TBX15 and SDHB expression changes in colorectal cancer serve as potential prognostic biomarkers.

Alterations in the expression of certain genes could be associated with both patient mortality rates and drug resistance. This study aimed to identify genes in colorectal cancer (CRC) that potentially serve as hub genes influencing patient survival rates. RNA-Seq data were downloaded from the cancer genome atlas database, and differential expression analysis was performed between tumors and healthy controls. Through the utilization of univariate and multivariate Cox regression analyses, in combination with the MCODE clustering module, the genes whose expression changes were related to survival rate and the hub genes related to them were identified. The mortality risk model was computed using the hub genes. CRC samples and the RT-qPCR method were utilized to confirm the outcomes. PharmacoGx data were employed to link the expression of potential genes to medication resistance and sensitivity. The results revealed the discovery of seven hub genes, which emerged as independent prognostic markers. These included HOXC6, HOXC13, HOXC8, and TBX15, which were associated with poor prognosis and overexpression, as well as SDHB, COX5A, and UQCRC1, linked to favorable prognosis and downregulation. Applying the risk model developed with the mentioned genes revealed a markedly higher incidence of deceased patients in the high-risk group compared to the low-risk group. RT-qPCR results indicated a decrease in SDHB expression and an elevation in TBX15 levels in cancer samples relative to adjacent healthy tissue. Also, PharmacoGx data indicated that the expression level of SDHB was correlated with drug sensitivity to Crizotinib and Dovitinib. Our findings highlight the potential association between alterations in the expression of genes such as HOXC6, HOXC13, HOXC8, TBX15, SDHB, COX5A, and UQCRC1 and increased mortality rates in CRC patients. As revealed by the PPI network, these genes exhibited the most connections with other genes linked to survival.

Intellectual disability associated with craniofacial dysmorphism due to POLR3B mutation and defect in spliceosomal machinery.

BACKGROUND: Intellectual disability (ID) is a clinically important disease and a most prevalent neurodevelopmental disorder. The etiology and pathogenesis of ID are poorly recognized. Exome sequencing revealed a homozygous missense mutation in the POLR3B gene in a consanguineous family with three Intellectual disability with craniofacial anomalies patients. POLR3B gene encoding the second largest subunit of RNA polymerase III. METHODS: We performed RNA sequencing on blood samples to obtain insights into the biological pathways influenced by POLR3B mutation. We applied the results of our RNA-Seq analysis to several gene ontology programs such as ToppGene, Enrichr, KEGG. RESULTS: A significant decrease in expression of several spliceosomal RNAs, ribosomal proteins, and transcription factors was detected in the affected, compared to unaffected, family members. CONCLUSIONS: We hypothesize that POLR3B mutation dysregulates the expression of some important transcription factors, ribosomal and spliceosomal genes, and impairments in protein synthesis and splicing mediated in part by transcription factors such as FOXC2 and GATA1 contribute to impaired neuronal function and concurrence of intellectual disability and craniofacial anomalies in our patients. Our study highlights the emerging role of the spliceosome and ribosomal proteins in intellectual disability.

Identification of gene signature in RNA-Seq hepatocellular carcinoma data by Pareto-optimal cluster algorithm.

Aim: This study aimed to detect gene signatures in RNA-sequencing (RNA-seq) data using Pareto-optimal cluster size identification. Background: RNA-seq has emerged as an important technology for transcriptome profiling in recent years. Gene expression signatures involving tens of genes have been proven to be predictive of disease type and patient response to treatment. Methods: Data related to the liver cancer RNA-seq dataset, which included 35 paired hepatocellular carcinoma (HCC) and non-tumor tissue samples, was used in this study. The differentially expressed genes (DEGs) were identified after performing pre-filtering and normalization. After that, a multi-objective optimization technique, namely multi-objective optimization for collecting cluster alternatives (MOCCA), was used to discover the Pareto-optimal cluster size for these DEGs. Then, the k-means clustering method was performed on the RNA-seq data. The best cluster, as a signature for the disease, was found by calculating the average Spearman's correlation score of all genes in the module in a pair-wise manner. All analyses were performed in the R 4.1.1 package in virtual space with 100 Gb of RAM memory. Results: Using MOCCA, eight Pareto-optimal clusters were obtained. Ultimately, two clusters with the greatest average Spearman's correlation coefficient scores were chosen as gene signatures. Eleven prognostic genes involved in HCC's abnormal metabolism were identified. In addition, three differentially expressed pathways were identified between tumor and non-tumor tissues. Conclusion: These identified metabolic prognostic genes help us to provide more powerful prognostic information and enhance survival prediction for HCC patients. In addition, Pareto-optimal cluster size identification is suggested for gene signature in other RNA-Seq data.

