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.

Nim1-related kinases coordinate cell cycle progression with the organization of the peripheral cytoskeleton in yeast

Abstract: The mechanisms that couple cell cycle progression with the organization of the peripheral cytoskeleton are poorly understood. In Saccharomyces cerevisiae, the Swe1 protein has been shown previously to phosphorylate and inactivate the cyclin-dependent kinase, Cdc28, thereby delaying the onset of mitosis. The nim1-related protein kinase, Hsl1, induces entry into mitosis by negatively regulating Swe1. We have found that Hsl1 physically associates with the septin cytoskeleton in vivo and that Hsl1 kinase activity depends on proper septin function. Genetic analysis indicates that two additional Hsl1-related kinases, Kcc4 and Gin4, act redundantly with Hsl1 to regulate Swe1. Kcc4, like Hsl1 and Gin4, was found to localize to the bud neck in a septin-dependent fashion. Interestingly, hsl1 kcc4 gin4 triple mutants develop a cellular morphology extremely similar to that of septin mutants. Consistent with the idea that Hsl1, Kcc4, and Gin4 link entry into mitosis to proper septin organization, we find that septin mutants incubated at the restrictive temperature trigger a Swe1-dependent mitotic delay that is necessary to maintain cell viability. These results reveal for the first time how cells monitor the organization of their cytoskeleton and demonstrate the existence of a cell cycle checkpoint that responds to defects in the peripheral cytoskeleton. Moreover, Hsl1, Kcc4, and Gin4 have homologs in higher eukaryotes, suggesting that the regulation of Swe1/Wee1 by this class of kinases is highly conserved.

Wearables and the medical revolution.

Abstract: Wearable sensors are already impacting healthcare and medicine by enabling health monitoring outside of the clinic and prediction of health events. This paper reviews current and prospective wearable technologies and their progress toward clinical application. We describe technologies underlying common, commercially available wearable sensors and early-stage devices and outline research, when available, to support the use of these devices in healthcare. We cover applications in the following health areas: metabolic, cardiovascular and gastrointestinal monitoring; sleep, neurology, movement disorders and mental health; maternal, pre- and neo-natal care; and pulmonary health and environmental exposures. Finally, we discuss challenges associated with the adoption of wearable sensors in the current healthcare ecosystem and discuss areas for future research and development.

Comparison of the transcriptional landscapes between human and mouse tissues

Abstract: Although the similarities between humans and mice are typically highlighted, morphologically and genetically, there are many differences. To better understand these two species on a molecular level, we performed a comparison of the expression profiles of 15 tissues by deep RNA sequencing and examined the similarities and differences in the transcriptome for both protein-coding and -noncoding transcripts. Although commonalities are evident in the expression of tissue-specific genes between the two species, the expression for many sets of genes was found to be more similar in different tissues within the same species than between species. These findings were further corroborated by associated epigenetic histone mark analyses. We also find that many noncoding transcripts are expressed at a low level and are not detectable at appreciable levels across individuals. Moreover, the majority lack obvious sequence homologs between species, even when we restrict our attention to those which are most highly reproducible across biological replicates. Overall, our results indicate that there is considerable RNA expression diversity between humans and mice, well beyond what was described previously, likely reflecting the fundamental physiological differences between these two organisms.

Non-equivalence of Wnt and R-spondin ligands during Lgr5 + intestinal stem-cell self-renewal

Abstract: The canonical Wnt/β-catenin signalling pathway governs diverse developmental, homeostatic and pathological processes. Palmitoylated Wnt ligands engage cell-surface frizzled (FZD) receptors and LRP5 and LRP6 co-receptors, enabling β-catenin nuclear translocation and TCF/LEF-dependent gene transactivation. Mutations in Wnt downstream signalling components have revealed diverse functions thought to be carried out by Wnt ligands themselves. However, redundancy between the 19 mammalian Wnt proteins and 10 FZD receptors and Wnt hydrophobicity have made it difficult to attribute these functions directly to Wnt ligands. For example, individual mutations in Wnt ligands have not revealed homeostatic phenotypes in the intestinal epithelium-an archetypal canonical, Wnt pathway-dependent, rapidly self-renewing tissue, the regeneration of which is fueled by proliferative crypt Lgr5+ intestinal stem cells (ISCs). R-spondin ligands (RSPO1-RSPO4) engage distinct LGR4-LGR6, RNF43 and ZNRF3 receptor classes, markedly potentiate canonical Wnt/β-catenin signalling, and induce intestinal organoid growth in vitro and Lgr5+ ISCs in vivo. However, the interchangeability, functional cooperation and relative contributions of Wnt versus RSPO ligands to in vivo canonical Wnt signalling and ISC biology remain unknown. Here we identify the functional roles of Wnt and RSPO ligands in the intestinal crypt stem-cell niche. We show that the default fate of Lgr5+ ISCs is to differentiate, unless both RSPO and Wnt ligands are present. However, gain-of-function studies using RSPO ligands and a new non-lipidated Wnt analogue reveal that these ligands have qualitatively distinct, non-interchangeable roles in ISCs. Wnt proteins are unable to induce Lgr5+ ISC self-renewal, but instead confer a basal competency by maintaining RSPO receptor expression that enables RSPO ligands to actively drive and specify the extent of stem-cell expansion. This functionally non-equivalent yet cooperative interaction between Wnt and RSPO ligands establishes a molecular precedent for regulation of mammalian stem cells by distinct priming and self-renewal factors, with broad implications for precise control of tissue regeneration.

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.