Evaluation of somatic copy number variation detection by NGS technologies and bioinformatics tools on a hyper-diploid cancer genome.

BACKGROUND: Copy number variation (CNV) is a key genetic characteristic for cancer diagnostics and can be used as a biomarker for the selection of therapeutic treatments. Using data sets established in our previous study, we benchmark the performance of cancer CNV calling by six most recent and commonly used software tools on their detection accuracy, sensitivity, and reproducibility. In comparison to other orthogonal methods, such as microarray and Bionano, we also explore the consistency of CNV calling across different technologies on a challenging genome. RESULTS: While consistent results are observed for copy gain, loss, and loss of heterozygosity (LOH) calls across sequencing centers, CNV callers, and different technologies, variation of CNV calls are mostly affected by the determination of genome ploidy. Using consensus results from six CNV callers and confirmation from three orthogonal methods, we establish a high confident CNV call set for the reference cancer cell line (HCC1395). CONCLUSIONS: NGS technologies and current bioinformatics tools can offer reliable results for detection of copy gain, loss, and LOH. However, when working with a hyper-diploid genome, some software tools can call excessive copy gain or loss due to inaccurate assessment of genome ploidy. With performance matrices on various experimental conditions, this study raises awareness within the cancer research community for the selection of sequencing platforms, sample preparation, sequencing coverage, and the choice of CNV detection tools.

Recommendations for Uniform Variant Calling of SARS-CoV-2 Genome Sequence across Bioinformatic Workflows.

Genomic sequencing of clinical samples to identify emerging variants of SARS-CoV-2 has been a key public health tool for curbing the spread of the virus. As a result, an unprecedented number of SARS-CoV-2 genomes were sequenced during the COVID-19 pandemic, which allowed for rapid identification of genetic variants, enabling the timely design and testing of therapies and deployment of new vaccine formulations to combat the new variants. However, despite the technological advances of deep sequencing, the analysis of the raw sequence data generated globally is neither standardized nor consistent, leading to vastly disparate sequences that may impact identification of variants. Here, we show that for both Illumina and Oxford Nanopore sequencing platforms, downstream bioinformatic protocols used by industry, government, and academic groups resulted in different virus sequences from same sample. These bioinformatic workflows produced consensus genomes with differences in single nucleotide polymorphisms, inclusion and exclusion of insertions, and/or deletions, despite using the same raw sequence as input datasets. Here, we compared and characterized such discrepancies and propose a specific suite of parameters and protocols that should be adopted across the field. Consistent results from bioinformatic workflows are fundamental to SARS-CoV-2 and future pathogen surveillance efforts, including pandemic preparation, to allow for a data-driven and timely public health response.

Reduction of the trans-cortical vessel was associated with bone loss, another underlying mechanism of osteoporosis.

RATIONALE: Numerous studies have established a robust association between bone morrow microvascular diseases and osteoporosis. This study sought to investigate the relationship between alterations in trans-cortical vessel (TCVs) and the onset of osteoporosis in various mouse models. METHODS: Aged mice, ovariectomized mice, and db/db mice, were utilized as osteoporosis models. TCVs in the tibia were detected using tissue clearing and light sheet fluorescence microscopy imaging. Femurs bone mass were analyzed using micro-CT scanning. Correlations between the number of TCVs and bone mass were analyzed using Pearson correlation analysis. RESULTS: All osteoporosis mouse models showed a significant reduction in the number of TCVs compared to the control group. Correlation analysis revealed a positive association between the number of TCVs and bone mass. TCVs were also expressed high levels of CD31 and EMCN proteins as type H vessels. CONCLUSIONS: This study underscores a consistent correlation between the number of TCVs and bone mass. Moreover, TCVs may serve as a potential biomarker for bone mass evaluation.

Efficient Synthesis of Cyclic Poly(ethylene glycol)s under High Concentration Conditions by the Assistance of Pseudopolyrotaxane with Cyclodextrin Derivatives.

