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Dive into the research topics where Anna-Liisa Prabhu is active.

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Featured researches published by Anna-Liisa Prabhu.


Genome Research | 2008

Application of massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells

Ryan D. Morin; Michael D. O'Connor; Malachi Griffith; Florian Kuchenbauer; Allen Delaney; Anna-Liisa Prabhu; Yongjun Zhao; Helen McDonald; Thomas Zeng; Martin Hirst; Connie J. Eaves; Marco A. Marra

MicroRNAs (miRNAs) are emerging as important, albeit poorly characterized, regulators of biological processes. Key to further elucidation of their roles is the generation of more complete lists of their numbers and expression changes in different cell states. Here, we report a new method for surveying the expression of small RNAs, including microRNAs, using Illumina sequencing technology. We also present a set of methods for annotating sequences deriving from known miRNAs, identifying variability in mature miRNA sequences, and identifying sequences belonging to previously unidentified miRNA genes. Application of this approach to RNA from human embryonic stem cells obtained before and after their differentiation into embryoid bodies revealed the sequences and expression levels of 334 known plus 104 novel miRNA genes. One hundred seventy-one known and 23 novel microRNA sequences exhibited significant expression differences between these two developmental states. Owing to the increased number of sequence reads, these libraries represent the deepest miRNA sampling to date, spanning nearly six orders of magnitude of expression. The predicted targets of those miRNAs enriched in either sample shared common features. Included among the high-ranked predicted gene targets are those implicated in differentiation, cell cycle control, programmed cell death, and transcriptional regulation.


Nature Methods | 2010

De novo assembly and analysis of RNA-seq data

Gordon Robertson; Jacqueline E. Schein; Readman Chiu; Richard Corbett; Matthew A. Field; Shaun D. Jackman; Karen Mungall; Sam Lee; Hisanaga Mark Okada; Jenny Q. Qian; Malachi Griffith; Anthony Raymond; Nina Thiessen; Timothee Cezard; Yaron S N Butterfield; Richard Newsome; Simon K. Chan; Rong She; Richard Varhol; Baljit Kamoh; Anna-Liisa Prabhu; Angela Tam; Yongjun Zhao; Richard A. Moore; Martin Hirst; Marco A. Marra; Steven J.M. Jones; Pamela A. Hoodless; Inanc Birol

We describe Trans-ABySS, a de novo short-read transcriptome assembly and analysis pipeline that addresses variation in local read densities by assembling read substrings with varying stringencies and then merging the resulting contigs before analysis. Analyzing 7.4 gigabases of 50-base-pair paired-end Illumina reads from an adult mouse liver poly(A) RNA library, we identified known, new and alternative structures in expressed transcripts, and achieved high sensitivity and specificity relative to reference-based assembly methods.


Nature | 2002

A physical map of the mouse genome

Simon G. Gregory; Mandeep Sekhon; Jacqueline E. Schein; Shaying Zhao; Kazutoyo Osoegawa; Carol Scott; Richard S. Evans; Paul W. Burridge; Tony Cox; Christopher A. Fox; Richard D. Hutton; Ian R. Mullenger; Kimbly J. Phillips; James Smith; Jim Stalker; Glen Threadgold; Ewan Birney; Kristine M. Wylie; Asif T. Chinwalla; John W. Wallis; LaDeana W. Hillier; Jason Carter; Tony Gaige; Sara Jaeger; Colin Kremitzki; Dan Layman; Jason Maas; Rebecca McGrane; Kelly Mead; Rebecca Walker

A physical map of a genome is an essential guide for navigation, allowing the location of any gene or other landmark in the chromosomal DNA. We have constructed a physical map of the mouse genome that contains 296 contigs of overlapping bacterial clones and 16,992 unique markers. The mouse contigs were aligned to the human genome sequence on the basis of 51,486 homology matches, thus enabling use of the conserved synteny (correspondence between chromosome blocks) of the two genomes to accelerate construction of the mouse map. The map provides a framework for assembly of whole-genome shotgun sequence data, and a tile path of clones for generation of the reference sequence. Definition of the human–mouse alignment at this level of resolution enables identification of a mouse clone that corresponds to almost any position in the human genome. The human sequence may be used to facilitate construction of other mammalian genome maps using the same strategy.


