Single-cell nanobiopsy enables multigenerational longitudinal transcriptomics of cancer cells.

Single-cell RNA sequencing has revolutionized our understanding of cellular heterogeneity, but routine methods require cell lysis and fail to probe the dynamic trajectories responsible for cellular state transitions, which can only be inferred. Here, we present a nanobiopsy platform that enables the injection of exogenous molecules and multigenerational longitudinal cytoplasmic sampling from a single cell and its progeny. The technique is based on scanning ion conductance microscopy (SICM) and, as a proof of concept, was applied to longitudinally profile the transcriptome of single glioblastoma (GBM) brain tumor cells in vitro over 72 hours. The GBM cells were biopsied before and after exposure to chemotherapy and radiotherapy, and our results suggest that treatment either induces or selects for more transcriptionally stable cells. We envision the nanobiopsy will contribute to transforming standard single-cell transcriptomics from a static analysis into a dynamic assay.

m6aViewer: software for the detection, analysis, and visualization of N6-methyladenosine peaks from m6A-seq/ME-RIP sequencing data.

Recent methods for transcriptome-wide N6-methyladenosine (m6A) profiling have facilitated investigations into the RNA methylome and established m6A as a dynamic modification that has critical regulatory roles in gene expression and may play a role in human disease. However, bioinformatics resources available for the analysis of m6A sequencing data are still limited. Here, we describe m6aViewer-a cross-platform application for analysis and visualization of m6A peaks from sequencing data. m6aViewer implements a novel m6A peak-calling algorithm that identifies high-confidence methylated residues with more precision than previously described approaches. The application enables data analysis through a graphical user interface, and thus, in contrast to other currently available tools, does not require the user to be skilled in computer programming. m6aViewer and test data can be downloaded here: http://dna2.leeds.ac.uk/m6a.

A Chromosome 7 Pericentric Inversion Defined at Single-Nucleotide Resolution Using Diagnostic Whole Genome Sequencing in a Patient with Hand-Foot-Genital Syndrome.

Next generation sequencing methodologies are facilitating the rapid characterisation of novel structural variants at nucleotide resolution. These approaches are particularly applicable to variants initially identified using alternative molecular methods. We report a child born with bilateral postaxial syndactyly of the feet and bilateral fifth finger clinodactyly. This was presumed to be an autosomal recessive syndrome, due to the family history of consanguinity. Karyotype analysis revealed a homozygous pericentric inversion of chromosome 7 (46,XX,inv(7)(p15q21)x2) which was confirmed to be heterozygous in both unaffected parents. Since the resolution of the karyotype was insufficient to identify any putatively causative gene, we undertook medium-coverage whole genome sequencing using paired-end reads, in order to elucidate the molecular breakpoints. In a two-step analysis, we first narrowed down the region by identifying discordant read-pairs, and then determined the precise molecular breakpoint by analysing the mapping locations of "soft-clipped" breakpoint-spanning reads. PCR and Sanger sequencing confirmed the identified breakpoints, both of which were located in intergenic regions. Significantly, the 7p15 breakpoint was located 523 kb upstream of HOXA13, the locus for hand-foot-genital syndrome. By inference from studies of HOXA locus control in the mouse, we suggest that the inversion has delocalised a HOXA13 enhancer to produce the phenotype observed in our patient. This study demonstrates how modern genetic diagnostic approach can characterise structural variants at nucleotide resolution and provide potential insights into functional regulation.

Deficiency of the myogenic factor MyoD causes a perinatally lethal fetal akinesia.

BACKGROUND: Lethal fetal akinesia deformation sequence (FADS) describes a clinically and genetically heterogeneous phenotype that includes fetal akinesia, intrauterine growth retardation, arthrogryposis and developmental anomalies. Affected babies die as a result of pulmonary hypoplasia. We aimed to identify the underlying genetic cause of this disorder in a family in which there were three affected individuals from two sibships. METHODS: Autosomal-recessive inheritance was suggested by a family history of consanguinity and by recurrence of the phenotype between the two sibships. We performed exome sequencing of the affected individuals and their unaffected mother, followed by autozygosity mapping and variant filtering to identify the causative gene. RESULTS: Five autozygous regions were identified, spanning 31.7 Mb of genomic sequence and including 211 genes. Using standard variant filtering criteria, we excluded all variants as being the likely pathogenic cause, apart from a single novel nonsense mutation, c.188C>A p.(Ser63*) (NM_002478.4), in MYOD1. This gene encodes an extensively studied transcription factor involved in muscle development, which has nonetheless not hitherto been associated with a hereditary human disease phenotype. CONCLUSIONS: We provide the first description of a human phenotype that appears to result from MYOD1 mutation. The presentation with FADS is consistent with a large body of data demonstrating that in the mouse, MyoD is a major controller of precursor cell commitment to the myogenic differentiation programme.

