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Transcriptional maturation of the mouse auditory forebrain.

Hackett TA, Guo Y, Clause A, Hackett NJ, Garbett K, Zhang P, Polley DB, Mirnics K - BMC Genomics (2015)

Bottom Line: Gene expression in the auditory forebrain during postnatal development is in constant flux and becomes increasingly stable with age.Maturational changes are evident at the global through single gene levels.The database generated by this study provides a rich foundation for the identification of novel developmental biomarkers, functional gene pathways, and targeted studies of postnatal maturation in the auditory forebrain.

View Article: PubMed Central - PubMed

Affiliation: Department of Hearing and Speech Sciences, Vanderbilt University School of Medicine, Nashville, TN, USA. troy.a.hackett@vanderbilt.edu.

ABSTRACT

Background: The maturation of the brain involves the coordinated expression of thousands of genes, proteins and regulatory elements over time. In sensory pathways, gene expression profiles are modified by age and sensory experience in a manner that differs between brain regions and cell types. In the auditory system of altricial animals, neuronal activity increases markedly after the opening of the ear canals, initiating events that culminate in the maturation of auditory circuitry in the brain. This window provides a unique opportunity to study how gene expression patterns are modified by the onset of sensory experience through maturity. As a tool for capturing these features, next-generation sequencing of total RNA (RNAseq) has tremendous utility, because the entire transcriptome can be screened to index expression of any gene. To date, whole transcriptome profiles have not been generated for any central auditory structure in any species at any age. In the present study, RNAseq was used to profile two regions of the mouse auditory forebrain (A1, primary auditory cortex; MG, medial geniculate) at key stages of postnatal development (P7, P14, P21, adult) before and after the onset of hearing (~P12). Hierarchical clustering, differential expression, and functional geneset enrichment analyses (GSEA) were used to profile the expression patterns of all genes. Selected genesets related to neurotransmission, developmental plasticity, critical periods and brain structure were highlighted. An accessible repository of the entire dataset was also constructed that permits extraction and screening of all data from the global through single-gene levels. To our knowledge, this is the first whole transcriptome sequencing study of the forebrain of any mammalian sensory system. Although the data are most relevant for the auditory system, they are generally applicable to forebrain structures in the visual and somatosensory systems, as well.

Results: The main findings were: (1) Global gene expression patterns were tightly clustered by postnatal age and brain region; (2) comparing A1 and MG, the total numbers of differentially expressed genes were comparable from P7 to P21, then dropped to nearly half by adulthood; (3) comparing successive age groups, the greatest numbers of differentially expressed genes were found between P7 and P14 in both regions, followed by a steady decline in numbers with age; (4) maturational trajectories in expression levels varied at the single gene level (increasing, decreasing, static, other); (5) between regions, the profiles of single genes were often asymmetric; (6) GSEA revealed that genesets related to neural activity and plasticity were typically upregulated from P7 to adult, while those related to structure tended to be downregulated; (7) GSEA and pathways analysis of selected functional networks were not predictive of expression patterns in the auditory forebrain for all genes, reflecting regional specificity at the single gene level.

Conclusions: Gene expression in the auditory forebrain during postnatal development is in constant flux and becomes increasingly stable with age. Maturational changes are evident at the global through single gene levels. Transcriptome profiles in A1 and MG are distinct at all ages, and differ from other brain regions. The database generated by this study provides a rich foundation for the identification of novel developmental biomarkers, functional gene pathways, and targeted studies of postnatal maturation in the auditory forebrain.

No MeSH data available.


