Fast computation and applications of genome mappability

Identifying and Classifying Shared Selective Sweeps from Multilocus Data

Positive selection causes beneficial alleles to rise to high frequency, resulting in a selective sweep of the diversity surrounding the selected sites. Accordingly, the signature of a selective sweep in an ancestral population may still remain in its descendants. Identifying signatures of selection in the ancestor that are shared among its descendants is important to contextualize the timing of a sweep, but few methods exist for this purpose. We introduce the statistic SS-H12, which can identify genomic regions under shared positive selection across populations and is based on the theory of the expected haplotype homozygosity statistic H12, which detects recent hard and soft sweeps from the presence of high-frequency haplotypes. SS-H12 is distinct from comparable statistics because it requires a minimum of only two populations, and properly identifies and differentiates between independent convergent sweeps and true ancestral sweeps, with high power and robustness to a variety of demographic models. Furthermore, we can apply SS-H12 in conjunction with the ratio of statistics we term [Formula: see text] and [Formula: see text] to further classify identified shared sweeps as hard or soft. Finally, we identified both previously reported and novel shared sweep candidates from human whole-genome sequences. Previously reported candidates include the well-characterized ancestral sweeps at LCT and SLC24A5 in Indo-Europeans, as well as GPHN worldwide. Novel candidates include an ancestral sweep at RGS18 in sub-Saharan Africans involved in regulating the platelet response and implicated in sudden cardiac death, and a convergent sweep at C2CD5 between European and East Asian populations that may explain their different insulin responses.

AnnoGen: annotating genome-wide pragmatic features

MOTIVATION

Genome annotation is an important step for all in-depth bioinformatics analysis. It is imperative to augment quantity and diversity of genome-wide annotation data for the latest reference genome to promote its adoption by ongoing and future impactful studies.

RESULTS

We developed a python toolkit AnnoGen, which at the first time, allows the annotation of three pragmatic genomic features for the GRCh38 genome in enormous base-wise quantities. The three features are chemical binding Energy, sequence information Entropy and Homology Score. The Homology Score is an exceptional feature that captures the genome-wide homology through single-base-offset tiling windows of 100 continual nucleotide bases. AnnoGen is capable of annotating the proprietary pragmatic features for variable user-interested genomic regions and optionally comparing two parallel sets of genomic regions. AnnoGen is characterized with simple utility modes and succinct HTML report of informative statistical tables and plots.

AVAILABILITY AND IMPLEMENTATION

https://github.com/shengqh/annogen.

Tracing the Evolutionary History and Global Expansion of Candida auris Using Population Genomic Analyses

Candida auris has emerged globally as a multidrug-resistant yeast that can spread via nosocomial transmission. An initial phylogenetic study of isolates from Japan, India, Pakistan, South Africa, and Venezuela revealed four populations (clades I, II, III, and IV) corresponding to these geographic regions. Since this description, C. auris has been reported in more than 30 additional countries. To trace this global emergence, we compared the genomes of 304 C. auris isolates from 19 countries on six continents. We found that four predominant clades persist across wide geographic locations. We observed phylogeographic mixing in most clades; clade IV, with isolates mainly from South America, demonstrated the strongest phylogeographic substructure. C. auris isolates from two clades with opposite mating types were detected contemporaneously in a single health care facility in Kenya. We estimated a Bayesian molecular clock phylogeny and dated the origin of each clade within the last 360 years; outbreak-causing clusters from clades I, III, and IV originated 36 to 38 years ago. We observed high rates of antifungal resistance in clade I, including four isolates resistant to all three major classes of antifungals. Mutations that contribute to resistance varied between the clades, with Y132F in ERG11 as the most widespread mutation associated with azole resistance and S639P in FKS1 for echinocandin resistance. Copy number variants in ERG11 predominantly appeared in clade III and were associated with fluconazole resistance. These results provide a global context for the phylogeography, population structure, and mechanisms associated with antifungal resistance in C. aurisIMPORTANCE In less than a decade, C. auris has emerged in health care settings worldwide; this species is capable of colonizing skin and causing outbreaks of invasive candidiasis. In contrast to other Candida species, C. auris is unique in its ability to spread via nosocomial transmission and its high rates of drug resistance. As part of the public health response, whole-genome sequencing has played a major role in characterizing transmission dynamics and detecting new C. auris introductions. Through a global collaboration, we assessed genome evolution of isolates of C. auris from 19 countries. Here, we described estimated timing of the expansion of each C. auris clade and of fluconazole resistance, characterized discrete phylogeographic population structure of each clade, and compared genome data to sensitivity measurements to describe how antifungal resistance mechanisms vary across the population. These efforts are critical for a sustained, robust public health response that effectively utilizes molecular epidemiology.

The evolutionary history and genomics of European blackcap migration

Seasonal migration is a taxonomically widespread behaviour that integrates across many traits. The European blackcap exhibits enormous variation in migration and is renowned for research on its evolution and genetic basis. We assembled a reference genome for blackcaps and obtained whole genome resequencing data from individuals across its breeding range. Analyses of population structure and demography suggested divergence began ~30,000 ya, with evidence for one admixture event between migrant and resident continent birds ~5000 ya. The propensity to migrate, orientation and distance of migration all map to a small number of genomic regions that do not overlap with results from other species, suggesting that there are multiple ways to generate variation in migration. Strongly associated single nucleotide polymorphisms (SNPs) were located in regulatory regions of candidate genes that may serve as major regulators of the migratory syndrome. Evidence for selection on shared variation was documented, providing a mechanism by which rapid changes may evolve.

A highly accurate platform for clone-specific mutation discovery enables the study of active mutational processes

Bulk whole genome sequencing (WGS) enables the analysis of tumor evolution but, because of depth limitations, can only identify old mutational events. The discovery of current mutational processes for predicting the tumor’s evolutionary trajectory requires dense sequencing of individual clones or single cells. Such studies, however, are inherently problematic because of the discovery of excessive false positive (FP) mutations when sequencing picogram quantities of DNA. Data pooling to increase the confidence in the discovered mutations, moves the discovery back in the past to a common ancestor. Here we report a robust WGS and analysis pipeline (DigiPico/MutLX) that virtually eliminates all F results while retaining an excellent proportion of true positives. Using our method, we identified, for the first time, a hyper-mutation (kataegis) event in a group of ∼30 cancer cells from a recurrent ovarian carcinoma. This was unidentifiable from the bulk WGS data. Overall, we propose DigiPico/MutLX method as a powerful framework for the identification of clone-specific variants at an unprecedented accuracy.

Mapping the breast cancer metastatic cascade onto ctDNA using genetic and epigenetic clonal tracking

Circulating tumour DNA (ctDNA) allows tracking of the evolution of human cancers at high resolution, overcoming many limitations of tissue biopsies. However, exploiting ctDNA to determine how a patient's cancer is evolving in order to aid clinical decisions remains difficult. This is because ctDNA is a mix of fragmented alleles, and the contribution of different cancer deposits to ctDNA is largely unknown. Profiling ctDNA almost invariably requires prior knowledge of what genomic alterations to track. Here, we leverage on a rapid autopsy programme to demonstrate that unbiased genomic characterisation of several metastatic sites and concomitant ctDNA profiling at whole-genome resolution reveals the extent to which ctDNA is representative of widespread disease. We also present a methylation profiling method that allows tracking evolutionary changes in ctDNA at single-molecule resolution without prior knowledge. These results have critical implications for the use of liquid biopsies to monitor cancer evolution in humans and guide treatment.

