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Dive into the research topics where Michael R. Miller is active.

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Featured researches published by Michael R. Miller.


Cell | 2011

Mosaic Analysis with Double Markers Reveals Tumor Cell of Origin in Glioma

Chong Liu; Jonathan C. Sage; Michael R. Miller; Roel G.W. Verhaak; Simon Hippenmeyer; Hannes Vogel; Oded Foreman; Roderick T. Bronson; Akiko Nishiyama; Liqun Luo; Hui Zong

Cancer cell of origin is difficult to identify by analyzing cells within terminal stage tumors, whose identity could be concealed by the acquired plasticity. Thus, an ideal approach to identify the cell of origin is to analyze proliferative abnormalities in distinct lineages prior to malignancy. Here, we use mosaic analysis with double markers (MADM) in mice to model gliomagenesis by initiating concurrent p53/Nf1 mutations sporadically in neural stem cells (NSCs). Surprisingly, MADM-based lineage tracing revealed significant aberrant growth prior to malignancy only in oligodendrocyte precursor cells (OPCs), but not in any other NSC-derived lineages or NSCs themselves. Upon tumor formation, phenotypic and transcriptome analyses of tumor cells revealed salient OPC features. Finally, introducing the same p53/Nf1 mutations directly into OPCs consistently led to gliomagenesis. Our findings suggest OPCs as the cell of origin in this model, even when initial mutations occur in NSCs, and highlight the importance of analyzing premalignant stages to identify the cancer cell of origin.


Nature Reviews Genetics | 2016

Harnessing the power of RADseq for ecological and evolutionary genomics

Kimberly R. Andrews; Jeffrey M. Good; Michael R. Miller; Gordon Luikart; Paul A. Hohenlohe

High-throughput techniques based on restriction site-associated DNA sequencing (RADseq) are enabling the low-cost discovery and genotyping of thousands of genetic markers for any species, including non-model organisms, which is revolutionizing ecological, evolutionary and conservation genetics. Technical differences among these methods lead to important considerations for all steps of genomics studies, from the specific scientific questions that can be addressed, and the costs of library preparation and sequencing, to the types of bias and error inherent in the resulting data. In this Review, we provide a comprehensive discussion of RADseq methods to aid researchers in choosing among the many different approaches and avoiding erroneous scientific conclusions from RADseq data, a problem that has plagued other genetic marker types in the past.


Molecular Ecology | 2013

Genotyping‐by‐sequencing in ecological and conservation genomics

Shawn R. Narum; C. Alex Buerkle; John W. Davey; Michael R. Miller; Paul A. Hohenlohe

The fields of ecological and conservation genetics have developed greatly in recent decades through the use of molecular markers to investigate organisms in their natural habitat and to evaluate the effect of anthropogenic disturbances. However, many of these studies have been limited to narrow regions of the genome, allowing for limited inferences but making it difficult to generalize about the organisms and their evolutionary history. Tremendous advances in sequencing technology over the last decade (i.e. next-generation sequencing; NGS) have led to the ability to sample the genome much more densely and to observe the patterns of genetic variation that result from the full range of evolutionary processes acting across the genome (Allendorf et al. 2010; Stapley et al. 2010; Li et al. 2012). These studies are transforming molecular ecology by making many long-standing questions much more easily accessible in almost any organism. When studying the genetics of wild populations, it is desirable to samples tens, hundreds or even thousands of individuals. While it is now possible to sequence whole genomes for tens of individuals with small genome sizes, the sequencing of hundreds of individuals with large genomes remains prohibitively expensive, particularly where the genome sequence is unknown. Further, for the purpose of many studies, complete genomic sequence data for all individuals would be unnecessary and simply inflate the computational and bioinformatic costs. A major recent advance has been the development of genotyping-by-sequencing (GBS) approaches that allow a targeted fraction of the genome (a reduced representation library) to be sequenced with next-generation technology rather than the entire genome, even in species with little or no previous genomic information and large genomes. The subset of the genome to be sequenced in these GBS approaches may be targeted using restriction enzymes or capture probes or by sequencing the transcriptome (reviewed in Davey et al. 2011). In the future, as sequencing technology and computational and bioinformatic methods develop further, whole-genome resequencing may become the predominant method for ecological and conservation genomics. Currently, reduced representation approaches offer the ability to not only discover genetic variants such as SNPs but also genotype individuals at these newly discovered loci in the same data. This special issue on ‘Genotyping-by-Sequencing in Ecological and Conservation Genomics’ represents a diverse set of empirical and theoretical studies that demonstrate both the utility and some of the challenges of GBS in ecological and conservation genomics. The empirical studies include demonstrations of the utility of GBS for population genomics and association mapping, as well as the development of genomic resources (i.e. large SNP data sets) for target species. The studies also illustrate some of the differences between GBS methods, in particular, aligning paired-end reads to achieve longer consensus sequences in contrast to single-end reads with shorter alignments, and double-digest versus sonication methods to fragment DNA. In addition, several papers describe advanced data pipelines for handling GBS-related sequence data and critically evaluate best practices for GBS methods and potential biases and novel features associated with GBS data. Overall, this compilation of papers emphasizes that GBS has been quickly adopted by the scientific community and is expected to become a common tool for studies in molecular ecology.


