Small RNA Sequencing across Diverse Biofluids Identifies Optimal Methods for exRNA Isolation.

Poor reproducibility within and across studies arising from lack of knowledge regarding the performance of extracellular RNA (exRNA) isolation methods has hindered progress in the exRNA field. A systematic comparison of 10 exRNA isolation methods across 5 biofluids revealed marked differences in the complexity and reproducibility of the resulting small RNA-seq profiles. The relative efficiency with which each method accessed different exRNA carrier subclasses was determined by estimating the proportions of extracellular vesicle (EV)-, ribonucleoprotein (RNP)-, and high-density lipoprotein (HDL)-specific miRNA signatures in each profile. An interactive web-based application (miRDaR) was developed to help investigators select the optimal exRNA isolation method for their studies. miRDar provides comparative statistics for all expressed miRNAs or a selected subset of miRNAs in the desired biofluid for each exRNA isolation method and returns a ranked list of exRNA isolation methods prioritized by complexity, expression level, and reproducibility. These results will improve reproducibility and stimulate further progress in exRNA biomarker development.

IsoMiRmap: fast, deterministic and exhaustive mining of isomiRs from short RNA-seq datasets.

MOTIVATION: MicroRNA (miRNA) precursor arms give rise to multiple isoforms simultaneously called 'isomiRs.' IsomiRs from the same arm typically differ by a few nucleotides at either their 5' or 3' termini or both. In humans, the identities and abundances of isomiRs depend on a person's sex and genetic ancestry as well as on tissue type, tissue state and disease type/subtype. Moreover, nearly half of the time the most abundant isomiR differs from the miRNA sequence found in public databases. Accurate mining of isomiRs from deep sequencing data is thus important. RESULTS: We developed isoMiRmap, a fast, standalone, user-friendly mining tool that identifies and quantifies all isomiRs by directly processing short RNA-seq datasets. IsoMiRmap is a portable 'plug-and-play' tool, requires minimal setup, has modest computing and storage requirements, and can process an RNA-seq dataset with 50 million reads in just a few minutes on an average laptop. IsoMiRmap deterministically and exhaustively reports all isomiRs in a given deep sequencing dataset and quantifies them accurately (no double-counting). IsoMiRmap comprehensively reports all miRNA precursor locations from which an isomiR may be transcribed, tags as 'ambiguous' isomiRs whose sequences exist both inside and outside of the space of known miRNA sequences and reports the public identifiers of common single-nucleotide polymorphisms and documented somatic mutations that may be present in an isomiR. IsoMiRmap also identifies isomiRs with 3' non-templated post-transcriptional additions. Compared to similar tools, isoMiRmap is the fastest, reports more bona fide isomiRs, and provides the most comprehensive information related to an isomiR's transcriptional origin. AVAILABILITY AND IMPLEMENTATION: The codes for isoMiRmap are freely available at https://cm.jefferson.edu/isoMiRmap/ and https://github.com/TJU-CMC-Org/isoMiRmap/. IsomiR profiles for the datasets of the 1000 Genomes Project, spanning five population groups, and The Cancer Genome Atlas (TCGA), spanning 33 cancer studies, are also available at https://cm.jefferson.edu/isoMiRmap/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Unification of miRNA and isomiR research: the mirGFF3 format and the mirtop API.

