Expanding deep phenotypic spectrum associated with atypical pathogenic structural variations overlapping 15q11-q13 imprinting region.

BACKGROUND: The 15q11-q13 region is a genetic locus with genes subject to genomic imprinting, significantly influencing neurodevelopment. Genomic imprinting is an epigenetic phenomenon that causes differential gene expression based on the parent of origin. In most diploid organisms, gene expression typically involves an equal contribution from both maternal and paternal alleles, shaping the phenotype. Nevertheless, in mammals, including humans, mice, and marsupials, the functional equivalence of parental alleles is not universally maintained. Notably, during male and female gametogenesis, parental alleles may undergo differential marking or imprinting, thereby modifying gene expression without altering the underlying DNA sequence. Neurodevelopmental disorders, such as Prader-Willi syndrome (PWS) (resulting from the absence of paternally expressed genes in this region), Angelman syndrome (AS) (associated with the absence of the maternally expressed UBE3A gene), and 15q11-q13 duplication syndrome (resulting from the two common forms of duplications-either an extra isodicentric 15 chromosome or an interstitial 15 duplication), are the outcomes of genetic variations in this imprinting region. METHODS: Conducted a genomic study to identify the frequency of pathogenic variants impacting the 15q11-q13 region in an ethnically homogenous population from Bangladesh. Screened all known disorders from the DECIPHER database and identified variant enrichment within this cohort. Using the Horizon analysis platform, performed enrichment analysis, requiring at least >60% overlap between a copy number variation and a disorder breakpoint. Deep clinical phenotyping was carried out through multiple examination sessions to evaluate a range of clinical symptoms. RESULTS: This study included eight individuals with clinically suspected PWS/AS, all previously confirmed through chromosomal microarray analysis, which revealed chromosomal breakpoints within the 15q11-q13 region. Among this cohort, six cases (75%) exhibited variable lengths of deletions, whereas two cases (25%) showed duplications. These included one type 2 duplication, one larger atypical duplication, one shorter type 2 deletion, one larger type 1 deletion, and four cases with atypical deletions. Furthermore, thorough clinical assessments led to the diagnosis of four PWS patients, two AS patients, and two individuals with 15q11-q13 duplication syndrome. CONCLUSION: Our deep phenotypic observations identified a spectrum of clinical features that overlap and are unique to PWS, AS, and Dup15q syndromes. Our findings establish genotype-phenotype correlation for patients impacted by variable structural variations within the 15q11-q13 region.

Lack of ethnic diversity in single-cell transcriptomics hinders cell type detection and precision medicine inclusivity.

Perhaps one of the most revolutionary next generation sequencing technologies is single-cell (SC) transcriptomics, which was recognized by Nature in 2013 as the method of the year. SC-technologies delve deep into genomics at the single-cell level, revealing previously restricted, valuable information on the identity of single cells, particularly highlighting their heterogeneity. Understanding the cellular heterogeneity of complex tissue provides insight about the gene expression and regulation across different biological and environmental conditions. This vast heterogeneity of cells and their markers makes identifying populations and sub-clusters especially difficult, even more so in rare cell types limited by the absence of rare sub-population markers. One particularly overlooked challenge is the lack of adequate ethnic representation in single-cell data. As the availability of cell types and their markers grow exponentially through new discoveries, the need to study ethnically driven heterogeneity becomes more feasible, while offering the opportunity to further elaborate ethnicity-related heterogeneity. In this commentary, we will discuss this major single-cell limitation particularly focusing on the repercussions it has on disease research, therapeutic design, and precision medicine.

Overlapping pathogenic de novo CNVs in neurodevelopmental disorders and congenital anomalies impacting constraint genes regulating early development.

Neurodevelopmental disorders (NDDs) and congenital anomalies (CAs) are rare disorders with complex etiology. In this study, we investigated the less understood genomic overlap of copy number variants (CNVs) in two large cohorts of NDD and CA patients to identify de novo CNVs and candidate genes associated with both phenotypes. We analyzed clinical microarray CNV data from 10,620 NDD and 3176 CA cases annotated using Horizon platform of GenomeArc Analytics and applied rigorous downstream analysis to evaluate overlapping genes from NDD and CA CNVs. Out of 13,796 patients, only 195 cases contained 218 validated de novo CNVs. Eighteen percent (31/170) de novo CNVs in NDD cases and 40% (19/48) de novo CNVs in CA cases contained genomic overlaps impacting developmentally constraint genes. Seventy-nine constraint genes (10.1% non-OMIM entries) were found to have significantly enriched genomic overlap within rare de novo pathogenic deletions (P value = 0.01, OR = 1.58) and 45 constraint genes (13.3% non-OMIM entries) within rare de novo pathogenic duplications (P value = 0.01, OR = 1.97). Analysis of spatiotemporal transcriptome demonstrated both pathogenic deletion and duplication genes to be highly expressed during the prenatal stage in human developmental brain (P value = 4.95 X 10-6). From the list of overlapping genes, EHMT1, an interesting known NDD gene encompassed pathogenic deletion CNVs from both NDD and CA patients, whereas FAM189A1, and FSTL5 are new candidate genes from non-OMIM entries. In summary, we have identified constraint overlapping genes from CNVs (including de novo) in NDD and CA patients that have the potential to play a vital role in common disease etiology.