Added Value of Clinical Sequencing: WGS-Based Profiling of Pharmacogenes

Although several pharmacogenetic (PGx) predispositions affecting drug efficacy and safety are well established, drug selection and dosing as well as clinical trials are often performed in a non-pharmacogenetically-stratified manner, ultimately burdening healthcare systems. Pre-emptive PGx testing offers a solution which is often performed using microarrays or targeted gene panels, testing for common/known PGx variants. However, as an added value, whole-genome sequencing (WGS) could detect not only disease-causing but also pharmacogenetically-relevant variants in a single assay. Here, we present our WGS-based pipeline that extends the genetic testing of Mendelian diseases with PGx profiling, enabling the detection of rare/novel PGx variants as well. From our in-house WGS (PCR-free 60× PE150) data of 547 individuals we extracted PGx variants with drug-dosing recommendations of the Dutch Pharmacogenetics Working Group (DPWG). Furthermore, we explored the landscape of DPWG pharmacogenes in gnomAD and our in-house cohort as well as compared bioinformatic tools for WGS-based structural variant detection in CYP2D6. We show that although common/known PGx variants comprise the vast majority of detected DPWG pharmacogene alleles, for better precision medicine, PGx testing should move towards WGS-based approaches. Indeed, WGS-based PGx profiling is not only feasible and future-oriented but also the most comprehensive all-in-one approach without generating significant additional costs.

Global genome diversity of the Leishmania donovani complex

Protozoan parasites of the Leishmania donovani complex - L. donovani and L. infantum - cause the fatal disease visceral leishmaniasis. We present the first comprehensive genome-wide global study, with 151 cultured field isolates representing most of the geographical distribution. L. donovani isolates separated into five groups that largely coincide with geographical origin but vary greatly in diversity. In contrast, the majority of L. infantum samples fell into one globally-distributed group with little diversity. This picture is complicated by several hybrid lineages. Identified genetic groups vary in heterozygosity and levels of linkage, suggesting different recombination histories. We characterise chromosome-specific patterns of aneuploidy and identified extensive structural variation, including known and suspected drug resistance loci. This study reveals greater genetic diversity than suggested by geographically-focused studies, provides a resource of genomic variation for future work and sets the scene for a new understanding of the evolution and genetics of the Leishmania donovani complex.

Pericentromeric heterochromatin is hierarchically organized and spatially contacts H3K9me2 islands in euchromatin

Membraneless pericentromeric heterochromatin (PCH) domains play vital roles in chromosome dynamics and genome stability. However, our current understanding of 3D genome organization does not include PCH domains because of technical challenges associated with repetitive sequences enriched in PCH genomic regions. We investigated the 3D architecture of Drosophila melanogaster PCH domains and their spatial associations with the euchromatic genome by developing a novel analysis method that incorporates genome-wide Hi-C reads originating from PCH DNA. Combined with cytogenetic analysis, we reveal a hierarchical organization of the PCH domains into distinct “territories.” Strikingly, H3K9me2-enriched regions embedded in the euchromatic genome show prevalent 3D interactions with the PCH domain. These spatial contacts require H3K9me2 enrichment, are likely mediated by liquid-liquid phase separation, and may influence organismal fitness. Our findings have important implications for how PCH architecture influences the function and evolution of both repetitive heterochromatin and the gene-rich euchromatin.

The three dimensional (3D) organization of genomes in cell nuclei can influence a wide variety of genome functions. However, most of our understanding of this critical architecture has been limited to the gene-rich euchromatin, and largely ignores the gene-poor and repeat-rich pericentromeric heterochromatin, or PCH. PCH comprises a large part of most eukaryotic genomes, forms 3D membraneless PCH domains in nuclei, and plays a vital role in chromosome dynamics and genome stability. In this study, we developed a new method that overcomes the technical challenges imposed by the highly repetitive PCH DNA, and generated a comprehensive picture of its 3D organization. Combined with image analyses, we reveal a hierarchical organization of the PCH domains. Surprisingly, we showed that distant euchromatic regions enriched for repressive epigenetic marks also dynamically interact with the main PCH domains. These 3D interactions are likely mediated by liquid-liquid phase separation (similar to how oil and vinegar separate in salad dressing) and the resulting liquid-like fusion events, and can influence the fitness of individuals. Our discoveries have strong implications for how seemingly “junk” DNA could impact functions in the gene-rich euchromatin.

A dominant-negative effect drives selection of TP53 missense mutations in myeloid malignancies

TP53, which encodes the tumor suppressor p53, is the most frequently mutated gene in human cancer. The selective pressures shaping its mutational spectrum, dominated by missense mutations, are enigmatic, and neomorphic gain-of-function (GOF) activities have been implicated. We used CRISPR-Cas9 to generate isogenic human leukemia cell lines of the most common TP53 missense mutations. Functional, DNA-binding, and transcriptional analyses revealed loss of function but no GOF effects. Comprehensive mutational scanning of p53 single-amino acid variants demonstrated that missense variants in the DNA-binding domain exert a dominant-negative effect (DNE). In mice, the DNE of p53 missense variants confers a selective advantage to hematopoietic cells on DNA damage. Analysis of clinical outcomes in patients with acute myeloid leukemia showed no evidence of GOF for TP53 missense mutations. Thus, a DNE is the primary unit of selection for TP53 missense mutations in myeloid malignancies.

Pervasive Differential Splicing in Marek's Disease Virus can Discriminate CVI-988 Vaccine Strain from RB-1B Very Virulent Strain in Chicken Embryonic Fibroblasts

Marek's disease is a major scourge challenging poultry health worldwide. It is caused by the highly contagious Marek's disease virus (MDV), an alphaherpesvirus. Here, we showed that, similar to other members of its Herpesviridae family, MDV also presents a complex landscape of splicing events, most of which are uncharacterised and/or not annotated. Quite strikingly, and although the biological relevance of this fact is unknown, we found that a number of viral splicing isoforms are strain-specific, despite the close sequence similarity of the strains considered: very virulent RB-1B and vaccine CVI-988. We validated our findings by devising an assay that discriminated infections caused by the two strains in chicken embryonic fibroblasts on the basis of the presence of some RNA species. To our knowledge, this study is the first to accomplish such a result, emphasizing how relevant a comprehensive picture of the viral transcriptome is to fully understand viral pathogenesis.

SVXplorer: Three-tier approach to identification of structural variants via sequential recombination of discordant cluster signatures

The identification of structural variants using short-read data remains challenging. Most approaches that use discordant paired-end sequences ignore non-trivial signatures presented by variants containing 3 breakpoints, such as those generated by various copy-paste and cut-paste mechanisms. This can result in lower precision and sensitivity in the identification of the more common structural variants such as deletions and duplications. We present SVXplorer, which uses a graph-based clustering approach streamlined by the integration of non-trivial signatures from discordant paired-end alignments, split-reads and read depth information to improve upon existing methods. We show that SVXplorer is more sensitive and precise compared to several existing approaches on multiple real and simulated datasets. SVXplorer is available for download at https://github.com/kunalkathuria/SVXplorer.

Characterization of functional transposable element enhancers in acute myeloid leukemia

Transposable elements (TEs) have been shown to have important gene regulatory functions and their alteration could lead to disease phenotypes. Acute myeloid leukemia (AML) develops as a consequence of a series of genetic changes in hematopoietic precursor cells, including mutations in epigenetic factors. Here, we set out to study the gene regulatory role of TEs in AML. We first explored the epigenetic landscape of TEs in AML patients using ATAC-seq data. We show that a large number of TEs in general, and more specifically mammalian-wide interspersed repeats (MIRs), are more enriched in AML cells than in normal blood cells. We obtained a similar finding when analyzing histone modification data in AML patients. Gene Ontology enrichment analysis showed that genes near MIRs in open chromatin regions are involved in leukemogenesis. To functionally validate their regulatory role, we selected 19 MIR regions in AML cells, and tested them for enhancer activity in an AML cell line (Kasumi-1) and a chronic myeloid leukemia (CML) cell line (K562); the results revealed several MIRs to be functional enhancers. Taken together, our results suggest that TEs are potentially involved in myeloid leukemogenesis and highlight these sequences as potential candidates harboring AML-associated variation.