Study on SARS-CoV-2 strains in Iran reveals potential contribution of co-infection with and recombination between different strains to the emergence of new strains.

We aimed to describe SARS-CoV-2 strains in Iranians from nine distributed cities infected during two months expanding late 2020 and early 2021 by genotyping known informative single nucleotide in five PCR amplicons. Two variants associated with haplotype H1 (clade G) and nine additional variants associated with other haplotypes were genotyped, respectively, in RNA isolates of 244 and 85 individuals. The variants associated with the H1a (GR) and H1b (GH) haplotypes were most prevalent, indicating a significant change in infection pattern with passage of time. The most important findings were that recombinant genomes and co-infection, respectively, were surmised in 44.7% and 12.9% of the samples extensively genotyped. Partners of many of the recombinations were relatively common strains. Co-existing viruses were among those currently circulating in Iran. In addition to random mutations, co-infection with different existing strains and recombination between their genomes may significantly contribute to the emergence of new SARS-CoV-2 strains.

World-wide tracking of major SARS-CoV-2 genome haplotypes in sequences of June 1 to November 15, 2020 and discovery of rapid expansion of a new haplotype.

Earlier, 13 haplotype groups defined by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome sequence variations were identified in 2790 sequences available in March 2020. Also, 23403A>G that causes p. Asp614Gly in the spike protein and is one of the defining variations of the haplotype group H1, was becoming increasingly prevalent. As a follow-up, 74922 SARS-CoV-2 sequences retrieved from individuals infected in June 1 to November 15 were analyzed. Consistent with the reports on 23403A>G, H1 haplotype frequency increased world-wide; among August to November sequences, only 0.3% were associated with non-H1 haplotypes. This finding prompted assessment of H1 sub-haplotypes among the sequences of the later stage of the coronavirus disease 2019 pandemic. The distribution of the sub-haplotypes differed in different regions, but 98.4% of the sequences were associated with five H1 sub-haplotypes. One of these had not been previously observed and had emerged in Europe by June 2020. The most important finding of the present study is identification of this new sub-haplotype (H1r) and finding evidence that suggest it may have a high potential for expansion. Its frequency had reached 10%-90% in various countries/territories of Europe by the end of September. The new sub-haplotype is defined by seven sequence variations, one of which causes Ala222Val in the spike protein.

Evolution of SARS-CoV-2 genome from December 2019 to late March 2020: Emerged haplotypes and informative Tag nucleotide variations.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes serious disease in humans. First identified in November/December 2019 in China, it has rapidly spread worldwide. We analyzed 2790 SARS-CoV-2 genome sequences from 56 countries that were available on April 2, 2020, to assess the evolution of the virus during this early phase of its expansion. We aimed to assess sequence variations that had evolved in virus genomes, giving the greatest attention to the S gene. We also aimed to identify haplotypes that the variations may define and consider their geographic and chronologic distribution. Variations at 1930 positions that together cause 1203 amino acid changes were identified. The frequencies of changes normalized to the lengths of genes and encoded proteins were relatively high in ORF3a and relatively low in M. A variation that causes an Asp614Gly near the receptor-binding domain of S were found at a high frequency, and it was considered that this may contribute to the rapid spread of viruses with this variation. Our most important findings relate to haplotypes. Sixty-six haplotypes that constitute thirteen haplotype groups (H1-H13) were identified, and 84.6% of the 2790 sequences analyzed were associated with these haplotypes. The majority of the sequences (75.1%) were associated with haplotype groups H1-H3. The distribution pattern of the haplotype groups differed in various geographic regions. A few were country/territory specific. The location and time of emergence of some haplotypes are discussed. Importantly, nucleotide variations that define the various haplotypes and Tag/signature variations for most of the haplotypes are reported. The practical applications of these variations are discussed.

Deep geno- and phenotyping in two consanguineous families with CMT2 reveals HADHA as an unusual disease-causing gene and an intronic variant in GDAP1 as an unusual mutation.

