Chromosomal rearrangements with duplication of the lamin B1 (LMNB1) gene underlie autosomal dominant adult-onset demyelinating leukodystrophy (ADLD), a rare neurological disorder in which overexpression of LMNB1 causes progressive central nervous system demyelination. However, we previously reported an ADLD family (ADLD-1-TO) without evidence of duplication or other mutation in LMNB1 despite linkage to the LMNB1 locus and lamin B1 overexpression. By custom array-CGH, we further investigated this family and report here that patients carry a large (∼660 kb) heterozygous deletion that begins 66 kb upstream of the LMNB1 promoter. Lamin B1 overexpression was confirmed in further ADLD-1-TO tissues and in a postmortem brain sample, where lamin B1 was increased in the frontal lobe. Through parallel studies, we investigated both loss of genetic material and chromosomal rearrangement as possible causes of LMNB1 overexpression, and found that ADLD-1-TO plausibly results from an enhancer adoption mechanism. The deletion eliminates a genome topological domain boundary, allowing normally forbidden interactions between at least three forebrain-directed enhancers and the LMNB1 promoter, in line with the observed mainly cerebral localization of lamin B1 overexpression and myelin degeneration. This second route to LMNB1 overexpression and ADLD is a new example of the relevance of regulatory landscape modifications in determining Mendelian phenotypes.

X-chromosome inactivation (XCI) provides a dosage compensation mechanism where, in each female cell, one of the two X chromosomes is randomly silenced. However, some genes on the inactive X chromosome and outside the pseudoautosomal regions escape from XCI and are expressed from both alleles (escapees). We investigated XCI at single-cell resolution combining deep single-cell RNA sequencing with whole-genome sequencing to examine allelic-specific expression in 935 primary fibroblast and 48 lymphoblastoid single cells from five female individuals. In this framework we integrated an original method to identify and exclude doublets of cells. In fibroblast cells, we have identified 55 genes as escapees including five undescribed escapee genes. Moreover, we observed that all genes exhibit a variable propensity to escape XCI in each cell and cell type and that each cell displays a distinct expression profile of the escapee genes. A metric, the Inactivation Score—defined as the mean of the allelic expression profiles of the escapees per cell—enables us to discover a heterogeneous and continuous degree of cellular XCI with extremes represented by “inactive” cells, i.e., cells exclusively expressing the escaping genes from the active X chromosome and “escaping” cells expressing the escapees from both alleles. We found that this effect is associated with cell-cycle phases and, independently, with the XIST expression level, which is higher in the quiescent phase (G0). Single-cell allele-specific expression is a powerful tool to identify novel escapees in different tissues and provide evidence of an unexpected cellular heterogeneity of XCI.

Rare, atypical, and undiagnosed autosomal-recessive disorders frequently occur in the offspring of consanguineous couples. Current routine diagnostic genetic tests fail to establish a diagnosis in many cases. We employed exome sequencing to identify the underlying molecular defects in patients with unresolved but putatively autosomal-recessive disorders in consanguineous families and postulated that the pathogenic variants would reside within homozygous regions. Fifty consanguineous families participated in the study, with a wide spectrum of clinical phenotypes suggestive of autosomal-recessive inheritance, but with no definitive molecular diagnosis. DNA samples from the patient(s), unaffected sibling(s), and the parents were genotyped with a 720K SNP array. Exome sequencing and array CGH (comparative genomic hybridization) were then performed on one affected individual per family. High-confidence pathogenic variants were found in homozygosity in known disease-causing genes in 18 families (36%) (one by array CGH and 17 by exome sequencing), accounting for the clinical phenotype in whole or in part. In the remainder of the families, no causative variant in a known pathogenic gene was identified. Our study shows that exome sequencing, in addition to being a powerful diagnostic tool, promises to rapidly expand our knowledge of rare genetic Mendelian disorders and can be used to establish more detailed causative links between mutant genotypes and clinical phenotypes.

