7: no template control; Lane 8: no reverse transcription (RT) control. C, Lane2: conventional Pten; Lane3: no template control for Pten; Lane4: no RT control for Pten; Lane5: Pten J2; Lane 6: no template control for Pten J2; Lane 7: no RT control for Pten J2. Schematic representations of Atf3 and Pten isoforms are below each gel (not to scale). Primer positions are indicated with colored arrows. D, The ratio of Pten J2 expression to Pten conventional + Pten J1 expression (in FPKM). The FPKMs for Pten and Pten J1 were summed because there is no way to distinguish the isoforms by PCR. Pten J2 expression is reduced 80–90%. E, qPCR validates the reduction in Pten J2 expression. F, Western blot for PTEN (50 kD) and PTEN J2 (32 kD) confirms that both proteins can be produced from the corresponding cDNAs.
Figure 3 Validation and functional testing of novel isoforms. A, Expression of 15 isoforms was assessed by qPCR in DRG neurons and CGNs. Isoform expression was compared to the fold change in FPKM. (Relative expression and FPKM ratios in Table 3). B, C, Atf3 and Pten isoform specific primers (bottom panels) were used on DRG cDNA and produced PCR products of the predicted sizes. B, Lane2: Atf3 cDNA (Open BioSystems); Lane3: conventional Atf3; Lane4: Atf3 J1; Lane5: Atf2 J2; Lane 6: Atf3 J3; Lane7: no template control; Lane 8: no reverse transcription (RT) control. C, Lane2: conventional Pten; Lane3: no template control for Pten; Lane4: no RT control for Pten; Lane5: Pten J2; Lane 6: no template control for Pten J2; Lane 7: no RT control for Pten J2. Schematic representations of Atf3 and Pten isoforms are below each gel (not to scale). Primer positions are indicated with colored arrows. D, The ratio of Pten J2 expression to Pten conventional + Pten J1 expression (in FPKM). The FPKMs for Pten and Pten J1 were summed because there is no way to distinguish the isoforms by PCR. Pten J2 expression is reduced 80–90%. E, qPCR validates the reduction in Pten J2 expression. F, Western blot for PTEN (50 kD) and PTEN J2 (32 kD) confirms that both proteins can be produced from the corresponding cDNAs.CC BY · PubMed Central
Figure 4 Hierarchical clustering of transcription factor binding sites in differentially expressed isoforms. Heat map showing Z-scores reflecting the frequency of binding sites for TFs found in the promoters overexpressed for each comparison. Green indicates high relative abundance for the TF binding site, and red low relative abundance. Clusters I and V represent TFBSs whose binding sites are enriched in DRGs. Cluster III, IV, VI and VII consists of TFBSs with low abundance in all comparisons.
Figure 4 Hierarchical clustering of transcription factor binding sites in differentially expressed isoforms. Heat map showing Z-scores reflecting the frequency of binding sites for TFs found in the promoters overexpressed for each comparison. Green indicates high relative abundance for the TF binding site, and red low relative abundance. Clusters I and V represent TFBSs whose binding sites are enriched in DRGs. Cluster III, IV, VI and VII consists of TFBSs with low abundance in all comparisons.CC BY · PubMed Central
Figure 5 Hierarchical clustering of miRNA target sites in the 3′ UTRs of differentially expressed isoforms. Heat map representing Z-scores derived from MRE frequency. Red indicates a frequent appearance of the MRE (suggesting low miRNA activity in the corresponding cell type) and green a low frequency (suggesting possible high miRNA activity in the corresponding cell type). Cluster II contains miRNAs with responsive elements appearing in 3′UTRs of transcripts overexpressed in DRGs. Cluster I miRNAs are present in most of the transcripts regardless of comparison indicating these miRNAs may not be active in neurons. Clusters VI-VIII represent miRNAs that could be potentially active in DRG enriched transcripts due to their low appearance in DRG 3′UTRs, while Cluster II and III represent miRNAs potentially active in CGNs. Cluster IV and V represent miRNAs with a low abundance of target sites regardless of cell type suggesting these miRNAs may be active in both neuronal types.
Figure 5 Hierarchical clustering of miRNA target sites in the 3′ UTRs of differentially expressed isoforms. Heat map representing Z-scores derived from MRE frequency. Red indicates a frequent appearance of the MRE (suggesting low miRNA activity in the corresponding cell type) and green a low frequency (suggesting possible high miRNA activity in the corresponding cell type). Cluster II contains miRNAs with responsive elements appearing in 3′UTRs of transcripts overexpressed in DRGs. Cluster I miRNAs are present in most of the transcripts regardless of comparison indicating these miRNAs may not be active in neurons. Clusters VI-VIII represent miRNAs that could be potentially active in DRG enriched transcripts due to their low appearance in DRG 3′UTRs, while Cluster II and III represent miRNAs potentially active in CGNs. Cluster IV and V represent miRNAs with a low abundance of target sites regardless of cell type suggesting these miRNAs may be active in both neuronal types.CC BY · PubMed Central
Figure 6 Interaction networks between TFs and miRNAs. The shortest paths algorithm was used to examine interactions between the TFs in Clusters I and V (Figure 4) and the miRNAs in Clusters II, VI, VII, and VIII (Figure 5; GeneGo, MetaCore, Inc,). The number of steps was limited to one. All interactions are shown. Interactions that support the findings from TFBS and miRNA clustering are indicated in bold. Green indicates activation and red inhibition.
Figure 6 Interaction networks between TFs and miRNAs. The shortest paths algorithm was used to examine interactions between the TFs in Clusters I and V (Figure 4) and the miRNAs in Clusters II, VI, VII, and VIII (Figure 5; GeneGo, MetaCore, Inc,). The number of steps was limited to one. All interactions are shown. Interactions that support the findings from TFBS and miRNA clustering are indicated in bold. Green indicates activation and red inhibition.CC BY · PubMed Central

