Differential Allelic Expression in the Human Genome: A Robust Approach To Identify Genetic and Epigenetic Cis-Acting Mechanisms Regulating Gene Expression

The recent development of whole genome association studies has lead to the robust identification of several loci involved in different common human diseases. Interestingly, some of the strongest signals of association observed in these studies arise from non-coding regions located in very large introns or far away from any annotated genes, raising the possibility that these regions are involved in the etiology of the disease through some unidentified regulatory mechanisms. These findings highlight the importance of better understanding the mechanisms leading to inter-individual differences in gene expression in humans. Most of the existing approaches developed to identify common regulatory polymorphisms are based on linkage/association mapping of gene expression to genotypes. However, these methods have some limitations, notably their cost and the requirement of extensive genotyping information from all the individuals studied which limits their applications to a specific cohort or tissue. Here we describe a robust and high-throughput method to directly measure differences in allelic expression for a large number of genes using the Illumina Allele-Specific Expression BeadArray platform and quantitative sequencing of RT-PCR products. We show that this approach allows reliable identification of differences in the relative expression of the two alleles larger than 1.5-fold (i.e., deviations of the allelic ratio larger than 60∶40) and offers several advantages over the mapping of total gene expression, particularly for studying humans or outbred populations. Our analysis of more than 80 individuals for 2,968 SNPs located in 1,380 genes confirms that differential allelic expression is a widespread phenomenon affecting the expression of 20% of human genes and shows that our method successfully captures expression differences resulting from both genetic and epigenetic cis-acting mechanisms

Parental Effect of DNA (Cytosine-5) Methyltransferase 1 on Grandparental-Origin-Dependent Transmission Ratio Distortion in Mouse Crosses and Human Families

Transmission ratio distortion (TRD) is a deviation from the expected Mendelian 1:1 ratio of alleles transmitted from parents to offspring and may arise by different mechanisms. Earlier we described a grandparental-origin-dependent sex-of-offspring-specific TRD of maternal chromosome 12 alleles closely linked to an imprinted region and hypothesized that it resulted from imprint resetting errors in the maternal germline. Here, we report that the genotype of the parents for loss-of-function mutations in the Dnmt1 gene influences the transmission of grandparental chromosome 12 alleles. More specifically, maternal Dnmt1 mutations restore Mendelian transmission ratios of chromosome 12 alleles. Transmission of maternal alleles depends upon the presence of the Dnmt1 mutation in the mother rather than upon the Dnmt1 genotype of the offspring. Paternal transmission mirrors the maternal one: live-born offspring of wild-type fathers display 1:1 transmission ratios, whereas offspring of heterozygous Dnmt1 mutant fathers tend to inherit grandpaternal alleles. Analysis of allelic transmission in the homologous region of human chromosome 14q32 detected preferential transmission of alleles from the paternal grandfather to grandsons. Thus, parental Dnmt1 is a modifier of transmission of alleles at an unlinked chromosomal region and perhaps has a role in the genesis of TRD

Performance of the McGill Interactive Pediatric OncoGenetic Guidelines for Identifying Cancer Predisposition Syndromes.

Importance Prompt recognition of a child with a cancer predisposition syndrome (CPS) has implications for cancer management, surveillance, genetic counseling, and cascade testing of relatives. Diagnosis of CPS requires practitioner expertise, access to genetic testing, and test result interpretation. This diagnostic process is not accessible in all institutions worldwide, leading to missed CPS diagnoses. Advances in electronic health technology can facilitate CPS risk assessment. Objective To evaluate the diagnostic accuracy of a CPS prediction tool (McGill Interactive Pediatric OncoGenetic Guidelines [MIPOGG]) in identifying children with cancer who have a low or high likelihood of having a CPS. Design, Setting, and Participants In this international, multicenter diagnostic accuracy study, 1071 pediatric (<19 years of age) oncology patients who had a confirmed CPS (12 oncology referral centers) or who underwent germline DNA sequencing through precision medicine programs (6 centers) from January 1, 2000, to July 31, 2020, were studied. Exposures Exposures were MIPOGG application in patients with cancer and a confirmed CPS (diagnosed through routine clinical care; n = 413) in phase 1 and MIPOGG application in patients with cancer who underwent germline DNA sequencing (n = 658) in phase 2. Study phases did not overlap. Data analysts were blinded to genetic test results. Main Outcomes and Measures The performance of MIPOGG in CPS recognition was compared with that of routine clinical care, including identifying a CPS earlier than practitioners. The tool's test characteristics were calculated using next-generation germline DNA sequencing as the comparator. Results In phase 1, a total of 413 patients with cancer (median age, 3.0 years; range, 0-18 years) and a confirmed CPS were identified. MIPOGG correctly recognized 410 of 412 patients (99.5%) as requiring referral for CPS evaluation at the time of primary cancer diagnosis. Nine patients diagnosed with a CPS by a practitioner after their second malignant tumor were detected by MIPOGG using information available at the time of the first cancer. In phase 2, of 658 children with cancer (median age, 6.6 years; range, 0-18.8 years) who underwent comprehensive germline DNA sequencing, 636 had sufficient information for MIPOGG application. When compared with germline DNA sequencing for CPS detection, the MIPOGG test characteristics for pediatric-onset CPSs were as follows: sensitivity, 90.7%; specificity, 60.5%; positive predictive value, 17.6%; and negative predictive value, 98.6%. Tumor DNA sequencing data confirmed the MIPOGG recommendation for CPS evaluation in 20 of 22 patients with established cancer-CPS associations. Conclusions and Relevance In this diagnostic study, MIPOGG exhibited a favorable accuracy profile for CPS screening and reduced time to CPS recognition. These findings suggest that MIPOGG implementation could standardize and rationalize recommendations for CPS evaluation in children with cancer