BACKGROUND: Charcot-Marie-Tooth (CMT) disease is a prevalent and heterogeneous peripheral neuropathy. Most patients affected with the axonal form of CMT (CMT2) do not harbor mutations in the approximately 90 known CMT-associated genes. We aimed to identify causative genes in two CMT2 pedigrees. METHODS: Neurologic examination, laboratory tests and brain MRIs were performed. Genetic analysis included exome sequencing of four patients from the two pedigrees. The predicted effect of a deep intronic mutation on splicing was tested by regular and real-time PCR and sequencing. RESULTS: Clinical data were consistent with CMT2 diagnosis. Inheritance patterns were autosomal recessive. Exome data of CMT2-101 did not include mutations in known CMT-associated genes. Sequence data, segregation analysis, bioinformatics analysis, evolutionary conservation, and information in the literature strongly implicated HADHA as the causative gene. An intronic variation positioned 23 nucleotides away from following intron/exon border in GDAP1 was ultimately identified as cause of CMT in CMT2-102. It was shown to affect splicing. CONCLUSION: The finding of a HADHA mutation as a cause of CMT is of interest because its encoded protein is a subunit of the mitochondrial trifunctional protein (MTP) complex, a mitochondrial enzyme involved in long chain fatty acid oxidation. Long chain fatty acid oxidation is an important source of energy for skeletal muscles. The mutation found in CMT2-102 is only the second intronic mutation reported in GDAP1. The mutation in the CMT2-102 pedigree was outside the canonical splice site sequences, emphasizing the importance of careful examination of available intronic sequences in exome sequence data.

Whole-Transcriptome Analysis Reveals Dysregulation of Actin-Cytoskeleton Pathway in Intellectual Disability Patients.

A significant level of genetic heterogeneity has been demonstrated in intellectual disability (ID). More than 700 genes have been identified in ID patients. To identify molecular pathways underlying this heterogeneity, we applied whole-transcriptome analysis using RNA-Seq in consanguineous families with ID. Significant changes in expression of genes related to neuronal and actin cytoskeletal functions were observed in all the ID families. Remarkably, we found a significant down-regulation of SHTN1 gene and up-regulation of FGFR2 gene in all ID patients. FGFR2, but not SHTN1, was previously reported as an ID causing gene. Detailed gene ontology analyses identified pathways linked to tyrosine protein kinase, actin cytoskeleton, and axonogenesis to be affected in ID patients. The findings reported here provide new insights into the candidate genes and molecular pathways underling ID and highlight the key role of actin cytoskeleton in etiology of ID.

Sex-based differences in myocardial gene expression in recently deceased organ donors with no prior cardiovascular disease.

Sex differences in the development of the normal heart and the prevalence of cardiomyopathies have been reported. The molecular basis of these differences remains unclear. Sex differences in the human heart might be related to patterns of gene expression. Recent studies have shown that sex specific differences in gene expression in tissues including the brain, kidney, skeletal muscle, and liver. Similar data is limited for the heart. Herein we address this issue by analyzing donor and post-mortem adult human heart samples originating from 46 control individuals to study whole-genome gene expression in the human left ventricle. Using data from the genotype tissue expression (GTEx) project, we compared the transcriptome expression profiles of male and female hearts. We found that genes located on sex chromosomes were the most abundant ones among the sexually dimorphic genes. The majority of differentially expressed autosomal genes were those involved in the regulation of inflammation, which has been found to be an important contributor to left ventricular remodeling. Specifically, genes on autosomal chromosomes encoding chemokines with inflammatory functions (e.g. CCL4, CX3CL1, TNFAIP3) and a gene that regulates adhesion of immune cells to the endothelium (e.g., VCAM1) were identified with sex-specific expression levels. This study underlines the relevance of sex as an important modifier of cardiac gene expression. These results have important implications in the understanding of the differences in the physiology of the male and female heart transcriptome and how they may lead to different sex specific difference in human cardiac health and its control.

iPSC-derived cardiomyocytes reveal abnormal TGF-ß signalling in left ventricular non-compaction cardiomyopathy.

Left ventricular non-compaction (LVNC) is the third most prevalent cardiomyopathy in children and its pathogenesis has been associated with the developmental defect of the embryonic myocardium. We show that patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) generated from LVNC patients carrying a mutation in the cardiac transcription factor TBX20 recapitulate a key aspect of the pathological phenotype at the single-cell level and this was associated with perturbed transforming growth factor beta (TGF-ß) signalling. LVNC iPSC-CMs have decreased proliferative capacity due to abnormal activation of TGF-ß signalling. TBX20 regulates the expression of TGF-ß signalling modifiers including one known to be a genetic cause of LVNC, PRDM16, and genome editing of PRDM16 caused proliferation defects in iPSC-CMs. Inhibition of TGF-ß signalling and genome correction of the TBX20 mutation were sufficient to reverse the disease phenotype. Our study demonstrates that iPSC-CMs are a useful tool for the exploration of pathological mechanisms underlying poorly understood cardiomyopathies including LVNC.

