DNA repair-related heritable photosensitivity syndromes: Mutation landscape in a multiethnic cohort of 17 multigenerational families with high degree of consanguinity.

Inherited photosensitivity syndromes are a heterogeneous group of genetic skin disorders with tremendous phenotypic variability, characterized by photosensitivity and defective DNA repair, especially nucleotide excision repair. A cohort of 17 Iranian families with heritable photosensitivity syndromes was evaluated to identify their genetic defect. The patients' DNA was analyzed with either whole-exome sequencing or RNA sequencing (RNA-Seq). The interpretations of the genomic results were guided by genome-wide homozygosity mapping. Haplotype analysis was performed for cases with recurrent mutations. RNA-Seq, in addition to mutation detection, was also utilized to confirm the pathogenicity. Thirteen sequence variants, including six previously unreported pathogenic variants, were disclosed in 17 Iranian families, with XPC as the most common mutated gene in 10 families (59%). In one patient, RNA-Seq, as a first-tier diagnostic approach, revealed a non-canonical homozygous germline variant: XPC:c.413-9 T > A. The Sashimi plot showed skipping of exon 4 with dramatic XPC down-expression. Haplotype analysis of XPC:c.2251-1 G>C and XPC:1243 C>T in four families showed common haplotypes of 1.7 Mb and 2.6 Mb, respectively, denoting a founder effect. Lastly, two extremely rare cases were presented in this report: a homozygous UVSSA:c .1990 C>T was disclosed, and ERCC2-related cerebro-oculo-facio-skeletal (COFS) syndrome with an early childhood death. A direct comparison of our data with the results of previously reported cohorts demonstrates the international mutation landscape of DNA repair-related photosensitivity disorders, although population-specific differences were observed.

Integrating chromatin accessibility states in the design of targeted sequencing panels for liquid biopsy.

Dying tumor cells shed DNA fragments into the circulation that are known as circulating tumor DNA (ctDNA). Liquid biopsy tests aim to detect cancer using known markers, including genetic alterations and epigenetic profiles of ctDNA. Despite various advantages, the major limitation remains the low fraction of tumor-originating DNA fragments in a high background of normal blood-cell originating fragments in the cell-free DNA (cfDNA) pool in plasma. Deep targeted sequencing of cfDNA allows for enrichment of fragments in known cancer marker-associated regions of the genome, thus increasing the chances of detecting the low fraction variant harboring fragments. Most targeted sequencing panels are designed to include known recurrent mutations or methylation markers of cancer. Here, we propose the integration of cancer-specific chromatin accessibility states into panel designs for liquid biopsy. Using machine learning approaches, we first identify accessible and inaccessible chromatin regions specific to each major human cancer type. We then introduce a score that quantifies local chromatin accessibility in tumor relative to blood cells and show that this metric can be useful for prioritizing marker regions with higher chances of being detected in cfDNA for inclusion in future panel designs.

Whole-transcriptome sequencing-based concomitant detection of viral and human genetic determinants of cutaneous lesions.

Severe viral infections of the skin can occur in patients with inborn errors of immunity (IEI). We report an all-in-one whole-transcriptome sequencing-based method by RNA-Seq on a single skin biopsy for concomitantly identifying the cutaneous virome and the underlying IEI. Skin biopsies were obtained from healthy and lesional skin from patients with cutaneous infections suspected to be of viral origin. RNA-Seq was utilized as the first-tier strategy for unbiased human genome-wide rare variant detection. Reads unaligned to the human genome were utilized for the exploration of 926 viruses in a viral genome catalog. In 9 families studied, the patients carried pathogenic variants in 6 human IEI genes, including IL2RG, WAS, CIB1, STK4, GATA2, and DOCK8. Gene expression profiling also confirmed pathogenicity of the human variants and permitted genome-wide homozygosity mapping, which assisted in identification of candidate genes in consanguineous families. This automated, online, all-in-one computational pipeline, called VirPy, enables simultaneous detection of the viral triggers and the human genetic variants underlying skin lesions in patients with suspected IEI and viral dermatosis.

Investigation and characterization of human gut phageome in advanced liver cirrhosis of defined etiologies.

BACKGROUND: Liver cirrhosis is a major public health problem, accounting for high rates of morbidity and mortality worldwide. The cirrhosis etiology is a broad and essential step in planning a treatment strategy. Many recent studies have documented that gut microbiome alterations play a vital role in the development and progression of cirrhosis and its complications. Nevertheless, there is insufficient data on the correlation between liver cirrhosis and gut phageome alterations in patients with advanced liver diseases. This study aimed to analyze the taxonomic structure and functional attributes of the gut phageome in six different etiologies of advanced liver cirrhosis. METHODS: We first retrieved metagenomic sequencing data from three datasets of fecal samples taken from cirrhotic patients with various etiologies. Subsequently, several bioinformatics pipelines were used to analyze bacteriophage composition and determine their functionality. RESULTS: A gene catalog of 479,425 non-redundant genes was developed as a reference to measure gene prevalence. The results of the analysis revealed a few significant differences among the cohorts at the phage species level. However, the alternations were more evident as there were more in-depth analyses of the functional resolution of the gut phageome. CONCLUSIONS: Our findings suggest that the functional analysis of the gut phageome would provide meaningful markers to predict the progression of liver cirrhosis and facilitate the development of novel treatment approaches.

