Timothy I. Shaw
University of Georgia
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Featured researches published by Timothy I. Shaw.
Genome Research | 2011
Dent Earl; Keith Bradnam; John St. John; Aaron E. Darling; Dawei Lin; Joseph Fass; Hung On Ken Yu; Vince Buffalo; Daniel R. Zerbino; Mark Diekhans; Ngan Nguyen; Pramila Ariyaratne; Wing-Kin Sung; Zemin Ning; Matthias Haimel; Jared T. Simpson; Nuno A. Fonseca; Inanc Birol; T. Roderick Docking; Isaac Ho; Daniel S. Rokhsar; Rayan Chikhi; Dominique Lavenier; Guillaume Chapuis; Delphine Naquin; Nicolas Maillet; Michael C. Schatz; David R. Kelley; Adam M. Phillippy; Sergey Koren
Low-cost short read sequencing technology has revolutionized genomics, though it is only just becoming practical for the high-quality de novo assembly of a novel large genome. We describe the Assemblathon 1 competition, which aimed to comprehensively assess the state of the art in de novo assembly methods when applied to current sequencing technologies. In a collaborative effort, teams were asked to assemble a simulated Illumina HiSeq data set of an unknown, simulated diploid genome. A total of 41 assemblies from 17 different groups were received. Novel haplotype aware assessments of coverage, contiguity, structure, base calling, and copy number were made. We establish that within this benchmark: (1) It is possible to assemble the genome to a high level of coverage and accuracy, and that (2) large differences exist between the assemblies, suggesting room for further improvements in current methods. The simulated benchmark, including the correct answer, the assemblies, and the code that was used to evaluate the assemblies is now public and freely available from http://www.assemblathon.org/.
GigaScience | 2013
Keith Bradnam; Joseph Fass; Anton Alexandrov; Paul Baranay; Michael Bechner; Inanc Birol; Sébastien Boisvert; Jarrod Chapman; Guillaume Chapuis; Rayan Chikhi; Hamidreza Chitsaz; Wen Chi Chou; Jacques Corbeil; Cristian Del Fabbro; Roderick R. Docking; Richard Durbin; Dent Earl; Scott J. Emrich; Pavel Fedotov; Nuno A. Fonseca; Ganeshkumar Ganapathy; Richard A. Gibbs; Sante Gnerre; Élénie Godzaridis; Steve Goldstein; Matthias Haimel; Giles Hall; David Haussler; Joseph Hiatt; Isaac Ho
BackgroundThe process of generating raw genome sequence data continues to become cheaper, faster, and more accurate. However, assembly of such data into high-quality, finished genome sequences remains challenging. Many genome assembly tools are available, but they differ greatly in terms of their performance (speed, scalability, hardware requirements, acceptance of newer read technologies) and in their final output (composition of assembled sequence). More importantly, it remains largely unclear how to best assess the quality of assembled genome sequences. The Assemblathon competitions are intended to assess current state-of-the-art methods in genome assembly.ResultsIn Assemblathon 2, we provided a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and snake). This resulted in a total of 43 submitted assemblies from 21 participating teams. We evaluated these assemblies using a combination of optical map data, Fosmid sequences, and several statistical methods. From over 100 different metrics, we chose ten key measures by which to assess the overall quality of the assemblies.ConclusionsMany current genome assemblers produced useful assemblies, containing a significant representation of their genes and overall genome structure. However, the high degree of variability between the entries suggests that there is still much room for improvement in the field of genome assembly and that approaches which work well in assembling the genome of one species may not necessarily work well for another.
