Copy number variations burden on miRNA genes reveals layers of complexities involved in the regulation of pathways and phenotypic expression

Risk homozygous haplotype regions for autism identifies population-specific ten genes for numerous pathways

Background

Recessive homozygous haplotype (rHH) mapping is a reliable tool for identifying recessive genes by detecting homozygous segments of identical haplotype structures. These are shared at a higher frequency amongst probands compared to parental controls. Finding out such rHH blocks in autism subjects can help in deciphering the disorder etiology.

Objectives

The study aims to detect rHH segments of identical haplotype structure shared at a higher frequency in autism subjects than controls to identify recessive genes responsible for autism manifestation.

Methods

In the present study, 426 unrelated autism genotyped probands with 232 parents (116 trios) were obtained from Gene Expression Omnibus (GEO) Database. Homozygosity mapping analyses have been performed on the samples using standardized algorithms using the Affymetrix GeneChip® 500K SNP Nsp and Sty mapping arrays datasets.

Results

A total of 38 homozygous haplotype blocks were revealed across sample datasets. Upon downstream analysis, 10 autism genes were identified based on selected autism candidate genes criteria. Further, expressive Quantitative Trait Loci (QTL) analysis of SNPs revealed various binding sites for regulatory proteins BX3, FOS, BACH1, MYC, JUND, MAFK, POU2F2, RBBP5, RUNX3, and SMARCA4 impairing essential autism genes CEP290, KITLG, CHD8, and INS2. Pathways and processes such as adherens junction, dipeptidase activity, and platelet-derived growth factor—vital to autism manifestation were identified with varied protein-protein clustered interactions.

Conclusion

These findings bring various population clusters with significant rHH genes. It is suggestive of the existence of common but population-specific risk alleles in related autism subjects.

Bioinformatics and Machine Learning Approaches to Understand the Regulation of Mobile Genetic Elements

Simple Summary

Transposable elements (TEs) are DNA sequences that are, or were, able to move (transpose) within the genome of a single cell. They were first discovered by Barbara McClintock while working on maize, and they make up a large fraction of the genome. Transpositions can result in mutations and they can alter the genome size. Cells regulate the activity of TEs using a variety of mechanisms, such as chemical modifications of DNA and small RNAs. Machine learning (ML) is an interdisciplinary subject that studies computer algorithms that can improve through experience and by the use of data. ML has been successfully applied to a variety of problems in bioinformatics and has exhibited favorable precision and speed. Here, we provide a systematic and guided review on the ML and bioinformatic methods and tools that are used for the analysis of the regulation of TEs.

Abstract

Transposable elements (TEs, or mobile genetic elements, MGEs) are ubiquitous genetic elements that make up a substantial proportion of the genome of many species. The recent growing interest in understanding the evolution and function of TEs has revealed that TEs play a dual role in genome evolution, development, disease, and drug resistance. Cells regulate TE expression against uncontrolled activity that can lead to developmental defects and disease, using multiple strategies, such as DNA chemical modification, small RNA (sRNA) silencing, chromatin modification, as well as sequence-specific repressors. Advancements in bioinformatics and machine learning approaches are increasingly contributing to the analysis of the regulation mechanisms. A plethora of tools and machine learning approaches have been developed for prediction, annotation, and expression profiling of sRNAs, for methylation analysis of TEs, as well as for genome-wide methylation analysis through bisulfite sequencing data. In this review, we provide a guided overview of the bioinformatic and machine learning state of the art of fields closely associated with TE regulation and function.

Identification of primary copy number variations reveal enrichment of Calcium, and MAPK pathways sensitizing secondary sites for autism

Background

Autism is a neurodevelopmental condition with genetic heterogeneity. It is characterized by difficulties in reciprocal social interactions with strong repetitive behaviors and stereotyped interests. Copy number variations (CNVs) are genomic structural variations altering the genomic structure either by duplication or deletion. De novo or inherited CNVs are found in 5–10% of autistic subjects with a size range of few kilobases to several megabases. CNVs predispose humans to various diseases by altering gene regulation, generation of chimeric genes, and disruption of the coding region or through position effect. Although, CNVs are not the initiating event in pathogenesis; additional preceding mutations might be essential for disease manifestation. The present study is aimed to identify the primary CNVs responsible for autism susceptibility in healthy cohorts to sensitize secondary-hits. In the current investigation, primary-hit autism gene CNVs are characterized in 1715 healthy cohorts of varying ethnicities across 12 populations using Affymetrix high-resolution array study. Thirty-eight individuals from twelve families residing in Karnataka, India, with the age group of 13–73 years are included for the comparative CNV analysis. The findings are validated against global 179 autism whole-exome sequence datasets derived from Simons Simplex Collection. These datasets are deposited at the Simons Foundation Autism Research Initiative (SFARI) database.