An efficient synthesis of cyclic polymers (CPs) is in high demand due to their unique properties. However, polymer cyclization generally occurs at low concentrations (0.1 g/L), and the synthesis of CPs at high concentrations remains a challenge. Herein an efficient cyclization of poly(ethylene glycol) (Mn = 2000 g/mol, 4000 g/mol) (PEG-2k, PEG-4k) in high concentration (80 g/L) is realized by the assistance of pseudopolyrotaxane (pPRx). Water-soluble pPRx with a U-like-shape inclusion motif is prepared by mixing the 2-hydroxypropyl-γ-cyclodextrin (HPγCD) and PEG with (E)-3,4,5-trimethoxycinnamate (TCA-PEG-2k, TCA-PEG-4k). Subsequent irradiation of the pPRx solution (10-80 g/L) by UV light gives cyclic polymers through the intramolecular [2 + 2] photocycloaddition of the cinnamoyl moieties. The photoreaction of TCA-PEG-2k in the pPRx system gives cyclic monomers (C-1mer) as major products with a yield of 66% at 80 g/L. Additionally, the cyclization of TCA-PEG-4k also gives C-1mer as major products with a yield of 45% at a concentration of 80 g/L.

Structural variant analysis of a cancer reference cell line sample using multiple sequencing technologies.

BACKGROUND: The cancer genome is commonly altered with thousands of structural rearrangements including insertions, deletions, translocation, inversions, duplications, and copy number variations. Thus, structural variant (SV) characterization plays a paramount role in cancer target identification, oncology diagnostics, and personalized medicine. As part of the SEQC2 Consortium effort, the present study established and evaluated a consensus SV call set using a breast cancer reference cell line and matched normal control derived from the same donor, which were used in our companion benchmarking studies as reference samples. RESULTS: We systematically investigated somatic SVs in the reference cancer cell line by comparing to a matched normal cell line using multiple NGS platforms including Illumina short-read, 10X Genomics linked reads, PacBio long reads, Oxford Nanopore long reads, and high-throughput chromosome conformation capture (Hi-C). We established a consensus SV call set of a total of 1788 SVs including 717 deletions, 230 duplications, 551 insertions, 133 inversions, 146 translocations, and 11 breakends for the reference cancer cell line. To independently evaluate and cross-validate the accuracy of our consensus SV call set, we used orthogonal methods including PCR-based validation, Affymetrix arrays, Bionano optical mapping, and identification of fusion genes detected from RNA-seq. We evaluated the strengths and weaknesses of each NGS technology for SV determination, and our findings provide an actionable guide to improve cancer genome SV detection sensitivity and accuracy. CONCLUSIONS: A high-confidence consensus SV call set was established for the reference cancer cell line. A large subset of the variants identified was validated by multiple orthogonal methods.

Benchmarking challenging small variants with linked and long reads.

Genome in a Bottle benchmarks are widely used to help validate clinical sequencing pipelines and develop variant calling and sequencing methods. Here we use accurate linked and long reads to expand benchmarks in 7 samples to include difficult-to-map regions and segmental duplications that are challenging for short reads. These benchmarks add more than 300,000 SNVs and 50,000 insertions or deletions (indels) and include 16% more exonic variants, many in challenging, clinically relevant genes not covered previously, such as PMS2. For HG002, we include 92% of the autosomal GRCh38 assembly while excluding regions problematic for benchmarking small variants, such as copy number variants, that should not have been in the previous version, which included 85% of GRCh38. It identifies eight times more false negatives in a short read variant call set relative to our previous benchmark. We demonstrate that this benchmark reliably identifies false positives and false negatives across technologies, enabling ongoing methods development.

Towards increased accuracy and reproducibility in SARS-CoV-2 next generation sequence analysis for public health surveillance.

During the COVID-19 pandemic, SARS-CoV-2 surveillance efforts integrated genome sequencing of clinical samples to identify emergent viral variants and to support rapid experimental examination of genome-informed vaccine and therapeutic designs. Given the broad range of methods applied to generate new viral genomes, it is critical that consensus and variant calling tools yield consistent results across disparate pipelines. Here we examine the impact of sequencing technologies (Illumina and Oxford Nanopore) and 7 different downstream bioinformatic protocols on SARS-CoV-2 variant calling as part of the NIH Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Tracking Resistance and Coronavirus Evolution (TRACE) initiative, a public-private partnership established to address the COVID-19 outbreak. Our results indicate that bioinformatic workflows can yield consensus genomes with different single nucleotide polymorphisms, insertions, and/or deletions even when using the same raw sequence input datasets. We introduce the use of a specific suite of parameters and protocols that greatly improves the agreement among pipelines developed by diverse organizations. Such consistency among bioinformatic pipelines is fundamental to SARS-CoV-2 and future pathogen surveillance efforts. The application of analysis standards is necessary to more accurately document phylogenomic trends and support data-driven public health responses.