Cell | 2016
Kyung Ha Lee; Peipei Zhang; Hong Joo Kim; Diana M. Mitrea; Mohona Sarkar; Brian D. Freibaum; Jaclyn Cika; Maura Coughlin; James Messing; Amandine Molliex; Brian A. Maxwell; Nam Chul Kim; Jamshid Temirov; Jennifer C. Moore; Regina Maria Kolaitis; Timothy I. Shaw; Bing Bai; Junmin Peng; Richard W. Kriwacki; J. Paul Taylor
Expansion of a hexanucleotide repeat GGGGCC (G4C2) in C9ORF72 is the most common cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Transcripts carrying (G4C2) expansions undergo unconventional, non-ATG-dependent translation, generating toxic dipeptide repeat (DPR) proteins thought to contribute to disease. Here, we identify the interactome of all DPRs and find that arginine-containing DPRs, polyGly-Arg (GR) and polyPro-Arg (PR), interact with RNA-binding proteins and proteins with low complexity sequence domains (LCDs) that often mediate the assembly of membrane-less organelles. Indeed, most GR/PR interactors are components of membrane-less organelles such as nucleoli, the nuclear pore complex and stress granules. Genetic analysis in Drosophila demonstrated the functional relevance of these interactions to DPR toxicity. Furthermore, we show that GR and PR altered phase separation of LCD-containing proteins, insinuating into their liquid assemblies and changing their material properties, resulting in perturbed dynamics and/or functions of multiple membrane-less organelles.
Nucleic Acids Research | 2013
Timothy I. Shaw; Zheng Ruan; Travis C. Glenn; Liang Liu
The coalescent methods for species tree reconstruction are increasingly popular because they can accommodate coalescence and multilocus data sets. Herein, we present STRAW, a web server that offers workflows for reconstruction of phylogenies of species using three species tree methods—MP-EST, STAR and NJst. The input data are a collection of rooted gene trees (for STAR and MP-EST methods) or unrooted gene trees (for NJst). The output includes the estimated species tree, modified Robinson-Foulds distances between gene trees and the estimated species tree and visualization of trees to compare gene trees with the estimated species tree. The web sever is available at http://bioinformatics.publichealth.uga.edu/SpeciesTreeAnalysis/.
GigaScience | 2013
Keith Bradnam; Joseph Fass; Anton Alexandrov; Paul Baranay; Michael Bechner; Inanc Birol; Sébastien Boisvert; Jarrod Chapman; Guillaume Chapuis; Rayan Chikhi; Hamidreza Chitsaz; Wen-Chi Chou; Jacques Corbeil; Cristian Del Fabbro; T. Roderick Docking; Richard Durbin; Dent Earl; Scott J. Emrich; Pavel Fedotov; Nuno A. Fonseca; Ganeshkumar Ganapathy; Richard A. Gibbs; Sante Gnerre; Élénie Godzaridis; Steve Goldstein; Matthias Haimel; Giles Hall; David Haussler; Joseph Hiatt; Isaac Ho
BackgroundThe process of generating raw genome sequence data continues to become cheaper, faster, and more accurate. However, assembly of such data into high-quality, finished genome sequences remains challenging. Many genome assembly tools are available, but they differ greatly in terms of their performance (speed, scalability, hardware requirements, acceptance of newer read technologies) and in their final output (composition of assembled sequence). More importantly, it remains largely unclear how to best assess the quality of assembled genome sequences. The Assemblathon competitions are intended to assess current state-of-the-art methods in genome assembly.ResultsIn Assemblathon 2, we provided a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and snake). This resulted in a total of 43 submitted assemblies from 21 participating teams. We evaluated these assemblies using a combination of optical map data, Fosmid sequences, and several statistical methods. From over 100 different metrics, we chose ten key measures by which to assess the overall quality of the assemblies.ConclusionsMany current genome assemblers produced useful assemblies, containing a significant representation of their genes and overall genome structure. However, the high degree of variability between the entries suggests that there is still much room for improvement in the field of genome assembly and that approaches which work well in assembling the genome of one species may not necessarily work well for another.
