The UCSC Genome Browser database: extensions and updates 2013

Meyer, Laurence R.; Zweig, Ann S.; Hinrichs, Angie S.; Karolchik, Donna; Kuhn, Robert M.; Wong, Matthew C.; Sloan, Cricket A.; Rosenbloom, Kate R.; Dreszer, Timothy R.; Rhead, Brooke; Raney, Brian J.; Pohl, Andy; Malladi, Venkat S.; Li, Chin H.; Lee, Brian T.; Learned, Katrina; Kirkup, Vanessa M.; Hsu, Fan; Heitner, Steven G.; Harte, Rachel A.; Haeussler, Maximilian; Guruvadoo, Luvina; Goldman, Mary; Giardine, Belinda; Fujita, Pauline A.; Diekhans, Mark; Cline, Melissa; Clawson, Hiram; Barber, Galt P.; Haussler, David; Kent, W. James

doi:10.1093/nar/gks1048

Cited by 731 publications

(739 citation statements)

References 23 publications

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“…Poly(A)-selected RNA sequencing data from human embryonic stem cell (H1 hESC) (Bernstein et al 2012) were mapped to the syntenic regions, in humans, of the 104 mouse lncRNAs that did not overlap annotated mouse protein-coding and showed expression evidence in our data set (obtained using liftOver [Meyer et al 2013] with parameters: -minMatch = 0.2 -minBlocks = 0.01). A mouse lncRNA with at least five sequencing reads covering 20% or more of the syntenic region in humans was considered to be conserved in expression.…”

Section: Conservation Of Mouse Lncrna Expression In Humansmentioning

confidence: 99%

Extensive microRNA-mediated crosstalk between lncRNAs and mRNAs in mouse embryonic stem cells

et al. 2015

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Recently, a handful of intergenic long noncoding RNAs (lncRNAs) have been shown to compete with mRNAs for binding to miRNAs and to contribute to development and disease. Beyond these reports, little is yet known of the extent and functional consequences of miRNA-mediated regulation of mRNA levels by lncRNAs. To gain further insight into lncRNA-mRNA miRNA-mediated crosstalk, we reanalyzed transcriptome-wide changes induced by the targeted knockdown of over 100 lncRNA transcripts in mouse embryonic stem cells (mESCs). We predicted that, on average, almost one-fifth of the transcript level changes induced by lncRNAs are dependent on miRNAs that are highly abundant in mESCs. We validated these findings experimentally by temporally profiling transcriptome-wide changes in gene expression following the loss of miRNA biogenesis in mESCs. Following the depletion of miRNAs, we found that >50% of lncRNAs and their miRNA-dependent mRNA targets were up-regulated coordinately, consistent with their interaction being miRNA-mediated. These lncRNAs are preferentially located in the cytoplasm, and the response elements for miRNAs they share with their targets have been preserved in mammals by purifying selection. Lastly, miRNA-dependent mRNA targets of each lncRNA tended to share common biological functions. Post-transcriptional miRNA-mediated crosstalk between lncRNAs and mRNA, in mESCs, is thus surprisingly prevalent, conserved in mammals, and likely to contribute to critical developmental processes.

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Section: Conservation Of Mouse Lncrna Expression In Humansmentioning

confidence: 99%

Extensive microRNA-mediated crosstalk between lncRNAs and mRNAs in mouse embryonic stem cells

et al. 2015

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“…It has 432,854 repeat regions (45.7% of the chromosome), including SINE (37.4%), LINE (28.2%), and other repeats. We compared the HG00656 dataset from the 1000 Genomes Project (33) (∼5× coverage) with the human reference genome (hg19/ GRCh37) (54).…”

Section: Incomplete Coverage Of Tandem Repeats Contributes To Genotypingmentioning

confidence: 99%

Detection of genomic variations and DNA polymorphisms and impact on analysis of meiotic recombination and genetic mapping