Related in: MedlinePlus

Pathways analysis of critical periods genes. The 16 critical periods genes from Fig. 8 were used as seeds to generate a functional association network of known and predicted interactions using the GeneMANIA tool (http://genemania.org). Analysis based on gene ontology (GO) biological function annotations. a Network generated from the 16 critical periods genes (nodes with black circles) and 50 interacting genes (nodes with gray circles). Connection type is denoted by line color (see legend), and strength (line thickness) is weighted by linear regression-based computations of the functional association data in the databases indexed. b Connections of the 13 genes (out of 66) from the entire network that were listed in the GO category: regulation of synaptic transmission. The normalized counts of these genes are plotted below. c–d Detailed connections of 2 genes from panel b: JPH3 (junctophilin-3), CSPG5 (chondroitin sulfate proteoglycan 5). See text for details
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Fig9: Pathways analysis of critical periods genes. The 16 critical periods genes from Fig. 8 were used as seeds to generate a functional association network of known and predicted interactions using the GeneMANIA tool (http://genemania.org). Analysis based on gene ontology (GO) biological function annotations. a Network generated from the 16 critical periods genes (nodes with black circles) and 50 interacting genes (nodes with gray circles). Connection type is denoted by line color (see legend), and strength (line thickness) is weighted by linear regression-based computations of the functional association data in the databases indexed. b Connections of the 13 genes (out of 66) from the entire network that were listed in the GO category: regulation of synaptic transmission. The normalized counts of these genes are plotted below. c–d Detailed connections of 2 genes from panel b: JPH3 (junctophilin-3), CSPG5 (chondroitin sulfate proteoglycan 5). See text for details

Mentions: To further probe this custom geneset, we used the 16 critical periods genes from Fig. 8 as seeds to generate a functional association network of known and predicted interactions using the GeneMANIA tool (http://genemania.org) [65, 66], based on gene ontology (GO) biological function annotations. The network illustrated in Fig. 9a includes the 16 critical periods genes (nodes with black circles) and 50 interacting genes (nodes with gray circles). The number of interacting genes included is a user-selected option. Connection type is denoted by line color (see legend), and strength (line thickness) is weighted by linear regression-based computations of the functional association data in the databases indexed. In addition to a dense plexus of connections, the 66 genes in this network were cross-listed in 91 GO categories. Figure 9b depicts the connections of 13 genes that were contained within one of these GO categories: regulation of synaptic transmission. This includes 3 critical periods genes from Fig. 8 (Bdnf, Ntrk2, Camk2a), and 10 interacting genes from the pathways analysis. The normalized counts of these genes are plotted below. Note the expected close association between Bdnf (brain-derived neurotrophic factor) and its tyrosine kinase receptor, TrkB (Ntrk2).Fig. 9


Transcriptional maturation of the mouse auditory forebrain.

Hackett TA, Guo Y, Clause A, Hackett NJ, Garbett K, Zhang P, Polley DB, Mirnics K - BMC Genomics (2015)

Pathways analysis of critical periods genes. The 16 critical periods genes from Fig. 8 were used as seeds to generate a functional association network of known and predicted interactions using the GeneMANIA tool (http://genemania.org). Analysis based on gene ontology (GO) biological function annotations. a Network generated from the 16 critical periods genes (nodes with black circles) and 50 interacting genes (nodes with gray circles). Connection type is denoted by line color (see legend), and strength (line thickness) is weighted by linear regression-based computations of the functional association data in the databases indexed. b Connections of the 13 genes (out of 66) from the entire network that were listed in the GO category: regulation of synaptic transmission. The normalized counts of these genes are plotted below. c–d Detailed connections of 2 genes from panel b: JPH3 (junctophilin-3), CSPG5 (chondroitin sulfate proteoglycan 5). See text for details
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4536593&req=5

Fig9: Pathways analysis of critical periods genes. The 16 critical periods genes from Fig. 8 were used as seeds to generate a functional association network of known and predicted interactions using the GeneMANIA tool (http://genemania.org). Analysis based on gene ontology (GO) biological function annotations. a Network generated from the 16 critical periods genes (nodes with black circles) and 50 interacting genes (nodes with gray circles). Connection type is denoted by line color (see legend), and strength (line thickness) is weighted by linear regression-based computations of the functional association data in the databases indexed. b Connections of the 13 genes (out of 66) from the entire network that were listed in the GO category: regulation of synaptic transmission. The normalized counts of these genes are plotted below. c–d Detailed connections of 2 genes from panel b: JPH3 (junctophilin-3), CSPG5 (chondroitin sulfate proteoglycan 5). See text for details
Mentions: To further probe this custom geneset, we used the 16 critical periods genes from Fig. 8 as seeds to generate a functional association network of known and predicted interactions using the GeneMANIA tool (http://genemania.org) [65, 66], based on gene ontology (GO) biological function annotations. The network illustrated in Fig. 9a includes the 16 critical periods genes (nodes with black circles) and 50 interacting genes (nodes with gray circles). The number of interacting genes included is a user-selected option. Connection type is denoted by line color (see legend), and strength (line thickness) is weighted by linear regression-based computations of the functional association data in the databases indexed. In addition to a dense plexus of connections, the 66 genes in this network were cross-listed in 91 GO categories. Figure 9b depicts the connections of 13 genes that were contained within one of these GO categories: regulation of synaptic transmission. This includes 3 critical periods genes from Fig. 8 (Bdnf, Ntrk2, Camk2a), and 10 interacting genes from the pathways analysis. The normalized counts of these genes are plotted below. Note the expected close association between Bdnf (brain-derived neurotrophic factor) and its tyrosine kinase receptor, TrkB (Ntrk2).Fig. 9

