scholarly journals Developmental transcriptomics of the brittle star Amphiura filiformis reveals gene regulatory network rewiring in echinoderm larval skeleton evolution

2017 ◽  
Author(s):  
David Dylus ◽  
Liisa M. Blowes ◽  
Anna Czarkwiani ◽  
Maurice R. Elphick ◽  
Paola Oliveri
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
De Novo ◽  
Sea Urchins ◽  
Brittle Star ◽  
Stages Of Development ◽  
Sequence Alignments ◽  
Amphiura Filiformis ◽  
Gene Regulatory ◽  
Network Rewiring

ABSTRACTAmongst the echinoderms the class Ophiuroidea is of particular interest for its phylogenetic position, ecological importance, developmental and regenerative biology. However, compared to other echinoderms, notably echinoids (sea urchins), relatively little is known about developmental changes in gene expression in ophiuroids. To address this issue we have generated and assembled a large RNAseq data set of four key stages of development in the brittle star Amphiura filiformis and a de novo reference transcriptome of comparable quality to that of a model echinoderm - the sea urchin Strongyloncentrotus purpuratus. Furthermore, we provide access to the new data via a web interface: http://www.echinonet.eu/shiny/Amphiura_filiformis/. With a focus on skeleton development, we have identified highly conserved genes associated with the development of a biomineralized skeleton. We also identify important class-specific characters, including the independent duplication of the msp130 class of genes in different echinoderm classes and the unique occurrence of spicule matrix (sm) genes in echinoids. Using a new quantification pipeline for our de novo transcriptome, validated with other methodologies, we find major differences between brittle stars and sea urchins in the temporal expression of many transcription factor genes. This divergence in developmental regulatory states is more evident in early stages of development when cell specification begins, than when cells initiate differentiation. Our findings indicate that there has been a high degree of gene regulatory network rewiring in the evolution of echinoderm larval development.Data DepositionsAll sequence reads are available at Genbank SRR4436669 - SRR4436674. Any sequence alignments used are available by the corresponding author upon request.

scholarly journals Gene regulatory network rewiring by an adaptively evolving microRNA cluster in Drosophila

2017 ◽  
Author(s):  
Yang Lyu ◽  
Zhongqi Liufu ◽  
Juan Xiao ◽  
Yuxin Chen ◽  
Chung-I Wu ◽  
...  
Keyword(s):  
Gene Regulatory Network ◽  
Biological Networks ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
De Novo ◽  
Target Prediction ◽  
New Members ◽  
Microrna Cluster ◽  
Gene Regulatory ◽  
Network Rewiring

AbstractNew miRNAs are evolutionarily important but their impact on existing biological networks remains unclear. We report the evolution of a microRNA cluster, mir-972C, that arose de novo and the subsequently rewired gene regulatory networks in Drosophila. Molecular evolution analyses revealed that mir-972C originated in the common ancestor of Drosophila where it comprises five old miRNAs. It subsequently recruited five new members in the melanogaster subgroup after conservative evolution for at least 50 million years. Population genetics analyses reveal that young and old mir-972C miRNAs evolved rapidly under positive selection in both seed and non-seed regions. Combining target prediction and cell transfection experiments, we find that sequence changes in individual mir-972C members resulted in extensive gene regulatory network divergence among D. melanogaster, D. simulans, and D. virilis, whereas the target pool of the cluster as a whole remains relatively conserved. Our results suggest that clustering of young and old miRNAs at the same locus broadens target repertoires, resulting in the gain of new targets without losing many old ones. This may facilitate the establishment of new miRNAs within existing regulatory networks.

scholarly journals Genome-wide analysis of the skeletogenic gene regulatory network of sea urchins

