Genome Research Journal Impact Factor & Information

Publisher: Cold Spring Harbor Laboratory Press

Journal description

The journal focuses on genome studies in all species, and presents research that provides or aids in genome-based analyses of biological processes. The journal represents a nexus point where genomic information, applications, and technology come together with biological information to create a more global understanding of all biological systems.

Current impact factor: 14.63

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2014 Impact Factor 14.63
2013 Impact Factor 13.852
2012 Impact Factor 14.397
2011 Impact Factor 13.608
2010 Impact Factor 13.588
2009 Impact Factor 11.342
2008 Impact Factor 10.176
2007 Impact Factor 11.224
2006 Impact Factor 10.256
2005 Impact Factor 10.139
2004 Impact Factor 10.382
2003 Impact Factor 9.635
2002 Impact Factor 9.863
2001 Impact Factor 8.559
2000 Impact Factor 7.615
1999 Impact Factor 7.062

Impact factor over time

Impact factor

Additional details

5-year impact 15.57
Cited half-life 6.10
Immediacy index 3.20
Eigenfactor 0.14
Article influence 8.37
Website Genome Research website
Other titles Genome research (Online), Genome research
ISSN 1088-9051
OCLC 37589079
Material type Online system or service, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Cold Spring Harbor Laboratory Press

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Author's pre-print on preprint server
    • Author's pre-print must be updated with citation, DOI and link to article upon publication
    • Publisher's version/PDF may be used after 6 months
    • Publisher's version/PDF and Author's post-print on author's personal website, institutional repository, funder's designated repository
    • Authors retain copyright
    • Content automatically sent to PubMed Central after 6 months
    • Publisher copyright and source must be acknowledged
    • Publisher last contacted on 15/07/2013
  • Classification

