Modeling gene expression using chromatin features in various cellular contexts

Dong, Xianjun; Greven, Melissa C.; Kundaje, Anshul; Djebali, Sarah; Brown, James; Cheng, Chao; Gingeras, T; Gerstein, Mark; Guigó, Roderic; Birney, Ewan; Weng, Zhiping

doi:10.1186/gb-2012-13-9-r53

Cited by 242 publications

(256 citation statements)

References 45 publications

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“…FAIRE and RNA Pol II signals have very similar predictive abilities over both the Vβ and its downstream bins. These findings are strikingly similar to correlations observed between chromatin features and gene expression (50,51), further underscoring the relationship between transcriptional activity and Vβ recombination frequencies. A particularly satisfying outcome of this analysis is the correlation between FAIRE signals and the bins flanking RSSs, presumably reflecting a requirement for nucleosome depletion at RAG-1/2 targets (52, 53).…”

Section: Role Of Chromatin Environment In Determining Vβ Recombinationsupporting

confidence: 81%

“…To examine these combinatorial relationships, we used classification and regression analyses comparing chromatin features and predicted RSS quality with Vβ use. These analyses were guided by recent computational strategies devised to predict gene expression levels based on patterns of histone modifications (50,51). We applied one validated approach (50) to study whether chromatin features, predicted RSS quality, and spatial proximity are predictive of the observed Vβ repertoire.…”

Section: Role Of Chromatin Environment In Determining Vβ Recombinationmentioning

confidence: 99%

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Unifying model for molecular determinants of the preselection Vβ repertoire

Gopalakrishnan

Majumder

Predeus

et al. 2013

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

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The primary antigen receptor repertoire is sculpted by the process of V(D)J recombination, which must strike a balance between diversification and favoring gene segments with specialized functions. The precise determinants of how often gene segments are chosen to complete variable region coding exons remain elusive. We quantified Vβ use in the preselection Tcrb repertoire and report relative contributions of 13 distinct features that may shape their recombination efficiencies, including transcription, chromatin environment, spatial proximity to their DβJβ targets, and predicted quality of recombination signal sequences (RSSs). We show that, in contrast to functional Vβ gene segments, all pseudo-Vβ segments are sequestered in transcriptionally silent chromatin, which effectively suppresses wasteful recombination. Importantly, computational analyses provide a unifying model, revealing a minimum set of five parameters that are predictive of Vβ use, dominated by chromatin modifications associated with transcription, but largely independent of precise spatial proximity to DβJβ clusters. This learned model-building strategy may be useful in predicting the relative contributions of epigenetic, spatial, and RSS features in shaping preselection V repertoires at other antigen receptor loci. Ultimately, such models may also predict how designed or naturally occurring alterations of these loci perturb the preselection use of variable gene segments.lymphocytes | T-cell receptor | gene regulation G ene activity is regulated at multiple levels to coordinate expression during development. At a most basic level, the collection of cis-acting elements for a genetic locus recruits transcription factors that alter its chromatin environment to either induce or repress gene activity. Emerging studies indicate that the 3D conformation of a locus also plays an important role in the regulation of its composite genes (1). At most genes, many levels of control are integrated to achieve the requisite gene expression state. For example, transcriptional promoters interact with their cognate enhancers over considerable distances in the linear genome to generate "hubs" where the two cis elements are in spatial proximity (1, 2).All of these regulatory strategies are used to generate functional Ig (Ig) and T-cell receptor (Tcr) genes during lymphocyte development (3). Each antigen receptor (AgR) locus is composed of multiple variable (V), joining (J), and sometimes diversity (D) gene segments that are assembled by the process of V (D)J recombination, creating a potential variable region exon (4). Recombination is mediated by the RAG-1/2 enzymatic complex, which is expressed in all developing lymphocytes and recognizes semiconserved recombination signal sequences (RSSs) flanking all AgR gene segments (5). On selection of two compatible gene segments by RAG-1/2, recombination proceeds via a DNA break/repair mechanism, ultimately fusing the two selected segments (4, 5).The assembly of AgR genes is strictly regulated despite a common collection of ge...

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Section: Role Of Chromatin Environment In Determining Vβ Recombinationsupporting

confidence: 81%

Section: Role Of Chromatin Environment In Determining Vβ Recombinationmentioning

confidence: 99%

Unifying model for molecular determinants of the preselection Vβ repertoire

Gopalakrishnan

Majumder

Predeus

et al. 2013

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

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“…Recent studies with human cell lines studied by ENCODE (8) have reported detailed relationships between histone modification and expression levels (9). For a limited set of tissues (heart, lung, small bowel, spleen, liver, and brain), data on the same histone modifications exist from the human REMC and mouse ENCODE projects.…”

Section: Histone Mark Differences For Differentially Expressed Genes mentioning

confidence: 99%

Comparison of the transcriptional landscapes between human and mouse tissues

Lin

Nery

et al. 2014

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

330

297

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Although the similarities between humans and mice are typically highlighted, morphologically and genetically, there are many differences. To better understand these two species on a molecular level, we performed a comparison of the expression profiles of 15 tissues by deep RNA sequencing and examined the similarities and differences in the transcriptome for both protein-coding and -noncoding transcripts. Although commonalities are evident in the expression of tissue-specific genes between the two species, the expression for many sets of genes was found to be more similar in different tissues within the same species than between species. These findings were further corroborated by associated epigenetic histone mark analyses. We also find that many noncoding transcripts are expressed at a low level and are not detectable at appreciable levels across individuals. Moreover, the majority lack obvious sequence homologs between species, even when we restrict our attention to those which are most highly reproducible across biological replicates. Overall, our results indicate that there is considerable RNA expression diversity between humans and mice, well beyond what was described previously, likely reflecting the fundamental physiological differences between these two organisms.transcriptome | epigenome | species comparison | noncoding transcripts T he mouse has served as a valuable model organism for human biology and disease. It is widely assumed that biochemical, cellular, and developmental pathways in the mouse are highly conserved with humans and that many processes are clearly preserved at a molecular and genetic level. Moreover, recent detailed studies have examined gene expression in a limited number of tissues in humans and mice. These studies have indicated that gene expression is often conserved and is more similar between the comparable tissues of different organisms rather than within tissues of the same organism. In contrast, the transcript isoform repertoire was found to be markedly different between species (1, 2). Gene Expression Is More Similar Among Tissues Within a Species Than Between Corresponding Tissues of the Two SpeciesTo examine the similarities between humans and mice in much greater detail, we produced RNA-seq data from 13 human tissues [as part of the Encyclopedia Of DNA Elements (ENCODE)], another 11 human tissues [as part of the Roadmap Epigenomics Mapping Consortium (REMC) (3)], and 13 mouse tissues (for mouse ENCODE). We also included in our analysis other data from mouse ENCODE and the Illumina Human BodyMap 2.0 (HBM) (SI Materials and Methods). Sequencing was performed to a depth of 11,313,824-166,188,101 mappable reads (median of 68,399,538 with and an interquartile range of 31,557,836,199). In total, our analysis used 93 datasets encompassing the most tissue-diverse RNA-seq dataset to date spanning several major projects. Thirteen of the mouse and human orthologous datasets were produced by the same laboratory. For our analysis regarding noncoding transcripts, we incorporated an ad...

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“…Recently, additional methods have been developed to predict expression from histone ChIP-seq [22][23][24][25] . These methods were used to predict RNA-seq-based expression levels, using a large number of histone ChIP-seq data sets as input.…”

Section: Npgmentioning

confidence: 99%