Characterization of telomere variant repeats using long reads enables allele-specific telomere length estimation.

Telomeres are regions of repetitive DNA at the ends of linear chromosomes which protect chromosome ends from degradation. Telomere lengths have been extensively studied in the context of aging and disease, though most studies use average telomere lengths which are of limited utility. We present a method for identifying all 92 telomere alleles from long read sequencing data. Individual telomeres are identified using variant repeats proximal to telomere regions, which are unique across alleles. This high-throughput and high-resolution characterization of telomeres could be foundational to future studies investigating the roles of specific telomeres in aging and disease.

Experimental and Computational Approaches to Measure Telomere Length: Recent Advances and Future Directions.

PURPOSE OF REVIEW: The length of telomeres, protective structures at the chromosome ends, is a well-established biomarker for pathological conditions including multisystemic syndromes called telomere biology disorders. Approaches to measure telomere length (TL) differ on whether they estimate average, distribution, or chromosome-specific TL, and each presents their own advantages and limitations. RECENT FINDINGS: The development of long-read sequencing and publication of the telomere-to-telomere human genome reference has allowed for scalable and high-resolution TL estimation in pre-existing sequencing datasets but is still impractical as a dedicated TL test. As sequencing costs continue to fall and strategies for selectively enriching telomere regions prior to sequencing improve, these approaches may become a promising alternative to classic methods. Measurement methods rely on probe hybridization, qPCR or more recently, computational methods using sequencing data. Refinements of existing techniques and new approaches have been recently developed but a test that is accurate, simple, and scalable is still lacking.

Activation of homology-directed DNA repair plays key role in CRISPR-mediated genome correction.

Gene editing for the cure of inborn errors of metabolism (IEMs) has been limited by inefficiency of adult hepatocyte targeting. Here, we demonstrate that in utero CRISPR/Cas9-mediated gene editing in a mouse model of hereditary tyrosinemia type 1 provides stable cure of the disease. Following this, we performed an extensive gene expression analysis to explore the inherent characteristics of fetal/neonatal hepatocytes that make them more susceptible to efficient gene editing than adult hepatocytes. We showed that fetal and neonatal livers are comprised of proliferative hepatocytes with abundant expression of genes involved in homology-directed repair (HDR) of DNA double-strand breaks (DSBs), key for efficient gene editing by CRISPR/Cas9. We demonstrated the same is true of hepatocytes after undergoing a regenerative stimulus (partial hepatectomy), where post-hepatectomy cells show a higher efficiency of HDR and correction. Specifically, we demonstrated that HDR-related genome correction is most effective in the replicative phase, or S-phase, of an actively proliferating cell. In conclusion, this study shows that taking advantage of or triggering cell proliferation, specifically DNA replication in S-phase, may serve as an important tool to improve efficiency of CRISPR/Cas9-mediated genome editing in the liver and provide a curative therapy for IEMs in both children and adults.

CRISPR/Cas9-mediated excision of ALS/FTD-causing hexanucleotide repeat expansion in C9ORF72 rescues major disease mechanisms in vivo and in vitro.

A GGGGCC24+ hexanucleotide repeat expansion (HRE) in the C9ORF72 gene is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), fatal neurodegenerative diseases with no cure or approved treatments that substantially slow disease progression or extend survival. Mechanistic underpinnings of neuronal death include C9ORF72 haploinsufficiency, sequestration of RNA-binding proteins in the nucleus, and production of dipeptide repeat proteins. Here, we used an adeno-associated viral vector system to deliver CRISPR/Cas9 gene-editing machineries to effectuate the removal of the HRE from the C9ORF72 genomic locus. We demonstrate successful excision of the HRE in primary cortical neurons and brains of three mouse models containing the expansion (500-600 repeats) as well as in patient-derived iPSC motor neurons and brain organoids (450 repeats). This resulted in a reduction of RNA foci, poly-dipeptides and haploinsufficiency, major hallmarks of C9-ALS/FTD, making this a promising therapeutic approach to these diseases.

In vivo lentiviral vector gene therapy to cure hereditary tyrosinemia type 1 and prevent development of precancerous and cancerous lesions.