Bottom Line: Gene expression in the auditory forebrain during postnatal development is in constant flux and becomes increasingly stable with age.Maturational changes are evident at the global through single gene levels.The database generated by this study provides a rich foundation for the identification of novel developmental biomarkers, functional gene pathways, and targeted studies of postnatal maturation in the auditory forebrain.

View Article: PubMed Central - PubMed

Affiliation: Department of Hearing and Speech Sciences, Vanderbilt University School of Medicine, Nashville, TN, USA. troy.a.hackett@vanderbilt.edu.

ABSTRACT

Background: The maturation of the brain involves the coordinated expression of thousands of genes, proteins and regulatory elements over time. In sensory pathways, gene expression profiles are modified by age and sensory experience in a manner that differs between brain regions and cell types. In the auditory system of altricial animals, neuronal activity increases markedly after the opening of the ear canals, initiating events that culminate in the maturation of auditory circuitry in the brain. This window provides a unique opportunity to study how gene expression patterns are modified by the onset of sensory experience through maturity. As a tool for capturing these features, next-generation sequencing of total RNA (RNAseq) has tremendous utility, because the entire transcriptome can be screened to index expression of any gene. To date, whole transcriptome profiles have not been generated for any central auditory structure in any species at any age. In the present study, RNAseq was used to profile two regions of the mouse auditory forebrain (A1, primary auditory cortex; MG, medial geniculate) at key stages of postnatal development (P7, P14, P21, adult) before and after the onset of hearing (~P12). Hierarchical clustering, differential expression, and functional geneset enrichment analyses (GSEA) were used to profile the expression patterns of all genes. Selected genesets related to neurotransmission, developmental plasticity, critical periods and brain structure were highlighted. An accessible repository of the entire dataset was also constructed that permits extraction and screening of all data from the global through single-gene levels. To our knowledge, this is the first whole transcriptome sequencing study of the forebrain of any mammalian sensory system. Although the data are most relevant for the auditory system, they are generally applicable to forebrain structures in the visual and somatosensory systems, as well.

Results: The main findings were: (1) Global gene expression patterns were tightly clustered by postnatal age and brain region; (2) comparing A1 and MG, the total numbers of differentially expressed genes were comparable from P7 to P21, then dropped to nearly half by adulthood; (3) comparing successive age groups, the greatest numbers of differentially expressed genes were found between P7 and P14 in both regions, followed by a steady decline in numbers with age; (4) maturational trajectories in expression levels varied at the single gene level (increasing, decreasing, static, other); (5) between regions, the profiles of single genes were often asymmetric; (6) GSEA revealed that genesets related to neural activity and plasticity were typically upregulated from P7 to adult, while those related to structure tended to be downregulated; (7) GSEA and pathways analysis of selected functional networks were not predictive of expression patterns in the auditory forebrain for all genes, reflecting regional specificity at the single gene level.

Conclusions: Gene expression in the auditory forebrain during postnatal development is in constant flux and becomes increasingly stable with age. Maturational changes are evident at the global through single gene levels. Transcriptome profiles in A1 and MG are distinct at all ages, and differ from other brain regions. The database generated by this study provides a rich foundation for the identification of novel developmental biomarkers, functional gene pathways, and targeted studies of postnatal maturation in the auditory forebrain.

No MeSH data available.


Related in: MedlinePlus