Matching Items (6)
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- All Subjects: Bioinformatics
- Genre: Doctoral Dissertation
- Creators: Kusumi, Kenro
- Status: Published
Description
The development of the vertebrate musculoskeletal system is a highly dynamic process, requiring tight control of the specification and patterning of myogenic, chondrogenic and tenogenic cell types. Development of the diverse musculoskeletal lineages from a common embryonic origin in the paraxial mesoderm indicates the presence of a regulatory network of transcription factors that direct lineage decisions. The basic helix-loop-helix transcription factor, PARAXIS, is expressed in the paraxial mesoderm during vertebrate somitogenesis, where it has been shown to play a critical role in the mesenchymal-to-epithelial transition associated with somitogenesis, and the development of the hypaxial skeletal musculature and axial skeleton. In an effort to elucidate the underlying genetic mechanism by which PARAXIS regulates the musculoskeletal system, I performed a microarray-based, genome-wide analysis comparing transcription levels in the somites of Paraxis-/- and Paraxis+/+ embryos. This study revealed targets of PARAXIS involved in multiple aspects of mesenchymal-to-epithelial transition, including Fap and Dmrt2, which modulate cell-extracellular matrix adhesion. Additionally, in the epaxial dermomyotome, PARAXIS activates the expression of the integrin subunits a4 and a6, which bind fibronectin and laminin, respectively, and help organize the patterning of trunk skeletal muscle. Finally, PARAXIS activates the expression of genes required for the epithelial-to-mesenchymal transition and migration of hypaxial myoblasts into the limb, including Lbx1 and Met. Together, these data point to a role for PARAXIS in the morphogenetic control of musculoskeletal patterning.
ContributorsRowton, Megan (Author) / Rawls, Alan (Thesis advisor) / Wilson-Rawls, Jeanne (Committee member) / Kusumi, Kenro (Committee member) / Gadau, Juergen (Committee member) / Arizona State University (Publisher)
Created2013
Description
Postnatal skeletal muscle repair is dependent on the tight regulation of an adult stem cell population known as satellite cells. In response to injury, these quiescent cells are activated, proliferate and express skeletal muscle-specific genes. The majority of satellite cells will fuse to damaged fibers or form new muscle fibers, while a subset will return to a quiescent state, where they are available for future rounds of repair. Robust muscle repair is dependent on the signals that regulate the mutually exclusive decisions of differentiation and self-renewal. A likely candidate for regulating this process is NUMB, an inhibitor of Notch signaling pathway that has been shown to asymmetrically localize in daughter cells undergoing cell fate decisions. In order to study the role of this protein in muscle repair, an inducible knockout of Numb was made in mice. Numb deficient muscle had a defective repair response to acute induced damage as characterized by smaller myofibers, increased collagen deposition and infiltration of fibrotic cells. Satellite cells isolated from Numb-deficient mice show decreased proliferation rates. Subsequent analyses of gene expression demonstrated that these cells had an aberrantly up-regulated Myostatin (Mstn), an inhibitor of myoblast proliferation. Further, this defect could be rescued with Mstn specific siRNAs. These data indicate that NUMB is necessary for postnatal muscle repair and early proliferative expansion of satellite cells. We used an evolutionary compatible to examine processes controlling satellite cell fate decisions, primary satellite cell lines were generated from Anolis carolinensis. This green anole lizard is evolutionarily the closet animal to mammals that forms de novo muscle tissue while undergoing tail regeneration. The mechanism of regeneration in anoles and the sources of stem cells for skeletal muscle, cartilage and nerves are poorly understood. Thus, satellite cells were isolated from A. carolinensis and analyzed for their plasticity. Anole satellite cells show increased plasticity as compared to mouse as determined by expression of key markers specific for bone and cartilage without administration of exogenous morphogens. These novel data suggest that satellite cells might contribute to more than muscle in tail regeneration of A. carolinensis.