Results

The study revealed that 34.8% of the subjects carried 2% primary-hit CNV burden with 73 singleton-autism genes in different clusters. Of these, three conserved CNV breakpoints were identified with ARHGAP11B, DUSP22, and CHRNA7 as the target genes across 12 populations. Enrichment analysis of the population-specific autism genes revealed two signaling pathways—calcium and mitogen-activated protein kinases (MAPK) in the CNV identified regions. These impaired pathways affected the downstream cascades of neuronal function and physiology, leading to autism behavior. The pathway analysis of enriched genes unravelled complex protein interaction networks, which sensitized secondary sites for autism. Further, the identification of miRNA targets associated with autism gene CNVs added severity to the condition.

Conclusion

These findings contribute to an atlas of primary-hit genes to detect autism susceptibility in healthy cohorts, indicating their impact on secondary sites for manifestation.

Pan-cancer analysis of somatic mutations in miRNA genes

Background

miRNAs are considered important players in oncogenesis, serving either as oncomiRs or suppressormiRs. Although the accumulation of somatic alterations is an intrinsic aspect of cancer development and many important cancer-driving mutations have been identified in protein-coding genes, the area of functional somatic mutations in miRNA genes is heavily understudied.

Methods

Here, based on the analysis of large genomic datasets, mostly the whole-exome sequencing of over 10,000 cancer/normal sample pairs deposited within the TCGA repository, we undertook an analysis of somatic mutations in miRNA genes.

Findings

We identified and characterized over 10,000 somatic mutations and showed that some of the miRNA genes are overmutated in Pan-Cancer and/or specific cancers. Nonrandom occurrence of the identified mutations was confirmed by a strong association of overmutated miRNA genes with KEGG pathways, most of which were related to specific cancer types or cancer-related processes. Additionally, we showed that mutations in some of the overmutated genes correlate with miRNA expression, cancer staging, and patient survival.

Interpretation

Our study is the first comprehensive Pan-Cancer study of cancer somatic mutations in miRNA genes. It may help to understand the consequences of mutations in miRNA genes and the identification of miRNA functional mutations. The results may also be the first step (form the basis and provide the resources) in the development of computational and/or statistical approaches/tools dedicated to the identification of cancer-driver miRNA genes.

Funding

This work was supported by research grants from the Polish National Science Centre 2016/22/A/NZ2/00184 and 2015/17/N/NZ3/03629.

Artificial Intelligence and the detection of pediatric concussion using epigenomic analysis

Concussion, also referred to as mild traumatic brain injury (mTBI) is the most common type of traumatic brain injury. Currently concussion is an area ofintensescientific interest to better understand the biological mechanisms and for biomarker development. We evaluated whole genome-wide blood DNA cytosine ('CpG') methylation in 17 pediatric concussion isolated cases and 18 unaffected controls using Illumina Infinium MethylationEPIC assay. Pathway analysis was performed using Ingenuity Pathway Analysis to help elucidate the epigenetic and molecular mechanisms of the disorder. Area under the receiver operating characteristics (AUC) curves and FDR p-values were calculated for mTBI detection based on CpG methylation levels. Multiple Artificial Intelligence (AI) platforms including Deep Learning (DL), the newest form of AI, were used to predict concussion based on i) CpG methylation markers alone, and ii) combined epigenetic, clinical and demographic predictors. We found 449 CpG sites (473 genes), those were statistically significantly methylated in mTBI compared to controls. There were four CpGs with excellent individual accuracy (AUC ≥ 0.90-1.00) while 119 displayed good accuracy (AUC ≥ 0.80-0.89) for the prediction of mTBI. The CpG methylation changes ≥10% were observed in many CpG loci after concussion suggesting biological significance. Pathway analysis identified several biologically important neurological pathways that were perturbed including those associated with: impaired brain function, cognition, memory, neurotransmission, intellectual disability and behavioral change and associated disorders. The combination of epigenomic and clinical predictors were highly accurate for the detection of concusion using AI techniques. Using DL/AI, a combination of epigenomic and clinical markers had sensitivity and specificity ≧95% for prediction of mTBI. In this novel study, we identified significant methylation changes in multiple genes in response to mTBI. Gene pathways that were epigenetically dysregulated included several known to be involved in neurological function, thus giving biological plausibility to our findings.

