Biomedical subjects

Junhyong Kim

Publications and source records attributed to Junhyong Kim.

11 recordsLinked to original sources

PubMed2006

Patterns of sequence conservation in presynaptic neural genes.

BACKGROUND: The neuronal synapse is a fundamental functional unit in the central nervous system of animals. Because synaptic function is evolutionarily conserved, we reasoned that functional sequences of genes and related genomic elements known to play important roles in neurotransmitter release would also be conserved. RESULTS: Evolutionary rate analysis revealed that presynaptic proteins evolve slowly, although some members of large gene families exhibit accelerated evolutionary rates relative to other family members. Comparative sequence analysis of 46 megabases spanning 150 presynaptic genes identified more than 26,000 elements that are highly conserved in eight vertebrate species, as well as a small subset of sequences (6%) that are shared among unrelated presynaptic genes. Analysis of large gene families revealed that upstream and intronic regions of closely related family members are extremely divergent. We also identified 504 exceptionally long conserved elements (> or =360 base pairs, > or =80% pair-wise identity between human and other mammals) in intergenic and intronic regions of presynaptic genes. Many of these elements form a highly stable stem-loop RNA structure and consequently are candidates for novel regulatory elements, whereas some conserved noncoding elements are shown to correlate with specific gene expression profiles. The SynapseDB online database integrates these findings and other functional genomic resources for synaptic genes. CONCLUSION: Highly conserved elements in nonprotein coding regions of 150 presynaptic genes represent sequences that may be involved in the transcriptional or post-transcriptional regulation of these genes. Furthermore, comparative sequence analysis will facilitate selection of genes and noncoding sequences for future functional studies and analysis of variation studies in neurodevelopmental and psychiatric disorders.

Animals↗

PubMed2005

A mutation accumulation assay reveals a broad capacity for rapid evolution of gene expression.

Mutation is the ultimate source of biological diversity because it generates the variation that fuels evolution. Gene expression is the first step by which an organism translates genetic information into developmental change. Here we estimate the rate at which mutation produces new variation in gene expression by measuring transcript abundances across the genome during the onset of metamorphosis in 12 initially identical Drosophila melanogaster lines that independently accumulated mutations for 200 generations. We find statistically significant mutational variation for 39% of the genome and a wide range of variability across corresponding genes. As genes are upregulated in development their variability decreases, and as they are downregulated it increases, indicating that developmental context affects the evolution of gene expression. A strong correlation between mutational variance and environmental variance shows that there is the potential for widespread canalization. By comparing the evolutionary rates that we report here with differences between species, we conclude that gene expression does not evolve according to strictly neutral models. Although spontaneous mutations have the potential to generate abundant variation in gene expression, natural variation is relatively constrained.

Animals↗

PubMed2005

The cobweb of life revealed by genome-scale estimates of horizontal gene transfer.

With the availability of increasing amounts of genomic sequences, it is becoming clear that genomes experience horizontal transfer and incorporation of genetic information. However, to what extent such horizontal gene transfer (HGT) affects the core genealogical history of organisms remains controversial. Based on initial analyses of complete genomic sequences, HGT has been suggested to be so widespread that it might be the "essence of phylogeny" and might leave the treelike form of genealogy in doubt. On the other hand, possible biased estimation of HGT extent and the findings of coherent phylogenetic patterns indicate that phylogeny of life is well represented by tree graphs. Here, we reexamine this question by assessing the extent of HGT among core orthologous genes using a novel statistical method based on statistical comparisons of tree topology. We apply the method to 40 microbial genomes in the Clusters of Orthologous Groups database over a curated set of 297 orthologous gene clusters, and we detect significant HGT events in 33 out of 297 clusters over a wide range of functional categories. Estimates of positions of HGT events suggest a low mean genome-specific rate of HGT (2.0%) among the orthologous genes, which is in general agreement with other quantitative of HGT. We propose that HGT events, even when relatively common, still leave the treelike history of phylogenies intact, much like cobwebs hanging from tree branches.

Algorithms↗

PubMed2004

Molecular phylogeny of coral-reef sea cucumbers (Holothuriidae: Aspidochirotida) based on 16S mitochondrial ribosomal DNA sequence.