PLOS ONE | 2012
Timothy I. Shaw; Anuj Srivastava; Wen-Chi Chou; Liang Liu; Ann Hawkinson; Travis C. Glenn; Rick A. Adams; Tony Schountz
The Jamaican fruit bat (Artibeus jamaicensis) is one of the most common bats in the tropical Americas. It is thought to be a potential reservoir host of Tacaribe virus, an arenavirus closely related to the South American hemorrhagic fever viruses. We performed transcriptome sequencing and annotation from lung, kidney and spleen tissues using 454 and Illumina platforms to develop this species as an animal model. More than 100,000 contigs were assembled, with 25,000 genes that were functionally annotated. Of the remaining unannotated contigs, 80% were found within bat genomes or transcriptomes. Annotated genes are involved in a broad range of activities ranging from cellular metabolism to genome regulation through ncRNAs. Reciprocal BLAST best hits yielded 8,785 sequences that are orthologous to mouse, rat, cattle, horse and human. Species tree analysis of sequences from 2,378 loci was used to achieve 95% bootstrap support for the placement of bat as sister to the clade containing horse, dog, and cattle. Through substitution rate estimation between bat and human, 32 genes were identified with evidence for positive selection. We also identified 466 immune-related genes, which may be useful for studying Tacaribe virus infection of this species. The Jamaican fruit bat transcriptome dataset is a resource that should provide additional candidate markers for studying bat evolution and ecology, and tools for analysis of the host response and pathology of disease.
Immunity | 2017
Haiyan Tan; Kai Yang; Yuxin Li; Timothy I. Shaw; Yanyan Wang; Daniel Bastardo Blanco; Xusheng Wang; Ji-Hoon Cho; Hong Wang; Sherri Rankin; Cliff Guy; Junmin Peng; Hongbo Chi
SUMMARY The molecular circuits by which antigens activate quiescent T cells remain poorly understood. We combined temporal profiling of the whole proteome and phosphoproteome via multiplexed isobaric labeling proteomics technology, computational pipelines for integrating multi‐omics datasets, and functional perturbation to systemically reconstruct regulatory networks underlying T cell activation. T cell receptors activated the T cell proteome and phosphoproteome with discrete kinetics, marked by early dynamics of phosphorylation and delayed ribosome biogenesis and mitochondrial activation. Systems biology analyses identified multiple functional modules, active kinases, transcription factors and connectivity between them, and mitochondrial pathways including mitoribosomes and complex IV. Genetic perturbation revealed physiological roles for mitochondrial enzyme COX10‐mediated oxidative phosphorylation in T cell quiescence exit. Our multi‐layer proteomics profiling, integrative network analysis, and functional studies define landscapes of the T cell proteome and phosphoproteome and reveal signaling and bioenergetics pathways that mediate lymphocyte exit from quiescence. HIGHLIGHTSProteome and phosphoproteome profiling reveals temporal dynamics of T cell activationTCR activates interconnected functional modules, kinases, and transcription factorsmTORC1 links TCR to mitoribosome biogenesis and complex IV activityCOX10 is crucial for T cell activation in vitro and in vivo &NA; Tan et al. apply multi‐layer proteomic profiling and systems biology approaches to define T cell proteome and phosphoproteome landscapes, and they identify signaling networks and bioenergetics pathways that mediate T cell quiescence exit. These data establish the function and mechanisms of oxidative phosphorylation and mitochondrial activation in antigen‐induced T cell responses.
BMC Bioinformatics | 2012
Yingfeng Wang; Amir Manzour; Pooya Shareghi; Timothy I. Shaw; Ying-Wai Li; Russell L. Malmberg; Liming Cai
BackgroundThe computational identification of RNAs in genomic sequences requires the identification of signals of RNA sequences. Shannon base pairing entropy is an indicator for RNA secondary structure fold certainty in detection of structural, non-coding RNAs (ncRNAs). Under the Boltzmann ensemble of secondary structures, the probability of a base pair is estimated from its frequency across all the alternative equilibrium structures. However, such an entropy has yet to deliver the desired performance for distinguishing ncRNAs from random sequences. Developing novel methods to improve the entropy measure performance may result in more effective ncRNA gene finding based on structure detection.ResultsThis paper shows that the measuring performance of base pairing entropy can be significantly improved with a constrained secondary structure ensemble in which only canonical base pairs are assumed to occur in energetically stable stems in a fold. This constraint actually reduces the space of the secondary structure and may lower the probabilities of base pairs unfavorable to the native fold. Indeed, base pairing entropies computed with this constrained model demonstrate substantially narrowed gaps of Z-scores between ncRNAs, as well as drastic increases in the Z-score for all 13 tested ncRNA sets, compared to shuffled sequences.ConclusionsThese results suggest the viability of developing effective structure-based ncRNA gene finding methods by investigating secondary structure ensembles of ncRNAs.