Inhibition of expression of BmNPV cg30 by bmo-miRNA-390 is a host response to baculovirus invasion

Bombyx mori larvae exhibit in vivo defensive reactions immediately after invasion by a virus. One of these defense systems is to express appropriate microRNAs (miRNAs) to respond to the infection. A novel Bombyx mori-encoded miRNA, bmo-miR-390, was identified previously by high-throughput sequencing. Based on bioinformatic predictions, the Bombyx mori nuclear polyhedrosis virus cg30 gene (BmNPV-cg30) is one of the target genes of bmo-miR-390. In this study, expression vectors with an enhanced green fluorescence protein (EGFP) or a luciferase (luc) reporter gene together with bm-miR-390 or the cg30 3' UTR were constructed and used to co-transfect BmN cells. Using a dual luciferase reporter (DLR) assay, we found that bmo-miR-390 significantly downregulates the expression of BmNPV-cg30 (P < 0.05) in vitro. Moreover, artificially synthesized bmo-miR-390 mimics enhanced the regulatory effect of bmo-miR-390, while an inhibitor eliminated the inhibitory effect. These results show for the first time that bmo-miR-390 can effectively downregulate the expression of BmNPV-cg30 in BmNPV-infected BmN cells.

Dysregulation of NRXN1 by mutant MIR8485 leads to calcium overload in pre-synapses inducing neurodegeneration in Multiple sclerosis

OBJECTIVES

To identify Damaging mutations in microRNAs (miRNAs) and 3' untranslated regions (UTRs) of target genes to establish Multiple sclerosis (MS) disease pathway.

METHODS

Female aged 16, with Relapsing Remitting Multiple sclerosis (RRMS) was reported with initial symptoms of blurred vision, severe immobility, upper and lower limb numbness and backache. Whole Exome Sequencing (WES) and disease pathway analysis was performed to identify mutations in miRNAs and UTRs.

RESULTS

We identified Deleterious/Damaging multibase mutations in MIR8485 and NRXN1. miR-8485 was found carrying frameshift homozygous deletion of bases CA, while NRXN1 was found carrying nonframeshift homozygous substitution of bases CT to TC in exon 8 replacing Serine with Leucine.

CONCLUSIONS

Mutations in miR-8485 and NRXN1 was found to alter calcium homeostasis and NRXN1/NLGN1 cell adhesion molecule binding affinities. The miR-8485 mutation leads to overexpression of NRXN1 altering pre-synaptic Ca²⁺ homeostasis, inducing neurodegeneration.

Deletion Extents Are Not the Cause of Clinical Variability in 22q11.2 Deletion Syndrome: Does the Interaction between DGCR8 and miRNA-CNVs Play a Major Role?

In humans, the most common genomic disorder is the hemizygous deletion of the chromosome 22q11.2 region, that results in the “22q11.2 deletion syndrome” (22q11.2DS). A peculiarity of 22q11.2DS is its great phenotypic variability that makes this pathology a classic example of a syndrome with variable expressivity and incomplete penetrance. The reasons for this variability have not been elucidated yet, and the molecular substrates underlying the different clinical features of 22q11.2DS are still debated. A cohort of 21 patients has been analyzed by array CGH in order to detect some of the genetic differences that may influence this variability. Two aspects have been investigated: (1) the precise localization of the deletion breakpoints within the low copy repeats (LCRs), (2) the additional Copy Number Variations (CNVs) elsewhere in the genome, by analyzing their gene content. Both protein-coding genes and miRNAs were considered, in order to discover possible epistatic interactions between genes of the 22q11.2 region and the rest of the genome. Eighteen out of twenty-one patients had a deletion of ~3 Mb mediated by LCR22-A and D, whereas 3/21 had a smaller deletion. The breakpoints within the LCR22-A and D do not have a major role in the phenotypic variability since they are rather clustered and the small differences concern genes that are not directly related to clinical signs of 22q11.2DS. A detailed analysis of the gene content of 22q11.2 deleted region indicates that this syndrome could be a bioenergetic disorder or consequence of an altered post-transcriptional gene regulation, due to the presence of DGCR8, a major player of the microRNA (miRNA) biogenesis. Only four genes with mitochondrial function are harbored in the additional CNVs, whereas 11 miRNA, all related to biological pathways present in the 22q11.2DS, have been detected in 19/21 patients. CNVs and miRNAs are new entities that have changed the order of complexity at the level of gene expression and regulation, thus CNV-miRNAs (miRNA harbored in the CNVs) are potential functional variants that should be considered high priority candidate variants in genotype-phenotype association studies. Deletion of DGCR8, the main actor in miRNA biogenesis, amplifies this variability. To our knowledge, this is the first report that focus on the miRNA-CNVs in 22q11.2DS, with the aim of trying to better understand their role in the variable expressivity and incomplete penetrance.

High-resolution arrays reveal burden of copy number variations on Parkinson disease genes associated with increased disease risk in random cohorts

BACKGROUND

Parkinson disease (PD) is a neurological disease responsible for a considerable rate of mortality and morbidity in the society. Since the symptoms of the disease appear much later than the actual onset of neuron degeneration, a majority of cases remain undiagnosed until the manifestation of the symptoms.

