Melissa S. Cline
University of California, Santa Cruz
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Publication
Featured researches published by Melissa S. Cline.
Nucleic Acids Research | 2012
Timothy R. Dreszer; Donna Karolchik; Ann S. Zweig; Angie S. Hinrichs; Brian J. Raney; Robert M. Kuhn; Laurence R. Meyer; Matthew C. Wong; Cricket A. Sloan; Kate R. Rosenbloom; Greg Roe; Brooke Rhead; Andy Pohl; Venkat S. Malladi; Chin H. Li; Katrina Learned; Vanessa M. Kirkup; Fan Hsu; Rachel A. Harte; Luvina Guruvadoo; Mary Goldman; Belinda Giardine; Pauline A. Fujita; Mark Diekhans; Melissa S. Cline; Hiram Clawson; Galt P. Barber; David Haussler; W. James Kent
The University of California Santa Cruz Genome Browser (http://genome.ucsc.edu) offers online public access to a growing database of genomic sequence and annotations for a wide variety of organisms. The Browser is an integrated tool set for visualizing, comparing, analyzing and sharing both publicly available and user-generated genomic data sets. In the past year, the local database has been updated with four new species assemblies, and we anticipate another four will be released by the end of 2011. Further, a large number of annotation tracks have been either added, updated by contributors, or remapped to the latest human reference genome. Among these are new phenotype and disease annotations, UCSC genes, and a major dbSNP update, which required new visualization methods. Growing beyond the local database, this year we have introduced ‘track data hubs’, which allow the Genome Browser to provide access to remotely located sets of annotations. This feature is designed to significantly extend the number and variety of annotation tracks that are publicly available for visualization and analysis from within our site. We have also introduced several usability features including track search and a context-sensitive menu of options available with a right-click anywhere on the Browsers image.
Nucleic Acids Research | 2003
Guoying Liu; Ann E. Loraine; Ron Shigeta; Melissa S. Cline; Jill Cheng; Venu Valmeekam; Shaw Sun; David Kulp; Michael A. Siani-Rose
NetAffx (http://www.affymetrix.com) details and annotates probesets on Affymetrix GeneChip microarrays. These annotations include (i) static information specific to the probeset composition; (ii) sequence annotations extracted from public databases; and (iii) protein sequence-level annotations derived from public domain programs, as well as libraries of hidden Markov models (HMMs) developed at Affymetrix. For each probeset, NetAffx lists the probe sequences, and the consensus sequence interrogated by the probes; for the larger chip sets, interactive maps display this sequence data in genomic context. Sequence annotations include Gene Ontology (GO) terms and depiction of GO graph relationships; predicted protein domains and motifs; orthologous sequences; links to relevant pathways; and links to public databases including UniGene, LocusLink, SWISS-PROT and OMIM.
Nature Genetics | 2005
Jernej Ule; Aljaž Ule; Joanna L. Spencer; Alan Williams; Jing Shan Hu; Melissa S. Cline; Hui Wang; Tyson A. Clark; Claire E. Fraser; Matteo Ruggiu; Barry R. Zeeberg; David Kane; John N. Weinstein; John E. Blume; Robert B. Darnell
Alternative RNA splicing greatly increases proteome diversity and may thereby contribute to tissue-specific functions. We carried out genome-wide quantitative analysis of alternative splicing using a custom Affymetrix microarray to assess the role of the neuronal splicing factor Nova in the brain. We used a stringent algorithm to identify 591 exons that were differentially spliced in the brain relative to immune tissues, and 6.6% of these showed major splicing defects in the neocortex of Nova2−/− mice. We tested 49 exons with the largest predicted Nova-dependent splicing changes and validated all 49 by RT-PCR. We analyzed the encoded proteins and found that all those with defined brain functions acted in the synapse (34 of 40, including neurotransmitter receptors, cation channels, adhesion and scaffold proteins) or in axon guidance (8 of 40). Moreover, of the 35 proteins with known interaction partners, 74% (26) interact with each other. Validating a large set of Nova RNA targets has led us to identify a multi-tiered network in which Nova regulates the exon content of RNAs encoding proteins that interact in the synapse.
Genome Biology | 2012
John A. Stamatoyannopoulos; Michael Snyder; Ross C. Hardison; Bing Ren; Thomas R. Gingeras; David M. Gilbert; Mark Groudine; M. A. Bender; Rajinder Kaul; Theresa K. Canfield; Erica Giste; Audra K. Johnson; Mia Zhang; Gayathri Balasundaram; Rachel Byron; Vaughan Roach; Peter J. Sabo; Richard Sandstrom; A Sandra Stehling; Robert E. Thurman; Sherman M. Weissman; Philip Cayting; Manoj Hariharan; Jin Lian; Yong Cheng; Stephen G. Landt; Zhihai Ma; Barbara J. Wold; Job Dekker; Gregory E. Crawford
To complement the human Encyclopedia of DNA Elements (ENCODE) project and to enable a broad range of mouse genomics efforts, the Mouse ENCODE Consortium is applying the same experimental pipelines developed for human ENCODE to annotate the mouse genome.