Genomic imprinting results in parental-specific gene expression. Imprinted genes are involved in the etiology of rare syndromes and have been associated with common diseases such as diabetes and cancer. Standard RNA bulk cell sequencing applied to whole-tissue samples has been used to detect imprinted genes in human and mouse models. However, lowly expressed genes cannot be detected by using RNA bulk approaches. Here, we report an original and robust method that combines single-cell RNA-seq and whole-genome sequencing into an optimized statistical framework to analyze genomic imprinting in specific cell types and in different individuals. Using samples from the probands of 2 family trios and 3 unrelated individuals, 1,084 individual primary fibroblasts were RNA sequenced and more than 700,000 informative heterozygous single-nucleotide variations (SNVs) were genotyped. The allele-specific coverage per gene of each SNV in each single cell was used to fit a beta-binomial distribution to model the likelihood of a gene being expressed from one and the same allele. Genes presenting a significant aggregate allelic ratio (between 0.9 and 1) were retained to identify of the allelic parent of origin. Our approach allowed us to validate the imprinting status of all of the known imprinted genes expressed in fibroblasts and the discovery of nine putative imprinted genes, thereby demonstrating the advantages of single-cell over bulk RNA-seq to identify imprinted genes. The proposed single-cell methodology is a powerful tool for establishing a cell type-specific map of genomic imprinting.

Aneuploidy is a major source of gene dosage imbalance due to copy number alterations (CNA), and viable human trisomies are model disorders of altered gene expression. We study gene and allele-specific expression (ASE) of 9668 single-cell fibroblasts from trisomy 21 (T21) discordant twins and from mosaic T21, T18, T13 and T8. We examine 928 single cells with deep scRNAseq. Expected and observed overexpression of trisomic genes in trisomic vs. diploid bulk RNAseq is not detectable in trisomic vs. diploid single cells. Instead, for trisomic genes with low-to-average expression, their altered gene dosage is mainly due to the higher fraction of trisomic cells simultaneously expressing these genes, in agreement with a stochastic 2-state burst-like model of transcription. These results, confirmed in a further analysis of 8740 single fibroblasts with shallow scRNAseq, suggest that the specific transcriptional profile of each gene contributes to the phenotypic variability of trisomies. We propose an improved model to understand the effects of CNA and, generally, of gene regulation on gene dosage imbalance.

36In eutherian mammals, X chromosome inactivation (XCI) provides a dosage compensation 37 mechanism where in each female cell one of the two X chromosomes is randomly silenced. 38 However, some genes on the inactive X chromosome and outside the pseudoautosomal 39 regions escape from XCI and are expressed from both alleles (escapees). Given the relevance 40 of the escapees in biology and medicine, we investigated XCI at an unprecedented single-cell 41 resolution. We combined deep single-cell RNA sequencing with whole genome sequencing 42 to examine allelic specific expression (ASE) in 935 primary fibroblast and 48 lymphoblastoid 43 single cells from five female individuals. In this framework we integrated an original method 44 to identify and exclude doublets of cells. We have identified 55 genes as escapees including 5 45 novel escapee genes. Moreover, we observed that all genes exhibit a variable propensity to 46 escape XCI in each cell and cell type, and that each cell displays a distinct expression profile 47 of the escapee genes. We devised a novel metric, the Inactivation Score (IS), defined as the 48 mean of the allelic expression profiles of the escapees per cell, and discovered a 49 heterogeneous and continuous degree of cellular XCI with extremes represented by 50 "inactive" cells, i.e., exclusively expressing the escaping genes from the active X 51 chromosome, and "escaping" cells, expressing the escapees from both alleles. Intriguingly we 52 found that XIST is the major genetic determinant of IS, and that XIST expression, higher in 53 G0 phase, is negatively correlated with the expression of escapees, inactivated and 54 pseudoautosomal genes. In this study we use single-cell allele specific expression to identify 55 novel escapees in different tissues and provide evidence of an unexpected cellular 56 heterogeneity of XCI driven by a possible regulatory activity of XIST. 57 58 59 60 65 chromosome is transcribed (Xa; X-active), whereas the second X chromosome is silenced 66 (Xi; X-inactive) (Lyon 1961). Marsupials have an imprinted pattern of XCI, and the paternal 67 allele is predominantly inactive (Sharman 1971). In mice, an imprinted form of XCI occurs 68 3 through early embryonic developmental stages (4-8 cell stage)(Huynh and Lee 2003; 69 Okamoto et al. 2004; Okamoto et al. 2005; Patrat et al. 2009), followed by inner cell mass 70 reactivation and random XCI in epiblast cells (Mak et al. 2004). In humans, the two X 71 chromosomes are active during post-zygotic stages, achieve gene dosage compensation by 72 dampening their expression up to or even after late blastocyst formation, until one of the X 73 chromosomes is randomly inactivated in each cell (Petropoulos et al. 2016). In female 74 somatic cells, random XCI is stable, resulting in a mosaicism for gene expression on the X 75 chromosome, in which an average of 50% of cells express the active paternal X and 50% the 76 active maternal X alleles. Most of the genes on the Xi chromosome are transcriptionally 77 silenced through epigenetic processe...