The Journal of Pediatrics | 1965

Hypoventilation and cor pulmonale due to chronic upper airway obstruction

Victor D. Menashe; Cyrus Farrehi; Michael R. Miller

A syndrome of chronic upper airway obstruction, hypoventilation, and cor pulmonale seen in 2 patients is described. These children both manifested varying degrees of CO 2 retention, pulmonary hypertension, and right ventricular hypertrophy. Relief of the upper airway obstruction by tonsillectomy and adenoidectomy resulted in regression of the presenting symptoms and signs.


BMC Bioinformatics | 2006

A simple spreadsheet-based, MIAME-supportive format for microarray data: MAGE-TAB

Tim F. Rayner; Philippe Rocca-Serra; Paul T. Spellman; Helen C. Causton; Anna Farne; Ele Holloway; Rafael A. Irizarry; Junmin Liu; Donald Maier; Michael R. Miller; Kjell Petersen; John Quackenbush; Gavin Sherlock; Christian J. Stoeckert; Joseph White; Patricia L. Whetzel; Farrell Wymore; Helen Parkinson; Ugis Sarkans; Catherine A. Ball; Alvis Brazma

BackgroundSharing of microarray data within the research community has been greatly facilitated by the development of the disclosure and communication standards MIAME and MAGE-ML by the MGED Society. However, the complexity of the MAGE-ML format has made its use impractical for laboratories lacking dedicated bioinformatics support.ResultsWe propose a simple tab-delimited, spreadsheet-based format, MAGE-TAB, which will become a part of the MAGE microarray data standard and can be used for annotating and communicating microarray data in a MIAME compliant fashion.ConclusionMAGE-TAB will enable laboratories without bioinformatics experience or support to manage, exchange and submit well-annotated microarray data in a standard format using a spreadsheet. The MAGE-TAB format is self-contained, and does not require an understanding of MAGE-ML or XML.


Molecular Ecology | 2012

A conserved haplotype controls parallel adaptation in geographically distant salmonid populations

Michael R. Miller; Joseph P. Brunelli; Paul A. Wheeler; Sixin Liu; Caird E. Rexroad; Yniv Palti; Chris Q. Doe; Gary H. Thorgaard

Salmonid fishes exhibit extensive local adaptations owing to abundant environmental variation and precise natal homing. This extensive local adaptation makes conservation and restoration of salmonids a challenge. For example, defining unambiguous units of conservation is difficult, and restoration attempts often fail owing to inadequate adaptive matching of translocated populations. A better understanding of the genetic architecture of local adaptation in salmonids could provide valuable information to assist in conserving and restoring natural populations of these important species. Here, we use a combination of laboratory crosses and next‐generation sequencing to investigate the genetic architecture of the parallel adaptation of rapid development rate in two geographically and genetically distant populations of rainbow trout (Oncorhynchus mykiss). Strikingly, we find that not only is a parallel genetic mechanism used but that a conserved haplotype is responsible for this intriguing adaptation. The repeated use of adaptive genetic variation across distant geographical areas could be a general theme in salmonids and have important implications for conservation and restoration.


Nature Methods | 2009

TU-tagging: cell type–specific RNA isolation from intact complex tissues

Michael R. Miller; Kristin J. Robinson; Michael D. Cleary; Chris Q. Doe

We found that the combination of spatially restricted uracil phosphoribosyltransferase (UPRT) expression with 4-thiouracil delivery can be used to label and purify cell type–specific RNA from intact complex tissues in Drosophila melanogaster. This method is useful for isolating RNA from cell types that are difficult to isolate by dissection or dissociation methods and should work in many organisms, including mammals and other vertebrates.