RNA Sequencing of CD4+ T Cells in Relapsing-Remitting Multiple Sclerosis Patients at Relapse: Deciphering the Involvement of Novel genes and Pathways.

CD4+ T cells are known as a noteworthy potential modulator of inflammation in multiple sclerosis (MS). In the current study, we investigated the transcriptome profile of CD4+ T cells in patients with relapsing-remitting MS (RRMS) at the relapse phase. We performed RNA sequencing of CD4+ T cells isolated from four relapsing-remitting MS (RRMS) patients at the relapse phase and four age- and sex-matched healthy controls. The edgeR statistical method was employed to determine differentially expressed genes (DEGs). Gene set enrichment analysis was subsequently performed. Applying a physical interaction network, genes with higher degrees were selected as hub genes. A total of 1278 and 1034 genes were defined at significantly higher or lower levels, respectively, in CD4+ T cells of RRMS patients at the relapse phase as compared with healthy controls. The top up- and downregulated genes were JAML and KDM3A. The detected DEGs were remarkable on chromosomes 1 and 2, respectively. The DEGs were mainly enriched in the pathways "regulation of transcription, DNA-templated," "regulation of B cell receptor signaling pathway," "protein phosphorylation," "epidermal growth factor receptor signaling pathway," and "positive regulation of neurogenesis." Moreover, 16 KEGG pathways mostly associated with the immune system and viral infections were enriched. In the constructed physical interaction networks, UBA52 and TP53 were shown to be the most highly ranked hub genes among upregulated and downregulated genes, respectively. By applying global transcriptome profiling of CD4+ T cells, we deciphered the involvement of several novel genes and pathways in MS pathogenesis. The present results must be confirmed by in vivo and in vitro studies.

Whole-Transcriptome Analysis by RNA Sequencing for Genetic Diagnosis of Mendelian Skin Disorders in the Context of Consanguinity.

BACKGROUND: Among the approximately 8000 Mendelian disorders, >1000 have cutaneous manifestations. In many of these conditions, the underlying mutated genes have been identified by DNA-based techniques which, however, can overlook certain types of mutations, such as exonic-synonymous and deep-intronic sequence variants. Whole-transcriptome sequencing by RNA sequencing (RNA-seq) can identify such mutations and provide information about their consequences. METHODS: We analyzed the whole transcriptome of 40 families with different types of Mendelian skin disorders with extensive genetic heterogeneity. The RNA-seq data were examined for variant detection and prioritization, pathogenicity confirmation, RNA expression profiling, and genome-wide homozygosity mapping in the case of consanguineous families. Among the families examined, RNA-seq was able to provide information complementary to DNA-based analyses for exonic and intronic sequence variants with aberrant splicing. In addition, we tested the possibility of using RNA-seq as the first-tier strategy for unbiased genome-wide mutation screening without information from DNA analysis. RESULTS: We found pathogenic mutations in 35 families (88%) with RNA-seq in combination with other next-generation sequencing methods, and we successfully prioritized variants and found the culprit genes. In addition, as a novel concept, we propose a pipeline that increases the yield of variant calling from RNA-seq by concurrent use of genome and transcriptome references in parallel. CONCLUSIONS: Our results suggest that "clinical RNA-seq" could serve as a primary approach for mutation detection in inherited diseases, particularly in consanguineous families, provided that tissues and cells expressing the relevant genes are available for analysis.

Co-abundance analysis reveals hidden players associated with high methane yield phenotype in sheep rumen microbiome.

Rumen microbial environment hosts a variety of microorganisms that interact with each other to carry out the feed digestion and generation of several by-products especially methane, which plays an essential role in global warming as a greenhouse gas. However, due to its multi-factorial nature, the exact cause of methane production in the rumen has not yet been fully determined. The current study is an attempt to use system modeling to analyze the relationship between interacting components of rumen microbiome and its role in methane production. Metagenomic data of sheep rumen, with equal numbers of high methane yield (HMY) and low methane yield (LMY) samples, were used. As a well-known approach for the systematic comparative study of complex traits, the co-abundance networks were constructed in both operational taxonomic unit (OTU) and gene levels. A gene-catalog of 1,444 different rumen microbial strains was developed as a reference to measure gene abundances. The results from both types of co-abundance networks showed that methanogens, which are the main ruminal source for methanogenesis, need other microbial species to accomplish the task of methane production through producing the main precursor molecules like H2 and acetate for methanogenesis pathway as their byproducts. KEGG Orthology(KO) analysis of the current study shows that the metabolism and growth rate of methanogens will be increased due to the higher rate of the metabolism and carbohydrate/fiber digestion pathways in the hidden elements. This finding proposes that any ruminant methane yield alteration strategy should consider complex interactions of rumen microbiome components as one tightly integrated unit rather than several separate parts.