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Chaperones, nucleosome remodeling complexes and histone acetyltransferases have been implicated in nucleosome disassembly at promoters of particular yeast genes, but whether these co-factors function ubiquitously, and the impact of nucleosome eviction on transcription genome-wide, are poorly understood. We used chromatin immunoprecipitation of histone H3 and RNA polymerase II (Pol II) in mutants lacking single or multiple co-factors to address these issues for ~200 genes belonging to the Gcn4 transcriptome, of which ~70 exhibit marked reductions in H3 promoter occupancy on induction by amino acid starvation. Examining four target genes in a panel of mutants indicated that SWI/SNF, Gcn5, the Hsp70 co-chaperone Ydj1, and chromatin-associated factor Yta7 are required downstream of Gcn4 binding, whereas Asf1/Rtt109, Nap1, RSC and H2AZ are dispensable, for robust H3 eviction in otherwise wild-type cells. Using ChIP-seq to interrogate all 70 exemplar genes in single, double and triple mutants implicated Gcn5, Snf2 and Ydj1 in H3 eviction at most, but not all Gcn4 target promoters, with Gcn5 generally playing the greatest role and Ydj1 the least. Remarkably, these 3 co-factors cooperate similarly in H3 eviction at virtually all yeast promoters. Defective H3 eviction in co-factor mutants was coupled with reduced Pol II occupancies for the Gcn4 transcriptome and the most highly expressed uninduced genes, but the relative Pol II levels at most genes were unaffected or even elevated. These findings indicate that nucleosome eviction is crucial for robust transcription of highly expressed genes, but that other steps in gene activation are more rate-limiting for most other yeast genes.
    Genome Research 11/2015; DOI:10.1101/gr.196337.115
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    ABSTRACT: Cis-regulatory elements (CREs, e.g., promoters and enhancers) regulate gene expression, and variants within CREs can modulate disease risk. Next-generation sequencing has enabled the rapid generation of genomic data that predict the locations of CREs, but a bottleneck lies in functionally interpreting these data. To address this issue, massively parallel reporter assays (MPRAs) have emerged, in which barcoded reporter libraries are introduced into cells and the resulting barcoded transcripts are quantified by next-generation sequencing. Thus far, MPRAs have been largely restricted to assaying short CREs in a limited repertoire of cultured cell types. Here, we present two advances that extend the biological relevance and applicability of MPRAs. First, we adapt exome capture technology to instead capture candidate CREs, thereby tiling across the targeted regions and markedly increasing the length of candidate CREs that can be readily assayed. Second, we package the library into adeno-associated virus (AAV), thereby allowing delivery of candidate CREs to target organs in vivo. As a proof-of-concept, we introduce a capture library of ~46,000 constructs, corresponding to ~3,500 DNase I hypersensitive (DHS) sites, into the mouse retina by ex vivo plasmid electroporation and into the mouse cerebral cortex by in vivo AAV injection. We demonstrate tissue-specific cis-regulatory activity of DHSs and provide examples of high-resolution truncation mutation analysis for multiplex parsing of CREs. Our approach should enable massively parallel functional analysis of a wide range of CREs in any organ or species that can be infected by AAV, such as non-human primates and human stem cell-derived organoids.
    Genome Research 11/2015; DOI:10.1101/gr.193789.115
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    ABSTRACT: Synthetic chromosome rearrangement and modification by loxP-mediated evolution (SCRaMbLE) generates combinatorial genomic diversity through rearrangements at designed recombinase sites. We applied SCRaMbLE to yeast synthetic chromosome arm synIXR (43 recombinase sites), and then use a computational pipeline to infer or unscramble the sequence of recombinations that created the observed genomes. Deep sequencing of 64 synIXR SCRaMbLE strains revealed 156 deletions, 89 inversions, 94 duplications, and 55 additional complex rearrangements; several duplications are consistent with a double rolling circle mechanism. Every SCRaMbLE strain was unique, validating the capability of SCRaMbLE to explore a diverse space of genomes. Rearrangements occurred exclusively at designed loxPsym sites, with no significant evidence for ectopic rearrangements or mutations involving synthetic regions, the 99% non-synthetic nuclear genome, or the mitochondrial genome. Deletion frequencies identified genes required for viability or fast growth. Replacement of 3' UTR by non-UTR sequence had surprisingly little effect on fitness. SCRaMbLE generates genome diversity in designated regions, reveals fitness constraints, and should scale to simultaneous evolution of multiple synthetic chromosomes.
    Genome Research 11/2015; DOI:10.1101/gr.193433.115
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    ABSTRACT: RNA secondary structure plays an integral role in catalytic, ribosomal, small nuclear, micro, and transfer RNAs. Discovering a prevalent role for secondary structure in pre-mRNAs has proven more elusive. By utilizing a variety of computational and biochemical approaches, we present evidence for a class of nuclear intron that relies upon secondary structure for correct splicing. These introns are defined by simple repeat expansions of complimentary AC and GT dimers that co-occur at opposite boundaries of an intron to form a bridging structure that enforces correct splice site pairing. Remarkably, this class of intron does not require U2AF65, a core component of the spliceosome, for its processing. Phylogenetic analysis suggests that this mechanism was present in the ancestral vertebrate lineage prior to the divergence of tetrapods from teleosts. While largely lost from land dwelling vertebrates, this class of introns is found in 10% of all zebrafish genes.