MOTIVATION: MicroRNAs (miRNAs) are small RNA molecules (∼22 nucleotide long) involved in post-transcriptional gene regulation. Advances in high-throughput sequencing technologies led to the discovery of isomiRs, which are miRNA sequence variants. While many miRNA-seq analysis tools exist, the diversity of output formats hinders accurate comparisons between tools and precludes data sharing and the development of common downstream analysis methods. RESULTS: To overcome this situation, we present here a community-based project, miRNA Transcriptomic Open Project (miRTOP) working towards the optimization of miRNA analyses. The aim of miRTOP is to promote the development of downstream isomiR analysis tools that are compatible with existing detection and quantification tools. Based on the existing GFF3 format, we first created a new standard format, mirGFF3, for the output of miRNA/isomiR detection and quantification results from small RNA-seq data. Additionally, we developed a command line Python tool, mirtop, to create and manage the mirGFF3 format. Currently, mirtop can convert into mirGFF3 the outputs of commonly used pipelines, such as seqbuster, isomiR-SEA, sRNAbench, Prost! as well as BAM files. Some tools have also incorporated the mirGFF3 format directly into their code, such as, miRge2.0, IsoMIRmap and OptimiR. Its open architecture enables any tool or pipeline to output or convert results into mirGFF3. Collectively, this isomiR categorization system, along with the accompanying mirGFF3 and mirtop API, provide a comprehensive solution for the standardization of miRNA and isomiR annotation, enabling data sharing, reporting, comparative analyses and benchmarking, while promoting the development of common miRNA methods focusing on downstream steps of miRNA detection, annotation and quantification. AVAILABILITY AND IMPLEMENTATION: https://github.com/miRTop/mirGFF3/ and https://github.com/miRTop/mirtop. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MINTbase v2.0: a comprehensive database for tRNA-derived fragments that includes nuclear and mitochondrial fragments from all The Cancer Genome Atlas projects.

MINTbase is a repository that comprises nuclear and mitochondrial tRNA-derived fragments ('tRFs') found in multiple human tissues. The original version of MINTbase comprised tRFs obtained from 768 transcriptomic datasets. We used our deterministic and exhaustive tRF mining pipeline to process all of The Cancer Genome Atlas datasets (TCGA). We identified 23 413 tRFs with abundance of ≥ 1.0 reads-per-million (RPM). To facilitate further studies of tRFs by the community, we just released version 2.0 of MINTbase that contains information about 26 531 distinct human tRFs from 11 719 human datasets as of October 2017. Key new elements include: the ability to filter tRFs on-the-fly by minimum abundance thresholding; the ability to filter tRFs by tissue keywords; easy access to information about a tRF's maximum abundance and the datasets that contain it; the ability to generate relative abundance plots for tRFs across cancer types and convert them into embeddable figures; MODOMICS information about modifications of the parental tRNA, etc. Version 2.0 of MINTbase contains 15x more datasets and nearly 4x more distinct tRFs than the original version, yet continues to offer fast, interactive access to its contents. Version 2.0 is available freely at http://cm.jefferson.edu/MINTbase/.

Autosomal recessive congenital ichthyosis: Genomic landscape and phenotypic spectrum in a cohort of 125 consanguineous families.

Autosomal recessive congenital ichthyosis (ARCI), a phenotypically heterogeneous group of non-syndromic Mendelian disorders of keratinization, is caused by mutations in as many as 13 distinct genes. We examined a cohort of 125 consanguineous families with ARCI for underlying genetic mutations. The patients' DNA was analyzed with a gene-targeted next generation sequencing panel comprising 38 ichthyosis associated genes. The interpretations of results of genomic data were assisted by genome-wide homozygosity mapping and transcriptome sequencing. Sequence data analysis identified biallelic mutations in 106 families out of a total of 125 (85%), most of them (102, 96.2%) being homozygous, reflecting consanguinity in these families. Among the 85 distinct mutations in 10 different genes, 45 (53%) were previously unreported. Phenotype-genotype correlations allowed assignment of specific genes in the majority of the families to a specific subtype of ARCI, lamellar ichthyosis (LI) versus congenital ichthyosiform erythroderma (CIE). Interestingly, mutations in several genes could give rise to an overlapping phenotype consistent with either LI or CIE. Also, this is the third report for SDR9C7 and SULT2B1, and fourth report for CERS3 mutations. Direct comparison of our results with previously published regional cohorts highlights the global mutation landscape of ARCI, however, population specific differences were noted.

Single-Cell Genomics.

BACKGROUND: Single-cell genomics is an approach to investigate cell heterogeneity and to identify new molecular features correlated with clinical outcomes. This approach allows identification of the complexity of cell diversity in a sample without the loss of information that occurs when multicellular or bulk tissue samples are analyzed. CONTENT: The first single-cell RNA-sequencing study was published in 2009, and since then many more studies and single-cell sequencing methods have been published. These studies have had a major impact on several fields, including microbiology, neurobiology, cancer, and developmental biology. Recently, improvements in reliability and the development of commercial single-cell isolation platforms are opening the potential of this technology to the clinical laboratory. SUMMARY: In this review we provide an overview of the current state of single-cell genomics. We describe opportunities in clinical research and medical applications.

