Dataset Information

Prediction of gene network models in limb muscle precursors.

ABSTRACT: The ventrolateral dermomyotome gives rise to all muscles of the limbs through the delamination and migration of cells into the limb buds. These cells proliferate and form myoblasts, withdraw from the cell cycle and become terminally differentiated. The myogenic lineage colonizes pre-patterned regions to form muscle anlagen as muscle fibers are assembled. The regulatory mechanisms that control the later steps of this myogenic program are not well understood. The homeodomain transcription factor Pitx2 is expressed in the muscle lineage from the migration of precursors to adult muscle. Ablation of Pitx2 results in distortion, rather than loss, of limb muscle anlagen, suggesting that its function becomes critical during the colonization of, and/or fiber assembly in, the anlagen. Gene expression arrays were used to identify changes in gene expression in flow-sorted migratory muscle precursors, labeled by Lbx1(EGFP), which resulted from the loss of Pitx2. Target genes of Pitx2 were clustered using the "David Bioinformatics Functional Annotation Tool" to bin genes according to enrichment of gene ontology keywords. This provided a way to both narrow the target genes and identify potential gene families regulated by Pitx2. Representative target genes in the most enriched bins were analyzed for the presence and evolutionary conservation of Pitx2 consensus binding sequence, TAATCY, on the -20kb, intronic, and coding regions of the genes. Fifteen Pitx2 target genes were selected based on the above analysis and were identified as having functions involving cytoskeleton organization, tissue specification, and transcription factors. Data from these studies suggest that Pitx2 acts to regulate cell motility and expression of muscle specific genes in the muscle precursors during forelimb muscle development. This work provides a framework to develop the gene network leading to skeletal muscle development, growth and regeneration.

SUBMITTER: Campbell AL

PROVIDER: S-EPMC3506249 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature

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Prediction of gene network models in limb muscle precursors.

Campbell Adam L AL Eng Diana D Gross Michael K MK Kioussi Chrissa C

Gene 20120820 1

The ventrolateral dermomyotome gives rise to all muscles of the limbs through the delamination and migration of cells into the limb buds. These cells proliferate and form myoblasts, withdraw from the cell cycle and become terminally differentiated. The myogenic lineage colonizes pre-patterned regions to form muscle anlagen as muscle fibers are assembled. The regulatory mechanisms that control the later steps of this myogenic program are not well understood. The homeodomain transcription factor P ...[more]

PMID: 22917675

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Project description:BACKGROUND: Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. RESULTS: We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. CONCLUSION: SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require randomization of multiple alignments can be considered. AVAILABILITY: SISSIz is available as open source C code that can be compiled for every major platform and downloaded here: http://sourceforge.net/projects/sissiz.

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Dataset Information

Prediction of gene network models in limb muscle precursors.

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Prediction of gene network models in limb muscle precursors.

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