Personalized genome assembly for accurate cancer somatic mutation discovery using tumor-normal paired reference samples.

BACKGROUND: The use of a personalized haplotype-specific genome assembly, rather than an unrelated, mosaic genome like GRCh38, as a reference for detecting the full spectrum of somatic events from cancers has long been advocated but has never been explored in tumor-normal paired samples. Here, we provide the first demonstrated use of de novo assembled personalized genome as a reference for cancer mutation detection and quantifying the effects of the reference genomes on the accuracy of somatic mutation detection. RESULTS: We generate de novo assemblies of the first tumor-normal paired genomes, both nuclear and mitochondrial, derived from the same individual with triple negative breast cancer. The personalized genome was chromosomal scale, haplotype phased, and annotated. We demonstrate that it provides individual specific haplotypes for complex regions and medically relevant genes. We illustrate that the personalized genome reference not only improves read alignments for both short-read and long-read sequencing data but also ameliorates the detection accuracy of somatic SNVs and SVs. We identify the equivalent somatic mutation calls between two genome references and uncover novel somatic mutations only when personalized genome assembly is used as a reference. CONCLUSIONS: Our findings demonstrate that use of a personalized genome with individual-specific haplotypes is essential for accurate detection of the full spectrum of somatic mutations in the paired tumor-normal samples. The unique resource and methodology established in this study will be beneficial to the development of precision oncology medicine not only for breast cancer, but also for other cancers.

The role of PI3K/Akt signalling pathway in spinal cord injury.

Spinal cord injury (SCI) is a severely disabling central nervous system injury with complex pathological mechanisms that leads to sensory and motor dysfunction. The current treatment for SCI is aimed at symptomatic symptom relief rather than the pathological causes. Several studies have reported that signaling pathways play a key role in SCI pathological processes and neuronal recovery mechanisms. The PI3K/Akt signaling pathway is an important pathway closely related to the pathological process of SCI, and activation of this pathway can delay the inflammatory response, prevent glial scar formation, and promote neurological function recovery. Activation of this pathway can promote the recovery of neurological function after SCI by reducing cell apoptosis. Based on the role of the PI3K/Akt pathway in SCI, it may be a potential therapeutic target. This review highlights the role of activating or inhibiting the PI3K/Akt signaling pathway in SCI-induced inflammatory response, apoptosis, autophagy, and glial scar formation. We also summarize the latest evidence on treating SCI by targeting the PI3K/Akt pathway, discuss the shortcomings and deficiencies of PI3K/Akt research in the field of SCI, and identify potential challenges in developing these clinical therapeutic SCI strategies, and provide appropriate solutions.

Effect of dexmedetomidine administration on analgesic, respiration and inflammatory responses in patients undergoing percutaneous endoscopic lumbar discectomy: a prospective observational study.

BACKGROUND: Local anesthesia has been recommended for percutaneous endoscopic lumbar discectomy (PELD) in recent years; however, the efficacy, including oxidative stress, inflammatory reactions and ventilation effects, when intravenous dexmedetomidine (DEX) is administered during PELD has not been described. METHODS: Sixty adult patients undergoing PELD were randomly allocated to either an intravenous DEX sedation group (Group A) or a normal saline group (Group B). Respiratory data, including minute ventilation (MV), tidal volume (TV), and respiratory rate (RR), were recorded using a respiratory volume monitor (RVM), and peripheral oxygen saturation (SpO2) was monitored by pulse oximetry. The visual analog score (VAS) was used to assess the level of pain. The serum levels of inflammatory biomarkers including interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) were to assess inflammatory reactions. The serum levels of oxidative stress biomarkers including malondialdehyde (MDA) and glutathione peroxidase (GSH-PX) were also recorded to evaluate oxidative stress. RESULTS: There were no significant differences in RR, MV, TV and SpO2 between the two groups at any time point (P > 0.05). Group B exhibited lower serum levels of GSH-PX (P < 0.0001) and higher serum levels of MDA (p < 0.0001) than Group A at the end of surgery. Twenty-four hours after surgery, Group B exhibited higher serum levels of IL-6 (P = 0.0033), TNF-α (P = 0.0002), and MDA (P < 0.0001) and lower serum levels of GSH-PX (P < 0.0001) than Group A. In addition, Group A exhibited lower VAS (P < 0.0001) than Group B during surgery. CONCLUSIONS: DEX administration using RVM not only provides analgesia without ventilatory depression but also alleviates oxidative stress and inflammatory reactions in patients undergoing PELD.