Chromatin-Based Classification of Genetically Heterogeneous AMLs into Two Distinct Subtypes with Diverse Stemness Phenotypes

Global investigation of histone marks in acute myeloid leukemia (AML) remains limited. Analyses of 38 AML samples through integrated transcriptional and chromatin mark analysis exposes 2 major subtypes. One subtype is dominated by patients with NPM1 mutations or MLL-fusion genes, shows activation of the regulatory pathways involving HOX-family genes as targets, and displays high self-renewal capacity and stemness. The second subtype is enriched for RUNX1 or spliceosome mutations, suggesting potential interplay between the 2 aberrations, and mainly depends on IRF family regulators. Cellular consequences in prognosis predict a relatively worse outcome for the first subtype. Our integrated profiling establishes a rich resource to probe AML subtypes on the basis of expression and chromatin data.

ChromID identifies the protein interactome at chromatin marks

Chromatin modifications regulate genome function by recruiting protein factors to the genome. However, the protein composition at distinct chromatin modifications remains to be fully characterized. Here, we use natural protein domains as modular building blocks to develop engineered chromatin readers (eCRs) selective for DNA methylation and histone tri-methylation at H3K4, H3K9 a H3K27 residues. We first demonstrate their utility as selective chromatin binders in living cells by stably expressing eCRs in mouse embryonic stem cells and measuring their subnuclear localisation, genomic distribution and histone modification–binding preference. By fusing eCRs to the biotin ligase BASU, we establish ChromID, a method for identifying the chromatin-dependent protein interactome based on proximity biotinylation, and apply it to distinct chromatin modifications in mouse stem cells. Using a synthetic dual-modification reader, we also uncover the protein composition at bivalent promoters marked by H3K4me3 and H3K27me3. These results highlight the ability of ChromID to obtain a detailed view of protein interaction networks on chromatin.

Accurate Tracking of the Mutational Landscape of Diploid Hybrid Genomes

Mutations, recombinations, and genome duplications may promote genetic diversity and trigger evolutionary processes. However, quantifying these events in diploid hybrid genomes is challenging. Here, we present an integrated experimental and computational workflow to accurately track the mutational landscape of yeast diploid hybrids (MuLoYDH) in terms of single-nucleotide variants, small insertions/deletions, copy-number variants, aneuploidies, and loss-of-heterozygosity. Pairs of haploid Saccharomyces parents were combined to generate ancestor hybrids with phased genomes and varying levels of heterozygosity. These diploids were evolved under different laboratory protocols, in particular mutation accumulation experiments. Variant simulations enabled the efficient integration of competitive and standard mapping of short reads, depending on local levels of heterozygosity. Experimental validations proved the high accuracy and resolution of our computational approach. Finally, applying MuLoYDH to four different diploids revealed striking genetic background effects. Homozygous Saccharomyces cerevisiae showed a ∼4-fold higher mutation rate compared with its closely related species S. paradoxus. Intraspecies hybrids unveiled that a substantial fraction of the genome (∼250 bp per generation) was shaped by loss-of-heterozygosity, a process strongly inhibited in interspecies hybrids by high levels of sequence divergence between homologous chromosomes. In contrast, interspecies hybrids exhibited higher single-nucleotide mutation rates compared with intraspecies hybrids. MuLoYDH provided an unprecedented quantitative insight into the evolutionary processes that mold diploid yeast genomes and can be generalized to other genetic systems.

Direct full-length RNA sequencing reveals unexpected transcriptome complexity during Caenorhabditis elegans development

Massively parallel sequencing of the polyadenylated RNAs has played a key role in delineating transcriptome complexity, including alternative use of an exon, promoter, 5′ or 3′ splice site or polyadenylation site, and RNA modification. However, reads derived from the current RNA-seq technologies are usually short and deprived of information on modification, compromising their potential in defining transcriptome complexity. Here, we applied a direct RNA sequencing method with ultralong reads using Oxford Nanopore Technologies to study the transcriptome complexity in Caenorhabditis elegans. We generated approximately six million reads using native poly(A)-tailed mRNAs from three developmental stages, with average read lengths ranging from 900 to 1100 nt. Around half of the reads represent full-length transcripts. To utilize the full-length transcripts in defining transcriptome complexity, we devised a method to classify the long reads as the same as existing transcripts or as a novel transcript using sequence mapping tracks rather than existing intron/exon structures, which allowed us to identify roughly 57,000 novel isoforms and recover at least 26,000 out of the 33,500 existing isoforms. The sets of genes with differential expression versus differential isoform usage over development are largely different, implying a fine-tuned regulation at isoform level. We also observed an unexpected increase in putative RNA modification in all bases in the coding region relative to the UTR, suggesting their possible roles in translation. The RNA reads and the method for read classification are expected to deliver new insights into RNA processing and modification and their underlying biology in the future.

PeakPass: Automating ChIP-Seq Blacklist Creation

ChIP-Seq blacklists contain genomic regions that frequently produce artifacts and noise in ChIP-Seq experiments. To improve signal-to-noise ratio, ChIP-Seq pipelines often remove data points that map to blacklist regions. Existing blacklists have been compiled in a manual or semiautomated way. In this article we describe PeakPass, an efficient method to generate blacklists, and demonstrate that blacklists can increase ChIP-Seq data quality. PeakPass leverages machine learning and attempts to automate blacklist generation. PeakPass uses a random forest classifier in combination with genomic features such as sequence, annotated repeats, complexity, assembly gaps, and the ratio of multimapping to uniquely mapping reads to identify artifact regions. We have validated PeakPass on a large data set and tested it for the purpose of upgrading a blacklist to a new reference genome version. We trained PeakPass on the ENCODE blacklist for the hg19 human reference genome, and created an updated blacklist for hg38. To assess the performance of this blacklist, we tested 42 ChIP-Seq replicates from 24 experiments using 10 ChIP-Seq quality metrics including relative strand coefficient, standardized standard deviation, and enrichment of reads in promoter regions. Using the blacklist generated by PeakPass resulted in a statistically significant improvement for nine of these metrics.

Loss of Imprinting in Human Placentas Is Widespread, Coordinated, and Predicts Birth Phenotypes

Genomic imprinting leads to mono-allelic expression of genes based on parent of origin. Therian mammals and angiosperms evolved this mechanism in nutritive tissues, the placenta, and endosperm, where maternal and paternal genomes are in conflict with respect to resource allocation. We used RNA-seq to analyze allelic bias in the expression of 91 known imprinted genes in term human placentas from a prospective cohort study in Mali. A large fraction of the imprinted exons (39%) deviated from mono-allelic expression. Loss of imprinting (LOI) occurred in genes with either maternal or paternal expression bias, albeit more frequently in the former. We characterized LOI using binomial generalized linear mixed models. Variation in LOI was predominantly at the gene as opposed to the exon level, consistent with a single promoter driving the expression of most exons in a gene. Some genes were less prone to LOI than others, particularly lncRNA genes were rarely expressed from the repressed allele. Further, some individuals had more LOI than others and, within a person, the expression bias of maternally and paternally imprinted genes was correlated. We hypothesize that trans-acting maternal effect genes mediate correlated LOI and provide the mother with an additional lever to control fetal growth by extending her influence to LOI of the paternally imprinted genes. Limited evidence exists to support associations between LOI and offspring phenotypes. We show that birth length and placental weight were associated with allelic bias, making this the first comprehensive report of an association between LOI and a birth phenotype.

A highly sensitive and specific workflow for detecting rare copy-number variants from exome sequencing data

Background

Exome sequencing (ES) is a first-tier diagnostic test for many suspected Mendelian disorders. While it is routine to detect small sequence variants, it is not a standard practice in clinical settings to detect germline copy-number variants (CNVs) from ES data due to several reasons relating to performance. In this work, we comprehensively characterized one of the most sensitive ES-based CNV tools, ExomeDepth, against SNP array, a standard of care test in clinical settings to detect genome-wide CNVs.

