MaGIC: a Machine Learning Tool Set and Web Application for Monoallelic Gene Inference from Chromatin

Overview

Journal BMC Bioinformatics

Publisher Biomed Central

Specialty Biology

Date 2019 Mar 2

PMID 30819107

Citations 4

Authors

Svetlana Vinogradova

Sachit D Saksena

Henry N Ward

Sebastien Vigneau

Alexander A Gimelbrant

Affiliations

Soon will be listed here.

Abstract

Background: A large fraction of human and mouse autosomal genes are subject to random monoallelic expression (MAE), an epigenetic mechanism characterized by allele-specific gene expression that varies between clonal cell lineages. MAE is highly cell-type specific and mapping it in a large number of cell and tissue types can provide insight into its biological function. Its detection, however, remains challenging.

Results: We previously reported that a sequence-independent chromatin signature identifies, with high sensitivity and specificity, genes subject to MAE in multiple tissue types using readily available ChIP-seq data. Here we present an implementation of this method as a user-friendly, open-source software pipeline for monoallelic gene inference from chromatin (MaGIC). The source code for the MaGIC pipeline and the Shiny app is available at https://github.com/gimelbrantlab/magic .

Conclusion: The pipeline can be used by researchers to map monoallelic expression in a variety of cell types using existing models and to train new models with additional sets of chromatin marks.

Citing Articles

Monoallelic expression can govern penetrance of inborn errors of immunity.

Stewart O, Gruber C, Randolph H, Patel R, Ramba M, Calzoni E Nature. 2025; 637(8048):1186-1197.

PMID: 39743591 PMC: 11804961. DOI: 10.1038/s41586-024-08346-4.

Foreign RNA spike-ins enable accurate allele-specific expression analysis at scale.

Mendelevich A, Gupta S, Pakharev A, Teodosiadis A, Mironov A, Gimelbrant A Bioinformatics. 2023; 39(39 Suppl 1):i431-i439.

PMID: 37387154 PMC: 10311301. DOI: 10.1093/bioinformatics/btad254.

Foreign RNA spike-ins enable accurate allele-specific expression analysis at scale.

Mendelevich A, Gupta S, Pakharev A, Teodosiadis A, Mironov A, Gimelbrant A bioRxiv. 2023; .

PMID: 36798258 PMC: 9934692. DOI: 10.1101/2023.02.11.528027.

Replicate sequencing libraries are important for quantification of allelic imbalance.

Mendelevich A, Vinogradova S, Gupta S, Mironov A, Sunyaev S, Gimelbrant A Nat Commun. 2021; 12(1):3370.

PMID: 34099647 PMC: 8184992. DOI: 10.1038/s41467-021-23544-8.

References

Gimelbrant A, Hutchinson J, Thompson B, Chess A . Widespread monoallelic expression on human autosomes. Science. 2007; 318(5853):1136-40. DOI: 10.1126/science.1148910. View

Kent W, Zweig A, Barber G, Hinrichs A, Karolchik D . BigWig and BigBed: enabling browsing of large distributed datasets. Bioinformatics. 2010; 26(17):2204-7. PMC: 2922891. DOI: 10.1093/bioinformatics/btq351. View

Zwemer L, Zak A, Thompson B, Kirby A, Daly M, Chess A . Autosomal monoallelic expression in the mouse. Genome Biol. 2012; 13(2):R10. PMC: 3334567. DOI: 10.1186/gb-2012-13-2-r10. View

Ha G, Roth A, Lai D, Bashashati A, Ding J, Goya R . Integrative analysis of genome-wide loss of heterozygosity and monoallelic expression at nucleotide resolution reveals disrupted pathways in triple-negative breast cancer. Genome Res. 2012; 22(10):1995-2007. PMC: 3460194. DOI: 10.1101/gr.137570.112. View

. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012; 489(7414):57-74. PMC: 3439153. DOI: 10.1038/nature11247. View

Polson E, Lewis J, Celik H, Mann V, Stower M, Simms M . Monoallelic expression of TMPRSS2/ERG in prostate cancer stem cells. Nat Commun. 2013; 4:1623. DOI: 10.1038/ncomms2627. View

Savova V, Vigneau S, Gimelbrant A . Autosomal monoallelic expression: genetics of epigenetic diversity?. Curr Opin Genet Dev. 2013; 23(6):642-8. DOI: 10.1016/j.gde.2013.09.001. View

Nag A, Savova V, Fung H, Miron A, Yuan G, Zhang K . Chromatin signature of widespread monoallelic expression. Elife. 2014; 2:e01256. PMC: 3873816. DOI: 10.7554/eLife.01256. View

Pohl A, Beato M . bwtool: a tool for bigWig files. Bioinformatics. 2014; 30(11):1618-9. PMC: 4029031. DOI: 10.1093/bioinformatics/btu056. View

10.

Eckersley-Maslin M, Spector D . Random monoallelic expression: regulating gene expression one allele at a time. Trends Genet. 2014; 30(6):237-44. PMC: 4037383. DOI: 10.1016/j.tig.2014.03.003. View

11.

Nag A, Vigneau S, Savova V, Zwemer L, Gimelbrant A . Chromatin Signature Identifies Monoallelic Gene Expression Across Mammalian Cell Types. G3 (Bethesda). 2015; 5(8):1713-20. PMC: 4528328. DOI: 10.1534/g3.115.018853. View

12.

Savova V, Chun S, Sohail M, McCole R, Witwicki R, Gai L . Genes with monoallelic expression contribute disproportionately to genetic diversity in humans. Nat Genet. 2016; 48(3):231-237. PMC: 4942303. DOI: 10.1038/ng.3493. View

13.

Chess A . Monoallelic Gene Expression in Mammals. Annu Rev Genet. 2016; 50:317-327. DOI: 10.1146/annurev-genet-120215-035120. View

14.

Savova V, Vinogradova S, Pruss D, Gimelbrant A, Weiss L . Risk alleles of genes with monoallelic expression are enriched in gain-of-function variants and depleted in loss-of-function variants for neurodevelopmental disorders. Mol Psychiatry. 2017; 22(12):1785-1794. PMC: 5589474. DOI: 10.1038/mp.2017.13. View

15.

Gui B, Slone J, Huang T . Perspective: Is Random Monoallelic Expression a Contributor to Phenotypic Variability of Autosomal Dominant Disorders?. Front Genet. 2017; 8:191. PMC: 5718016. DOI: 10.3389/fgene.2017.00191. View

16.

Landis J, Koch G . The measurement of observer agreement for categorical data. Biometrics. 1977; 33(1):159-74. View