sábado, 2 de julio de 2016

Read our latest Special Issue on Single-Cell 'Omics

Single-Cell Omics

BioMed Central – The Open Access Publisher





Dear Prof CERASALE MORTEO,

Our Special Issue on Single-Cell 'Omics, guest-edited by Sarah Teichmann of the Sanger Institute and Sten Linnarsson of the Karolinska Institutet, is now launched.
Advances in single-cell approaches are now enabling us to study differences between cell types and subpopulations, at the level of the genome, transcriptome and epigenome. Single-cell technologies are being used to study diverse areas of biology and disease, such as development, microbial population composition, and cancer evolution.
We highlight these advances with cutting-edge research, review and comment articles. Look out for more special issue papers coming soon.

Table Of Contents
Comment
EDITORIAL
Single-cell genomics: coming of age
Sten Linnarsson and Sarah Teichmann

RESEARCH HIGHLIGHT
Single-cell profiling of lncRNAs in the developing human brain
Qing Ma and Howard Y. Chang

RESEARCH HIGHLIGHT
Computing tumor trees from single cells
Alexander Davis and Nicholas E. Navin

Review
OPINION
The potential of single-cell profiling in plants
Idan Efroni and Kenneth D. Birnbaum




REVIEW
Single-cell sequencing in stem cell biology
Lu Wen and Fuchou Tang

Research







METHOD
Beyond comparisons of means: understanding changes in gene expression at the single-cell level
Catalina A. Vallejos, Sylvia Richardson and John C. Marioni


METHOD
OncoNEM: inferring tumor evolution from single-cell sequencing data
Edith M. Ross and Florian Markowetz

METHOD
Tree inference for single-cell data
Katharina Jahn, Jack Kuipers, and Niko Beerenwinkel


METHOD
Pooling across cells to normalize single-cell RNA sequencing data with many zero counts
Aaron T. L. Lun, Karsten Bach and John C. Marioni





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Single-Cell Omics

Guest Editors: Sarah Teichmann and Sten Linnarsson

 Advances in single-cell approaches are now enabling us to study differences between cell types and subpopulations, at the level of the genome, transcriptome and epigenome. Single-cell technologies are being used to study diverse areas of biology and disease, such as development, microbial population composition, and cancer evolution.
Genome Biology highlights the emergence of this field with a special issue focused on single-cell methods and their applications.
  1. RESEARCH

    Single-cell sequencing reveals karyotype heterogeneity in murine and human malignancies

    Chromosome instability leads to aneuploidy, a state in which cells have abnormal numbers of chromosomes, and is found in two out of three cancers. In a chromosomal instable p53 deficient mouse model with accel...
    Bjorn Bakker, Aaron Taudt, Mirjam E. Belderbos, David Porubsky, Diana C. J. Spierings, Tristan V. de Jong, Nancy Halsema, Hinke G. Kazemier, Karina Hoekstra-Wakker, Allan Bradley, Eveline S. J. M. de Bont, Anke van den Berg, Victor Guryev, Peter M. Lansdorp, Maria Colomé-Tatché and Floris Foijer
    Genome Biology 2016 17:115
    Published on: 31 May 2016
  2. RESEARCH

    Single-cell whole genome sequencing reveals no evidence for common aneuploidy in normal and Alzheimer’s disease neurons

    Alzheimer’s disease (AD) is a neurodegenerative disease of the brain and the most common form of dementia in the elderly. Aneuploidy, a state in which cells have an abnormal number of chromosomes, has been pro...
    Hilda van den Bos, Diana C. J. Spierings, Aaron Taudt, Bjorn Bakker, David Porubský, Ester Falconer, Carolina Novoa, Nancy Halsema, Hinke G. Kazemier, Karina Hoekstra-Wakker, Victor Guryev, Wilfred F. A. den Dunnen, Floris Foijer, Maria Colomé-Tatché, Hendrikus W. G. M. Boddeke and Peter M. Lansdorp
    Genome Biology 2016 17:116
    Published on: 31 May 2016
    The Erratum to this article has been published in Genome Biology 2016 17:143
  3. RESEARCH HIGHLIGHT

    Computing tumor trees from single cells

    Computational methods have been developed to reconstruct evolutionary lineages from tumors using single-cell genomic data. The resulting tumor trees have important applications in cancer research and clinical ...
    Alexander Davis and Nicholas E. Navin
    Genome Biology 2016 17:113
    Published on: 26 May 2016
  4. RESEARCH

    Single-cell analysis of CD4+ T-cell differentiation reveals three major cell states and progressive acceleration of proliferation

    Differentiation of lymphocytes is frequently accompanied by cell cycle changes, interplay that is of central importance for immunity but is still incompletely understood. Here, we interrogate and quantitativel...
    Valentina Proserpio, Andrea Piccolo, Liora Haim-Vilmovsky, Gozde Kar, Tapio Lönnberg, Valentine Svensson, Jhuma Pramanik, Kedar Nath Natarajan, Weichao Zhai, Xiuwei Zhang, Giacomo Donati, Melis Kayikci, Jurij Kotar, Andrew N. J. McKenzie, Ruddy Montandon, Oliver Billker…
    Genome Biology 2016 17:103
    Published on: 12 May 2016
    The Erratum to this article has been published in Genome Biology 2016 17:133
  5. METHOD