Conventional therapy for hereditary tyrosinemia type-1 (HT1) with 2-(2-nitro-4-trifluoromethylbenzoyl)-1,3-cyclohexanedione (NTBC) delays and in some cases fails to prevent disease progression to liver fibrosis, liver failure, and activation of tumorigenic pathways. Here we demonstrate cure of HT1 by direct, in vivo administration of a therapeutic lentiviral vector targeting the expression of a human fumarylacetoacetate hydrolase (FAH) transgene in the porcine model of HT1. This therapy is well tolerated and provides stable long-term expression of FAH in pigs with HT1. Genomic integration displays a benign profile, with subsequent fibrosis and tumorigenicity gene expression patterns similar to wild-type animals as compared to NTBC-treated or diseased untreated animals. Indeed, the phenotypic and genomic data following in vivo lentiviral vector administration demonstrate comparative superiority over other therapies including ex vivo cell therapy and therefore support clinical application of this approach.

Telogator: a method for reporting chromosome-specific telomere lengths from long reads.

MOTIVATION: Telomeres are the repetitive sequences found at the ends of eukaryotic chromosomes and are often thought of as a 'biological clock,' with their average length shortening during division in most cells. In addition to their association with senescence, abnormal telomere lengths are well known to be associated with multiple cancers, short telomere syndromes and as risk factors for a broad range of diseases. While a majority of methods for measuring telomere length will report average lengths across all chromosomes, it is known that aberrations in specific chromosome arms are biomarkers for certain diseases. Due to their repetitive nature, characterizing telomeres at this resolution is prohibitive for short read sequencing approaches, and is challenging still even with longer reads. RESULTS: We present Telogator: a method for reporting chromosome-specific telomere length from long read sequencing data. We demonstrate Telogator's sensitivity in detecting chromosome-specific telomere length in simulated data across a range of read lengths and error rates. Telogator is then applied to 10 germline samples, yielding a high correlation with short read methods in reporting average telomere length. In addition, we investigate common subtelomere rearrangements and identify the minimum read length required to anchor telomere/subtelomere boundaries in samples with these haplotypes. AVAILABILITY AND IMPLEMENTATION: Telogator is written in Python3 and is available at github.com/zstephens/telogator. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Quality Performance of a Transfer Center Reduces Interhospital Transfer and Direct Admission-Related ED Evaluations.

Transfer centers play a vital role in the efficient triage of hospital admission requests that generate outside the emergency department (ED) of the given facility. This cohort study includes all the calls processed through the transfer center requesting an admission to Mayo Clinic, Rochester, from January 2016 to December 2018. More than 116,000 transfer request calls were processed. Of these, about 65% (75,000) were accepted for ED evaluation or direct admission. Of the 75,000 patients, >50% were accepted as direct admits. Among patients accepted for direct admission, a trend toward reduced utilization of ED reevaluation at the receiving facility was noted from 2016 to 2018. A temporal trend of overall reduced ED utilization reflects the adeptness of the transfer center. An effective transfer center promotes value-based care, optimizes the workflow in a hospital, and augments hospital administrative decisions to allocate resources.

Exogene: A performant workflow for detecting viral integrations from paired-end next-generation sequencing data.

The integration of viruses into the human genome is known to be associated with tumorigenesis in many cancers, but the accurate detection of integration breakpoints from short read sequencing data is made difficult by human-viral homologies, viral genome heterogeneity, coverage limitations, and other factors. To address this, we present Exogene, a sensitive and efficient workflow for detecting viral integrations from paired-end next generation sequencing data. Exogene's read filtering and breakpoint detection strategies yield integration coordinates that are highly concordant with long read validation. We demonstrate this concordance across 6 TCGA Hepatocellular carcinoma (HCC) tumor samples, identifying integrations of hepatitis B virus that are also supported by long reads. Additionally, we applied Exogene to targeted capture data from 426 previously studied HCC samples, achieving 98.9% concordance with existing methods and identifying 238 high-confidence integrations that were not previously reported. Exogene is applicable to multiple types of paired-end sequence data, including genome, exome, RNA-Seq and targeted capture.