Molecular Ecology | 2013

Genomic patterns of introgression in rainbow and westslope cutthroat trout illuminated by overlapping paired‐end RAD sequencing

Paul A. Hohenlohe; Mitch D. Day; Stephen J. Amish; Michael R. Miller; Nick Kamps-Hughes; Matthew C. Boyer; Clint C. Muhlfeld; Fred W. Allendorf; Eric A. Johnson; Gordon Luikart

Rapid and inexpensive methods for genomewide single nucleotide polymorphism (SNP) discovery and genotyping are urgently needed for population management and conservation. In hybridized populations, genomic techniques that can identify and genotype thousands of species‐diagnostic markers would allow precise estimates of population‐ and individual‐level admixture as well as identification of ‘super invasive’ alleles, which show elevated rates of introgression above the genomewide background (likely due to natural selection). Techniques like restriction‐site‐associated DNA (RAD) sequencing can discover and genotype large numbers of SNPs, but they have been limited by the length of continuous sequence data they produce with Illumina short‐read sequencing. We present a novel approach, overlapping paired‐end RAD sequencing, to generate RAD contigs of >300–400 bp. These contigs provide sufficient flanking sequence for design of high‐throughput SNP genotyping arrays and strict filtering to identify duplicate paralogous loci. We applied this approach in five populations of native westslope cutthroat trout that previously showed varying (low) levels of admixture from introduced rainbow trout (RBT). We produced 77 141 RAD contigs and used these data to filter and genotype 3180 previously identified species‐diagnostic SNP loci. Our population‐level and individual‐level estimates of admixture were generally consistent with previous microsatellite‐based estimates from the same individuals. However, we observed slightly lower admixture estimates from genomewide markers, which might result from natural selection against certain genome regions, different genomic locations for microsatellites vs. RAD‐derived SNPs and/or sampling error from the small number of microsatellite loci (n = 7). We also identified candidate adaptive super invasive alleles from RBT that had excessively high admixture proportions in hybridized cutthroat trout populations.


Nature Biotechnology | 2007

The Functional Genomics Experiment model (FuGE): an extensible framework for standards in functional genomics

Andrew R. Jones; Michael R. Miller; Ruedi Aebersold; Rolf Apweiler; Catherine A. Ball; Alvis Brazma; James DeGreef; Nigel Hardy; Henning Hermjakob; Simon J. Hubbard; Peter Hussey; Mark Igra; Helen Jenkins; Randall K. Julian; Kent Laursen; Stephen G. Oliver; Norman W. Paton; Susanna-Assunta Sansone; Ugis Sarkans; Christian J. Stoeckert; Chris F. Taylor; Patricia L. Whetzel; Joseph White; Paul T. Spellman; Angel Pizarro

The Functional Genomics Experiment data model (FuGE) has been developed to facilitate convergence of data standards for high-throughput, comprehensive analyses in biology. FuGE models the components of an experimental activity that are common across different technologies, including protocols, samples and data. FuGE provides a foundation for describing entire laboratory workflows and for the development of new data formats. The Microarray Gene Expression Data society and the Proteomics Standards Initiative have committed to using FuGE as the basis for defining their respective standards, and other standards groups, including the Metabolomics Standards Initiative, are evaluating FuGE in their development efforts. Adoption of FuGE by multiple standards bodies will enable uniform reporting of common parts of functional genomics workflows, simplify data-integration efforts and ease the burden on researchers seeking to fulfill multiple minimum reporting requirements. Such advances are important for transparent data management and mining in functional genomics and systems biology.


Cell | 2013

Developmentally regulated subnuclear genome reorganization restricts neural progenitor competence in Drosophila.

Minoree Kohwi; Joshua R. Lupton; Sen-Lin Lai; Michael R. Miller; Chris Q. Doe

Stem and/or progenitor cells often generate distinct cell types in a stereotyped birth order and over time lose competence to specify earlier-born fates by unknown mechanisms. In Drosophila, the Hunchback transcription factor acts in neural progenitors (neuroblasts) to specify early-born neurons, in part by indirectly inducing the neuronal transcription of its target genes, including the hunchback gene. We used in vivo immuno-DNA FISH and found that the hunchback gene moves to the neuroblast nuclear periphery, a repressive subnuclear compartment, precisely when competence to specify early-born fate is lost and several hours and cell divisions after termination of its transcription. hunchback movement to the lamina correlated with downregulation of the neuroblast nuclear protein, Distal antenna (Dan). Either prolonging Dan expression or disrupting lamina interfered with hunchback repositioning and extended neuroblast competence. We propose that neuroblasts undergo a developmentally regulated subnuclear genome reorganization to permanently silence Hunchback target genes that results in loss of progenitor competence.

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Eric A. Johnson

University of Wisconsin-Madison

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Chris Q. Doe

Howard Hughes Medical Institute

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Sean O'Rourke

University of California

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Omar A. Ali

University of California

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