Methods

We propose a modified ExomeDepth workflow by excluding exons with low mappability prior to variant calling to drastically reduce the false positives originating from the repetitive regions of the genome, and an iterative variant calling framework to assess the reproducibility. We used a cohort of 307 individuals with clinical ES data and clinical SNP array to estimate the sensitivity and false discovery rate of the CNV detection using exome sequencing. Further, we performed targeted testing of the STRC gene in 1972 individuals. To reduce the number of variants for downstream analysis, we performed a large-scale iterative variant calling process with random control cohorts to assess the reproducibility of the CNVs.

Results

The modified workflow presented in this paper reduced the number of total variants identified by one third while retaining a higher sensitivity of 97% and resulted in an improved false discovery rate of 11.4% compared to the default ExomeDepth pipeline. The exclusion of exons with low mappability removes 4.5% of the exons, including a subset of exons (0.6%) in disease-associated genes which are intractable by short-read next-generation sequencing (NGS). Results from the reproducibility analysis showed that the clinically reported variants were reproducible 100% of the time and that the modified workflow can be used to rank variants from high to low confidence. Targeted testing of 30 CNVs identified in STRC, a challenging gene to ascertain by NGS, showed a 100% validation rate.

Conclusions

In summary, we introduced a modification to the default ExomeDepth workflow to reduce the false positives originating from the repetitive regions of the genome, created a large-scale iterative variant calling framework for reproducibility, and provided recommendations for implementation in clinical settings.

Tumor suppressor genes and allele-specific expression: mechanisms and significance

Recent findings indicate that allele-specific expression (ASE) at specific cancer driver gene loci may be of importance in onset/progression of the disease. Of particular interest are loss-of-function (LOF) of tumor suppressor gene (TSGs) alleles. While LOF tumor suppressor mutations are typically considered to be recessive, if these mutant alleles can be significantly differentially expressed relative to wild-type alleles in heterozygotes, the clinical consequences could be significant. LOF TSG alleles are shown to be segregating at high frequencies in world-wide populations of normal/healthy individuals. Matched sets of normal and tumor tissues isolated from 233 cancer patients representing four diverse tumor types demonstrate functionally important changes in patterns of ASE in individuals heterozygous for LOF TSG alleles associated with cancer onset/progression. While a variety of molecular mechanisms were identified as potentially contributing to changes in ASE patterns in cancer, changes in DNA copy number and allele-specific alternative splicing possibly mediated by antisense RNA emerged as predominant factors. In conclusion, LOF TSGs are segregating in human populations at significant frequencies indicating that many otherwise healthy individuals are at elevated risk of developing cancer. Changes in ASE between normal and cancer tissues indicates that LOF TSG alleles may contribute to cancer onset/progression even when heterozygous with wild-type functional alleles.

Mechanisms governing the pioneering and redistribution capabilities of the non-classical pioneer PU.1

Establishing gene regulatory networks during differentiation or reprogramming requires master or pioneer transcription factors (TFs) such as PU.1, a prototype master TF of hematopoietic lineage differentiation. To systematically determine molecular features that control its activity, here we analyze DNA-binding in vitro and genome-wide in vivo across different cell types with native or ectopic PU.1 expression. Although PU.1, in contrast to classical pioneer factors, is unable to access nucleosomal target sites in vitro, ectopic induction of PU.1 leads to the extensive remodeling of chromatin and redistribution of partner TFs. De novo chromatin access, stable binding, and redistribution of partner TFs both require PU.1's N-terminal acidic activation domain and its ability to recruit SWI/SNF remodeling complexes, suggesting that the latter may collect and distribute co-associated TFs in conjunction with the non-classical pioneer TF PU.1.

Elucidation of de novo small insertion/deletion biology with parent-of-origin phasing

The mechanisms underlying de novo insertion/deletion (indel) genesis, such as polymerase slippage, have been hypothesized but not well characterized in the human genome. We implemented two methodological improvements, which were leveraged to dissect indel mutagenesis. We assigned de novo variants to parent-of-origin (i.e., phasing) with low-coverage long-read whole-genome sequencing, achieving better phasing compared to short-read sequencing (medians of 84% and 23%, respectively). We then wrote an application programming interface to classify indels into three subtypes according to sequence context. Across three cohorts with different phasing methods (N_trios  = 540, all cohorts), we observed that one de novo indel subtype, change in copy count (CCC), was significantly correlated with father's (p = 7.1 × 10^-4 ) but not mother's (p = .45) age at conception. We replicated this effect in three cohorts without de novo phasing (p_paternal  = 1.9 × 10^-9 , p_maternal  = .61; N_trios  = 3,391, all cohorts). Although this is consistent with polymerase slippage during spermatogenesis, the percentage of variance explained by paternal age was low, and we did not observe an association with replication timing. These results suggest that spermatogenesis-specific events have a minor role in CCC indel mutagenesis, one not observed for other indel subtypes nor for maternal age in general. These results have implications for indel modeling in evolution and disease.

Whole genome DNA sequencing provides an atlas of somatic mutagenesis in healthy human cells and identifies a tumor-prone cell type

BACKGROUND

The lifelong accumulation of somatic mutations underlies age-related phenotypes and cancer. Mutagenic forces are thought to shape the genome of aging cells in a tissue-specific way. Whole genome analyses of somatic mutation patterns, based on both types and genomic distribution of variants, can shed light on specific processes active in different human tissues and their effect on the transition to cancer.

RESULTS

To analyze somatic mutation patterns, we compile a comprehensive genetic atlas of somatic mutations in healthy human cells. High-confidence variants are obtained from newly generated and publicly available whole genome DNA sequencing data from single non-cancer cells, clonally expanded in vitro. To enable a well-controlled comparison of different cell types, we obtain single genome data (92% mean coverage) from multi-organ biopsies from the same donors. These data show multiple cell types that are protected from mutagens and display a stereotyped mutation profile, despite their origin from different tissues. Conversely, the same tissue harbors cells with distinct mutation profiles associated to different differentiation states. Analyses of mutation rate in the coding and non-coding portions of the genome identify a cell type bearing a unique mutation pattern characterized by mutation enrichment in active chromatin, regulatory, and transcribed regions.

CONCLUSIONS

Our analysis of normal cells from healthy donors identifies a somatic mutation landscape that enhances the risk of tumor transformation in a specific cell population from the kidney proximal tubule. This unique pattern is characterized by high rate of mutation accumulation during adult life and specific targeting of expressed genes and regulatory regions.

Prospective clinical evaluation of Momguard non-invasive prenatal test in 1011 Korean high-risk pregnant women

Clinical performance of the Momguard non-invasive prenatal test (NIPT) was evaluated in a cohort of Korean pregnant women. The foetal trisomies 21, 18 and 13 (T21, T18 and T13) were screened by low-coverage massive parallel sequencing in the maternal blood. Among the 1011 confirmed samples, 32 cases (3.2%) had positive NIPT results. Of these positive cases, 20 cases of T21, all cases of T18 and two cases of T13 had concordant karyotype findings. Only one case out of the remaining 979 negative NIPT samples showed a false negative result. The overall sensitivity and specificity of Momguard to detect the three chromosomal aneuploidies were 96.8% and 99.8%, respectively. Momguard is a clinically useful tool for the detection of T21, T18 and T13 in singleton pregnancy. However, as other NIPT tests, it carries the risk of false positive and false negative results. Hence, the genetic counsellors should provide these limitations to the examinees.Impact StatementWhat is already known on this subject? The NIPT approach using massive parallel sequencing (MPS) showed high sensitivity and specificity in various clinical studies. These results are based on analysis systems using their own bioinformatics algorithms.What the results of this study add? When this NIPT technology was introduced in Korea, the first biological specimens collected in Korea were transported overseas for processing in overseas laboratories and analysed by other country's analysis methods. We needed our own NIPT algorithm and developed Momguard NIPT for the first time in Korea. This study attempted to evaluate this Momguard NIPT protocol prospectively in a large number of samples obtained from three Korean hospitals.What the implications are of these findings for clinical practice and/or further research? The overall sensitivity and specificity to identify T13, T18 and T21 were 96.8% and 99.8%, respectively. These accuracy values were comparable to that of other studies. From this study, we found that Momguard is a clinically useful tool for the detection of three chromosomal aneuploidies. However, as other NIPT tests, it carries the risk of false positive and false negative results. Hence, the genetic counsellors should provide these limitations to the examinees.