P2T2: Protein Panoramic annoTation Tool for the interpretation of protein coding genetic variants.

MOTIVATION: Genomic data are prevalent, leading to frequent encounters with uninterpreted variants or mutations with unknown mechanisms of effect. Researchers must manually aggregate data from multiple sources and across related proteins, mentally translating effects between the genome and proteome, to attempt to understand mechanisms. MATERIALS AND METHODS: P2T2 presents diverse data and annotation types in a unified protein-centric view, facilitating the interpretation of coding variants and hypothesis generation. Information from primary sequence, domain, motif, and structural levels are presented and also organized into the first Paralog Annotation Analysis across the human proteome. RESULTS: Our tool assists research efforts to interpret genomic variation by aggregating diverse, relevant, and proteome-wide information into a unified interactive web-based interface. Additionally, we provide a REST API enabling automated data queries, or repurposing data for other studies. CONCLUSION: The unified protein-centric interface presented in P2T2 will help researchers interpret novel variants identified through next-generation sequencing. Code and server link available at github.com/GenomicInterpretation/p2t2.

PB-Motif-A Method for Identifying Gene/Pseudogene Rearrangements With Long Reads: An Application to CYP21A2 Genotyping.

Long read sequencing technologies have the potential to accurately detect and phase variation in genomic regions that are difficult to fully characterize with conventional short read methods. These difficult to sequence regions include several clinically relevant genes with highly homologous pseudogenes, many of which are prone to gene conversions or other types of complex structural rearrangements. We present PB-Motif, a new method for identifying rearrangements between two highly homologous genomic regions using PacBio long reads. PB-Motif leverages clustering and filtering techniques to efficiently report rearrangements in the presence of sequencing errors and other systematic artifacts. Supporting reads for each high-confidence rearrangement can then be used for copy number estimation and phased variant calling. First, we demonstrate PB-Motif's accuracy with simulated sequence rearrangements of PMS2 and its pseudogene PMS2CL using simulated reads sweeping over a range of sequencing error rates. We then apply PB-Motif to 26 clinical samples, characterizing CYP21A2 and its pseudogene CYP21A1P as part of a diagnostic assay for congenital adrenal hyperplasia. We successfully identify damaging variation and patient carrier status concordant with clinical diagnosis obtained from multiplex ligation-dependent amplification (MLPA) and Sanger sequencing. The source code is available at: github.com/zstephens/pb-motif.

Re-Evaluate Fusion Genes in Prostate Cancer.

BACKGROUND: Thousands of gene fusions have been reported in prostate cancer, but their authenticity, incidence, and tumor specificity have not been thoroughly evaluated, nor have their genomic characteristics been carefully explored. METHODS: We developed FusionVet to dedicatedly validate known fusion genes using RNA-seq alignments. Using FusionVet, we re-assessed 2727 gene fusions reported from 36 studies using the RNA-seq data generated by The Cancer Genome Atlas (TCGA). We also explored their genomic characteristics and interrogated the transcriptomic and DNA methylomic consequences of the E26 transformation-specific (ETS) fusions. RESULTS: We found that nearly two-thirds of reported fusions are intra-chromosomal, and 80% of them were formed between 2 protein-coding genes. Although most (76%) genes were fused to only 1 partner, we observed many fusion hub genes that have multiple fusion partners, including ETS family genes, androgen receptor signaling pathway genes, tumor suppressor genes, and proto-oncogenes. More than 90% of the reported fusions cannot be validated by TCGA RNA-seq data. For those fusions that can be validated, 5% were detected from tumor and normal samples with similar frequencies, and only 4% (120 fusions) were tumor-specific. The occurrences of ERG, ETV1, and ETV4 fusions were mutually exclusive, and their fusion statuses were tightly associated with overexpressions. Besides, we found ERG fusions were significantly co-occurred with PTEN deletion but mutually exclusive with common genomic alterations such as SPOP mutation and FOXA1 mutation. CONCLUSIONS: Most of the reported fusion genes cannot be validated by TCGA samples. The ETS family and androgen response genes were significantly enriched in prostate cancer-specific fusion genes. Transcription activity was significantly repressed, and the DNA methylation was significantly increased in samples carrying ERG fusion.