Early Clinical Efficacy of Endo-TLIF in the Treatment of Lumbar Disc Herniation.

OBJECTIVE: We aimed to compare the early clinical efficacy of endoscopy-assisted transforaminal lumbar interbody fusion (Endo-TLIF) and traditional Open-TLIF in the treatment of lumbar disc herniation and lumbar instability. METHODS: Forty-six patients with lumbar disc herniation and lumbar instability admitted to the hospital were retrospectively studied from October 11, 2018 to October 11, 2020. Patients (including 17 males and 29 females) were randomly divided into Endo-TLIF and Open-TLIF groups according to the different surgical treatment. Parameters such as intraoperative blood loss, operation time, and intraoperative fluoroscopy time during the surgery as well as preoperative and postoperative lumbar lordosis angle and lumbar clearance height and related complications were recorded in detail. RESULTS: Endo-TLIF significantly reduced intraoperative blood loss and bleeding volume compared with traditional Open-TLIF. The incision length in the Endo-TLIF group was shorter than in the Open-TLIF group and the intraoperative fluoroscopy time was also shorter than in the Open-TLIF group. The bed rest time and hospital discharge time were shortened in Endo-TLIF surgery compared with traditional Open-TLIF surgery. The creatine kinase (CK) values of the Endo-TLIF group were lower than that of the Open-TLIF group on the 1st and 3rd day after operation. Although computed tomography images of the lumbar lordosis angle did not show a significant difference between the Endo-TLIF group (43.97 ± 8.91°) and Open-TLIF group (49.08 ± 9.42°), the visual analogue scale score and Oswestry dysfunction index of lower back pain in the Endo-TLIF group were significantly lower than in the Open-TLIF group at 1 month and half a year after surgery. Complications in the Endo-TLIF group, such as lower limb neurological dysfunction and diseases of the respiratory or urinary system, effectively improved compared with the Open-TLIF group. CONCLUSION: Endo-TLIF appears to be a safer and more effective option for the treatment of lumbar disc herniation and lumbar instability, with a shorter recovery time, less trauma, less bleeding, no need for postoperative drainage, and less iatrogenic injury.

A complete reference genome improves analysis of human genetic variation.

Compared to its predecessors, the Telomere-to-Telomere CHM13 genome adds nearly 200 million base pairs of sequence, corrects thousands of structural errors, and unlocks the most complex regions of the human genome for clinical and functional study. We show how this reference universally improves read mapping and variant calling for 3202 and 17 globally diverse samples sequenced with short and long reads, respectively. We identify hundreds of thousands of variants per sample in previously unresolved regions, showcasing the promise of the T2T-CHM13 reference for evolutionary and biomedical discovery. Simultaneously, this reference eliminates tens of thousands of spurious variants per sample, including reduction of false positives in 269 medically relevant genes by up to a factor of 12. Because of these improvements in variant discovery coupled with population and functional genomic resources, T2T-CHM13 is positioned to replace GRCh38 as the prevailing reference for human genetics.

Curated variation benchmarks for challenging medically relevant autosomal genes.

The repetitive nature and complexity of some medically relevant genes poses a challenge for their accurate analysis in a clinical setting. The Genome in a Bottle Consortium has provided variant benchmark sets, but these exclude nearly 400 medically relevant genes due to their repetitiveness or polymorphic complexity. Here, we characterize 273 of these 395 challenging autosomal genes using a haplotype-resolved whole-genome assembly. This curated benchmark reports over 17,000 single-nucleotide variations, 3,600 insertions and deletions and 200 structural variations each for human genome reference GRCh37 and GRCh38 across HG002. We show that false duplications in either GRCh37 or GRCh38 result in reference-specific, missed variants for short- and long-read technologies in medically relevant genes, including CBS, CRYAA and KCNE1. When masking these false duplications, variant recall can improve from 8% to 100%. Forming benchmarks from a haplotype-resolved whole-genome assembly may become a prototype for future benchmarks covering the whole genome.

Achieving robust somatic mutation detection with deep learning models derived from reference data sets of a cancer sample.