Knowledge about the presence or absence of miRNA isoforms (isomiRs) can successfully discriminate amongst 32 TCGA cancer types.

Isoforms of human miRNAs (isomiRs) are constitutively expressed with tissue- and disease-subtype-dependencies. We studied 10 271 tumor datasets from The Cancer Genome Atlas (TCGA) to evaluate whether isomiRs can distinguish amongst 32 TCGA cancers. Unlike previous approaches, we built a classifier that relied solely on 'binarized' isomiR profiles: each isomiR is simply labeled as 'present' or 'absent'. The resulting classifier successfully labeled tumor datasets with an average sensitivity of 90% and a false discovery rate (FDR) of 3%, surpassing the performance of expression-based classification. The classifier maintained its power even after a 15× reduction in the number of isomiRs that were used for training. Notably, the classifier could correctly predict the cancer type in non-TCGA datasets from diverse platforms. Our analysis revealed that the most discriminatory isomiRs happen to also be differentially expressed between normal tissue and cancer. Even so, we find that these highly discriminating isomiRs have not been attracting the most research attention in the literature. Given their ability to successfully classify datasets from 32 cancers, isomiRs and our resulting 'Pan-cancer Atlas' of isomiR expression could serve as a suitable framework to explore novel cancer biomarkers.

Whole exome sequencing identifies a germline MET mutation in two siblings with hereditary wild-type RET medullary thyroid cancer.

Whole exome sequencing (WES) was used to investigate two Italian siblings with wild-type RET genotype, who developed medullary thyroid cancers (MTCs) and, later, primary prostate and breast cancers, respectively. The proband's MTC harbored a p.Met918Thr RET mutation; his sister's MTC was RET/RAS wild-type. Both siblings had a germline mutation (p.Arg417Gln) in the extracellular Sema domain of the proto-oncogene MET. Experiments involving ectopic expression of MET p.Arg417Gln in MET-negative T47D breast cancer cells documented the mutant receptor's functionality and its ability to enhance cell migration and invasion. Our findings highlight a possible link between MET germline mutations and MTCs and suggest that MET p. Arg417Gln may promote an invasive malignant phenotype. The possibility that MTC can be driven/co-driven by a MET mutation has potential management implications, since the tyrosine-kinase inhibitor cabozantinib-approved for treating advanced MTCs-is a specific MET inhibitor.

Threshold-seq: a tool for determining the threshold in short RNA-seq datasets.

SUMMARY: We present 'Threshold-seq,' a new approach for determining thresholds in deep-sequencing datasets of short RNA transcripts. Threshold-seq addresses the critical question of how many reads need to support a short RNA molecule in a given dataset before it can be considered different from 'background.' The proposed scheme is easy to implement and incorporate into existing pipelines. AVAILABILITY AND IMPLEMENTATION: Source code of Threshold-seq is freely available as an R package at: http://cm.jefferson.edu/threshold-seq/. CONTACT: isidore.rigoutsos@jefferson.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Analysis of 13 cell types reveals evidence for the expression of numerous novel primate- and tissue-specific microRNAs.

Two decades after the discovery of the first animal microRNA (miRNA), the number of miRNAs in animal genomes remains a vexing question. Here, we report findings from analyzing 1,323 short RNA sequencing samples (RNA-seq) from 13 different human tissue types. Using stringent thresholding criteria, we identified 3,707 statistically significant novel mature miRNAs at a false discovery rate of ≤ 0.05 arising from 3,494 novel precursors; 91.5% of these novel miRNAs were identified independently in 10 or more of the processed samples. Analysis of these novel miRNAs revealed tissue-specific dependencies and a commensurate low Jaccard similarity index in intertissue comparisons. Of these novel miRNAs, 1,657 (45%) were identified in 43 datasets that were generated by cross-linking followed by Argonaute immunoprecipitation and sequencing (Ago CLIP-seq) and represented 3 of the 13 tissues, indicating that these miRNAs are active in the RNA interference pathway. Moreover, experimental investigation through stem-loop PCR of a random collection of newly discovered miRNAs in 12 cell lines representing 5 tissues confirmed their presence and tissue dependence. Among the newly identified miRNAs are many novel miRNA clusters, new members of known miRNA clusters, previously unreported products from uncharacterized arms of miRNA precursors, and previously unrecognized paralogues of functionally important miRNA families (e.g., miR-15/107). Examination of the sequence conservation across vertebrate and invertebrate organisms showed 56.7% of the newly discovered miRNAs to be human-specific whereas the majority (94.4%) are primate lineage-specific. Our findings suggest that the repertoire of human miRNAs is far more extensive than currently represented by public repositories and that there is a significant number of lineage- and/or tissue-specific miRNAs that are uncharacterized.