Proteins | 2003
Rachel Karchin; Melissa S. Cline; Yael Mandel-Gutfreund; Kevin Karplus
An important problem in computational biology is predicting the structure of the large number of putative proteins discovered by genome sequencing projects. Fold‐recognition methods attempt to solve the problem by relating the target proteins to known structures, searching for template proteins homologous to the target. Remote homologs that may have significant structural similarity are often not detectable by sequence similarities alone. To address this, we incorporated predicted local structure, a generalization of secondary structure, into two‐track profile hidden Markov models (HMMs). We did not rely on a simple helix‐strand‐coil definition of secondary structure, but experimented with a variety of local structure descriptions, following a principled protocol to establish which descriptions are most useful for improving fold recognition and alignment quality. On a test set of 1298 nonhomologous proteins, HMMs incorporating a 3‐letter STRIDE alphabet improved fold recognition accuracy by 15% over amino‐acid‐only HMMs and 23% over PSI‐BLAST, measured by ROC‐65 numbers. We compared two‐track HMMs to amino‐acid‐only HMMs on a difficult alignment test set of 200 protein pairs (structurally similar with 3–24% sequence identity). HMMs with a 6‐letter STRIDE secondary track improved alignment quality by 62%, relative to DALI structural alignments, while HMMs with an STR track (an expanded DSSP alphabet that subdivides strands into six states) improved by 40% relative to CE. Proteins 2003;51:504–514.
Nucleic Acids Research | 2011
Mary Goldman; Brian Craft; Teresa Swatloski; Kyle Ellrott; Melissa S. Cline; Mark Diekhans; Singer Ma; Chris Wilks; Joshua M. Stuart; David Haussler; Jingchun Zhu
The UCSC Cancer Genomics Browser (https://genome-cancer.ucsc.edu) comprises a suite of web-based tools to integrate, visualize and analyze cancer genomics and clinical data. The browser displays whole-genome views of genome-wide experimental measurements for multiple samples alongside their associated clinical information. Multiple data sets can be viewed simultaneously as coordinated ‘heatmap tracks’ to compare across studies or different data modalities. Users can order, filter, aggregate, classify and display data interactively based on any given feature set including clinical features, annotated biological pathways and user-contributed collections of genes. Integrated standard statistical tools provide dynamic quantitative analysis within all available data sets. The browser hosts a growing body of publicly available cancer genomics data from a variety of cancer types, including data generated from the Cancer Genome Atlas project. Multiple consortiums use the browser on confidential prepublication data enabled by private installations. Many new features have been added, including the hgMicroscope tumor image viewer, hgSignature for real-time genomic signature evaluation on any browser track, and ‘PARADIGM’ pathway tracks to display integrative pathway activities. The browser is integrated with the UCSC Genome Browser; thus inheriting and integrating the Genome Browser’s rich set of human biology and genetics data that enhances the interpretability of the cancer genomics data.
Neuron | 2012
Konstantinos Charizanis; Kuang Yung Lee; Ranjan Batra; Marianne Goodwin; Chaolin Zhang; Yuan Yuan; Lily Shiue; Melissa S. Cline; Marina M. Scotti; Guangbin Xia; Ashok V. Kumar; Tetsuo Ashizawa; H. Brent Clark; Takashi Kimura; Masanori P. Takahashi; Harutoshi Fujimura; Kenji Jinnai; Hiroo Yoshikawa; Mário Gomes-Pereira; Geneviève Gourdon; Noriaki Sakai; Seiji Nishino; Thomas C. Foster; Manuel Ares; Robert B. Darnell; Maurice S. Swanson
The RNA-mediated disease model for myotonic dystrophy (DM) proposes that microsatellite C(C)TG expansions express toxic RNAs that disrupt splicing regulation by altering MBNL1 and CELF1 activities. While this model explains DM manifestations in muscle, less is known about the effects of C(C)UG expression on the brain. Here, we report that Mbnl2 knockout mice develop several DM-associated central nervous system (CNS) features including abnormal REM sleep propensity and deficits in spatial memory. Mbnl2 is prominently expressed in the hippocampus and Mbnl2 knockouts show a decrease in NMDA receptor (NMDAR) synaptic transmission and impaired hippocampal synaptic plasticity. While Mbnl2 loss did not significantly alter target transcript levels in the hippocampus, misregulated splicing of hundreds of exons was detected using splicing microarrays, RNA-seq, and HITS-CLIP. Importantly, the majority of the Mbnl2-regulated exons examined were similarly misregulated in DM. We propose that major pathological features of the DM brain result from disruption of the MBNL2-mediated developmental splicing program.