Surface Roughness of Titanium Orthopedic Implants Alters the Biological Phenotype of Human Mesenchymal Stromal Cells.

Metal orthopedic implants are largely biocompatible and generally achieve long-term structural fixation. However, some orthopedic implants may loosen over time even in the absence of infection. In vivo fixation failure is multifactorial, but the fundamental biological defect is cellular dysfunction at the host-implant interface. Strategies to reduce the risk of short- and long-term loosening include surface modifications, implant metal alloy type, and adjuvant substances such as polymethylmethacrylate cement. Surface modifications (e.g., increased surface rugosity) can increase osseointegration and biological ingrowth of orthopedic implants. However, the localized responses of cells to implant surface modifications need to be better characterized. As an in vitro model for investigating cellular responses to metallic orthopedic implants, we cultured mesenchymal stromal/stem cells on clinical-grade titanium disks (Ti6Al4V) that differed in surface roughness as high (porous structured), medium (grit blasted), and low (bead blasted). Topological characterization of clinically relevant titanium (Ti) materials combined with differential mRNA expression analyses (RNA-seq and real-time quantitative polymerase chain reaction) revealed alterations to the biological phenotype of cells cultured on titanium structures that favor early extracellular matrix production and observable responses to oxidative stress and heavy metal stress. These results provide a descriptive model for the interpretation of cellular responses at the interface between native host tissues and three-dimensionally printed modular orthopedic implants, and will guide future studies aimed at increasing the long-term retention of such materials after total joint arthroplasty. Impact statement Using an in vitro model of implant-to-cell interactions by culturing mesenchymal stromal cells (MSCs) on clinically relevant titanium materials of varying topological roughness, we identified mRNA expression patterns consistent with early extracellular matrix (ECM) production and responses to oxidative/heavy metal stress. Implants with high surface roughness may delay the differentiation and ECM formation of MSCs and alter the expression of genes sensitive to reactive oxygen species and protein kinases. In combination with ongoing animal studies, these results will guide future studies aimed at increasing the long-term retention of widely used titanium materials after total joint arthroplasty.

Elevated Expression of Plasminogen Activator Inhibitor (PAI-1/SERPINE1) is Independent from rs1799889 Genotypes in Arthrofibrosis.

Arthrofibrosis is characterized by excessive extracellular matrix deposition in patients with total knee arthroplasties (TKAs) and causes undesirable joint stiffness. The pathogenesis of arthrofibrosis remains elusive and currently there are no diagnostic biomarkers for the pathological formation of this connective tissue. Fibrotic soft tissues are known to have elevated levels of plasminogen activator inhibitor-1 (PAI-1) (encoded by SERPINE1), a secreted serine protease inhibitor that moderates extracellular matrix remodeling and tissue homeostasis. The 4G/5G insertion/deletion (rs1799889) is a well-known SERPINE1 polymorphism that directly modulates PAI-1 levels. Homozygous 4G/4G allele carriers typically have higher PAI-1 levels and may predispose patients to soft tissue fibrosis (e.g., liver, lung, and kidney). Here, we examined the genetic contribution of the SERPINE1 rs1799889 polymorphism to musculoskeletal fibrosis in arthrofibrotic (n = 100) and non-arthrofibrotic (n = 100) patients using Sanger Sequencing. Statistical analyses revealed that the allele frequencies of the SERPINE1 rs1799889 polymorphism are similar in arthrofibrotic and non-arthrofibrotic patient cohorts. Because the fibrosis related SERPINE1 rs1799889 polymorphism is independent of arthrofibrosis susceptibility in TKA patients, the possibility arises that fibrosis of joint connective tissues may involve unique genetic determinants distinct from those linked to classical soft tissue fibrosis.

Determining mutational burden and signature using RNA-seq from tumor-only samples.

