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Author

Michael Snyder

Bio: Michael Snyder is an academic researcher from Stanford University. The author has contributed to research in topics: Gene & Genome. The author has an hindex of 169, co-authored 840 publications receiving 130225 citations. Previous affiliations of Michael Snyder include Wyss Institute for Biologically Inspired Engineering & Public Health Research Institute.
Topics: Gene, Genome, Medicine, Chromatin, Human genome


Papers
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Journal ArticleDOI
TL;DR: Tilescope is a fully integrated data processing pipeline for analyzing high-density tiling-array data, designed with a modular, three-tiered architecture, facilitating parallelism, and a graphic user-friendly interface.
Abstract: We developed Tilescope, a fully integrated data processing pipeline for analyzing high-density tiling-array data http://tilescope.gersteinlab.org. In a completely automated fashion, Tilescope will normalize signals between channels and across arrays, combine replicate experiments, score each array element, and identify genomic features. The program is designed with a modular, three-tiered architecture, facilitating parallelism, and a graphic user-friendly interface, presenting results in an organized web page, downloadable for further analysis.

50 citations

Journal ArticleDOI
TL;DR: In this paper, the effects of individual gene variants on sarcomeric protein biomechanics were investigated at the cellular level in hypertrophic cardiomyopathy (HCM) patients.
Abstract: Background: Hypertrophic cardiomyopathy (HCM) is a complex disease partly explained by the effects of individual gene variants on sarcomeric protein biomechanics. At the cellular level, HCM mutatio...

50 citations

Journal ArticleDOI
24 Aug 2010-Yeast
TL;DR: A 1026 bp gene (CaHygB) that encodes Escherichia coli hygromycin B phosphotransferase with C. albicans codons should be a useful tool for genetic manipulation of different C.Albicans strains, including clinical isolates.
Abstract: Synthetic genes that confer resistance to the antibiotic nourseothricin in the pathogenic fungus Candida albicans are available, but genes conferring resistance to other antibiotics are not. We found that multiple C. albicans strains were inhibited by hygromycin B, so we designed a 1026 bp gene (CaHygB) that encodes Escherichia coli hygromycin B phosphotransferase with C. albicans codons. CaHygB conferred hygromycin B resistance in C. albicans transformed with ars2-containing plasmids or single-copy integrating vectors. Since CaHygB did not confer nourseothricin resistance and since the nourseothricin resistance marker SAT-1 did not confer hygromycin B resistance, we reasoned that these two markers could be used for homologous gene disruptions in wild-type C. albicans. We used PCR to fuse CaHygB or SAT-1 to approximately 1 kb of 5′ and 3′ noncoding DNA from C. albicans ARG4, HIS1 and LEU2, and introduced the resulting amplicons into six wild-type C. albicans strains. Homologous targeting frequencies were approximately 50–70%, and disruption of ARG4, HIS1 and LEU2 alleles was verified by the respective transformants' inabilities to grow without arginine, histidine and leucine. CaHygB should be a useful tool for genetic manipulation of different C. albicans strains, including clinical isolates. Copyright © 2010 John Wiley & Sons, Ltd.

49 citations

Journal ArticleDOI
TL;DR: Identification of tissue-specific binding profiles and effector target genes reveals important insights into the mechanisms by which Rb/E2F controls distinct cell fates in vivo.
Abstract: Background The tumor suppressor Rb/E2F regulates gene expression to control differentiation in multiple tissues during development, although how it directs tissue-specific gene regulation in vivo is poorly understood.

49 citations

Journal ArticleDOI
TL;DR: How 5-LO-mediated pulmonary inflammation synergized with phenotypically-silent Bmpr2 defects to elicit significant pulmonary vascular disease in rats is determined and suggests that TGF-β is critical for neointimal transformation.
Abstract: Background: Bmpr2 (bone morphogenetic protein receptor 2) mutations are critical risk factors for hereditary pulmonary arterial hypertension (PAH) with approximately 20% of carriers developing dise...

49 citations


Cited by
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Journal ArticleDOI
TL;DR: The Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure outperforms other aligners by a factor of >50 in mapping speed.
Abstract: Motivation Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. Results To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. Availability and implementation STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.

30,684 citations

Journal ArticleDOI
TL;DR: Bowtie extends previous Burrows-Wheeler techniques with a novel quality-aware backtracking algorithm that permits mismatches and can be used simultaneously to achieve even greater alignment speeds.
Abstract: Bowtie is an ultrafast, memory-efficient alignment program for aligning short DNA sequence reads to large genomes. For the human genome, Burrows-Wheeler indexing allows Bowtie to align more than 25 million reads per CPU hour with a memory footprint of approximately 1.3 gigabytes. Bowtie extends previous Burrows-Wheeler techniques with a novel quality-aware backtracking algorithm that permits mismatches. Multiple processor cores can be used simultaneously to achieve even greater alignment speeds. Bowtie is open source http://bowtie.cbcb.umd.edu.

20,335 citations

28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
TL;DR: It is shown that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads, and estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired- end reads, depending on the number of possible splice forms for each gene.
Abstract: RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.

14,524 citations

Journal ArticleDOI
06 Sep 2012-Nature
TL;DR: The Encyclopedia of DNA Elements project provides new insights into the organization and regulation of the authors' genes and genome, and is an expansive resource of functional annotations for biomedical research.
Abstract: The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research.

13,548 citations