ObjectivesFrom the first description by Leo Kanner [1], autism has been an enigmatic neurobehavioral phenomenon. The new genetic/genomic technologies of the past decade have not been as productive as originally anticipated in unveiling the mysteries of autism. The specific etiology of the majority of cases of autism spectrum disorder (ASD) is unknown, although numerous genetic/genomic variants and alterations of diverse cellular functions have been reported. Prompted by this failure, we have investigated whether the metabolomics approach might yield results which could simultaneously lead to a blood-based screening/diagnostic test and to treatment options. Methods Plasma samples from a clinically well-defined cohort of 100 male individuals, ages 2-16+ years, with ASD and 32 age-matched typically developing (TD) controls were subjected to global metabolomic analysis. ResultsWe have identified more than 25 plasma metabolites among the approximately 650 metabolites analyzed, representing over 70 biochemical pathways, that can discriminate children with ASD as young as 2 years from children that are developing typically. The discriminating power was greatest in the 2-10 year age group and weaker in older age groups. The initial findings were validated in a second cohort of 83 children, males and females, ages 2-10 years, with ASD and 76 age and gender-matched TD children. The discriminant metabolites were associated with several key biochemical pathways suggestive of potential contributions of increased oxidative stress, mitochondrial dysfunction, inflammation and immune dysregulation in ASD. Further, targeted quantitative analysis of a subset of discriminating metabolites using tandem mass spectrometry provided a reliable laboratory method to detect children with ASD. Conclusion Metabolic profiling appears to be a robust technique to identify children with ASD ages 2-10 years and provides insights into the altered metabolic pathways in ASD, which could lead to treatment strategies. ObjectivesTo uncover novel traits associated with nicotine and alcohol use genetics, we performed a phenome-wide association study in a large multi-ethnic cohort. Methods We investigated 7,688 African-Americans (AFR), 1,133 Asian-Americans (ASN), 14,081 European-Americans (EUR), and 3,492 Hispanic-Americans (HISP) from the Women's Health Initiative, analyzing risk alleles located in the CHRNA5-CHRNA3 locus (rs8034191, rs1051730, rs12914385, rs2036527, and rs16969968) for nicotine-related traits and ADH1B (rs1229984 and rs2066702) and ALDH2 (rs671) for alcohol-related traits with respect to anthropometric characteristics, dietary habits, social status, psychological circumstances, reproductive history, health conditions, and nicotine-and alcohol-related traits. ResultsThe investigated loci resulted associated with novel traits: rs1229984 were associated with family income (p=4.1*10 −12 ), having a pet (p=6.5*10 −11 ), partner education (p=1.8*10 −10 ), "usually expect the best" (p=2.4*10 −7), "felt calm and peaceful" (p=2.6*10 ), and num...

The mechanisms underlying cellular and organismal phenotypes due to copy number alterations (CNA) are not fully understood. Aneuploidy is a major source of gene dosage imbalance due to CNA and viable human trisomies are model disorders of altered gene expression. To understand the cellular impact of gene dosage imbalance, we studied gene and allele specific expression (ASE) of 9668 single-cell fibroblasts in trisomies T21, T18, T13 and T8. To limit the bias of interindividual noise, all comparisons between euploid and trisomic single-cells were performed on an isogenic setting for all trisomies studied. Initially we examined 928 single cells with deep RNA-Seq. For T21 we used fibroblasts from one pair of monozygotic twins discordant for T21 and from mosaic T21. For T18, T13 and T8 we analyzed single cells from mosaic individuals. Single-cell analyses revealed inconsistencies concerning the overexpression of some genes observed in differential trisomic vs euploid bulk RNAseq while this imbalance was not detectable in trisomic vs. euploid single cells. Moreover, ASE profiling of all single cells uncovered a substantial monoallelic pattern of expression in the trisomic fraction of the genome. By classifying genes according to the level of mono and bi-allelic transcription, we have observed that, for genes with monoallelic and low-to-average expression, the altered gene dosage is mainly due to the higher fraction of cells simultaneously expressing these genes in the trisomic samples. These results were confirmed in a further experiment of 8740 single fibroblasts from the monozygotic twins discordant for T21 samples. We conclude that gene dosage imbalance is of bidimensional nature: over time (simultaneous expression of all alleles resulting in increased accumulation of RNA of copy altered genes in each single cell) as previously stated, and over space (increased fraction of cells simultaneously expressing copy altered genes). These results strongly suggest that each class of genes contributes to the phenotypic variability of trisomies according to its temporal and spatial behavior and propose an improved model to understand the effects of copy number alterations.