BACKGROUND: Traditionally, mutational burden and mutational signatures have been assessed by tumor-normal pair DNA sequencing. The requirement of having both normal and tumor samples is not always feasible from a clinical perspective, and led us to investigate the efficacy of using RNA sequencing of only the tumor sample to determine the mutational burden and signatures, and subsequently molecular cause of the cancer. The potential advantages include reducing the cost of testing, and simultaneously providing information on the gene expression profile and gene fusions present in the tumor. RESULTS: In this study, we devised supervised and unsupervised learning methods to determine mutational signatures from tumor RNA-seq data. As applications, we applied the methods to a training set of 587 TCGA uterine cancer RNA-seq samples, and examined in an independent testing set of 521 TCGA colorectal cancer RNA-seq samples. Both diseases are known associated with microsatellite instable high (MSI-H) and driver defects in DNA polymerase ɛ (POLɛ). From RNA-seq called variants, we found majority (> 95%) are likely germline variants, leading to C > T enriched germline variants (dbSNP) widely applicable in tumor and normal RNA-seq samples. We found significant associations between RNA-derived mutational burdens and MSI/POLɛ status, and insignificant relationship between RNA-seq total coverage and derived mutational burdens. Additionally we found that over 80% of variants could be explained by using the COSMIC mutational signature-5, -6 and -10, which are implicated in natural aging, MSI-H, and POLɛ, respectively. For classifying tumor type, within UCEC we achieved a recall of 0.56 and 0.78, and specificity of 0.66 and 0.99 for MSI and POLɛ respectively. By applying learnt RNA signatures from UCEC to COAD, we were able to improve our classification of both MSI and POLɛ. CONCLUSIONS: Taken together, our work provides a novel method to detect RNA-seq derived mutational signatures with effective procedures to remove likely germline variants. It can leads to accurate classification of underlying driving mechanisms of DNA damage deficiency.

CpGtools: a python package for DNA methylation analysis.

MOTIVATION: DNA methylation can be measured at the single CpG level using sodium bisulfite conversion of genomic DNA followed by sequencing or array hybridization. Many analytic tools have been developed, yet there is still a high demand for a comprehensive and multifaceted tool suite to analyze, annotate, QC and visualize the DNA methylation data. RESULTS: We developed the CpGtools package to analyze DNA methylation data generated from bisulfite sequencing or Illumina methylation arrays. The CpGtools package consists of three types of modules: (i) 'CpG position modules' focus on analyzing the genomic positions of CpGs, including associating other genomic and epigenomic features to a given list of CpGs and generating the DNA motif logo enriched in the genomic contexts of a given list of CpGs; (ii) 'CpG signal modules' are designed to analyze DNA methylation values, such as performing the PCA or t-SNE analyses, using Bayesian Gaussian mixture modeling to classify CpG sites into fully methylated, partially methylated and unmethylated groups, profiling the average DNA methylation level over user-specified genomics regions and generating the bean/violin plots and (iii) 'differential CpG analysis modules' focus on identifying differentially methylated CpGs between groups using different statistical methods including Fisher's Exact Test, Student's t-test, ANOVA, non-parametric tests, linear regression, logistic regression, beta-binomial regression and Bayesian estimation. AVAILABILITY AND IMPLEMENTATION: CpGtools is written in Python under the open-source GPL license. The source code and documentation are freely available at https://github.com/liguowang/cpgtools. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A Potential Theragnostic Regulatory Axis for Arthrofibrosis Involving Adiponectin (ADIPOQ) Receptor 1 and 2 (ADIPOR1 and ADIPOR2), TGFß1, and Smooth Muscle α-Actin (ACTA2).