Reliability of Whole-Exome Sequencing for Assessing Intratumor Genetic Heterogeneity

Multi-region sequencing is used to detect intratumor genetic heterogeneity (ITGH) in tumors. To assess whether genuine ITGH can be distinguished from sequencing artifacts, we performed whole-exome sequencing (WES) on three anatomically distinct regions of the same tumor with technical replicates to estimate technical noise. Somatic variants were detected with three different WES pipelines and subsequently validated by high-depth amplicon sequencing. The cancer-only pipeline was unreliable, with about 69% of the identified somatic variants being false positive. Even with matched normal DNA for which 82% of the somatic variants were detected reliably, only 36%-78% were found consistently in technical replicate pairs. Overall, 34%-80% of the discordant somatic variants, which could be interpreted as ITGH, were found to constitute technical noise. Excluding mutations affecting low-mappability regions or occurring in certain mutational contexts was found to reduce artifacts, yet detection of subclonal mutations by WES in the absence of orthogonal validation remains unreliable.

Identification of African-Specific Admixture between Modern and Archaic Humans

Recent work has demonstrated that two archaic human groups (Neanderthals and Denisovans) interbred with modern humans and contributed to the contemporary human gene pool. These findings relied on the availability of high-coverage genomes from both Neanderthals and Denisovans. Here we search for evidence of archaic admixture from a worldwide panel of 1,667 individuals using an approach that does not require the presence of an archaic human reference genome. We find no evidence for archaic admixture in the Andaman Islands, as previously claimed, or on the island of Flores, where Homo floresiensis fossils have been found. However, we do find evidence for at least one archaic admixture event in sub-Saharan Africa, with the strongest signal in Khoesan and Pygmy individuals from Southern and Central Africa. The locations of these putative archaic admixture tracts are weighted against functional regions of the genome, consistent with the long-term effects of purifying selection against introgressed genetic material.

Physical and functional interaction between SET1/COMPASS complex component CFP-1 and a Sin3S HDAC complex in C. elegans

The CFP1 CXXC zinc finger protein targets the SET1/COMPASS complex to non-methylated CpG rich promoters to implement tri-methylation of histone H3 Lys4 (H3K4me3). Although H3K4me3 is widely associated with gene expression, the effects of CFP1 loss vary, suggesting additional chromatin factors contribute to context dependent effects. Using a proteomics approach, we identified CFP1 associated proteins and an unexpected direct link between Caenorhabditis elegans CFP-1 and an Rpd3/Sin3 small (SIN3S) histone deacetylase complex. Supporting a functional connection, we find that mutants of COMPASS and SIN3 complex components genetically interact and have similar phenotypic defects including misregulation of common genes. CFP-1 directly binds SIN-3 through a region including the conserved PAH1 domain and recruits SIN-3 and the HDA-1/HDAC subunit to H3K4me3 enriched promoters. Our results reveal a novel role for CFP-1 in mediating interaction between SET1/COMPASS and a Sin3S HDAC complex at promoters.

Allele frequency-free inference of close familial relationships from genotypes or low-depth sequencing data

Knowledge of how individuals are related is important in many areas of research, and numerous methods for inferring pairwise relatedness from genetic data have been developed. However, the majority of these methods were not developed for situations where data are limited. Specifically, most methods rely on the availability of population allele frequencies, the relative genomic position of variants and accurate genotype data. But in studies of non‐model organisms or ancient samples, such data are not always available. Motivated by this, we present a new method for pairwise relatedness inference, which requires neither allele frequency information nor information on genomic position. Furthermore, it can be applied not only to accurate genotype data but also to low‐depth sequencing data from which genotypes cannot be accurately called. We evaluate it using data from a range of human populations and show that it can be used to infer close familial relationships with a similar accuracy as a widely used method that relies on population allele frequencies. Additionally, we show that our method is robust to SNP ascertainment and applicable to low‐depth sequencing data generated using different strategies, including resequencing and RADseq, which is important for application to a diverse range of populations and species.

Recent Advances in Machine Learning Based Prediction of RNA-protein Interactions

The interactions between RNAs and proteins play critical roles in many biological processes. Therefore, characterizing these interactions becomes critical for mechanistic, biomedical, and clinical studies. Many experimental methods can be used to determine RNA-protein interactions in multiple aspects. However, due to the facts that RNA-protein interactions are tissuespecific and condition-specific, as well as these interactions are weak and frequently compete with each other, those experimental techniques can not be made full use of to discover the complete spectrum of RNA-protein interactions. To moderate these issues, continuous efforts have been devoted to developing high quality computational techniques to study the interactions between RNAs and proteins. Many important progresses have been achieved with the application of novel techniques and strategies, such as machine learning techniques. Especially, with the development and application of CLIP techniques, more and more experimental data on RNA-protein interaction under specific biological conditions are available. These CLIP data altogether provide a rich source for developing advanced machine learning predictors. In this review, recent progresses on computational predictors for RNA-protein interaction were summarized in the following aspects: dataset, prediction strategies, and input features. Possible future developments were also discussed at the end of the review.

Passenger Hotspot Mutations in Cancer

Current statistical models for assessing hotspot significance do not properly account for variation in site-specific mutability, thereby yielding many false-positives. We thus (i) detail a Log-normal-Poisson (LNP) background model that accounts for this variability in a manner consistent with models of mutagenesis; (ii) use it to show that passenger hotspots arise from all common mutational processes; and (iii) apply it to a ∼10,000-patient cohort to nominate driver hotspots with far fewer false-positives compared with conventional methods. Overall, we show that many cancer hotspot mutations recurring at the same genomic site across multiple tumors are actually passenger events, recurring at inherently mutable genomic sites under no positive selection.

Clinical sequencing: From raw data to diagnosis with lifetime value

High-throughput sequencing (HTS) has revolutionized genetics by enabling the detection of sequence variants at hitherto unprecedented large scale. Despite these advances, however, there are still remaining challenges in the complete coverage of targeted regions (genes, exome or genome) as well as in HTS data analysis and interpretation. Moreover, it is easy to get overwhelmed by the plethora of available methods and tools for HTS. Here, we review the step-by-step process from the generation of sequence data to molecular diagnosis of Mendelian diseases. Highlighting advantages and limitations, this review addresses the current state of (1) HTS technologies, considering targeted, whole-exome, and whole-genome sequencing on short- and long-read platforms; (2) read alignment, variant calling and interpretation; as well as (3) regulatory issues related to genetic counseling, reimbursement, and data storage.

Meiotic sex in Chagas disease parasite Trypanosoma cruzi

Genetic exchange enables parasites to rapidly transform disease phenotypes and exploit new host populations. Trypanosoma cruzi, the parasitic agent of Chagas disease and a public health concern throughout Latin America, has for decades been presumed to exchange genetic material rarely and without classic meiotic sex. We present compelling evidence from 45 genomes sequenced from southern Ecuador that T. cruzi in fact maintains truly sexual, panmictic groups that can occur alongside others that remain highly clonal after past hybridization events. These groups with divergent reproductive strategies appear genetically isolated despite possible co-occurrence in vectors and hosts. We propose biological explanations for the fine-scale disconnectivity we observe and discuss the epidemiological consequences of flexible reproductive modes. Our study reinvigorates the hunt for the site of genetic exchange in the T. cruzi life cycle, provides tools to define the genetic determinants of parasite virulence, and reforms longstanding theory on clonality in trypanosomatid parasites.