Beyond the one-locus-one-miRNA paradigm: microRNA isoforms enable deeper insights into breast cancer heterogeneity.

Here we describe our study of miRNA isoforms (isomiRs) in breast cancer (BRCA) and normal breast data sets from the Cancer Genome Atlas (TCGA) repository. We report that the full isomiR profiles, from both known and novel human-specific miRNA loci, are particularly rich in information and can distinguish tumor from normal tissue much better than the archetype miRNAs. IsomiR expression is also dependent on the patient's race, exemplified by miR-183-5p, several isomiRs of which are upregulated in triple negative BRCA in white but not black women. Additionally, we find that an isomiR's 5' endpoint and length, but not the genomic origin, are key determinants of the regulation of its expression. Overexpression of distinct miR-183-5p isomiRs in MDA-MB-231 cells followed by microarray analysis revealed that each isomiR has a distinct impact on the cellular transcriptome. Parallel integrative analysis of mRNA expression from BRCA data sets of the TCGA repository demonstrated that isomiRs can distinguish between the luminal A and luminal B subtypes and explain in more depth the molecular differences between them than the archetype molecules. In conclusion, our findings provide evidence that post-transcriptional studies of BRCA will benefit from transcending the one-locus-one-miRNA paradigm and taking into account all isoforms from each miRNA locus as well as the patient's race.

Clinical exome performance for reporting secondary genetic findings.

BACKGROUND: Reporting clinically actionable incidental genetic findings in the course of clinical exome testing is recommended by the American College of Medical Genetics and Genomics (ACMG). However, the performance of clinical exome methods for reporting small subsets of genes has not been previously reported. METHODS: In this study, 57 exome data sets performed as clinical (n = 12) or research (n = 45) tests were retrospectively analyzed. Exome sequencing data was examined for adequacy in the detection of potentially pathogenic variant locations in the 56 genes described in the ACMG incidental findings recommendation. All exons of the 56 genes were examined for adequacy of sequencing coverage. In addition, nucleotide positions annotated in HGMD (Human Gene Mutation Database) were examined. RESULTS: The 56 ACMG genes have 18 336 nucleotide variants annotated in HGMD. None of the 57 exome data sets possessed a HGMD variant. The clinical exome test had inadequate coverage for >50% of HGMD variant locations in 7 genes. Six exons from 6 different genes had consistent failure across all 3 test methods; these exons had high GC content (76%-84%). CONCLUSIONS: The use of clinical exome sequencing for the interpretation and reporting of subsets of genes requires recognition of the substantial possibility of inadequate depth and breadth of sequencing coverage at clinically relevant locations. Inadequate depth of coverage may contribute to false-negative clinical exome results.

Donor splice-site mutation in CUL4B is likely cause of X-linked intellectual disability.