Members of the Holothuriidae, found globally at low to middle latitudes, are often a dominant component of Indo-West Pacific coral reefs. We present the first phylogeny of the group, using 8 species from the 5 currently recognized genera and based on approximately 540 nucleotides from a polymerase chain reaction-amplified and conserved 3' section of 16S mitochondrial ribosomal DNA. Parsimony and likelihood analyses returned identical topologies, permitting several robust inferences to be drawn. Several points corroborated the Linnean classification. Actinopyga and Bohadschia each appear monophyletic and Pearsonothuria is sister to Bohadschia. Other aspects of our phylogeny, however, were not in accord with the taxonomy of Holothuriidae or previous speculations about the group's evolutionary history. Most notably, the genus Holothuria appears paraphyletic. Actinopyga and Bohadschia, sometimes held to be closely related to one another because of certain morphologic similarities, are only distantly related. The morphologically distinct Labidodemas, even thought to warrant separation at the family level, is nested well within Holothuria. A maximum parsimony reconstruction of ancestral ossicle form on the phylogeny indicated that, in addition to a probable bout of elaboration in ossicle form (the modification of rods or rosettes to holothuriid-type buttons), at least 2 rounds of ossicle simplification also transpired in which buttons reverted to rods or rosettes. Cuvierian tubules, defensive organs unique to numerous members of Holothuriidae, were probably present before the initial radiation of the family, but the reconstruction is ambiguous as to their ancestral function.

Animals↗

PubMed2004

Estimating genomic coexpression networks using first-order conditional independence.

We describe a computationally efficient statistical framework for estimating networks of coexpressed genes. This framework exploits first-order conditional independence relationships among gene-expression measurements to estimate patterns of association. We use this approach to estimate a coexpression network from microarray gene-expression measurements from Saccharomyces cerevisiae. We demonstrate the biological utility of this approach by showing that a large number of metabolic pathways are coherently represented in the estimated network. We describe a complementary unsupervised graph search algorithm for discovering locally distinct subgraphs of a large weighted graph. We apply this algorithm to our coexpression network model and show that subgraphs found using this approach correspond to particular biological processes or contain representatives of distinct gene families.

Algorithms↗

PubMed2004

Expression profiling using a hexamer-based universal microarray.

We describe a transcriptional analysis platform consisting of a universal micro-array system (UMAS) combined with an enzymatic manipulation step that is capable of generating expression profiles from any organism without requiring a priori species-specific knowledge of transcript sequences. The transcriptome is converted to cDNA and processed with restriction endonucleases to generate low-complexity pools (approximately 80-120) of equal length DNA fragments. The resulting material is amplified and detected with the UMAS system, comprising all possible 4,096 (4(6)) DNA hexamers. Ligation to the arrays yields thousands of 14-mer sequence tags. The compendium of signals from all pools in the array-of-universal arrays comprises a full-transcriptome expression profile. The technology was validated by analysis of the galactose response of Saccharomyces cerevisiae, and the resulting profiles showed excellent agreement with the literature and real-time PCR assays. The technology was also used to demonstrate expression profiling from a hybrid organism in a proof-of-concept experiment where a T-cell receptor gene was expressed in yeast.

3' Untranslated Regions↗

PubMed2003

Unwrapping glial biology: Gcm target genes regulating glial development, diversification, and function.

Glia are the most abundant cell type in the mammalian brain. They regulate neuronal development and function, CNS immune surveillance, and stem cell biology, yet we know surprisingly little about glia in any organism. Here we identify over 40 new Drosophila glial genes. We use glial cells missing (gcm) mutants and misexpression to verify they are Gcm regulated in vivo. Many genes show unique spatiotemporal responsiveness to Gcm in the CNS, and thus glial subtype diversification requires spatially or temporally restricted Gcm cofactors. These genes provide insights into glial biology: we show unc-5 (a repulsive netrin receptor) orients glial migrations and the draper gene mediates glial engulfment of apoptotic neurons and larval locomotion. Many identified Drosophila glial genes have homologs expressed in mammalian glia, revealing conserved molecular features of glial cells. 80% of these Drosophila glial genes have mammalian homologs; these are now excellent candidates for regulating human glial development, function, or disease.