Nucleic Acids Research | 2011
Brian J. Raney; Melissa S. Cline; Kate R. Rosenbloom; Timothy R. Dreszer; Katrina Learned; Galt P. Barber; Laurence R. Meyer; Cricket A. Sloan; Venkat S. Malladi; Krishna M. Roskin; Bernard B. Suh; Angie S. Hinrichs; Hiram Clawson; Ann S. Zweig; Vanessa M. Kirkup; Pauline A. Fujita; Brooke Rhead; Kayla E. Smith; Andy Pohl; Robert M. Kuhn; Donna Karolchik; David Haussler; W. James Kent
The ENCODE project is an international consortium with a goal of cataloguing all the functional elements in the human genome. The ENCODE Data Coordination Center (DCC) at the University of California, Santa Cruz serves as the central repository for ENCODE data. In this role, the DCC offers a collection of high-throughput, genome-wide data generated with technologies such as ChIP-Seq, RNA-Seq, DNA digestion and others. This data helps illuminate transcription factor-binding sites, histone marks, chromatin accessibility, DNA methylation, RNA expression, RNA binding and other cell-state indicators. It includes sequences with quality scores, alignments, signals calculated from the alignments, and in most cases, element or peak calls calculated from the signal data. Each data set is available for visualization and download via the UCSC Genome Browser (http://genome.ucsc.edu/). ENCODE data can also be retrieved using a metadata system that captures the experimental parameters of each assay. The ENCODE web portal at UCSC (http://encodeproject.org/) provides information about the ENCODE data and links for access.
Proteins | 1997
Kevin Karplus; Kimmen Sjolander; Christian Barrett; Melissa S. Cline; David Haussler; Richard Hughey; Liisa Holm
We discuss how methods based on hidden Markov models performed in the fold‐recognition section of the CASP2 experiment. Hidden Markov models were built for a representative set of just over 1,000 structures from the Protein Data Bank (PDB). Each CASP2 target sequence was scored against this library of HMMs. In addition, an HMM was built for each of the target sequences and all of the sequences in PDB were scored against that target model, with a good score on both methods indicating a high probability that the target sequence is homologous to the structure. The method worked well in comparison to other methods used at CASP2 for targets of moderate difficulty, where the closest structure in PDB could be aligned to the target with at least 15% residue identity. Proteins, Suppl. 1:134–139, 1997.
Proceedings of the National Academy of Sciences of the United States of America | 2010
Nathan Salomonis; Christopher R. Schlieve; Laura Pereira; Christine Wahlquist; Alexandre Colas; Alexander C. Zambon; Karen Vranizan; Matthew J. Spindler; Alexander R. Pico; Melissa S. Cline; Tyson A. Clark; Alan Williams; John E. Blume; Eva Samal; Mark Mercola; Bradley J. Merrill; Bruce R. Conklin
Two major goals of regenerative medicine are to reproducibly transform adult somatic cells into a pluripotent state and to control their differentiation into specific cell fates. Progress toward these goals would be greatly helped by obtaining a complete picture of the RNA isoforms produced by these cells due to alternative splicing (AS) and alternative promoter selection (APS). To investigate the roles of AS and APS, reciprocal exon–exon junctions were interrogated on a genome-wide scale in differentiating mouse embryonic stem (ES) cells with a prototype Affymetrix microarray. Using a recently released open-source software package named AltAnalyze, we identified 144 genes for 170 putative isoform variants, the majority (67%) of which were predicted to alter protein sequence and domain composition. Verified alternative exons were largely associated with pathways of Wnt signaling and cell-cycle control, and most were conserved between mouse and human. To examine the functional impact of AS, we characterized isoforms for two genes. As predicted by AltAnalyze, we found that alternative isoforms of the gene Serca2 were targeted by distinct microRNAs (miRNA-200b, miRNA-214), suggesting a critical role for AS in cardiac development. Analysis of the Wnt transcription factor Tcf3, using selective knockdown of an ES cell-enriched and characterized isoform, revealed several distinct targets for transcriptional repression (Stmn2, Ccnd2, Atf3, Klf4, Nodal, and Jun) as well as distinct differentiation outcomes in ES cells. The findings herein illustrate a critical role for AS in the specification of ES cells with differentiation, and highlight the utility of global functional analyses of AS.