    Genome Research 11/2015; DOI:10.1101/gr.181008.114
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    ABSTRACT: While Next-generation sequencing (NGS) has become the primary technology for discovering gene fusions we are still faced with the challenge of ensuring that causative mutations are not missed while minimizing false positives. Currently, there are many computational tools that predict structural variations (SV) and gene fusions using whole genome (WGS) and transcriptome sequencing (RNA-seq) data separately. However, as both WGS and RNA-seq have their limitations when used independently we hypothesize that the orthogonal validation from integrating WGS and RNA-seq could generate a sensitive and specific approach for detecting high confidence gene fusion predictions. Fortunately, decreasing NGS costs have resulted in a growing quantity of patients with available genome and transcriptome sequencing data. Therefore, we developed a gene fusion discovery tool, INTEGRATE, that leverages both RNA-seq and WGS data to reconstruct gene fusion junctions and genomic breakpoints by split-read mapping. To evaluate INTEGRATE we compared it with eight additional gene fusion discovery tools using the well-characterized breast cell line HCC1395 and peripheral blood lymphocytes derived from the same patient (HCC1395BL). The predictions subsequently underwent a targeted validation leading to the discovery of 131 novel fusions in addition to the seven previously reported fusions. Overall, INTEGRATE only missed 6 out of the 138 validated gene fusions and had the highest accuracy of the nine tools evaluated. Additionally, we applied INTEGRATE to 62 breast cancer patients from the TCGA and found multiple recurrent gene fusions including a subset involving estrogen receptor. Taken together, INTEGRATE is a highly sensitive and accurate tool that is freely available for academic use.
    Genome Research 11/2015; DOI:10.1101/gr.186114.114
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    ABSTRACT: Forward genetic screens using Sleeping Beauty (SB) mobilized T2/Onc transposons have been used to identify Common Insertion Sites (CIS) associated with tumor formation. Recurrent sites of transposon insertion are commonly identified using Ligation Mediated PCR (LM-PCR). Here, we use RNA-sequencing (RNA-seq) data to directly identify transcriptional events mediated by T2/Onc. Surprisingly, the majority (~80%) of LM-PCR identified junction fragments do not lead to observable changes in RNA transcripts. However, in CIS regions, direct transcriptional effects of transposon insertions are observed. We developed an automated method to systematically identify T2/Onc-genome RNA fusion sequences in RNA-seq data. RNA fusion based CIS were identified corresponding to both DNA based CIS (Cdkn2a, Mycl1, Nf2, Pten, Sema6d and Rere) and additional regions strongly associated with cancer that were not observed by LM-PCR (Myc, Akt1, Pth, Csf1r, Fgfr2, Wisp1, Map3k5 and Map4k3). In addition to calculating recurrent CIS, we also present complementary methods to identify potential driver events via determination of strongly supported fusions and fusions with large transcript level changes in the absence of multi-tumor recurrence. These methods independently identify CIS regions, and also point to cancer-associated genes like Braf. We anticipate RNA-seq analyses of tumors from forward genetic screens will become an efficient tool to identify causal events.
    Genome Research 11/2015; DOI:10.1101/gr.188649.114
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    ABSTRACT: It has been almost 15 years since the first microarray-based studies creating multigene biomarkers to subtype and predict survival of cancer patients. This Perspective looks at why only a handful of genomic biomarkers have reached clinical application and what advances are needed over the next 15 years to grow this number. I discuss challenges in creating biomarkers and reproducing them at the genomic and computational levels, including the problem of spatio-genomic heterogeneity in an individual cancer. I then outline the challenges in translating newly discovered genome-wide or regional events, like trinucleotide mutation signatures, kataegis, and chromothripsis, into biomarkers, as well as the importance of incorporating prior biological knowledge. Lastly, I outline the practical problems of pharmaco-economics and adoption: Are new biomarkers viewed as economically rational by potential funders? And if they are, how can their results be communicated effectively to patients and their clinicians? Genomic-based diagnostics have immense potential for transforming the management of cancer. The next 15 years will see a surge of research into the topics here that, when combined with a stream of new targeted therapies being developed, will personalize the cancer clinic.
    Genome Research 10/2015; 25(10). DOI:10.1101/gr.191114.115
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    ABSTRACT: Deep characterization of molecular function of genetic variants in the human genome is becoming increasingly important for understanding genetic associations to disease and for learning to read the regulatory code of the genome. In this paper, I discuss how recent advances in both quantitative genetics and molecular biology have contributed to understanding functional effects of genetic variants, lessons learned from eQTL studies, and future challenges in this field.
    Genome Research 10/2015; 25(10). DOI:10.1101/gr.190983.115