Animals↗

PubMed2003

Reconstructing the temporal ordering of biological samples using microarray data.

MOTIVATION: Accurate time series for biological processes are difficult to estimate due to problems of synchronization, temporal sampling and rate heterogeneity. Methods are needed that can utilize multi-dimensional data, such as those resulting from DNA microarray experiments, in order to reconstruct time series from unordered or poorly ordered sets of observations. RESULTS: We present a set of algorithms for estimating temporal orderings from unordered sets of sample elements. The techniques we describe are based on modifications of a minimum-spanning tree calculated from a weighted, undirected graph. We demonstrate the efficacy of our approach by applying these techniques to an artificial data set as well as several gene expression data sets derived from DNA microarray experiments. In addition to estimating orderings, the techniques we describe also provide useful heuristics for assessing relevant properties of sample datasets such as noise and sampling intensity, and we show how a data structure called a PQ-tree can be used to represent uncertainty in a reconstructed ordering. AVAILABILITY: Academic implementations of the ordering algorithms are available as source code (in the programming language Python) on our web site, along with documentation on their use. The artificial 'jelly roll' data set upon which the algorithm was tested is also available from this web site. The publicly available gene expression data may be found at http://genome-www.stanford.edu/cellcycle/ and http://caulobacter.stanford.edu/CellCycle/.

Algorithms↗

PubMed2003

Evolution of gene expression in the Drosophila melanogaster subgroup.

Little is known about broad patterns of variation and evolution of gene expression during any developmental process. Here we investigate variation in genome-wide gene expression among Drosophila simulans, Drosophila yakuba and four strains of Drosophila melanogaster during a major developmental transition--the start of metamorphosis. Differences in gene activity between these lineages follow a phylogenetic pattern, and 27% of all of the genes in these genomes differ in their developmental gene expression between at least two strains or species. We identify, on a gene-by-gene basis, the evolutionary forces that shape this variation and show that, both within the transcriptional network that controls metamorphosis and across the whole genome, the expression changes of transcription factor genes are relatively stable, whereas those of their downstream targets are more likely to have evolved. Our results demonstrate extensive evolution of developmental gene expression among closely related species.

Algorithms↗

PubMed2002

Gene discovery by e-genetics: Drosophila odor and taste receptors.

A new algorithm that examines DNA databases for proteins that have a particular structure, as opposed to a particular sequence, represents a novel 'e-genetics' approach to gene discovery. The algorithm has successfully identified new G-protein-coupled receptors, which have a characteristic seven-transmembrane-domain structure, from the Drosophila genome database. In particular, it has revealed novel families of odor receptors and taste receptors, which had long eluded identification by other means. The two new gene families, the Or and Gr genes, are expressed in neurons of olfactory and taste sensilla and are highly divergent from all other known G-protein-coupled receptor genes. Modification of the algorithm should allow identification of other classes of multitransmembrane-domain protein.

Algorithms↗

PubMed2002

A combinatorial toolbox for protein sequence design and landscape analysis in the grand canonical model.

In modern biology, one of the most important research problems is to understand how protein sequences fold into their native 3D structures. To investigate this problem at a high level, one wishes to analyze the protein landscapes, i.e., the structures of the space of all protein sequences and their native 3D structures. Perhaps the most basic computational problem at this level is to take a target 3D structure as input and design a fittest protein sequence with respect to one or more fitness functions of the target 3D structure. We develop a toolbox of combinatorial techniques for protein landscape analysis in the Grand Canonical model of Sun, Brem, Chan, and Dill. The toolbox is based on linear programming, network flow, and a linear-size representation of all minimum cuts of a network. It not only substantially expands the network flow technique for protein sequence design in Kleinberg's seminal work but also is applicable to a considerably broader collection of computational problems than those considered by Kleinberg. We have used this toolbox to obtain a number of efficient algorithms and hardness results. We have further used the algorithms to analyze 3D structures drawn from the Protein Data Bank and have discovered some novel relationships between such native 3D structures and the Grand Canonical model.

Algorithms↗