Dataset Information

A lacZ reporter gene expression atlas for 313 adult KOMP mutant mouse lines.

ABSTRACT: Expression of the bacterial beta-galactosidase reporter gene (lacZ) in the vector used for the Knockout Mouse Project (KOMP) is driven by the endogenous promoter of the target gene. In tissues from KOMP mice, histochemical staining for LacZ enzyme activity can be used to determine gene expression patterns. With this technique, we have produced a comprehensive resource of gene expression using both whole mount (WM) and frozen section (FS) LacZ staining in 313 unique KOMP mutant mouse lines. Of these, ? 80% of mutants showed specific staining in one or more tissues, while ? 20% showed no specific staining, ? 13% had staining in only one tissue, and ? 25% had staining in >6 tissues. The highest frequency of specific staining occurred in the brain (? 50%), male gonads (42%), and kidney (39%). The WM method was useful for rapidly identifying whole organ and some substructure staining, while the FS method often revealed substructure and cellular staining specificity. Both staining methods had >90% repeatability in biological replicates. Nonspecific LacZ staining occurs in some tissues due to the presence of bacteria or endogenous enzyme activity. However, this can be effectively distinguished from reporter gene activity by the combination of the WM and FS methods. After careful annotation, LacZ staining patterns in a high percentage of mutants revealed a unique structure-function not previously reported for many of these genes. The validation of methods for LacZ staining, annotation, and expression analysis reported here provides unique insights into the function of genes for which little is currently known.

SUBMITTER: West DB

PROVIDER: S-EPMC4381530 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

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A lacZ reporter gene expression atlas for 313 adult KOMP mutant mouse lines.

West David B DB Pasumarthi Ravi K RK Baridon Brian B Djan Esi E Trainor Amanda A Griffey Stephen M SM Engelhard Eric K EK Rapp Jared J Li Bowen B de Jong Pieter J PJ Lloyd K C Kent KC

Genome research 20150115 4

Expression of the bacterial beta-galactosidase reporter gene (lacZ) in the vector used for the Knockout Mouse Project (KOMP) is driven by the endogenous promoter of the target gene. In tissues from KOMP mice, histochemical staining for LacZ enzyme activity can be used to determine gene expression patterns. With this technique, we have produced a comprehensive resource of gene expression using both whole mount (WM) and frozen section (FS) LacZ staining in 313 unique KOMP mutant mouse lines. Of th ...[more]

PMID: 25591789

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Project description:High-throughput, spatially resolved gene expression techniques are poised to be transformative across biology by overcoming a central limitation in single-cell biology: the lack of information on relationships that organize the cells into the functional groupings characteristic of tissues in complex multicellular organisms. Spatial expression is particularly interesting in the mammalian brain, which has a highly defined structure, strong spatial constraint in its organization, and detailed multimodal phenotypes for cells and ensembles of cells that can be linked to mesoscale properties such as projection patterns, and from there, to circuits generating behavior. However, as with any type of expression data, cross-dataset benchmarking of spatial data is a crucial first step. Here, we assess the replicability, with reference to canonical brain subdivisions, between the Allen Institute's in situ hybridization data from the adult mouse brain (Allen Brain Atlas (ABA)) and a similar dataset collected using spatial transcriptomics (ST). With the advent of tractable spatial techniques, for the first time, we are able to benchmark the Allen Institute's whole-brain, whole-transcriptome spatial expression dataset with a second independent dataset that similarly spans the whole brain and transcriptome. We use regularized linear regression (LASSO), linear regression, and correlation-based feature selection in a supervised learning framework to classify expression samples relative to their assayed location. We show that Allen Reference Atlas labels are classifiable using transcription in both data sets, but that performance is higher in the ABA than in ST. Furthermore, models trained in one dataset and tested in the opposite dataset do not reproduce classification performance bidirectionally. While an identifying expression profile can be found for a given brain area, it does not generalize to the opposite dataset. In general, we found that canonical brain area labels are classifiable in gene expression space within dataset and that our observed performance is not merely reflecting physical distance in the brain. However, we also show that cross-platform classification is not robust. Emerging spatial datasets from the mouse brain will allow further characterization of cross-dataset replicability ultimately providing a valuable reference set for understanding the cell biology of the brain.

Dataset Information

A lacZ reporter gene expression atlas for 313 adult KOMP mutant mouse lines.

Publications

A lacZ reporter gene expression atlas for 313 adult KOMP mutant mouse lines.

Similar Datasets

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