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.

Fast optimal genome tiling with applications to microarray design and homology search.

Abstract: In this paper, we consider several variations of the following basic tiling problem: given a sequence of real numbers with two size-bound parameters, we want to find a set of tiles of maximum total weight such that each tiles satisfies the size bounds. A solution to this problem is important to a number of computational biology applications such as selecting genomic DNA fragments for PCR-based amplicon microarrays and performing homology searches with long sequence queries. Our goal is to design efficient algorithms with linear or near-linear time and space in the normal range of parameter values for these problems. For this purpose, we first discuss the solution to a basic online interval maximum problem via a sliding-window approach and show how to use this solution in a nontrivial manner for many of the tiling problems introduced. We also discuss NP-hardness results and approximation algorithms for generalizing our basic tiling problem to higher dimensions. Finally, computational results from applying our tiling algorithms to genomic sequences of five model eukaryotes are reported.

Full Genome Sequence of the Western Reserve Strain of Vaccinia Virus Determined by Third-Generation Sequencing.

Abstract: The vaccinia virus is a large, complex virus belonging to the Poxviridae family. Here, we report the complete, annotated genome sequence of the neurovirulent Western Reserve laboratory strain of this virus, which was sequenced on the Pacific Biosciences RS II and Oxford Nanopore MinION platforms.

Serum profiling using protein microarrays to identify disease related antigens.

Abstract: Disease related antigens are of great importance in the clinic. They are used as markers to screen patients for various forms of cancer, to monitor response to therapy, or to serve as therapeutic targets (Chapman et al., Ann Oncol 18(5):868–873, 2007; Soussi et al., Cancer Res 60:1777–1788, 2000; Anderson and LaBaer, J Proteome Res 4:1123–1133, 2005; Levenson, Biochim Biophy Acta 1770:847–856, 2007). In cancer endogenous levels of protein expression may be disrupted or proteins may be expressed in an aberrant fashion resulting in an immune response that bypasses self tolerance (Soussi et al., Cancer Res 60:1777–1788, 2000; Disis et al., J Clin Oncol 15(11):3363–3367, 1997; Molina et al., Breast Cancer Res Treat 51:109–119, 1998). Protein microarrays, which represent a large fraction of the human proteome, have been used to identify antigens in multiple diseases including cancer (Anderson and LaBaer, J Proteome Res 4:1123–1133, 2005; Disis et al., J Clin Oncol 15(11):3363–3367, 1997; Hudson et al., Proc Natl Acad Sci U S A 104(44):17494–17499, 2007; Beyer et al., J Neuroimmunol 242:26–32, 2012). Typically, arrays are probed with immunoglobulin (Ig) samples from patients as well as healthy controls, then compared to determine which antigens (Ag's) are more reactive within the patient group (Hudson et al., Proc Natl Acad Sci U S A 104(44):17494–17499).

Isolated Congenital Anosmia and CNGA2 Mutation.

Abstract: Isolated congenital anosmia (ICA) is a rare condition that is associated with life-long inability to smell Here we report a genetic characterization of a large Iranian family segregating ICA Whole exome sequencing in five affected family members and five healthy members revealed a stop gain mutation in CNGA2 (OMIM 300338) (chrX:150,911,102; CNGA2 c577C > T; pArg193*) The mutation segregates in an X-linked pattern, as all the affected family members are hemizygotes, whereas healthy family members are either heterozygote or homozygote for the reference allele cnga2 knockout mice are congenitally anosmic and have abnormal olfactory system physiology, additionally Karstensen et al recently reported two anosmic brothers sharing a CNGA2 truncating variant Our study in concert with these findings provides strong support for role of CNGA2 gene with pathogenicity of ICA in humans Together, these results indicate that mutations in key olfactory signaling pathway genes are responsible for human disease

Two short autoepitopes on the nuclear dot antigen are similar to epitopes encoded by the Epstein-Barr virus.

Abstract: To understand the relationship between antibodies present in patients with anti-nuclear dot (ND) autoimmune disease and the proteins they recognize, epitopes that react with the autoantibodies were mapped. A panel of fusion proteins containing different portions of the ND protein were overproduced in Escherichia coli. Immunoblot analysis with anti-ND antibodies revealed that most (10 of 12) sera recognize two major autoepitopes that are each a maximum of 8 amino acids long. The other two sera recognize one of the two epitopes. In addition to the short linear autoepitopes, a conformational epitope appears to be present on the ND antigen. Each of the two linear epitope sequences shares sequence similarities with those of several viral proteins found in the databases. Furthermore, two fusion proteins containing short Epstein-Barr virus (EBV) protein sequences that are similar to the ND epitopes were recognized by the human autoimmune sera, indicating that the autoepitopes are present in EBV protein sequences. Our results are consistent with the hypothesis that ND autoimmune disease might be associated with EBV infections.

STAR: ultrafast universal RNA-seq aligner

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/.

Ultrafast and memory-efficient alignment of short DNA sequences to the human genome

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.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

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。

RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

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.

An integrated encyclopedia of DNA elements in the human genome

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.