(1) Background: Arthrofibrosis is a common cause of patient debility and dissatisfaction after total knee arthroplasty (TKA). The diversity of molecular pathways involved in arthrofibrosis disease progression suggest that effective treatments for arthrofibrosis may require a multimodal approach to counter the complex cellular mechanisms that direct disease pathogenesis. In this study, we leveraged RNA-seq data to define genes that are suppressed in arthrofibrosis patients and identified adiponectin (ADIPOQ) as a potential candidate. We hypothesized that signaling pathways activated by ADIPOQ and the cognate receptors ADIPOR1 and ADIPOR2 may prevent fibrosis-related events that contribute to arthrofibrosis. (2) Methods: Therefore, ADIPOR1 and ADIPOR2 were analyzed in a TGFß1 inducible cell model for human myofibroblastogenesis by both loss- and gain-of-function experiments. (3) Results: Treatment with AdipoRon, which is a small molecule agonist of ADIPOR1 and ADIPOR2, decreased expression of collagens (COL1A1, COL3A1, and COL6A1) and the myofibroblast marker smooth muscle α-actin (ACTA2) at both mRNA and protein levels in basal and TGFß1-induced cells. (4) Conclusions: Thus, ADIPOR1 and ADIPOR2 represent potential drug targets that may attenuate the pathogenesis of arthrofibrosis by suppressing TGFß-dependent induction of myofibroblasts. These findings also suggest that AdipoRon therapy may reduce the development of arthrofibrosis by mediating anti-fibrotic effects in joint capsular tissues.

Ex Vivo Cell Therapy by Ectopic Hepatocyte Transplantation Treats the Porcine Tyrosinemia Model of Acute Liver Failure.

The effectiveness of cell-based therapies to treat liver failure is often limited by the diseased liver environment. Here, we provide preclinical proof of concept for hepatocyte transplantation into lymph nodes as a cure for liver failure in a large-animal model with hereditary tyrosinemia type 1 (HT1), a metabolic liver disease caused by deficiency of fumarylacetoacetate hydrolase (FAH) enzyme. Autologous porcine hepatocytes were transduced ex vivo with a lentiviral vector carrying the pig Fah gene and transplanted into mesenteric lymph nodes. Hepatocytes showed early (6 h) and durable (8 months) engraftment in lymph nodes, with reproduction of vascular and hepatic microarchitecture. Subsequently, hepatocytes migrated to and repopulated the native diseased liver. The corrected cells generated sufficient liver mass to clinically ameliorate the acute liver failure and HT1 disease as early as 97 days post-transplantation. Integration site analysis defined the corrected hepatocytes in the liver as a subpopulation of hepatocytes from lymph nodes, indicating that the lymph nodes served as a source for healthy hepatocytes to repopulate a diseased liver. Therefore, ectopic transplantation of healthy hepatocytes cures this pig model of liver failure and presents a promising approach for the development of cures for liver disease in patients.

Coverage profile correction of shallow-depth circulating cell-free DNA sequencing via multidistance learning.

Shallow-depth whole-genome sequencing (WGS) of circulating cell-free DNA (ccfDNA) is a popular approach for non-invasive genomic screening assays, including liquid biopsy for early detection of invasive tumors as well as non-invasive prenatal screening (NIPS) for common fetal trisomies. In contrast to nuclear DNA WGS, ccfDNA WGS exhibits extensive inter- and intra- sample coverage variability that is not fully explained by typical sources of variation in WGS, such as GC content. This variability may inflate false positive and false negative screening rates of copy-number alterations and aneuploidy, particularly if these features are present at a relatively low proportion of total sequenced content. Herein, we propose an empirically-driven coverage correction strategy that leverages prior annotation information in a multi-distance learning context to improve within-sample coverage profile correction. Specifically, we train a weighted k-nearest neighbors-style method on non-pregnant female donor ccfDNA WGS samples, and apply it to NIPS samples to evaluate coverage profile variability reduction. We additionally characterize improvement in the discrimination of positive fetal trisomy cases relative to normal controls, and compare our results against a more traditional regression-based approach to profile coverage correction based on GC content and mappability. Under cross-validation, performance measures indicated benefit to combining the two feature sets relative to either in isolation. We also observed substantial improvement in coverage profile variability reduction in leave-out clinical NIPS samples, with variability reduced by 26.5-53.5% relative to the standard regression-based method as quantified by median absolute deviation. Finally, we observed improvement discrimination for screening positive trisomy cases reducing ccfDNA WGS coverage variability while additionally improving NIPS trisomy screening assay performance. Overall, our results indicate that machine learning approaches can substantially improve ccfDNA WGS coverage profile correction and downstream analyses.