OBJECTIVES

In order to investigate the existence of such susceptibility in the population, we analyzed Copy Number Variation (CNV) influences on PD genes in 1715 individuals from 12 different populations.

RESULTS

Overall, 16 CNV-PD genes, 3 known to be causal and 13 associated, were found to be significantly enriched. PARK2, was under heavy burden with ~1% of the population containing CNV in the exonic region. The impact of these genes on the genome and disease pathway was analyzed using several genome analysis tools. Protein interaction network of CNV-PD genes revealed a complex interaction of molecules forming a major hub by the α-Synuclein, whose direct interactors, LRRK2, PARK2 and ATP13A2 are under CNV influence.

CONCLUSIONS

We hypothesize that CNVs may not be the initiating event in the pathogenesis of PD and remain latent until additional secondary hits are acquired and also propose novel genes that may fall under the PD pathway which contribute in pathogenesis.

Global patterns of large copy number variations in the human genome reveal complexity in chromosome organization

Global patterns of copy number variations (CNVs) in chromosomes are required to understand the dynamics of genome organization and complexity. For this study, analysis was performed using the Affymetrix Genome-Wide Human SNP Array 6.0 chip and CytoScan High-Density arrays. We identified a total of 44 109 CNVs from 1715 genomes with a mean of 25 CNVs in an individual, which established the first drafts of population-specific CNV maps providing a rationale for prioritizing chromosomal regions. About 19 905 ancient CNVs were identified across all chromosomes and populations at varying frequencies. CNV count, and sometimes CNV size, contributed to the bulk CNV size of the chromosome. Population specific lengthening and shortening of chromosomal length was observed. Sex bias for CNV presence was largely dependent on ethnicity. Lower CNV inheritance rate was observed for India, compared to YRI and CEU. A total of 33 candidate CNV hotspots from 5382 copy number (CN) variable region (CNVR) clusters were identified. Population specific CNV distribution patterns in p and q arms disturbed the assumption that CNV counts in the p arm are less common compared to long arms, and the CNV occurrence and distribution in chromosomes is length independent. This study unraveled the force of independent evolutionary dynamics on genome organization and complexity across chromosomes and populations.

Homo sapiens exhibit a distinct pattern of CNV genes regulation: an important role of miRNAs and SNPs in expression plasticity

Gene expression regulation is a complex and highly organized process involving a variety of genomic factors. It is widely accepted that differences in gene expression can contribute to the phenotypic variability between species, and that their interpretation can aid in the understanding of the physiologic variability. CNVs and miRNAs are two major players in the regulation of expression plasticity and may be responsible for the unique phenotypic characteristics observed in different lineages. We have previously demonstrated that a close interaction between these two genomic elements may have contributed to the regulation of gene expression during evolution. This work presents the molecular interactions between CNV and non CNV genes with miRNAs and other genomic elements in eight different species. A comprehensive analysis of these interactions indicates a unique nature of human CNV genes regulation as compared to other species. By using genes with short 3′ UTR that abolish the “canonical” miRNA-dependent regulation, as a model, we demonstrate a distinct and tight regulation of human genes that might explain some of the unique features of human physiology. In addition, comparison of gene expression regulation between species indicated that there is a significant difference between humans and mice possibly questioning the effectiveness of the latest as experimental models of human diseases.

Copy number variation burden on asthma subgenome in normal cohorts identifies susceptibility markers

PURPOSE

Asthma is a complex disease caused by interplay of genes and environment on the genome of an individual. Copy number variations (CNVs) are more common compared to the other variations that disrupt genome organization. The effect of CNVs on asthma subgenome has been less studied compared to studies on the other variations. We report the assessments of CNV burden in asthma genes of normal cohorts carried out in different geographical areas of the world and discuss the relevance of the observation with respect to asthma pathogenesis.

METHODS

CNV analysis was performed using Affymerix high-resolution arrays, and various bioinformatics tools were used to understand the influence of genes on asthma pathogenesis.

RESULTS

This study identified 61 genes associated with asthma and provided various mechanisms and pathways underlying asthma pathogenesis. CCL3L1, ADAM8, and MUC5B were the most prevalent asthma genes. Among them, CCL3L1 was found across all 12 populations in varying copy number states. This study also identified the inheritance of asthma-CNVs from parents to offspring creating the latent period for manifestation of asthma.

CONCLUSIONS

This study revealed CNV burden with varying copy number states and identified susceptibility towards the disease manifestation. It can be hypothesized that primary CNVs may not be the initiating event in the pathogenesis of asthma and additional preceding mutations or CNVs may be required. The initiator or primary CNVs sensitize normal cohorts leading to an increased probability of accumulating mutations or exposure to allergic stimulating agents that can augment the development of asthma.