ContributorsGeorge, Rajani M (Author) / Wilson-Rawls, Jeanne (Thesis advisor) / Rawls, Alan (Committee member) / Whitfield, Kerr (Committee member) / Kusumi, Kenro (Committee member) / Arizona State University (Publisher)
Created2012
Description
Rapid advancements in genomic technologies have increased our understanding of rare human disease. Generation of multiple types of biological data including genetic variation from genome or exome, expression from transcriptome, methylation patterns from epigenome, protein complexity from proteome and metabolite information from metabolome is feasible. "Omics" tools provide comprehensive view into biological mechanisms that impact disease trait and risk. In spite of available data types and ability to collect them simultaneously from patients, researchers still rely on their independent analysis. Combining information from multiple biological data can reduce missing information, increase confidence in single data findings, and provide a more complete view of genotype-phenotype correlations. Although rare disease genetics has been greatly improved by exome sequencing, a substantial portion of clinical patients remain undiagnosed. Multiple frameworks for integrative analysis of genomic and transcriptomic data are presented with focus on identifying functional genetic variations in patients with undiagnosed, rare childhood conditions. Direct quantitation of X inactivation ratio was developed from genomic and transcriptomic data using allele specific expression and segregation analysis to determine magnitude and inheritance mode of X inactivation. This approach was applied in two families revealing non-random X inactivation in female patients. Expression based analysis of X inactivation showed high correlation with standard clinical assay. These findings improved understanding of molecular mechanisms underlying X-linked disorders. In addition multivariate outlier analysis of gene and exon level data from RNA-seq using Mahalanobis distance, and its integration of distance scores with genomic data found genotype-phenotype correlations in variant prioritization process in 25 families. Mahalanobis distance scores revealed variants with large transcriptional impact in patients. In this dataset, frameshift variants were more likely result in outlier expression signatures than other types of functional variants. Integration of outlier estimates with genetic variants corroborated previously identified, presumed causal variants and highlighted new candidate in previously un-diagnosed case. Integrative genomic approaches in easily attainable tissue will facilitate the search for biomarkers that impact disease trait, uncover pharmacogenomics targets, provide novel insight into molecular underpinnings of un-characterized conditions, and help improve analytical approaches that use large datasets.
ContributorsSzelinger, Szabolcs (Author) / Craig, David W. (Thesis advisor) / Kusumi, Kenro (Thesis advisor) / Narayan, Vinodh (Committee member) / Rosenberg, Michael S. (Committee member) / Huentelman, Matthew J (Committee member) / Arizona State University (Publisher)
Created2015
Description
Telomerase enzyme is a truly remarkable enzyme specialized for the addition of short, highly repetitive DNA sequences onto linear eukaryotic chromosome ends. The telomerase enzyme functions as a ribonucleoprotein, minimally composed of the highly conserved catalytic telomerase reverse transcriptase and essential telomerase RNA component containing an internalized short template region within the vastly larger non-coding RNA. Even among closely related groups of species, telomerase RNA is astonishingly divergent in sequence, length, and secondary structure. This massive disparity is highly prohibitive for telomerase RNA identification from previously unexplored groups of species, which is fundamental for secondary structure determination. Combined biochemical enrichment and computational screening methods were employed for the discovery of numerous telomerase RNAs from the poorly characterized echinoderm lineage. This resulted in the revelation that--while closely related to the vertebrate lineage and grossly resembling vertebrate telomerase RNA--the echinoderm telomerase RNA central domain varies extensively in structure and sequence, diverging even within echinoderms amongst sea urchins and brittle stars. Furthermore, the origins of telomerase RNA within the eukaryotic lineage have remained a persistent mystery. The ancient Trypanosoma telomerase RNA was previously identified, however, a functionally verified secondary structure remained elusive. Synthetic Trypanosoma telomerase was generated for molecular dissection of Trypanosoma telomerase RNA revealing two RNA domains functionally equivalent to those found in known telomerase RNAs, yet structurally distinct. This work demonstrates that telomerase RNA is uncommonly divergent in gross architecture, while retaining critical universal elements.