X-linked intellectual disability is the most common form of cognitive disability in males. Syndromic intellectual disability encompasses cognitive deficits with other medical and behavioral manifestations. Recently, a large family with a novel form of syndromic X-linked intellectual disability was characterized. Eight of 24 members of the family are male and had cognitive dysfunction, short stature, aphasia, skeletal abnormalities, and minor anomalies. To identify the causative gene(s), we performed exome sequencing in three affected boys, both parents, and an unaffected sister. We identified a haplotype consisting of eight variants located in cis within the linkage region that segregated with affected members in the family. Of these variants, two were novel. The first was at the splice-donor site of intron 7 (c.974+1G>T) in the cullin-RING ubiquitin ligase (E3) gene, CUL4B. This variant is predicted to result in failure to splice and remove intron 7 from the primary transcript. The second variant mapped to the 3'-UTR region of the KAISO gene (c.1127T>G). Sanger sequencing validated the variants in these relatives as well as in three affected males and five carriers. The KAISO gene variant was predicted to create a binding site for the microRNAs miR-4999 and miR-4774; however, luciferase expression assays failed to validate increased targeting of these miRNAs to the variant 3'-UTR. This SNP may affect 3'-UTR structure leading to decreased mRNA stability. Our results suggest that the intellectual disability phenotype in this family is caused by aberrant splicing and removal of intron 7 from CUL4B gene primary transcript.

The microRNAs within the DLK1-DIO3 genomic region: involvement in disease pathogenesis.

The mammalian genome is transcribed in a developmentally regulated manner, generating RNA strands ranging from long to short non-coding RNA (ncRNAs). NcRNAs generated by intergenic sequences and protein-coding loci, represent up to 98 % of the human transcriptome. Non-coding transcripts comprise short ncRNAs such as microRNAs, piwi-interacting RNAs, small nucleolar RNAs and long intergenic RNAs, most of which exercise a strictly controlled negative regulation of expression of protein-coding genes. In humans, the DLK1-DIO3 genomic region, located on human chromosome 14 (14q32) contains the paternally expressed imprinted genes DLK1, RTL1, and DIO3 and the maternally expressed imprinted genes MEG3 (Gtl2), MEG8 (RIAN), and antisense RTL1 (asRTL1). This region hosts, in addition to two long intergenic RNAs, the MEG3 and MEG8, one of the largest microRNA clusters in the genome, with 53 miRNAs in the forward strand and one (mir-1247) in the reverse strand. Many of these miRNAs are differentially expressed in several pathologic processes and various cancers. A better understanding of the pathophysiologic importance of the DLK1-DIO3 domain-containing microRNA cluster may contribute to innovative therapeutic strategies in a range of diseases. Here we present an in-depth review of this vital genomic region, and examine the role the microRNAs of this region may play in controlling tissue homeostasis and in the pathogenesis of some human diseases, mostly cancer, when aberrantly expressed. The potential clinical implications of this data are also discussed.

The complex transcriptional landscape of the anucleate human platelet.

BACKGROUND: Human blood platelets are essential to maintaining normal hemostasis, and platelet dysfunction often causes bleeding or thrombosis. Estimates of genome-wide platelet RNA expression using microarrays have provided insights to the platelet transcriptome but were limited by the number of known transcripts. The goal of this effort was to deep-sequence RNA from leukocyte-depleted platelets to capture the complex profile of all expressed transcripts. RESULTS: From each of four healthy individuals we generated long RNA (≥40 nucleotides) profiles from total and ribosomal-RNA depleted RNA preparations, as well as short RNA (<40 nucleotides) profiles. Analysis of ~1 billion reads revealed that coding and non-coding platelet transcripts span a very wide dynamic range (≥16 PCR cycles beyond ß-actin), a result we validated through qRT-PCR on many dozens of platelet messenger RNAs. Surprisingly, ribosomal-RNA depletion significantly and adversely affected estimates of the relative abundance of transcripts. Of the known protein-coding loci, ~9,500 are present in human platelets. We observed a strong correlation between mRNAs identified by RNA-seq and microarray for well-expressed mRNAs, but RNASeq identified many more transcripts of lower abundance and permitted discovery of novel transcripts. CONCLUSIONS: Our analyses revealed diverse classes of non-coding RNAs, including: pervasive antisense transcripts to protein-coding loci; numerous, previously unreported and abundant microRNAs; retrotransposons; and thousands of novel un-annotated long and short intronic transcripts, an intriguing finding considering the anucleate nature of platelets. The data are available through a local mirror of the UCSC genome browser and can be accessed at: http://cm.jefferson.edu/platelets_2012/.

HuR is a post-transcriptional regulator of core metabolic enzymes in pancreatic cancer.