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Metadata

Authors
Lerch, J. K., Kuo, F., Motti, D., Morris, R., Bixby, J. L., & Lemmon, V. P.
Affiliations
University of Miami (US)
Corresponding author
  • Bixby, John L.
  • Lemmon, Vance P.
ORCID
Venue
PLoS ONE
Publisher
Public Library of Science (PLoS)
Published
2012-01-17
Volume
7
Issue
1
Pages
e30417
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0030417
PMC
PMC3260295
OpenAlex
W2064384407
Cited by
50
References
62
Citations by year
2026: 1 · 2023: 4 · 2022: 3 · 2021: 3 · 2020: 5 · 2018: 3 · 2017: 5 · 2016: 7 · 2015: 6 · 2014: 6 · 2013: 4 · 2012: 3
FWCI
2.44
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • Figshare (submittedVersion, cc-by)
Funders
  • National Institutes of Health (W81XWH, HD057632)
  • National Institute of Neurological Disorders and Stroke (NS059866, R01NS059866)
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD057632, HD057632)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords
alternative splicing, isoform diversity, sensory neurons, neuronal gene expression, axon growth, transcription factor binding sites, microRNA binding sites, 3' untranslated region, cell type-specific gene expression, transcriptome
MeSH terms
Animals, Binding Sites, Cells, Cultured, Central Nervous System, Cerebellum, Ganglia, Spinal, Gene Expression Regulation, Mice, Inbred C57BL, Neurons, Sensory Receptor Cells, Transcription Factors, Cluster Analysis, Logistic Models, Open Reading Frames, Peripheral Nervous System, Protein Isoforms, 5' Untranslated Regions, Gene Expression Profiling, Transcription Initiation Site, MicroRNAs, Mice, Gene Regulatory Networks, High-Throughput Nucleotide Sequencing, Transcriptome

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