Genome Research | 2008

In-depth characterization of the microRNA transcriptome in a leukemia progression model

Florian Kuchenbauer; Ryan D. Morin; Bob Argiropoulos; Oleh Petriv; Malachi Griffith; Michael Heuser; Eric Yung; Jessica Piper; Allen Delaney; Anna-Liisa Prabhu; Yongjun Zhao; Helen McDonald; Thomas Zeng; Martin Hirst; Carl Hansen; Marco A. Marra; R. Keith Humphries

MicroRNAs (miRNAs) have been shown to play important roles in physiological as well as multiple malignant processes, including acute myeloid leukemia (AML). In an effort to gain further insight into the role of miRNAs in AML, we have applied the Illumina massively parallel sequencing platform to carry out an in-depth analysis of the miRNA transcriptome in a murine leukemia progression model. This model simulates the stepwise conversion of a myeloid progenitor cell by an engineered overexpression of the nucleoporin 98 (NUP98)-homeobox HOXD13 fusion gene (ND13), to aggressive AML inducing cells upon transduction with the oncogenic collaborator Meis1. From this data set, we identified 307 miRNA/miRNA species in the ND13 cells and 306 miRNA/miRNA species in ND13+Meis1 cells, corresponding to 223 and 219 miRNA genes. Sequence counts varied between two and 136,558, indicating a remarkable expression range between the detected miRNA species. The large number of miRNAs expressed and the nature of differential expression suggest that leukemic progression as modeled here is dictated by the repertoire of shared, but differentially expressed miRNAs. Our finding of extensive sequence variations (isomiRs) for almost all miRNA and miRNA species adds additional complexity to the miRNA transcriptome. A stringent target prediction analysis coupled with in vitro target validation revealed the potential for miRNA-mediated release of oncogenes that facilitates leukemic progression from the preleukemic to leukemia inducing state. Finally, 55 novel miRNAs species were identified in our data set, adding further complexity to the emerging world of small RNAs.


Genome Biology | 2007

LongSAGE profiling of nine human embryonic stem cell lines

Martin Hirst; Allen Delaney; Sean Rogers; Angelique Schnerch; Deryck R Persaud; Michael D. O'Connor; Thomas Zeng; Michelle Moksa; Keith Fichter; Diana Mah; Anne Go; Ryan D. Morin; Agnes Baross; Yongjun Zhao; Jaswinder Khattra; Anna-Liisa Prabhu; Pawan Pandoh; Helen McDonald; Jennifer Asano; Noreen Dhalla; Kevin Ma; Stephanie Lee; Adrian Ally; Neil Chahal; Stephanie Menzies; Asim Siddiqui; Robert A. Holt; Steven J.M. Jones; Daniela S. Gerhard; James A. Thomson

To facilitate discovery of novel human embryonic stem cell (ESC) transcripts, we generated 2.5 million LongSAGE tags from 9 human ESC lines. Analysis of this data revealed that ESCs express proportionately more RNA binding proteins compared with terminally differentiated cells, and identified novel ESC transcripts, at least one of which may represent a marker of the pluripotent state.


Current protocols in human genetics | 2010

Digital Gene Expression by Tag Sequencing on the Illumina Genome Analyzer

Sorana Morrissy; Yongjun Zhao; Allen Delaney; Jennifer Asano; Noreen Dhalla; Irene Li; Helen McDonald; Pawan Pandoh; Anna-Liisa Prabhu; Angela Tam; Martin Hirst; Marco A. Marra

This unit provides a protocol for performing digital gene expression profiling on the Illumina Genome Analyzer sequencing platform. Tag sequencing (Tag‐seq) is an implementation of the LongSAGE protocol on the Illumina sequencing platform that increases utility while reducing both the cost and time required to generate gene expression profiles. The ultra‐high‐throughput sequencing capability of the Illumina platform allows the cost‐effective generation of libraries containing an average of 20 million tags, a 200‐fold improvement over classical LongSAGE. Tag‐seq has less sequence composition bias, leading to a better representation of AT‐rich tag sequences, and allows a more accurate profiling of a subset of the transcriptome characterized by AT‐rich genes expressed at levels below the threshold of detection of LongSAGE (Morrissy et al., 2009). Curr. Protoc. Hum. Genet. 65:11.11.1‐11.11.36


BioTechniques | 2002

Resuspension of DNA sequencing reaction products in agarose increases sequence quality on an automated sequencer.