Dosage regulation, and variation in gene expression and copy number of human Y chromosome ampliconic genes

The Y chromosome harbors nine multi-copy ampliconic gene families expressed exclusively in testis. The gene copies within each family are >99% identical to each other, which poses a major challenge in evaluating their copy number. Recent studies demonstrated high variation in Y ampliconic gene copy number among humans. However, how this variation affects expression levels in human testis remains understudied. Here we developed a novel computational tool Ampliconic Copy Number Estimator (AmpliCoNE) that utilizes read sequencing depth information to estimate Y ampliconic gene copy number per family. We applied this tool to whole-genome sequencing data of 149 men with matched testis expression data whose samples are part of the Genotype-Tissue Expression (GTEx) project. We found that the Y ampliconic gene families with low copy number in humans were deleted or pseudogenized in non-human great apes, suggesting relaxation of functional constraints. Among the Y ampliconic gene families, higher copy number leads to higher expression. Within the Y ampliconic gene families, copy number does not influence gene expression, rather a high tolerance for variation in gene expression was observed in testis of presumably healthy men. No differences in gene expression levels were found among major Y haplogroups. Age positively correlated with expression levels of the HSFY and PRY gene families in the African subhaplogroup E1b, but not in the European subhaplogroups R1b and I1. We also found that expression of five Y ampliconic gene families is coordinated with that of their non-Y (i.e. X or autosomal) homologs. Indeed, five ampliconic gene families had consistently lower expression levels when compared to their non-Y homologs suggesting dosage regulation, while the HSFY family had higher expression levels than its X homolog and thus lacked dosage regulation.

A model of pulldown alignments from SssI-treated DNA improves DNA methylation prediction

Background

Protein pulldown using Methyl-CpG binding domain (MBD) proteins followed by high-throughput sequencing is a common method to determine DNA methylation. Algorithms have been developed to estimate absolute methylation level from read coverage generated by affinity enrichment-based techniques, but the most accurate one for MBD-seq data requires additional data from an SssI-treated Control experiment.

Results

Using our previous characterizations of Methyl-CpG/MBD2 binding in the context of an MBD pulldown experiment, we build a model of expected MBD pulldown reads as drawn from SssI-treated DNA. We use the program BayMeth to evaluate the effectiveness of this model by substituting calculated SssI Control data for the observed SssI Control data. By comparing methylation predictions against those from an RRBS data set, we find that BayMeth run with our modeled SssI Control data performs better than BayMeth run with observed SssI Control data, on both 100 bp and 10 bp windows. Adapting the model to an external data set solely by changing the average fragment length, our calculated data still informs the BayMeth program to a similar level as observed data in predicting methylation state on a pulldown data set with matching WGBS estimates.

Conclusion

In both internal and external MBD pulldown data sets tested in this study, BayMeth used with our modeled pulldown coverage performs better than BayMeth run without the inclusion of any estimate of SssI Control pulldown, and is comparable to – and in some cases better than – using observed SssI Control data with the BayMeth program. Thus, our MBD pulldown alignment model can improve methylation predictions without the need to perform additional control experiments.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-3011-2) contains supplementary material, which is available to authorized users.

An Accurate and Comprehensive Clinical Sequencing Assay for Cancer Targeted and Immunotherapies

BACKGROUND

Incorporation of next-generation sequencing (NGS) technology into clinical utility in targeted and immunotherapies requires stringent validation, including the assessment of tumor mutational burden (TMB) and microsatellite instability (MSI) status by NGS as important biomarkers for response to immune checkpoint inhibitors.

MATERIALS AND METHODS

We designed an NGS assay, Cancer Sequencing YS panel (CSYS), and applied algorithms to detect five classes of genomic alterations and two genomic features of TMB and MSI.

RESULTS

By stringent validation, CSYS exhibited high sensitivity and predictive positive value of 99.7% and 99.9%, respectively, for single nucleotide variation; 100% and 99.9%, respectively, for short insertion and deletion (indel); and 95.5% and 100%, respectively, for copy number alteration (CNA). Moreover, CSYS achieved 100% specificity for both long indel (50-3,000 bp insertion and deletion) and gene rearrangement. Overall, we used 33 cell lines and 208 clinical samples to validate CSYS's NGS performance, and genomic alterations in clinical samples were also confirmed by fluorescence in situ hybridization, immunohistochemistry, and polymerase chain reaction (PCR). Importantly, the landscape of TMB across different cancers of Chinese patients (n = 3,309) was studied. TMB by CSYS exhibited a high correlation (Pearson correlation coefficient r = 0.98) with TMB by whole exome sequencing (WES). MSI measurement showed 98% accuracy and was confirmed by PCR. Application of CSYS in a clinical setting showed an unexpectedly high occurrence of long indel (6.3%) in a cohort of tumors from Chinese patients with cancer (n = 3,309), including TP53, RB1, FLT3, BRCA2, and other cancer driver genes with clinical impact.

CONCLUSION

CSYS proves to be clinically applicable and useful in disclosing genomic alterations relevant to cancer target therapies and revealing biomarkers for immune checkpoint inhibitors.

IMPLICATIONS FOR PRACTICE

The study describes a specially designed sequencing panel assay to detect genomic alterations and features of 450 cancer genes, including its overall workflow and rigorous clinical and analytical validations. The distribution of pan-cancer tumor mutational burden, microsatellite instability, gene rearrangement, and long insertion and deletion mutations was assessed for the first time by this assay in a broad array of Chinese patients with cancer. The Cancer Sequencing YS panel and its validation study could serve as a blueprint for developing next-generation sequencing-based assays, particularly for the purpose of clinical application.

Maintenance of High Genome Integrity over Vegetative Growth in the Fairy-Ring Mushroom Marasmius oreades

Most mutations in coding regions of the genome are deleterious, causing selection to favor mechanisms that minimize the mutational load over time [1-5]. DNA replication during cell division is a major source of new mutations. It is therefore important to limit the number of cell divisions between generations, particularly for large and long-lived organisms [6-9]. The germline cells of animals and the slowly dividing cells in plant meristems are adaptations to control the number of mutations that accumulate over generations [9-11]. Fungi lack a separated germline while harboring species with very large and long-lived individuals that appear to maintain highly stable genomes within their mycelia [8, 12, 13]. Here, we studied genomic mutation accumulation in the fairy-ring mushroom Marasmius oreades. We generated a chromosome-level genome assembly using a combination of cutting-edge DNA sequencing technologies and re-sequenced 40 samples originating from six individuals of this fungus. The low number of mutations recovered in the sequencing data suggests the presence of an unknown mechanism that works to maintain extraordinary genome integrity over vegetative growth in M. oreades. The highly structured growth pattern of M. oreades allowed us to estimate the number of cell divisions leading up to each sample [14, 15], and from this data, we infer an incredibly low per mitosis mutation rate (3.8 × 10^-12 mutations per site and cell division) as one of several possible explanations for the low number of identified mutations.

Mutational processes contributing to the development of multiple myeloma

To gain insight into multiple myeloma (MM) tumorigenesis, we analyzed the mutational signatures in 874 whole-exome and 850 whole-genome data from the CoMMpass Study. We identified that coding and non-coding regions are differentially dominated by distinct single-nucleotide variant (SNV) mutational signatures, as well as five de novo structural rearrangement signatures. Mutational signatures reflective of different principle mutational processes—aging, defective DNA repair, and apolipoprotein B editing complex (APOBEC)/activation-induced deaminase activity—characterize MM. These mutational signatures show evidence of subgroup specificity—APOBEC-attributed signatures associated with MAF translocation t(14;16) and t(14;20) MM; potentially DNA repair deficiency with t(11;14) and t(4;14); and aging with hyperdiploidy. Mutational signatures beyond that associated with APOBEC are independent of established prognostic markers and appear to have relevance to predicting high-risk MM.