ContributorsPodlevsky, Joshua (Author) / Chen, Julian (Thesis advisor) / Mangone, Marco (Committee member) / Kusumi, Kenro (Committee member) / Wilson-Rawls, Norma (Committee member) / Arizona State University (Publisher)
Created2015
Description
Damage to the central nervous system due to spinal cord or traumatic brain injury, as well as degenerative musculoskeletal disorders such as arthritis, drastically impact the quality of life. Regeneration of complex structures is quite limited in mammals, though other vertebrates possess this ability. Lizards are the most closely related organism to humans that can regenerate de novo skeletal muscle, hyaline cartilage, spinal cord, vasculature, and skin. Progress in studying the cellular and molecular mechanisms of lizard regeneration has previously been limited by a lack of genomic resources. Building on the release of the genome of the green anole, Anolis carolinensis, we developed a second generation, robust RNA-Seq-based genome annotation, and performed the first transcriptomic analysis of tail regeneration in this species. In order to investigate gene expression in regenerating tissue, we performed whole transcriptome and microRNA transcriptome analysis of regenerating tail tip and base and associated tissues, identifying key genetic targets in the regenerative process. These studies have identified components of a genetic program for regeneration in the lizard that includes both developmental and adult repair mechanisms shared with mammals, indicating value in the translation of these findings to future regenerative therapies.
ContributorsHutchins, Elizabeth (Author) / Kusumi, Kenro (Thesis advisor) / Rawls, Jeffrey A. (Committee member) / Denardo, Dale F. (Committee member) / Huentelman, Matthew J. (Committee member) / Arizona State University (Publisher)
Created2015
Description
Next-generation sequencing is a powerful tool for detecting genetic variation. How-ever, it is also error-prone, with error rates that are much larger than mutation rates.
This can make mutation detection difficult; and while increasing sequencing depth
can often help, sequence-specific errors and other non-random biases cannot be de-
tected by increased depth. The problem of accurate genotyping is exacerbated when
there is not a reference genome or other auxiliary information available.
I explore several methods for sensitively detecting mutations in non-model or-
ganisms using an example Eucalyptus melliodora individual. I use the structure of
the tree to find bounds on its somatic mutation rate and evaluate several algorithms
for variant calling. I find that conventional methods are suitable if the genome of a
close relative can be adapted to the study organism. However, with structured data,
a likelihood framework that is aware of this structure is more accurate. I use the
techniques developed here to evaluate a reference-free variant calling algorithm.
I also use this data to evaluate a k-mer based base quality score recalibrator
(KBBQ), a tool I developed to recalibrate base quality scores attached to sequencing
data. Base quality scores can help detect errors in sequencing reads, but are often
inaccurate. The most popular method for correcting this issue requires a known
set of variant sites, which is unavailable in most cases. I simulate data and show
that errors in this set of variant sites can cause calibration errors. I then show that
KBBQ accurately recalibrates base quality scores while requiring no reference or other
information and performs as well as other methods.
Finally, I use the Eucalyptus data to investigate the impact of quality score calibra-
tion on the quality of output variant calls and show that improved base quality score
calibration increases the sensitivity and reduces the false positive rate of a variant
calling algorithm.
This can make mutation detection difficult; and while increasing sequencing depth
can often help, sequence-specific errors and other non-random biases cannot be de-
tected by increased depth. The problem of accurate genotyping is exacerbated when
there is not a reference genome or other auxiliary information available.
I explore several methods for sensitively detecting mutations in non-model or-
ganisms using an example Eucalyptus melliodora individual. I use the structure of
the tree to find bounds on its somatic mutation rate and evaluate several algorithms
for variant calling. I find that conventional methods are suitable if the genome of a
close relative can be adapted to the study organism. However, with structured data,
a likelihood framework that is aware of this structure is more accurate. I use the
techniques developed here to evaluate a reference-free variant calling algorithm.
I also use this data to evaluate a k-mer based base quality score recalibrator
(KBBQ), a tool I developed to recalibrate base quality scores attached to sequencing
data. Base quality scores can help detect errors in sequencing reads, but are often
inaccurate. The most popular method for correcting this issue requires a known
set of variant sites, which is unavailable in most cases. I simulate data and show
that errors in this set of variant sites can cause calibration errors. I then show that
KBBQ accurately recalibrates base quality scores while requiring no reference or other
information and performs as well as other methods.
Finally, I use the Eucalyptus data to investigate the impact of quality score calibra-
tion on the quality of output variant calls and show that improved base quality score
calibration increases the sensitivity and reduces the false positive rate of a variant
calling algorithm.
ContributorsOrr, Adam James (Author) / Cartwright, Reed (Thesis advisor) / Wilson, Melissa (Committee member) / Kusumi, Kenro (Committee member) / Taylor, Jesse (Committee member) / Pfeifer, Susanne (Committee member) / Arizona State University (Publisher)
Created2020