Chen

Copenhaver

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

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DNA polymorphisms are important markers in genetic analyses and are increasingly detected by using genome resequencing. However, the presence of repetitive sequences and structural variants can lead to false positives in the identification of polymorphic alleles. Here, we describe an analysis strategy that minimizes false positives in allelic detection and present analyses of recently published resequencing data from Arabidopsis meiotic products and individual humans. Our analysis enables the accurate detection of sequencing errors, small insertions and deletions (indels), and structural variants, including large reciprocal indels and copy number variants, from comparisons between the resequenced and reference genomes. We offer an alternative interpretation of the sequencing data of meiotic products, including the number and type of recombination events, to illustrate the potential for mistakes in single-nucleotide polymorphism calling. Using these examples, we propose that the detection of DNA polymorphisms using resequencing data needs to account for nonallelic homologous sequences. Fig. 1 A and B). They can have phenotypic consequences and also serve as molecular markers for genetic analyses, facilitating linkage and association studies of genetic diseases, and other traits in humans (4-6), animals, plants, (7)(8)(9)(10) and other organisms. Using DNA polymorphisms for modern genetic applications requires low-error, high-throughput analytical strategies. Here, we illustrate the use of short-read nextgeneration sequencing (NGS) data to detect DNA polymorphisms in the context of whole-genome analysis of meiotic products.There are many methods for detecting SNPs (11-14) and structural variants (SVs) (15-25), including NGS, which can capture nearly all DNA polymorphisms (26-28). This approach has been widely used to analyze markers in crop species such as rice (29), genes associated with diseases (6, 26), and meiotic recombination in yeast and plants (30,31). However, accurate identification of DNA polymorphisms can be challenging, in part because short-read sequencing data have limited information for inferring chromosomal context.Genomes usually contain repetitive sequences that can differ in copy number between individuals (26-28, 31); therefore, resequencing analyses must account for chromosomal context to avoid mistaking highly similar paralogous sequences for polymorphisms. Here, we use recently published datasets to describe several DNA sequence features that can be mistaken as allelic (32, 33) and describe a strategy for differentiating between repetitive sequences and polymorphic alleles. We illustrate the effectiveness of these analyses by examining the reported polymorphisms from the published datasets.Meiotic recombination is initiated by DNA double-strand breaks (DSBs) catalyzed by the topoisomerase-like SPORULATION 11 (SPO11). DSBs are repaired as either crossovers (COs) between chromosomes (Fig. 1C), or noncrossovers (NCOs). Both COs and NCOs can be accompanied by gene conversion (GC) events, whic...

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“…The H3K27ac track shows major peaks of histone H3K27 acetylation that are associated with active regulatory elements and these elements span the entire 3 Mb region. References for each SNP and its disease association can be found on the GWAS track of the UCSC Genome Browser (Meyer et al 2013). The expanded panel below shows local H3K27ac peaks near the rs6983267 SNP, which has been frequently associated with many types of cancer.…”

Section: Distal Regulation Of Myc: Early Observationsmentioning

confidence: 99%

“…The enhancer-linked modifications extend over a 4 kb region, part of which is highly conserved in mammalian evolution (bottom track). All data was extracted from the UCSC Genome Browser (Meyer et al 2013). …”

Section: Distal Regulation Of Myc: Early Observationsmentioning

confidence: 99%

MYC Association with Cancer Risk and a New Model of MYC-Mediated Repression

Cole

2014

Cold Spring Harbor Perspectives in Medicine

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MYC is one of the most frequently mutated and overexpressed genes in human cancer but the regulation of MYC expression and the ability of MYC protein to repress cellular genes (including itself ) have remained mysterious. Recent genome-wide association studies show that many genetic polymorphisms associated with disease risk map to distal regulatory elements that regulate the MYC promoter through large chromatin loops. Cancer risk-associated single-nucleotide polymorphisms (SNPs) contain more potent enhancer activity, promoting higher MYC levels and a greater risk of disease. The MYC promoter is also subject to complex regulatory circuits and limits its own expression by a feedback loop. A model for MYC autoregulation is discussed which involves a signaling pathway between the PTEN ( phosphatase and tensin homolog) tumor suppressor and repressive histone modifications laid down by the EZH2 methyltransferase.

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The UCSC Genome Browser database: extensions and updates 2013

Cited by 731 publications

References 23 publications

Extensive microRNA-mediated crosstalk between lncRNAs and mRNAs in mouse embryonic stem cells

Extensive microRNA-mediated crosstalk between lncRNAs and mRNAs in mouse embryonic stem cells

Detection of genomic variations and DNA polymorphisms and impact on analysis of meiotic recombination and genetic mapping

MYC Association with Cancer Risk and a New Model of MYC-Mediated Repression

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