BACKGROUND: Accurate detection of somatic mutations is challenging but critical in understanding cancer formation, progression, and treatment. We recently proposed NeuSomatic, the first deep convolutional neural network-based somatic mutation detection approach, and demonstrated performance advantages on in silico data. RESULTS: In this study, we use the first comprehensive and well-characterized somatic reference data sets from the SEQC2 consortium to investigate best practices for using a deep learning framework in cancer mutation detection. Using the high-confidence somatic mutations established for a cancer cell line by the consortium, we identify the best strategy for building robust models on multiple data sets derived from samples representing real scenarios, for example, a model trained on a combination of real and spike-in mutations had the highest average performance. CONCLUSIONS: The strategy identified in our study achieved high robustness across multiple sequencing technologies for fresh and FFPE DNA input, varying tumor/normal purities, and different coverages, with significant superiority over conventional detection approaches in general, as well as in challenging situations such as low coverage, low variant allele frequency, DNA damage, and difficult genomic regions.

Assessing reproducibility of inherited variants detected with short-read whole genome sequencing.

BACKGROUND: Reproducible detection of inherited variants with whole genome sequencing (WGS) is vital for the implementation of precision medicine and is a complicated process in which each step affects variant call quality. Systematically assessing reproducibility of inherited variants with WGS and impact of each step in the process is needed for understanding and improving quality of inherited variants from WGS. RESULTS: To dissect the impact of factors involved in detection of inherited variants with WGS, we sequence triplicates of eight DNA samples representing two populations on three short-read sequencing platforms using three library kits in six labs and call variants with 56 combinations of aligners and callers. We find that bioinformatics pipelines (callers and aligners) have a larger impact on variant reproducibility than WGS platform or library preparation. Single-nucleotide variants (SNVs), particularly outside difficult-to-map regions, are more reproducible than small insertions and deletions (indels), which are least reproducible when > 5 bp. Increasing sequencing coverage improves indel reproducibility but has limited impact on SNVs above 30×. CONCLUSIONS: Our findings highlight sources of variability in variant detection and the need for improvement of bioinformatics pipelines in the era of precision medicine with WGS.

MiRNA-375 inhibits retinoblastoma progression through targeting ERBB2 and inhibiting MAPK1/MAPK3 signalling pathway.

BACKGROUND: Increasing evidence has shown that the dysregulation of miRNAs is involved in the pathogenesis of retinoblastoma (RB). This present study was aimed to investigate the significance of miR-375 in RB progression, and the underlying mechanism. MATERIALS AND METHODS: The miR-375 expression was detected by RT-PCR. CCK-8 assay and transwell assays were used to measure RB cell viability, migration, and invasion. The downstream gene of miR-375 was verified by luciferase reporter assay. Western blot was applied to detect the related proteins of MAPK1/MAPK3 signalling pathway. RESULTS: MiR-375 was decreased significantly in RB tissues, and its down-regulation was associated with the poor prognosis of RB patients. Over-expression of miR-375 inhibited RB cell proliferation, migration, and invasion. More importantly, miR-375 modulated ERBB2 expression negatively, and ERBB2 was confirmed as the target of miR-375. Moreover, ERBB2 overturned the inhibitory effect of miR-375 mimic on the progression of RB. MiR-375 mimic suppressed RB progression via inhibiting the activation of MAPK1/MAPK3 signalling pathway. CONCLUSIONS: MiR-375 inhibited RB progression through targeting ERBB2 and suppressing MAPK1/MAPK3 signalling pathway, which might be a new target for the clinical treatment strategy.

Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study.

With the rapid advancement of sequencing technologies, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples and generated whole-genome (WGS) and whole-exome sequencing (WES) data using sixteen library protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies.

Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing.

Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.

A diploid assembly-based benchmark for variants in the major histocompatibility complex.

Most human genomes are characterized by aligning individual reads to the reference genome, but accurate long reads and linked reads now enable us to construct accurate, phased de novo assemblies. We focus on a medically important, highly variable, 5 million base-pair (bp) region where diploid assembly is particularly useful - the Major Histocompatibility Complex (MHC). Here, we develop a human genome benchmark derived from a diploid assembly for the openly-consented Genome in a Bottle sample HG002. We assemble a single contig for each haplotype, align them to the reference, call phased small and structural variants, and define a small variant benchmark for the MHC, covering 94% of the MHC and 22368 variants smaller than 50 bp, 49% more variants than a mapping-based benchmark. This benchmark reliably identifies errors in mapping-based callsets, and enables performance assessment in regions with much denser, complex variation than regions covered by previous benchmarks.

Author Correction: A robust benchmark for detection of germline large deletions and insertions.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.