Dong-Guk Shin

In-Depth Characterization of microRNA Transcriptome in Melanoma

The full repertoire of human microRNAs (miRNAs) that could distinguish common (benign) nevi from cutaneous (malignant) melanomas remains to be established. In an effort to gain further insight into the role of miRNAs in melanoma, we applied Illumina next-generation sequencing (NGS) platform to carry out an in-depth analysis of miRNA transcriptome in biopsies of nevi, thick primary (>4.0 mm) and metastatic melanomas with matched normal skin in parallel to melanocytes and melanoma cell lines (both primary and metastatic) (n = 28). From this data representing 698 known miRNAs, we defined a set of top-40 list, which properly classified normal from cancer; also confirming 23 (58%) previously discovered miRNAs while introducing an additional 17 (42%) known and top-15 putative novel candidate miRNAs deregulated during melanoma progression. Surprisingly, the miRNA signature distinguishing specimens of melanoma from nevus was significantly different than that of melanoma cell lines from melanocytes. Among the top list, miR-203, miR-204-5p, miR-205-5p, miR-211-5p, miR-23b-3p, miR-26a-5p and miR-26b-5p were decreased in melanomas vs. nevi. In a validation cohort (n = 101), we verified the NGS results by qRT-PCR and showed that receiver-operating characteristic curves for miR-211-5p expression accurately discriminated invasive melanoma (AUC = 0.933), melanoma in situ (AUC = 0.933) and dysplastic (atypical) nevi (AUC = 0.951) from common nevi. Target prediction analysis of co-transcribed miRNAs showed a cooperative regulation of key elements in the MAPK signaling pathway. Furthermore, we found extensive sequence variations (isomiRs) and other non-coding small RNAs revealing a complex melanoma transcriptome. Deep-sequencing small RNAs directly from clinically defined specimens provides a robust strategy to improve melanoma diagnostics.

Analysis of αSMA-Labeled Progenitor Cell Commitment Identifies Notch Signaling as an Important Pathway in Fracture Healing

Fracture healing is a regenerative process that involves coordinated responses of many cell types, but characterization of the roles of specific cell populations in this process has been limited. We have identified alpha smooth muscle actin (αSMA) as a marker of a population of mesenchymal progenitor cells in the periosteum that contributes to osteochondral elements during fracture healing. Using a lineage tracing approach, we labeled αSMA‐expressing cells, and characterized changes in the periosteal population during the early stages of fracture healing by histology, flow cytometry, and gene expression profiling. In response to fracture, the αSMA‐labeled population expanded and began to differentiate toward the osteogenic and chondrogenic lineages. The frequency of mesenchymal progenitor cell markers such as Sca1 and PDGFRα increased after fracture. By 6 days after fracture, genes involved in matrix production and remodeling were elevated. In contrast, genes associated with muscle contraction and Notch signaling were downregulated after fracture. We confirmed that activating Notch signaling in αSMA‐labeled cells inhibited differentiation into osteogenic and adipogenic lineages in vitro and ectopic bone formation in vivo. By characterizing changes in a selected αSMA‐labeled progenitor cell population during fracture callus formation, we have shown that modulation of Notch signaling may determine osteogenic potential of αSMA‐expressing progenitor cells during bone healing.

Nodal distance algorithm: calculating a phylogenetic tree comparison metric

Maintaining a phylogenetic relationship repository requires the development of tools that are useful for mining the data stored in the repository. One way to query a database of phylogenetic information would be to compare phylogenetic trees. Because the only existing tree comparison methods are computationally intensive, this is not a reasonable task. Presented here is the nodal distance algorithm which has significantly less computation time than the most widely used comparison method, the partition metric. When the metric is calculated for trees where one species has been repositioned to a distant part of the tree no further computation is required as is needed for the partition metric. The nodal distance algorithm provides a method for comparing large sets of phylogenetic trees in a reasonable amount of time.

Fragmenting relations horizontally using a knowledge-based approach

In distributed DBMSs, one major issue in developing a horizontal fragmentation technique is what criteria to use to guide the fragmentation. The authors propose to use, in addition to typical user queries, particular knowledge about the data itself. Use of this knowledge allows revision of typical user queries into more precise forms. The revised query expressions produce better estimations of user reference clusters to the database than the original query expressions. The estimated user reference clusters form a basis to partition relations horizontally. In the proposed approach, an ordinary many-sorted language is extended to represent the queries and knowledge compatibly. This knowledge is identified in terms of five axiom schemata. An inference procedure is developed to apply the knowledge to the queries deductively. >

GABRA2 Alcohol Dependence Risk Allele is Associated with Reduced Expression of Chromosome 4p12 GABAA Subunit Genes in Human Neural Cultures

