Genetic predisposition to porto-sinusoidal vascular disorder: A functional genomic-based, multigenerational family study.

BACKGROUND AND AIMS: Porto-sinusoidal vascular disorder (PSVD) is a group of liver vascular diseases featuring lesions encompassing the portal venules and sinusoids unaccompanied by cirrhosis, irrespective of the presence/absence of portal hypertension. It can occur secondary to coagulation disorders or insult by toxic agents. However, the cause of PSVD remains unknown in most cases. Hereditary cases of PSVD are exceptionally rare, but they are of particular interest and may unveil genetic alterations and molecular mechanisms associated with the disease. APPROACH AND RESULTS: We performed genome sequencing of four patients and two healthy individuals of a large multigenerational Lebanese family with PSVD and identified a heterozygous deleterious variant (c.547C>T, p.R183W) of FCH and double SH3 domains 1 ( FCHSD1 ), an uncharacterized gene, in patients. This variant segregated with the disease, and its pattern of inheritance was suggestive of autosomal dominant with variable expressivity. RNA structural modelling of human FCHSD1 suggests that the C-to-T substitution at position 547, corresponding to FCHSD1R183W , may increase both messenger RNA (mRNA) and protein stability and its interaction with MTOR-associated protein, LST8 homolog, a key protein of the mechanistic target of rapamycin (mTOR pathway). These predictions were substantiated by biochemical analyses, which showed that FCHSD1R183W induced high FCHSD1 mRNA stability, overexpression of FCHSD1 protein, and an increase in mTORC1 activation. This human FCHSD1 variant was introduced into mice through CRISPR/Cas9 genome editing. Nine out of the 15 mice carrying the human FCHSD1R183W variant mimicked the phenotype of human PSVD, including splenomegaly and enlarged portal vein. CONCLUSIONS: Aberrant FCHSD1 structure and function leads to mTOR pathway overactivation and may cause PSVD.

A Report on a Family with TMTC3-Related Syndrome and Review.

Recessive mutations in the TMTC3 gene have been reported in thirteen patients to date exhibiting development delay, intellectual disability (ID), seizures, and muscular hypotonia, accompanied occasionally by neuronal migration defects expressed as either cobblestone lissencephaly or periventricular hypertopia. Here, we report a new case of a TMTC3-related syndrome in a Lebanese family with two affected siblings showing severe psychomotor retardation, intellectual disability, microcephaly, absence of speech, muscular hypotonia, and seizures. Whole exome sequencing revealed a homozygous pathogenic variant c.211 C > T (p.R71C) in the TMTC3 gene in both siblings. A review of the literature on TMTC3-related syndrome and its causal mutations is provided.

Elucidating tissue specific genes using the Benford distribution.

BACKGROUND: The RNA-seq technique is applied for the investigation of transcriptional behaviour. The reduction in sequencing costs has led to an unprecedented trove of gene expression data from diverse biological systems. Subsequently, principles from other disciplines such as the Benford law, which can be properly judged only in data-rich systems, can now be examined on this high-throughput transcriptomic information. The Benford law, states that in many count-rich datasets the distribution of the first significant digit is not uniform but rather logarithmic. RESULTS: All tested digital gene expression datasets showed a Benford-like distribution when observing an entire gene set. This phenomenon was conserved in development and does not demonstrate tissue specificity. However, when obedience to the Benford law is calculated for individual expressed genes across thousands of cells, genes that best and least adhere to the Benford law are enriched with tissue specific or cell maintenance descriptors, respectively. Surprisingly, a positive correlation was found between the obedience a gene exhibits to the Benford law and its expression level, despite the former being calculated solely according to first digit frequency while totally ignoring the expression value itself. Nevertheless, genes with low expression that exhibit Benford behavior demonstrate tissue specific associations. These observations were extended to predict the likelihood of tissue specificity based on Benford behaviour in a supervised learning approach. CONCLUSIONS: These results demonstrate the applicability and potential predictability of the Benford law for gleaning biological insight from simple count data.