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    ABSTRACT: Arevolution in cellular measurement technology is under way: For the first time, we have the ability to monitor global gene regulation in thousands of individual cells in a single experiment. Such experiments will allow us to discover new cell types and states and trace their developmental origins. They overcome fundamental limitations inherent in measurements of bulk cell population that have frustrated efforts to resolve cellular states. Single-cell genomics and proteomics enable not only precise characterization of cell state, but also provide a stunningly high-resolution view of transitions between states. These measurements may finally make explicit the metaphor that C.H. Waddington posed nearly 60 years ago to explain cellular plasticity: Cells are residents of a vast "landscape" of possible states, over which they travel during development and in disease. Single-cell technology helps not only locate cells on this landscape, but illuminates the molecular mechanisms that shape the landscape itself. However, single-cell genomics is a field in its infancy, with many experimental and computational advances needed to fully realize its full potential.
    Genome Research 10/2015; 25(10):1491-1498. DOI:10.1101/gr.190595.115
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    ABSTRACT: The past two decades have been marked by a surge in research to understand the microbial communities that live in association with the human body, in part stimulated by affordable, high-throughput DNA sequencing technology. In the context of the skin, this Perspective focuses on the current state of genomic- and metagenomic-based host–microbe research and future challenges and opportunities to move the field forward. These include elucidating nonbacterial components of the skin microbiome (i.e., viruses); systematic studies to address common perturbations to the skin microbiome (e.g., antimicrobial drugs, topical cosmetic/hygienic products); improved approaches for identifying potential microbial triggers for skin diseases, including species- and strain-level resolution; and improved, clinically relevant models for studying the functional and mechanistic roles of the skin microbiome. In the next 20 years, we can realistically expect that our knowledge of the skin microbiome will inform the clinical management and treatment of skin disorders through diagnostic tests to stratify patient subsets and predict best treatment modality and outcomes and through treatment strategies such as targeted manipulation or reconstitution of microbial communities.
    Genome Research 10/2015; 25(10). DOI:10.1101/gr.191320.115
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    ABSTRACT: Advances in genome engineering technologies have made the precise control over genome sequence and regulation possible across a variety of disciplines. These tools can expand our understanding of fundamental biological processes and create new opportunities for therapeutic designs. The rapid evolution of these methods has also catalyzed a new era of genomics that includes multiple approaches to functionally characterize and manipulate the regulation of genomic information. Here, we review the recent advances of the most widely adopted genome engineering platforms and their application to functional genomics. This includes engineered zinc finger proteins, TALEs/TALENs, and the CRISPR/Cas9 system as nucleases for genome editing, transcription factors for epigenome editing, and other emerging applications. We also present current and potential future applications of these tools, as well as their current limitations and areas for future advances.
    Genome Research 10/2015; 25(10). DOI:10.1101/gr.190124.115
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    ABSTRACT: The last 20 years have been a remarkable era for biology and medicine. One of the most significant achievements has been the sequencing of the first human genomes, which has laid the foundation for profound insights into human genetics, the intricacies of regulation and development, and the forces of evolution. Incredibly, as we look into the future over the next 20 years, we see the very real potential for sequencing more than 1 billion genomes, bringing even deeper insight into human genetics as well as the genetics of millions of other species on the planet. Realizing this great potential for medicine and biology, though, will only be achieved through the integration and development of highly scalable computational and quantitative approaches that can keep pace with the rapid improvements to biotechnology. In this perspective, I aim to chart out these future technologies, anticipate the major themes of research, and call out the challenges ahead. One of the largest shifts will be in the training used to prepare the class of 2035 for their highly interdisciplinary world.
    Genome Research 10/2015; 25(10):1417-1422. DOI:10.1101/gr.191684.115
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    ABSTRACT: The regulatory potential of RNA has never ceased to amaze: from RNA catalysis, to RNA-mediated splicing, to RNA-based silencing of an entire chromosome during dosage compensation. More recently, thousands of long noncoding RNA (lncRNA) transcripts have been identified, the majority with unknown function. Thus, it is tempting to think that these lncRNAs represent a cadre of new factors that function through ribonucleic mechanisms. Some evidence points to several lncRNAs with tantalizing physiological contributions and thought-provoking molecular modalities. However, dissecting the RNA biology of lncRNAs has been difficult, and distinguishing the independent contributions of functional RNAs from underlying DNA elements, or the local act of transcription, is challenging. Here, we aim to survey the existing literature and highlight future approaches that will be needed to link the RNA-based biology and mechanisms of lncRNAs in vitro and in vivo.