Cancer cell metabolism differs from normal cells, yet the regulatory mechanisms responsible for these differences are incompletely understood, particularly in response to acute changes in the tumor microenvironment. HuR, an RNA-binding protein, acts under acute stress to regulate core signaling pathways in cancer through post-transcriptional regulation of mRNA targets. We demonstrate that HuR regulates the metabolic phenotype in pancreatic cancer cells and is critical for survival under acute glucose deprivation. Using three pancreatic cancer cell line models, HuR-proficient cells demonstrated superior survival under glucose deprivation when compared with isogenic cells with siRNA-silencing of HuR expression (HuR-deficient cells). We found that HuR-proficient cells utilized less glucose, but produced greater lactate, as compared with HuR-deficient cells. Acute glucose deprivation was found to act as a potent stimulus for HuR translocation from the nucleus to the cytoplasm, where HuR stabilizes its mRNA targets. We performed a gene expression array on ribonucleoprotein-immunoprecipitated mRNAs bound to HuR and identified 11 novel HuR target transcripts that encode enzymes central to glucose metabolism. Three (GPI, PRPS2 and IDH1) were selected for validation studies, and confirmed as bona fide HuR targets. These findings establish HuR as a critical regulator of pancreatic cancer cell metabolism and survival under acute glucose deprivation. Further explorations into HuR's role in cancer cell metabolism should uncover novel therapeutic targets that are critical for cancer cell survival in a metabolically compromised tumor microenvironment.

Whole-exome sequencing of DNA from peripheral blood mononuclear cells (PBMC) and EBV-transformed lymphocytes from the same donor.

BACKGROUND: The creation of lymphoblastoid cell lines (LCLs) through Epstein-Barr virus (EBV) transformation of B-lymphocytes can result in a valuable biomaterial for cell biology research and a renewable source of DNA. While LCLs have been used extensively in cellular and genetic studies, the process of cell transformation and expansion during culturing may introduce genomic changes that may impact their use and the interpretation of subsequent genetic findings. RESULTS: We performed whole exome sequencing on a tetrad family using DNA derived from peripheral blood mononuclear cells (PBMCs) and LCLs from each individual. We generated over 4.7 GB of mappable sequence to a 125X read coverage per sample. An average of 19,354 genetic variants were identified. Comparison of the two DNA sources from each individual showed an average concordance rate of 95.69%. By lowering the variant calling parameters, the concordance rate between the paired samples increased to 99.82%. Sanger sequencing of a subset of the remaining discordant variants did confirm the presence of de novo mutations arising in LCLs. CONCLUSIONS: By varying software stringency parameters, we identified 99% concordance between DNA sequences derived from the two different sources from the same donors. These results suggest that LCLs are an appropriate representation of the genetic material of the donor and suggest that EBV transformation can result in low-level generation of de novo mutations. Therefore, use of PBMC or early passage EBV-transformed cells is recommended. These findings have broad-reaching implications, as there are thousands of LCLs in public biorepositories and individual laboratories.

MicroRNA Isoforms Contribution to Melanoma Pathogenesis.

Cutaneous melanoma (CM) is the most lethal tumor among skin cancers, and its incidence is constantly increasing. A deeper understanding of the molecular processes guiding melanoma pathogenesis could improve diagnosis, treatment and prognosis. MicroRNAs play a key role in melanoma biology. Recently, next generation sequencing (NGS) experiments, designed to assess small-RNA expression, revealed the existence of microRNA variants with different length and sequence. These microRNA isoforms are known as isomiRs and provide an additional layer to the complex non-coding RNA world. Here, we collected data from NGS experiments to provide a comprehensive characterization of miRNA and isomiR dysregulation in benign nevi (BN) and early-stage melanomas. We observed that melanoma and BN express different and specific isomiRs and have a different isomiR abundance distribution. Moreover, isomiRs from the same microRNA can have opposite expression trends between groups. Using The Cancer Genome Atlas (TCGA) dataset of skin cancers, we analyzed isomiR expression in primary melanoma and melanoma metastasis and tested their association with NF1, BRAF and NRAS mutations. IsomiRs differentially expressed were identified and catalogued with reference to the canonical form. The reported non-random dysregulation of specific isomiRs contributes to the understanding of the complex melanoma pathogenesis and serves as the basis for further functional studies.