About the Database

While individual cases of MAE have been documented for over half a century, the prevalence and importance of MAE have only recently become appreciated through the advent of high-throughput allele-specific methods. To date, MAE has been experimentally measured in a number of different cell types by RNA-seq (and array) methods applied to individual clonal populations derived from F1 individuals in deeply sequenced trios -- in the case of human, or hybrid backgrounds in mouse. These assays relied on the availability of genetic variants in the coding region to quantify the allele-specific expression level of individual genes.Recently it was demonstrated that MAE can be idenified in the absence of coding variation on the basis of chromatin modifiers in human and mouse. Due to the latest developments, data on monoallelic expression has become available for the entire genome in multiple tissues and cell types in two major model organisms, creating a need for better access and dissemination. This database was created to address this need, with both basic and advanced functionality in mind.

Here are some suggestions on how to explore:

1) see if a gene you know is inferred or measured to be monoallelic in mouse or human tissues (e.g. Msx2)
2) check how classes of genes behave (by checking the prefix search box, and entering a partial name e.g. Msx)

Next, try some more advanced searches by clicking on the "Advanced" button:
3) check the status of the gene in a specific organism/tissue (e.g. Msx2 in mouse fibroblast)

Then, using the orange toggle button change to search by status check if a class of genes:
4) is inferred/known to be monoallelic anywhere ( Msx in any organisms).

...or
5) is inferred/known to be monoallelic in mouse fibroblasts specifically ( Msx in Mouse:fibroblast).

The status of a gene is indicated as monoallelic if there is evidence for monoallelic expression in at least one tissue in the organism of interest. Undetermined status indicates that the expression level of the gene is outside the validated scope of the chromatin identification method (<50% quantile rank). Biallelic status is assigned to a gene if all available assays point to biallelic expression.

Any feedback is much appreciated Send us an email.

Thanks!
-The dbMAE crew

Guiding principles

While the database relies on multiple sources from the literature, every effort is made for uniform analysis. Platforms of data collection are often similar, but the interpretation of the data resulting in MAE or BAE calls varies greatly by publication. For example, some publications consider the reads mapped on the the entire gene body (Eckersley-Maslin et al.), while others used calls based on individual variants (e.g. Gendrel et al. ). In addition, only individual sources provide a procedure for positively confirming biallelic expression.
To ensure equal reliability of calls across data sources, published datasets of experimental RNA-seq measurements have been subjected to the same statistical analysis procedure to infer MAE status, or confirm biallelic (BAE) status. The procedure was first described in Nag, Savova et al. (see Fig 2C ). Array data from Gimelbrant et al. and PMC3334567 et al. is handled categorically according to the supplementary tables of these publications. Chromatin data from Nag, Savova et al. Nag, Vigneau et al. has been made compatible by quantile normalization, which involved altering the expression reliability threshold used in Nag, Savova et al. to match an updated definition in the subsequent work.

About the Creators

dbMAE was developed in the Gimelbrant Lab, by Virginia Savova and Jon Patsenker. Sebastien Vigneau was responsible for compiling the data.

How to cite

Using dbMAE is free for academic use and to facilitate access, no registration is required. If you use dbMAE in your research, remember to cite the accompanying article "dbMAE: the database of autosomal monoallelic expression", published in Nucl. Acids Res. (2015)"
For the chromatin signature method, cite our primary publication ( Nag, Savova et al ). If you would like to learn about MAE and its potential for disrupting the relationship between genotype and phenotype, please read our review article Savova et al. .