Enhanced diagnostic yield in Meckel-Gruber and Joubert syndrome through exome sequencing supplemented with split-read mapping.

BACKGROUND: The widespread adoption of high-throughput sequencing technologies by genetic diagnostic laboratories has enabled significant expansion of their testing portfolios. Rare autosomal recessive conditions have been a particular focus of many new services. Here we report a cohort of 26 patients referred for genetic analysis of Joubert (JBTS) and Meckel-Gruber (MKS) syndromes, two clinically and genetically heterogeneous neurodevelopmental conditions that define a phenotypic spectrum, with MKS at the severe end. METHODS: Exome sequencing was performed for all cases, using Agilent SureSelect v5 reagents and Illumina paired-end sequencing. For two cases medium-coverage (9×) whole genome sequencing was subsequently undertaken. RESULTS: Using a standard analysis pipeline for the detection of single nucleotide and small insertion or deletion variants, molecular diagnoses were confirmed in 12 cases (4%). Seeking to determine whether our cohort harboured pathogenic copy number variants (CNV), in JBTS- or MKS-associated genes, targeted comparative read-depth analysis was performed using FishingCNV. These analyses identified a putative intragenic AHI1 deletion that included three exons spanning at least 3.4 kb and an intergenic MPP4 to TMEM237 deletion that included exons spanning at least 21.5 kb. Whole genome sequencing enabled confirmation of the deletion-containing alleles and precise characterisation of the mutation breakpoints at nucleotide resolution. These data were validated following development of PCR-based assays that could be subsequently used for "cascade" screening and/or prenatal diagnosis. CONCLUSIONS: Our investigations expand the AHI1 and TMEM237 mutation spectrum and highlight the importance of performing CNV screening of disease-associated genes. We demonstrate a robust increasingly cost-effective CNV detection workflow that is applicable to all MKS/JBTS referrals.

OVA: integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization.

MOTIVATION: Exome sequencing has become a de facto standard method for Mendelian disease gene discovery in recent years, yet identifying disease-causing mutations among thousands of candidate variants remains a non-trivial task. RESULTS: Here we describe a new variant prioritization tool, OVA (ontology variant analysis), in which user-provided phenotypic information is exploited to infer deeper biological context. OVA combines a knowledge-based approach with a variant-filtering framework. It reduces the number of candidate variants by considering genotype and predicted effect on protein sequence, and scores the remainder on biological relevance to the query phenotype.We take advantage of several ontologies in order to bridge knowledge across multiple biomedical domains and facilitate computational analysis of annotations pertaining to genes, diseases, phenotypes, tissues and pathways. In this way, OVA combines information regarding molecular and physical phenotypes and integrates both human and model organism data to effectively prioritize variants. By assessing performance on both known and novel disease mutations, we show that OVA performs biologically meaningful candidate variant prioritization and can be more accurate than another recently published candidate variant prioritization tool. AVAILABILITY AND IMPLEMENTATION: OVA is freely accessible at http://dna2.leeds.ac.uk:8080/OVA/index.jsp. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: umaan@leeds.ac.uk.

Rapid Detection of Rare Deleterious Variants by Next Generation Sequencing with Optional Microarray SNP Genotype Data.

Autozygosity mapping is a powerful technique for the identification of rare, autosomal recessive, disease-causing genes. The ease with which this category of disease gene can be identified has greatly increased through the availability of genome-wide SNP genotyping microarrays and subsequently of exome sequencing. Although these methods have simplified the generation of experimental data, its analysis, particularly when disparate data types must be integrated, remains time consuming. Moreover, the huge volume of sequence variant data generated from next generation sequencing experiments opens up the possibility of using these data instead of microarray genotype data to identify disease loci. To allow these two types of data to be used in an integrated fashion, we have developed AgileVCFMapper, a program that performs both the mapping of disease loci by SNP genotyping and the analysis of potentially deleterious variants using exome sequence variant data, in a single step. This method does not require microarray SNP genotype data, although analysis with a combination of microarray and exome genotype data enables more precise delineation of disease loci, due to superior marker density and distribution.