    Tree inference for single-cell data

    Understanding the mutational heterogeneity within tumors is a keystone for the development of efficient cancer therapies. Here, we present SCITE, a stochastic search algorithm to identify the evolutionary hist...
    Katharina Jahn, Jack Kuipers and Niko Beerenwinkel
    Genome Biology 2016 17:86
    Published on: 5 May 2016
  6. METHOD

    Simultaneous profiling of transcriptome and DNA methylome from a single cell

    Single-cell transcriptome and single-cell methylome technologies have become powerful tools to study RNA and DNA methylation profiles of single cells at a genome-wide scale. A major challenge has been to under...
    Youjin Hu, Kevin Huang, Qin An, Guizhen Du, Ganlu Hu, Jinfeng Xue, Xianmin Zhu, Cun-Yu Wang, Zhigang Xue and Guoping Fan
    Genome Biology 2016 17:88
    Published on: 5 May 2016
  7. RESEARCH

    Single-cell profiling of human megakaryocyte-erythroid progenitors identifies distinct megakaryocyte and erythroid differentiation pathways

    Recent advances in single-cell techniques have provided the opportunity to finely dissect cellular heterogeneity within populations previously defined by “bulk” assays and to uncover rare cell types. In human ...
    Bethan Psaila, Nikolaos Barkas, Deena Iskander, Anindita Roy, Stacie Anderson, Neil Ashley, Valentina S. Caputo, Jens Lichtenberg, Sandra Loaiza, David M. Bodine, Anastasios Karadimitris, Adam J. Mead and Irene Roberts
    Genome Biology 2016 17:83
    Published on: 3 May 2016
  8. RESEARCH

    Application of single-cell RNA sequencing in optimizing a combinatorial therapeutic strategy in metastatic renal cell carcinoma

    Intratumoral heterogeneity hampers the success of marker-based anticancer treatment because the targeted therapy may eliminate a specific subpopulation of tumor cells while leaving others unharmed. Accordingly...
    Kyu-Tae Kim, Hye Won Lee, Hae-Ock Lee, Hye Jin Song, Da Eun Jeong, Sang Shin, Hyunho Kim, Yoojin Shin, Do-Hyun Nam, Byong Chang Jeong, David G. Kirsch, Kyeung Min Joo and Woong-Yang Park
    Genome Biology 2016 17:80
    Published on: 29 April 2016
  9. METHOD

    CEL-Seq2: sensitive highly-multiplexed single-cell RNA-Seq

    Single-cell transcriptomics requires a method that is sensitive, accurate, and reproducible. Here, we present CEL-Seq2, a modified version of our CEL-Seq method, with threefold higher sensitivity, lower costs,...
    Tamar Hashimshony, Naftalie Senderovich, Gal Avital, Agnes Klochendler, Yaron de Leeuw, Leon Anavy, Dave Gennert, Shuqiang Li, Kenneth J. Livak, Orit Rozenblatt-Rosen, Yuval Dor, Aviv Regev and Itai Yanai
    Genome Biology 2016 17:77
    Published on: 28 April 2016
  10. METHOD

    OncoNEM: inferring tumor evolution from single-cell sequencing data

    Single-cell sequencing promises a high-resolution view of genetic heterogeneity and clonal evolution in cancer. However, methods to infer tumor evolution from single-cell sequencing data lag behind methods dev...
    Edith M. Ross and Florian Markowetz
    Genome Biology 2016 17:69
    Published on: 15 April 2016
  11. REVIEW

    Single-cell sequencing in stem cell biology

    Cell-to-cell variation and heterogeneity are fundamental and intrinsic characteristics of stem cell populations, but these differences are masked when bulk cells are used for omic analysis. Single-cell sequenc...
    Lu Wen and Fuchou Tang
    Genome Biology 2016 17:71
    Published on: 15 April 2016
  12. RESEARCH HIGHLIGHT

    Single-cell profiling of lncRNAs in the developing human brain

    Single-cell RNA-seq in samples from the human neocortex demonstrate that long noncoding RNAs (lncRNAs) are abundantly expressed in specific individual brain cells, despite being hard to detect in bulk samples....
    Qing Ma and Howard Y. Chang
    Genome Biology 2016 17:68
    Published on: 14 April 2016
  13. RESEARCH

    Single-cell analysis of long non-coding RNAs in the developing human neocortex

    Long non-coding RNAs (lncRNAs) comprise a diverse class of transcripts that can regulate molecular and cellular processes in brain development and disease. LncRNAs exhibit cell type- and tissue-specific expres...
    Siyuan John Liu, Tomasz J. Nowakowski, Alex A. Pollen, Jan H. Lui, Max A. Horlbeck, Frank J. Attenello, Daniel He, Jonathan S. Weissman, Arnold R. Kriegstein, Aaron A. Diaz and Daniel A. Lim
    Genome Biology 2016 17:67
    Published on: 14 April 2016
  14. OPINION

    The potential of single-cell profiling in plants

    Single-cell transcriptomics has been employed in a growing number of animal studies, but the technique has yet to be widely used in plants. Nonetheless, early studies indicate that single-cell RNA-seq protocol...
    Idan Efroni and Kenneth D. Birnbaum
    Genome Biology 2016 17:65
    Published on: 5 April 2016

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