G. Vatcher; Duane E. Smailus; Martin Krzywinski; Ranabir Guin; Jeff M. Stott; M. Tsai; Susanna Y. Chan; Pawan Pandoh; George S. Yang; Jennifer Asano; Teika Olson; Anna-Liisa Prabhu; Robin Coope; A. Marziali; Jacquie Schein; Steven J.M. Jones; Marco A. Marra

We are investigating approaches to increase DNA sequencing quality. Since a majorfactor in sequence generation is the cost of reagents and sample preparations, we have developed and optimized methods to sequence directly plasmid DNA isolated from alkaline lysis preparations. These methods remove the costly PCR and post-sequencing purification steps but can result in low sequence quality when using standard resuspension protocols on some sequencing platforms. This work outlines a simple, robust, and inexpensive resuspension protocol for DNA sequencing to correct this shortcoming. Resuspending the sequenced products in agarose before electrophoresis results in a substantial and reproducible increase in sequence quality and read length over resuspension in deionized water and has allowed us to use the aforementioned sample preparation methods to cut considerably the overall sequencing costs without sacrificing sequence quality. We demonstrate that resuspension of unpurified sequence products generated from template DNA isolated by a modified alkaline lysis technique in low concentrations of agarose yields a 384% improvement in sequence quality compared to resuspension in deionized water. Utilizing this protocol, we have produced more than 74,000 high-quality, long-read-length sequences from plasmid DNA template on the MegaBACET 1000 platform.


Plant Journal | 2007

A physical map of the highly heterozygous Populus genome: integration with the genome sequence and genetic map and analysis of haplotype variation.

Colin T. Kelleher; Readman Chiu; Heesun Shin; Ian Bosdet; Martin Krzywinski; Chris Fjell; Jennifer Wilkin; Tongming Yin; Stephen P. DiFazio; Johar Ali; Jennifer Asano; Susanna Chan; Alison Cloutier; Noreen Girn; Stephen Leach; Darlene Lee; Carrie Mathewson; Teika Olson; Katie O’Connor; Anna-Liisa Prabhu; Duane E. Smailus; Jeffery M. Stott; Miranda Tsai; Natasja Wye; George S. Yang; Jun Zhuang; Robert A. Holt; Nicholas H. Putnam; Julia Vrebalov; James J. Giovannoni


Genome Research | 2006

Large-scale production of SAGE libraries from microdissected tissues, flow-sorted cells, and cell lines.

Jaswinder Khattra; Allen Delaney; Yongjun Zhao; Asim Siddiqui; Jennifer Asano; Helen McDonald; Pawan Pandoh; Noreen Dhalla; Anna-Liisa Prabhu; Kevin Ma; Stephanie Lee; Adrian Ally; Angela Tam; Danne Sa; Sean Rogers; David L. Charest; Jeff M. Stott; Scott Zuyderduyn; Richard Varhol; Connie J. Eaves; Steven J.M. Jones; Robert A. Holt; Martin Hirst; Pamela A. Hoodless; Marco A. Marra


Nucleic Acids Research | 2002

An efficient strategy for large-scale high-throughput transposon-mediated sequencing of cDNA clones

Yaron S N Butterfield; Marco A. Marra; Jennifer Asano; Susanna Y. Chan; Ranabir Guin; Martin Krzywinski; Soo Sen Lee; Kim W. K. MacDonald; Carrie Mathewson; Teika Olson; Pawan Pandoh; Anna-Liisa Prabhu; Angelique Schnerch; Ursula Skalska; Duane E. Smailus; Jeff M. Stott; Miranda I. Tsai; George S. Yang; Scott Zuyderduyn; Jacqueline E. Schein; Steven J.M. Jones

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Marco A. Marra

University of British Columbia

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Martin Hirst

University of British Columbia

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Helen McDonald

University of British Columbia

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Jennifer Asano

University of British Columbia

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Angela Tam

University of British Columbia

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Noreen Dhalla

University of British Columbia

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Steven J.M. Jones

University of British Columbia

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