Molecular & Cellular Proteomics | 2015
Joseph Leo Mertz; Haiyan Tan; Vishwajeeth Pagala; Bing Bai; Ping-Chung Chen; Yuxin Li; Ji-Hoon Cho; Timothy I. Shaw; Xusheng Wang; Junmin Peng
The mind bomb 1 (Mib1) ubiquitin ligase is essential for controlling metazoan development by Notch signaling and possibly the Wnt pathway. It is also expressed in postmitotic neurons and regulates neuronal morphogenesis and synaptic activity by mechanisms that are largely unknown. We sought to comprehensively characterize the Mib1 interactome and study its potential function in neuron development utilizing a novel sequential elution strategy for affinity purification, in which Mib1 binding proteins were eluted under different stringency and then quantified by the isobaric labeling method. The strategy identified the Mib1 interactome with both deep coverage and the ability to distinguish high-affinity partners from low-affinity partners. A total of 817 proteins were identified during the Mib1 affinity purification, including 56 high-affinity partners and 335 low-affinity partners, whereas the remaining 426 proteins are likely copurified contaminants or extremely weak binding proteins. The analysis detected all previously known Mib1-interacting proteins and revealed a large number of novel components involved in Notch and Wnt pathways, endocytosis and vesicle transport, the ubiquitin-proteasome system, cellular morphogenesis, and synaptic activities. Immunofluorescence studies further showed colocalization of Mib1 with five selected proteins: the Usp9x (FAM) deubiquitinating enzyme, alpha-, beta-, and delta-catenins, and CDKL5. Mutations of CDKL5 are associated with early infantile epileptic encephalopathy-2 (EIEE2), a severe form of mental retardation. We found that the expression of Mib1 down-regulated the protein level of CDKL5 by ubiquitination, and antagonized CDKL5 function during the formation of dendritic spines. Thus, the sequential elution strategy enables biochemical characterization of protein interactomes; and Mib1 analysis provides a comprehensive interactome for investigating its role in signaling networks and neuronal development.
DNA Research | 2012
Anuj Srivastava; Kevin Winker; Timothy I. Shaw; Kenneth L. Jones; Travis C. Glenn
An effective way to understand the genomics of divergence in non-model organisms is to use the transcriptome to identify genes associated with divergence. We examine the transcriptome of the song sparrow (Melospiza melodia) and contrast it with the avian models zebra finch (Taeniopygia guttata) and chicken (Gallus gallus). We aimed to (i) obtain a functional annotation of a substantial portion of the song sparrow transcriptome; (ii) compare transcript divergence; (iii) efficiently characterize single nucleotide polymorphism/indel markers possibly fixed between song sparrow subspecies; and (iv) identify the most common set of transcripts in birds using the zebra finch as a reference. Using two individuals from each of three populations, whole-body mRNA was normalized and sequenced (110Mb total). The assembly yielded 38 539 contigs [N50 (the length–weighted median) = 482 bp]; 4574 were orthologous to both model genomes and 3680 are functionally annotated. This low-coverage scan of the song sparrow transcriptome revealed 29 982 SNPs/indels, 1402 fixed between populations and subspecies. Referencing zebra finch and chicken, we identified 43 and 5 fast-evolving genes, respectively. We also identified the most common set of transcripts present in birds with respect to zebra finch. This study provides new insight into songbird transcriptomes, and candidate markers identified here may help research in songbirds (oscine Passeriformes), a frequently studied group.