Development ◽  
2014 ◽  
Vol 141 (12) ◽  
pp. 2542-2542 ◽  
Author(s):  
K. Rafiq ◽  
T. Shashikant ◽  
C. J. McManus ◽  
C. A. Ettensohn
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Sea Urchins ◽  
Genome Wide Analysis ◽  
Genome Wide ◽  
Gene Regulatory

scholarly journals Dissecting the DNA binding landscape and gene regulatory network of p63 and p53

2020 ◽  
Author(s):  
Konstantin Riege ◽  
Helene Kretzmer ◽  
Arne Sahm ◽  
Simon S. McDade ◽  
Steve Hoffmann ◽  
...  
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Target Genes ◽  
De Novo ◽  
Therapeutic Interventions ◽  
Expression Studies ◽  
Gene Regulatory ◽  
Recognition Motifs ◽  
Gene Expression Studies ◽  
Search Approach

AbstractThe transcription factor (TF) p53 is the best-known tumor suppressor, but its ancient sibling p63 (ΔNp63) is a master regulator of epidermis development and a key oncogenic driver in squamous cell carcinomas (SCC). Despite multiple gene expression studies becoming available in recent years, the limited overlap of reported p63-dependent genes has made it difficult to decipher the p63 gene regulatory network (GRN). In particular, analyses of p63 response elements differed substantially among the studies. To address this intricate data situation, we provide an integrated resource that enables assessing the p63-dependent regulation of any human gene of interest. Here, we use a novel iterative de novo motif search approach in conjunction with extensive publicly available ChIP-seq data to achieve a precise global distinction between p53 and p63 binding sites, recognition motifs, and potential co-factors. We integrate all these data with enhancer:gene associations to predict p63 target genes and identify those that are commonly de-regulated in SCC and, thus, may represent candidates for therapeutic interventions.

scholarly journals Gene Regulatory Network Rewiring in the Immune Cells Associated with Cancer

Genes ◽  
2017 ◽  
Vol 8 (11) ◽  
pp. 308 ◽  
Author(s):  
Pengyong Han ◽  
Chandrasekhar Gopalakrishnan ◽  
Haiquan Yu ◽  
Edwin Wang
Keyword(s):  
Gene Regulatory Network ◽  
Immune Cells ◽  
Regulatory Network ◽  
Gene Regulatory ◽  
Network Rewiring

scholarly journals Genome-wide analysis of the skeletogenic gene regulatory network of sea urchins

Development ◽  
2014 ◽  
Vol 141 (4) ◽  
pp. 950-961 ◽  
Author(s):  
K. Rafiq ◽  
T. Shashikant ◽  
C. J. McManus ◽  
C. A. Ettensohn
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Sea Urchins ◽  
Genome Wide Analysis ◽  
Genome Wide ◽  
Gene Regulatory

scholarly journals Developmental gene regulatory networks in sea urchins and what we can learn from them

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 203 ◽  
Author(s):  
Megan L. Martik ◽  
Deirdre C. Lyons ◽  
David R. McClay
Keyword(s):  
Transcription Factors ◽  
Gene Regulatory Network ◽  
Sea Urchin ◽  
Network Model ◽  
Regulatory Network ◽  
Regulatory Networks ◽  
Sea Urchins ◽  
Cell Types ◽  
Zygotic Transcription ◽  
Gene Regulatory

Sea urchin embryos begin zygotic transcription shortly after the egg is fertilized.  Throughout the cleavage stages a series of transcription factors are activated and, along with signaling through a number of pathways, at least 15 different cell types are specified by the beginning of gastrulation.  Experimentally, perturbation of contributing transcription factors, signals and receptors and their molecular consequences enabled the assembly of an extensive gene regulatory network model.  That effort, pioneered and led by Eric Davidson and his laboratory, with many additional insights provided by other laboratories, provided the sea urchin community with a valuable resource.  Here we describe the approaches used to enable the assembly of an advanced gene regulatory network model describing molecular diversification during early development.  We then provide examples to show how a relatively advanced authenticated network can be used as a tool for discovery of how diverse developmental mechanisms are controlled and work.

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