    Genome Research 10/2015; 25(10). DOI:10.1101/gr.191122.115
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    ABSTRACT: Both intrinsic cell state changes and variations in the composition of stem cell populations have been implicated as contributors to aging. We used single cell RNA-seq to dissect variability in hematopoietic stem and progenitor cell populations from young and old mice from two strains. We found that cell cycle dominates the variability within each population, and that there is a lower frequency of cells in the G1 phase among old compared to young long-term hematopoietic stem cells, suggesting that they traverse through G1 faster. Moreover, transcriptional changes in HSCs during aging are inversely related to those upon HSC differentiation, such that old short term (ST)-HSCs resemble young long-term (LT-HSCs), suggesting that they exist in a less differentiated state. Our results indicate both compositional changes and intrinsic, population-wide changes with age and are consistent with a model where a relationship between cell-cycle progression and self-renewal versus differentiation of HSCs is affected by aging and may contribute to the functional decline of old HSCs.
    Genome Research 10/2015; DOI:10.1101/gr.192237.115
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    ABSTRACT: Genomics has recently celebrated reaching the $1000 genome milestone, making affordable DNA sequencing a reality. With this goal successfully completed, the next goal of the sequencing revolution can be sequencing sensors—miniaturized sequencing devices that are manufactured for real-time applications and deployed in large quantities at low costs. The first part of this manuscript envisions applications that will benefit from moving the sequencers to the samples in a range of domains. In the second part, the manuscript outlines the critical barriers that need to be addressed in order to reach the goal of ubiquitous sequencing sensors.
    Genome Research 10/2015; 25(10). DOI:10.1101/gr.191692.115
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    ABSTRACT: Eukaryotic genomes are packaged into an extensively folded state known as chromatin. Analysis of the structure of eukaryotic chromosomes has been revolutionized by development of a suite of genome-wide measurement technologies, collectively termed “epigenomics.” We review major advances in epigenomic analysis of eukaryotic genomes, covering aspects of genome folding at scales ranging from whole chromosome folding down to nucleotide-resolution assays that provide structural insights into protein-DNA interactions. We then briefly outline several challenges remaining and highlight new developments such as single-cell epigenomic assays that will help provide us with a high-resolution structural understanding of eukaryotic genomes.
    Genome Research 10/2015; 25(10). DOI:10.1101/gr.190165.115
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    ABSTRACT: Small-scale molecular systems biology, by which we mean the understanding of a how a few parts work together to control a particular biological process, is predicated on the assumption that cellular regulation is arranged in a circuit-like structure. Results from the omics revolution have upset this vision to varying degrees by revealing a high degree of interconnectivity, making it difficult to develop a simple, circuit-like understanding of regulatory processes. We here outline the limitations of the small-scale systems biology approach with examples from research into genetic algorithms, genetics, transcriptional network analysis, and genomics. We also discuss the difficulties associated with deriving true understanding from the analysis of large data sets and propose that the development of new, intelligent, computational tools may point to a way forward. Throughout, we intentionally oversimplify and talk about things in which we have little expertise, and it is likely that many of our arguments are wrong on one level or another. We do believe, however, that developing a true understanding via molecular systems biology will require a fundamental rethinking of our approach, and our goal is to provoke thought along these lines.
    Genome Research 10/2015; 25(10). DOI:10.1101/gr.190579.115
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    ABSTRACT: There are thousands of known associations between genetic variants and complex human phenotypes, and the rate of novel discoveries is rapidly increasing. Translating those associations into knowledge of disease mechanisms remains a fundamental challenge because the associated variants are overwhelmingly in noncoding regions of the genome where we have few guiding principles to predict their function. Intersecting the compendium of identified genetic associations with maps of regulatory activity across the human genome has revealed that phenotype-associated variants are highly enriched in candidate regulatory elements. Allele-specific analyses of gene regulation can further prioritize variants that likely have a functional effect on disease mechanisms; and emerging high-throughput assays to quantify the activity of candidate regulatory elements are a promising next step in that direction. Together, these technologies have created the ability to systematically and empirically test hypotheses about the function of noncoding variants and haplotypes at the scale needed for comprehensive and systematic follow-up of genetic association studies. Major coordinated efforts to quantify regulatory mechanisms across genetically diverse populations in increasingly realistic cell models would be highly beneficial to realize that potential.
    Genome Research 10/2015; 25(10). DOI:10.1101/gr.190603.115