A Rapid, High-Quality, Cost-Effective, Comprehensive and Expandable Targeted Next-Generation Sequencing Assay for Inherited Heart Diseases.

RATIONALE: Thousands of mutations across >50 genes have been implicated in inherited cardiomyopathies. However, options for sequencing this rapidly evolving gene set are limited because many sequencing services and off-the-shelf kits suffer from slow turnaround, inefficient capture of genomic DNA, and high cost. Furthermore, customization of these assays to cover emerging targets that suit individual needs is often expensive and time consuming. OBJECTIVE: We sought to develop a custom high throughput, clinical-grade next-generation sequencing assay for detecting cardiac disease gene mutations with improved accuracy, flexibility, turnaround, and cost. METHODS AND RESULTS: We used double-stranded probes (complementary long padlock probes), an inexpensive and customizable capture technology, to efficiently capture and amplify the entire coding region and flanking intronic and regulatory sequences of 88 genes and 40 microRNAs associated with inherited cardiomyopathies, congenital heart disease, and cardiac development. Multiplexing 11 samples per sequencing run resulted in a mean base pair coverage of 420, of which 97% had >20× coverage and >99% were concordant with known heterozygous single nucleotide polymorphisms. The assay correctly detected germline variants in 24 individuals and revealed several polymorphic regions in miR-499. Total run time was 3 days at an approximate cost of $100 per sample. CONCLUSIONS: Accurate, high-throughput detection of mutations across numerous cardiac genes is achievable with complementary long padlock probe technology. Moreover, this format allows facile insertion of additional probes as more cardiomyopathy and congenital heart disease genes are discovered, giving researchers a powerful new tool for DNA mutation detection and discovery.

Mutation in ST6GALNAC5 identified in family with coronary artery disease.

We aimed to identify the genetic cause of coronary artery disease (CAD) in an Iranian pedigree. Genetic linkage analysis identified three loci with an LOD score of 2.2. Twelve sequence variations identified by exome sequencing were tested for segregation with disease. A p.Val99Met causing mutation in ST6GALNAC5 was considered the likely cause of CAD. ST6GALNAC5 encodes sialyltransferase 7e. The variation affects a highly conserved amino acid, was absent in 800 controls, and was predicted to damage protein function. ST6GALNAC5 is positioned within loci previously linked to CAD-associated parameters. While hypercholesterolemia was a prominent feature in the family, clinical and genetic data suggest that this condition is not caused by the mutation in ST6GALNAC5. Sequencing of ST6GALNAC5 in 160 Iranian patients revealed a candidate causative stop-loss mutation in two other patients. The p.Val99Met and stop-loss mutations both caused increased sialyltransferase activity. Sequence data from combined Iranian and US controls and CAD affected individuals provided evidence consistent with potential role of ST6GALNAC5 in CAD. We conclude that ST6GALNAC5 mutations can cause CAD. There is substantial literature suggesting a relation between sialyltransferase and sialic acid levels and coronary disease. Our findings provide strong evidence for the existence of this relation.

Mutation in CYP27A1 identified in family with coronary artery disease.

Coronary artery disease (CAD) is a leading cause of death worldwide. Myocardial infarction is the most severe outcome of CAD. Despite extensive efforts, the genetics of CAD is poorly understood. We aimed to identify the genetic cause of CAD in a pedigree with several affected individuals. Exome sequencing led to identification of a mutation in CYP27A1 that causes p.Arg225His in the encoded protein sterol 27-hydroxylase as the likely cause of CAD in the pedigree. The enzyme is multifunctional, and several of its functions including its functions in vitamin D metabolism and reverse cholesterol transport (RCT) are relevant to the CAD phenotype. Measurements of vitamin D levels suggested that the mutation does not affect CAD by affecting this parameter. We suggest that the mutation may cause CAD by affecting RCT. Screening of all coding regions of the CYP27A1 in 100 additional patients led to finding four variations (p.Arg14Gly, p.Arg26Lys, p.Ala27Arg, and p.Val86Met) in seven patients that may contribute to their CAD status. CYP27A1 is the known causative gene of cerebrotendinous xanthomatosis, a disorder which is sometimes accompanied by early onset atherosclerosis. This and the observation of potentially harmful variations in unrelated CAD patients provide additional evidence for the suggested causative role of the p.Arg225His mutation in CAD.