Genome biology (Genome Biol )


Genome Biology publishes articles from the full spectrum of biology. Subjects covered include any aspect of molecular, cellular, organismal or population biology studied from a genomic perspective, as well as genomics, proteomics, bioinformatics, genomic methods (including structure prediction), computational biology, sequence analysis (including large-scale and cross-genome analyses), comparative biology and evolution.

Impact factor 10.47

  • Hide impact factor history
    Impact factor
  • 5-year impact
  • Cited half-life
  • Immediacy index
  • Eigenfactor
  • Article influence
  • Website
    Genome Biology website
  • Other titles
    Genome biology (Online), Genome biology,, GB. C
  • ISSN
  • OCLC
  • Material type
    Document, Periodical, Internet resource
  • Document type
    Internet Resource, Computer File, Journal / Magazine / Newspaper

Publications in this journal

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Although transcriptional elongation by RNA polymerase II is coupled with many RNA-related processes, genomewide elongation rates remain unknown. We describe a method, called 4sUDRB-seq, based on reversible inhibition of transcription elongation coupled with tagging newly transcribed RNA with 4-thiouridine and high throughput sequencing to measure simultaneously with high confidence genome-wide transcription elongation rates in cells. We find that most genes are transcribed at about 3.5 kb/min, with elongation rates varying between 2 kb/min - 6 kb/min. 4sUDRB-seq can facilitate genomewide exploration of the involvement of specific elongation factors in transcription and the contribution of deregulated transcription elongation to various pathologies.
    Genome biology 05/2014; 15(5):R69.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Cell lineage-specific DNA methylation patterns distinguish normal human leukocyte subsets and can be used to detect and quantify these subsets in peripheral blood. We have developed an approach that uses DNA methylation to simultaneously quantify multiple leukocyte subsets, enabling the investigation of immune modulations in virtually any blood sample including archived samples previously precluded from such analysis. Here we assess the performance characteristics and validity of this approach. Using Illumina Infinium HumanMethylation27 and VeraCode GoldenGate Methylation Assay microarrays, we measure DNA methylation in leukocyte subsets purified from human whole blood and identify cell lineage-specific DNA methylation signatures that distinguish human T-cells, B-cells, NK cells, monocytes, eosinophils, basophils and neutrophils. We then employ a bioinformatics-based approach to quantify these cell types in complex mixtures, including whole blood, using DNA methylation at as few as 20 CpG loci. A reconstruction experiment confirms that the approach could accurately measure the composition of mixtures of human blood leukocyte subsets. Applying the DNA methylation-based approach to quantify the cellular components of human whole blood, we verify its accuracy by direct comparison to gold standard immune quantification methods that utilize physical, optical and proteomic characteristics of the cells. We also demonstrate that the approach is not affected by storage of blood samples, even under conditions prohibiting the use of gold standard methods. Cell mixture distributions within peripheral blood can be assessed accurately and reliably using DNA methylation. Thus, precise immune cell differential estimates can be reconstructed using only DNA rather than whole cells.
    Genome biology 03/2014; 15(3):R50.