Recurrent miscalling of missense variation from short-read genome sequence data

Background

Short-read resequencing of genomes produces abundant information of the genetic variation of individuals. Due to their numerous nature, these variants are rarely exhaustively validated. Furthermore, low levels of undetected variant miscalling will have a systematic and disproportionate impact on the interpretation of individual genome sequence information, especially should these also be carried through into in reference databases of genomic variation.

Results

We find that sequence variation from short-read sequence data is subject to recurrent-yet-intermittent miscalling that occurs in a sequence intrinsic manner and is very sensitive to sequence read length. The miscalls arise from difficulties aligning short reads to redundant genomic regions, where the rate of sequencing error approaches the sequence diversity between redundant regions. We find the resultant miscalled variants to be sensitive to small sequence variations between genomes, and thereby are often intrinsic to an individual, pedigree, strain or human ethnic group. In human exome sequences, we identify 2–300 recurrent false positive variants per individual, almost all of which are present in public databases of human genomic variation. From the exomes of non-reference strains of inbred mice, we identify 3–5000 recurrent false positive variants per mouse – the number of which increasing with greater distance between an individual mouse strain and the reference C57BL6 mouse genome. We show that recurrently miscalled variants may be reproduced for a given genome from repeated simulation rounds of read resampling, realignment and recalling. As such, it is possible to identify more than two-thirds of false positive variation from only ten rounds of simulation.

Conclusion

Identification and removal of recurrent false positive variants from specific individual variant sets will improve overall data quality. Variant miscalls arising are highly sequence intrinsic and are often specific to an individual, pedigree or ethnicity. Further, read length is a strong determinant of whether given false variants will be called for any given genome – which has profound significance for cohort studies that pool datasets collected and sequenced at different points in time.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5863-2) contains supplementary material, which is available to authorized users.

Paired-end mappability of transposable elements in the human genome

Though transposable elements make up around half of the human genome, the repetitive nature of their sequences makes it difficult to accurately align conventional sequencing reads. However, in light of new advances in sequencing technology, such as increased read length and paired-end libraries, these repetitive regions are now becoming easier to align to. This study investigates the mappability of transposable elements with 50 bp, 76 bp and 100 bp paired-end read libraries. With respect to those read lengths and allowing for 3 mismatches during alignment, over 68, 85, and 88% of all transposable elements in the RepeatMasker database are uniquely mappable, suggesting that accurate locus-specific mapping of older transposable elements is well within reach.

Misidentification of MLL3 and other mutations in cancer due to highly homologous genomic regions

The MLL3 gene has been shown to be recurrently mutated in many malignancies including in families with acute myeloid leukemia. We demonstrate that many MLL3 variant calls made by exome sequencing are false positives due to misalignment to homologous regions, including a region on chr21, and can only be validated by long-range PCR. Numerous other recurrently mutated genes reported in COSMIC and TCGA databases have pseudogenes and cannot also be validated by conventional short read-based sequencing approaches. Genome-wide identification of pseudogene regions demonstrates that frequency of these homologous regions is increased with sequencing read lengths below 200 bps. To enable identification of poor quality sequencing variants in prospective studies, we generated novel genome-wide maps of regions with poor mappability that can be used in variant calling algorithms. Taken together, our findings reveal that pseudogene regions are a source of false-positive mutations in cancers.

Umap and Bismap: quantifying genome and methylome mappability

Short-read sequencing enables assessment of genetic and biochemical traits of individual genomic regions, such as the location of genetic variation, protein binding and chemical modifications. Every region in a genome assembly has a property called 'mappability', which measures the extent to which it can be uniquely mapped by sequence reads. In regions of lower mappability, estimates of genomic and epigenomic characteristics from sequencing assays are less reliable. These regions have increased susceptibility to spurious mapping from reads from other regions of the genome with sequencing errors or unexpected genetic variation. Bisulfite sequencing approaches used to identify DNA methylation exacerbate these problems by introducing large numbers of reads that map to multiple regions. Both to correct assumptions of uniformity in downstream analysis and to identify regions where the analysis is less reliable, it is necessary to know the mappability of both ordinary and bisulfite-converted genomes. We introduce the Umap software for identifying uniquely mappable regions of any genome. Its Bismap extension identifies mappability of the bisulfite-converted genome. A Umap and Bismap track hub for human genome assemblies GRCh37/hg19 and GRCh38/hg38, and mouse assemblies GRCm37/mm9 and GRCm38/mm10 is available at https://bismap.hoffmanlab.org for use with genome browsers.

High-Resolution Copy Number Patterns From Clinically Relevant FFPE Material

Systematic tumour profiling is essential for biomarker research and clinically for assessing response to therapy. Solving the challenge of delivering informative copy number (CN) profiles from formalin-fixed paraffin embedded (FFPE) material, the only likely readily available biospecimen for most cancers, involves successful processing of small quantities of degraded DNA. To investigate the potential for analysis of such lesions, whole-genome CNVseq was applied to 300 FFPE primary tumour samples, obtained from a large-scale epidemiological study of melanoma. The quality and the discriminatory power of CNVseq was assessed. Libraries were successfully generated for 93% of blocks, with input DNA quantity being the only predictor of success (success rate dropped to 65% if <20 ng available); 3% of libraries were dropped because of low sequence alignment rates. Technical replicates showed high reproducibility. Comparison with targeted CN assessment showed consistency with the Next Generation Sequencing (NGS) analysis. We were able to detect and distinguish CN changes with a resolution of ≤10 kb. To demonstrate performance, we report the spectrum of genomic CN alterations (CNAs) detected at 9p21, the major site of CN change in melanoma. This successful analysis of CN in FFPE material using NGS provides proof of principle for intensive examination of population-based samples.

piRNA-guided co-transcriptional silencing coopts nuclear export factors

The PIWI-interacting RNA (piRNA) pathway is a small RNA-based immune system that controls the expression of transposons and maintains genome integrity in animal gonads. In Drosophila, piRNA-guided silencing is achieved, in part, via co-transcriptional repression of transposons by Piwi. This depends on Panoramix (Panx); however, precisely how an RNA binding event silences transcription remains to be determined. Here we show that Nuclear Export Factor 2 (Nxf2) and its co-factor, Nxt1, form a complex with Panx and are required for co-transcriptional silencing of transposons in somatic and germline cells of the ovary. Tethering of Nxf2 or Nxt1 to RNA results in silencing of target loci and the concomitant accumulation of repressive chromatin marks. Nxf2 and Panx proteins are mutually required for proper localization and stability. We mapped the protein domains crucial for the Nxf2/Panx complex formation and show that the amino-terminal portion of Panx is sufficient to induce transcriptional silencing.

Bioinformatics Analysis for Circulating Cell-Free DNA in Cancer

Molecular analysis of cell-free DNA (cfDNA) that circulates in plasma and other body fluids represents a "liquid biopsy" approach for non-invasive cancer screening or monitoring. The rapid development of sequencing technologies has made cfDNA a promising source to study cancer development and progression. Specific genetic and epigenetic alterations have been found in plasma, serum, and urine cfDNA and could potentially be used as diagnostic or prognostic biomarkers in various cancer types. In this review, we will discuss the molecular characteristics of cancer cfDNA and major bioinformatics approaches involved in the analysis of cfDNA sequencing data for detecting genetic mutation, copy number alteration, methylation change, and nucleosome positioning variation. We highlight specific challenges in sensitivity to detect genetic aberrations and robustness of statistical analysis. Finally, we provide perspectives regarding the standard and continuing development of bioinformatics analysis to move this promising screening tool into clinical practice.