BACKGROUND Genetic variation in a region of chromosome 4p12 that includes the GABAA subunit gene GABRA2 has been reproducibly associated with alcohol dependence (AD). However, the molecular mechanisms underlying the association are unknown. This study examined correlates of in vitro gene expression of the AD-associated GABRA2 rs279858*C-allele in human neural cells using an induced pluripotent stem cell (iPSC) model system. METHODS We examined mRNA expression of chromosome 4p12 GABAA subunit genes (GABRG1, GABRA2, GABRA4, and GABRB1) in 36 human neural cell lines differentiated from iPSCs using quantitative polymerase chain reaction and next-generation RNA sequencing. mRNA expression in adult human brain was examined using the BrainCloud and BRAINEAC data sets. RESULTS We found significantly lower levels of GABRA2 mRNA in neural cell cultures derived from rs279858*C-allele carriers. Levels of GABRA2 RNA were correlated with those of the other 3 chromosome 4p12 GABAA genes, but not other neural genes. Cluster analysis based on the relative RNA levels of the 4 chromosome 4p12 GABAA genes identified 2 distinct clusters of cell lines, a low-expression cluster associated with rs279858*C-allele carriers and a high-expression cluster enriched for the rs279858*T/T genotype. In contrast, there was no association of genotype with chromosome 4p12 GABAA gene expression in postmortem adult cortex in either the BrainCloud or BRAINEAC data sets. CONCLUSIONS AD-associated variation in GABRA2 is associated with differential expression of the entire cluster of GABAA subunit genes on chromosome 4p12 in human iPSC-derived neural cell cultures. The absence of a parallel effect in postmortem human adult brain samples suggests that AD-associated genotype effects on GABAA expression, although not present in mature cortex, could have effects on regulation of the chromosome 4p12 GABAA cluster during neural development.

Computer-Automated Static, Dynamic and Cellular Bone Histomorphometry

Dynamic and cellular histomorphometry of trabeculae is the most biologically relevant way of assessing steady state bone health. Traditional measurement involves manual visual feature identification by a trained and qualified professional. Inherent with this methodology is the time and cost expenditure, as well as the subjectivity that naturally arises under human visual inspection. In this work, we propose a rapidly deployable, automated, and objective method for dynamic histomorphometry. We demonstrate that our method is highly effective in assessing cellular activities in distal femur and vertebra of mice which are injected with calcein and alizarin complexone 7 and 2 days prior to sacrifice. The mineralized bone tissues of mice are cryosectioned using a tape transfer protocol. A sequential workflow is implemented in which endogenous fluorescent signals (bone mineral, green and red mineralization lines), tartrate resistant acid phosphatase identified by ELF-97 and alkaline phosphatase identified by Fast Red are captured as individual tiled images of the section for each fluorescent color. All the images are then submitted to an image analysis pipeline that automates identification of the mineralized regions of bone and selection of a region of interest. The TRAP and AP stained images are aligned to the mineralized image using strategically placed fluorescent registration beads. Fluorescent signals are identified and are related to the trabecular surface within the ROI. Subsequently, the pipelined method computes static measurements, dynamic measurements, and cellular activities of osteoclast and osteoblast related to the trabecular surface. Our method has been applied to the distal femurs and vertebrae of 8 and 16 week old male and female C57Bl/6J mice. The histomorphometric results reveal a significantly greater bone turnover rate in female in contrast to male irrespective of age, validating similar outcomes reported by other studies.

Diversity and complexity in chromatin recognition by TFII-I transcription factors in pluripotent embryonic stem cells and embryonic tissues.

GTF2I and GTF2IRD1 encode a family of closely related transcription factors TFII-I and BEN critical in embryonic development. Both genes are deleted in Williams-Beuren syndrome, a complex genetic disorder associated with neurocognitive, craniofacial, dental and skeletal abnormalities. Although genome-wide promoter analysis has revealed the existence of multiple TFII-I binding sites in embryonic stem cells (ESCs), there was no correlation between TFII-I occupancy and gene expression. Surprisingly, TFII-I recognizes the promoter sequences enriched for H3K4me3/K27me3 bivalent domain, an epigenetic signature of developmentally important genes. Moreover, we discovered significant differences in the association between TFII-I and BEN with the cis-regulatory elements in ESCs and embryonic craniofacial tissues. Our data indicate that in embryonic tissues BEN, but not the highly homologous TFII-I, is primarily recruited to target gene promoters. We propose a “feed-forward model” of gene regulation to explain the specificity of promoter recognition by TFII-I factors in eukaryotic cells.

A multistrategy approach to classification learning in databases

Abstract This paper proposes a hybrid classification learning system for databases that integrates rule induction and lazy learning. For rule induction learning, we use an entropy function based on Hellinger divergence to measure the amount of information each inductive rule contains. For lazy learning, we also use the Hellinger measure to automatically generate attribute weights and to compute similarities between data values of non-numeric data types. Our system has been implemented and tested extensively on a number of well-known machine learning data sets. The performance of our system was favorable compared to those of other well-known classification learning techniques based on monostrategic learning methods.

Integrating an intelligent interface with a relational database for two way man-machine communication

The design of a system capable of handling ad hoc user responses to system-initiated questions is considered. An approach called the expectation-driven response understanding paradigm was developed. In this paradigm, it is assumed that each system-generated question is accompanied by an expectation of what the user should respond. The system attempts to link this expectation with the users response in order to quantify its appropriateness in relation to the systems original question. A prototype system based on this paradigm has been implemented and integrated with the INGRES database system.<<ETX>>

An expectation-driven response understanding paradigm

This paper describes a model that can account for ad hoc user-responses to argument interrogative type of system-initiated questions. Successful implementation of the model can provide an alternative solution that is more effective than the menu-driven approach that has been proposed as a meager solution to enable the system to ask a question to the user. The proposed model assumes that when the system asks a question, it maintains an expectation of the potential answers. The system then uses the expectation as the focus to perform the most likely interpretation of the users response. Without using such a focus the interpretation process could be unbounded. The interpretation process is mapped into a heuristic search problem. The interpretation process results in identifying a particular expectation-response relationship type, which the system can use to tailor its response strategy with respect to the given user-response. A prototype has been constructed to demonstrate the soundness of the proposed model. >