Transcriptome-wide survey of mouse CNS-derived cells reveals monoallelic expression within novel gene families.

Monoallelic expression is an integral component of regulation of a number of essential genes and gene families. To probe for allele-specific expression in cells of CNS origin, we used next-generation sequencing (RNA-seq) to analyze four clonal neural stem cell (NSC) lines derived from Mus musculus C57BL/6 (B6)×Mus musculus molossinus (JF1) adult female mice. We established a JF1 cSNP library, then ascertained transcriptome-wide expression from B6 vs. JF1 alleles in the NSC lines. Validating the assay, we found that 262 of 268 X-linked genes evaluable in at least one cell line showed monoallelic expression (at least 85% expression of the predominant allele, p-value<0.05). For autosomal genes 170 of 7,198 genes (2.4% of the total) showed monoallelic expression in at least 2 evaluable cell lines. The group included eight known imprinted genes with the expected pattern of allele-specific expression. Among the other autosomal genes with monoallelic expression were five members of the glutathione transferase gene superfamily, which processes xenobiotic compounds as well as carcinogens and cancer therapeutic agents. Monoallelic expression within this superfamily thus may play a functional role in the response to diverse and potentially lethal exogenous factors, as is the case for the immunoglobulin and olfactory receptor superfamilies. Other genes and gene families showing monoallelic expression include the annexin gene family and the Thy1 gene, both linked to inflammation and cancer, as well as genes linked to alcohol dependence (Gabrg1) and epilepsy (Kcnma1). The annotated set of genes will provide a resource for investigation of mechanisms underlying certain cases of these and other major disorders.

Evidence for sequenced molecular evolution of IDH1 mutant glioblastoma from a distinct cell of origin.

PURPOSE: Mutation in isocitrate dehydrogenase 1 (IDH1) at R132 (IDH1(R132MUT)) is frequent in low-grade diffuse gliomas and, within glioblastoma (GBM), has been proposed as a marker for GBMs that arise by transformation from lower-grade gliomas, regardless of clinical history. To determine how GBMs arising with IDH1(R132MUT) differ from other GBMs, we undertook a comprehensive comparison of patients presenting clinically with primary GBM as a function of IDH1(R132) mutation status. PATIENTS AND METHODS: In all, 618 treatment-naive primary GBMs and 235 lower-grade diffuse gliomas were sequenced for IDH1(R132) and analyzed for demographic, radiographic, anatomic, histologic, genomic, epigenetic, and transcriptional characteristics. RESULTS: Investigation revealed a constellation of features that distinguishes IDH1(R132MUT) GBMs from other GBMs (including frontal location and lesser extent of contrast enhancement and necrosis), relates them to lower-grade IDH1(R132MUT) gliomas, and supports the concept that IDH1(R132MUT) gliomas arise from a neural precursor population that is spatially and temporally restricted in the brain. The observed patterns of DNA sequence, methylation, and copy number alterations support a model of ordered molecular evolution of IDH1(R132MUT) GBM in which the appearance of mutant IDH1 protein is an initial event, followed by production of p53 mutant protein, and finally by copy number alterations of PTEN and EGFR. CONCLUSION: Although histologically similar, GBMs arising with and without IDH1(R132MUT) appear to represent distinct disease entities that arise from separate cell types of origin as the result of largely nonoverlapping sets of molecular events. Optimal clinical management should account for the distinction between these GBM disease subtypes.

Dual DNA methylation patterns in the CNS reveal developmentally poised chromatin and monoallelic expression of critical genes.

As a first step towards discovery of genes expressed from only one allele in the CNS, we used a tiling array assay for DNA sequences that are both methylated and unmethylated (the MAUD assay). We analyzed regulatory regions of the entire mouse brain transcriptome, and found that approximately 10% of the genes assayed showed dual DNA methylation patterns. They include a large subset of genes that display marks of both active and silent, i.e., poised, chromatin during development, consistent with a link between differential DNA methylation and lineage-specific differentiation within the CNS. Sixty-five of the MAUD hits and 57 other genes whose function is of relevance to CNS development and/or disorders were tested for allele-specific expression in F(1) hybrid clonal neural stem cell (NSC) lines. Eight MAUD hits and one additional gene showed such expression. They include Lgi1, which causes a subtype of inherited epilepsy that displays autosomal dominance with incomplete penetrance; Gfra2, a receptor for glial cell line-derived neurotrophic factor GDNF that has been linked to kindling epilepsy; Unc5a, a netrin-1 receptor important in neurodevelopment; and Cspg4, a membrane chondroitin sulfate proteoglycan associated with malignant melanoma and astrocytoma in human. Three of the genes, Camk2a, Kcnc4, and Unc5a, show preferential expression of the same allele in all clonal NSC lines tested. The other six genes show a stochastic pattern of monoallelic expression in some NSC lines and bi-allelic expression in others. These results support the estimate that 1-2% of genes expressed in the CNS may be subject to allelic exclusion, and demonstrate that the group includes genes implicated in major disorders of the CNS as well as neurodevelopment.

Unique retrotransposon LINE-1 distribution at the Prader-Willi Angelman syndrome locus.

We analyzed the distribution of long interspersed nuclear elements (LINE)-1 (L1) along mouse autosomes at a 1-Mb scale, and found a unique combination of high density and strand asymmetry of L1 elements at the imprinted Prader-Willi syndrome/Angelman syndrome (PWS/AS) locus on mouse chromosome 7. This L1 signature overlaps the paternally expressed domain of the locus, excluding the maternally expressed Ube3a gene, and is conserved in rat and human. Unlike the PWS/AS locus, other instances of high L1 density and strand asymmetry in the mouse are not associated with imprinted regions and are not evolutionarily conserved in human. The evolutionary conservation of the L1 signature at the PWS/AS locus despite differences in composition of L1 elements between rodent and human, requires a mechanism for active perpetuation of L1 asymmetry during bursts of L1 activity, and indicates a possible functional role for L1 elements at this locus. Aside from the PWS/AS locus, rodents have a far greater correlation of L1 densities between DNA strands than do humans; we provide evidence that this difference in interstrand correlation between the two taxa is due largely to the difference in average age of the dominant L1 families.

siRNA target site secondary structure predictions using local stable substructures.

The crystal structure based model of the catalytic center of Ago2 revealed that the siRNA and the mRNA must be able to form an A-helix for correct positing of the scissile phosphate bond for cleavage in RNAi. This suggests that base pairing of the target mRNA with itself, i.e. secondary structure, must be removed before cleavage. Early on in the siRNA design, GC-rich target sites were avoided because of their potential to be involved in strong secondary structure. It is still unclear how important a factor mRNA secondary structure is in RNAi. However, it has been established that a difference in the thermostability of the ends of an siRNA duplex dictate which strand is loaded into the RNA-induced silencing complex. Here, we use a novel secondary structure prediction method and duplex-end differential calculations to investigate the importance of a secondary structure in the siRNA design. We found that the differential duplex-end stabilities alone account for functional prediction of 60% of the 80 siRNA sites examined, and that secondary structure predictions improve the prediction of site efficacy. A total of 80% of the non-functional sites can be eliminated using secondary structure predictions and duplex-end differential.