A machine-learning approach for accurate detection of copy number variants from exome sequencing

Copy number variants (CNVs) are a major cause of several genetic disorders, making their detection an essential component of genetic analysis pipelines. Current methods for detecting CNVs from exome-sequencing data are limited by high false-positive rates and low concordance because of inherent biases of individual algorithms. To overcome these issues, calls generated by two or more algorithms are often intersected using Venn diagram approaches to identify "high-confidence" CNVs. However, this approach is inadequate, because it misses potentially true calls that do not have consensus from multiple callers. Here, we present CN-Learn, a machine-learning framework that integrates calls from multiple CNV detection algorithms and learns to accurately identify true CNVs using caller-specific and genomic features from a small subset of validated CNVs. Using CNVs predicted by four exome-based CNV callers (CANOES, CODEX, XHMM, and CLAMMS) from 503 samples, we demonstrate that CN-Learn identifies true CNVs at higher precision (∼90%) and recall (∼85%) rates while maintaining robust performance even when trained with minimal data (∼30 samples). CN-Learn recovers twice as many CNVs compared to individual callers or Venn diagram-based approaches, with features such as exome capture probe count, caller concordance, and GC content providing the most discriminatory power. In fact, ∼58% of all true CNVs recovered by CN-Learn were either singletons or calls that lacked support from at least one caller. Our study underscores the limitations of current approaches for CNV identification and provides an effective method that yields high-quality CNVs for application in clinical diagnostics.

Quantification of experimentally induced nucleotide conversions in high-throughput sequencing datasets

Background

Methods to read out naturally occurring or experimentally introduced nucleic acid modifications are emerging as powerful tools to study dynamic cellular processes. The recovery, quantification and interpretation of such events in high-throughput sequencing datasets demands specialized bioinformatics approaches.

Results

Here, we present Digital Unmasking of Nucleotide conversions in K-mers (DUNK), a data analysis pipeline enabling the quantification of nucleotide conversions in high-throughput sequencing datasets. We demonstrate using experimentally generated and simulated datasets that DUNK allows constant mapping rates irrespective of nucleotide-conversion rates, promotes the recovery of multimapping reads and employs Single Nucleotide Polymorphism (SNP) masking to uncouple true SNPs from nucleotide conversions to facilitate a robust and sensitive quantification of nucleotide-conversions. As a first application, we implement this strategy as SLAM-DUNK for the analysis of SLAMseq profiles, in which 4-thiouridine-labeled transcripts are detected based on T > C conversions. SLAM-DUNK provides both raw counts of nucleotide-conversion containing reads as well as a base-content and read coverage normalized approach for estimating the fractions of labeled transcripts as readout.

Conclusion

Beyond providing a readily accessible tool for analyzing SLAMseq and related time-resolved RNA sequencing methods (TimeLapse-seq, TUC-seq), DUNK establishes a broadly applicable strategy for quantifying nucleotide conversions.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2849-7) contains supplementary material, which is available to authorized users.

Mutations in TIMM50 cause severe mitochondrial dysfunction by targeting key aspects of mitochondrial physiology

3-Methylglutaconic aciduria (3-MGA-uria) syndromes comprise a heterogeneous group of diseases associated with mitochondrial membrane defects. Whole-exome sequencing identified compound heterozygous mutations in TIMM50 (c.[341 G>A];[805 G>A]) in a boy with West syndrome, optic atrophy, neutropenia, cardiomyopathy, Leigh syndrome, and persistent 3-MGA-uria. A comprehensive analysis of the mitochondrial function was performed in fibroblasts of the patient to elucidate the molecular basis of the disease. TIMM50 protein was severely reduced in the patient fibroblasts, regardless of the normal mRNA levels, suggesting that the mutated residues might be important for TIMM50 protein stability. Severe morphological defects and ultrastructural abnormalities with aberrant mitochondrial cristae organization in muscle and fibroblasts were found. The levels of fully assembled OXPHOS complexes and supercomplexes were strongly reduced in fibroblasts from this patient. High-resolution respirometry demonstrated a significant reduction of the maximum respiratory capacity. A TIMM50-deficient HEK293T cell line that we generated using CRISPR/Cas9 mimicked the respiratory defect observed in the patient fibroblasts; notably, this defect was rescued by transfection with a plasmid encoding the TIMM50 wild-type protein. In summary, we demonstrated that TIMM50 deficiency causes a severe mitochondrial dysfunction by targeting key aspects of mitochondrial physiology, such as the maintenance of proper mitochondrial morphology, OXPHOS assembly, and mitochondrial respiratory capacity.

Adaptation and Phenotypic Diversification in Arabidopsis through Loss-of-Function Mutations in Protein-Coding Genes

According to the less-is-more hypothesis, gene loss is an engine for evolutionary change. Loss-of-function (LoF) mutations resulting in the natural knockout of protein-coding genes not only provide information about gene function but also play important roles in adaptation and phenotypic diversification. Although the less-is-more hypothesis was proposed two decades ago, it remains to be explored on a large scale. In this study, we identified 60,819 LoF variants in 1071 Arabidopsis (Arabidopsis thaliana) genomes and found that 34% of Arabidopsis protein-coding genes annotated in the Columbia-0 genome do not have any LoF variants. We found that nucleotide diversity, transposable element density, and gene family size are strongly correlated with the presence of LoF variants. Intriguingly, 0.9% of LoF variants with minor allele frequency larger than 0.5% are associated with climate change. In addition, in the Yangtze River basin population, 1% of genes with LoF mutations were under positive selection, providing important insights into the contribution of LoF mutations to adaptation. In particular, our results demonstrate that LoF mutations shape diverse phenotypic traits. Overall, our results highlight the importance of the LoF variants for the adaptation and phenotypic diversification of plants.

Passenger mutations accurately classify human tumors

Determining the cancer type and molecular subtype has important clinical implications. The primary site is however unknown for some malignancies discovered in the metastatic stage. Moreover liquid biopsies may be used to screen for tumoral DNA, which upon detection needs to be assigned to a site-of-origin. Classifiers based on genomic features are a promising approach to prioritize the tumor anatomical site, type and subtype. We examined the predictive ability of causal (driver) somatic mutations in this task, comparing it against global patterns of non-selected (passenger) mutations, including features based on regional mutation density (RMD). In the task of distinguishing 18 cancer types, the driver mutations–mutated oncogenes or tumor suppressors, pathways and hotspots–classified 36% of the patients to the correct cancer type. In contrast, the features based on passenger mutations did so at 92% accuracy, with similar contribution from the RMD and the trinucleotide mutation spectra. The RMD and the spectra covered distinct sets of patients with predictions. In particular, introducing the RMD features into a combined classification model increased the fraction of diagnosed patients by 50 percentage points (at 20% FDR). Furthermore, RMD was able to discriminate molecular subtypes and/or anatomical site of six major cancers. The advantage of passenger mutations was upheld under high rates of false negative mutation calls and with exome sequencing, even though overall accuracy decreased. We suggest whole genome sequencing is valuable for classifying tumors because it captures global patterns emanating from mutational processes, which are informative of the underlying tumor biology.

Mutations accumulate throughout the lifetime of human somatic cells. While some may affect oncogenes or tumor suppressor genes and cause tumors–the ‘driver’ mutations–most are thought to be of no consequence. The density of such ‘passenger’ mutations across the human chromosomes is very uneven and is correlated with replication time and gene expression in the cell type the tumor had originated from. This property can be used to classify a tumor, assigning it to a tissue of origin and also the molecular subtype. This is useful in cases of those metastatic cancers where the location of the primary tumor is unknown and is also of interest for the upcoming ‘liquid biopsy’ diagnostic approaches, where DNA is directly sequenced from bodily fluids to detect the presence of a cancer. The ability to type and subtype tumors is important to guide more detailed diagnostics and therapy, because the organ and the cell type which generated the tumor determines response to a variety of therapies, including targeted drugs.