Targeted DNA-seq and RNA-seq of Reference Samples with Short-read and Long-read Sequencing.

Next-generation sequencing (NGS) has revolutionized genomic research by enabling high-throughput, cost-effective genome and transcriptome sequencing accelerating personalized medicine for complex diseases, including cancer. Whole genome/transcriptome sequencing (WGS/WTS) provides comprehensive insights, while targeted sequencing is more cost-effective and sensitive. In comparison to short-read sequencing, which still dominates the field due to high speed and cost-effectiveness, long-read sequencing can overcome alignment limitations and better discriminate similar sequences from alternative transcripts or repetitive regions. Hybrid sequencing combines the best strengths of different technologies for a more comprehensive view of genomic/transcriptomic variations. Understanding each technology's strengths and limitations is critical for translating cutting-edge technologies into clinical applications. In this study, we sequenced DNA and RNA libraries of reference samples using various targeted DNA and RNA panels and the whole transcriptome on both short-read and long-read platforms. This study design enables a comprehensive analysis of sequencing technologies, targeting protocols, and library preparation methods. Our expanded profiling landscape establishes a reference point for assessing current sequencing technologies, facilitating informed decision-making in genomic research and precision medicine.

Clonal hematopoiesis driven by mutated DNMT3A promotes inflammatory bone loss.

Clonal hematopoiesis of indeterminate potential (CHIP) arises from aging-associated acquired mutations in hematopoietic progenitors, which display clonal expansion and produce phenotypically altered leukocytes. We associated CHIP-DNMT3A mutations with a higher prevalence of periodontitis and gingival inflammation among 4,946 community-dwelling adults. To model DNMT3A-driven CHIP, we used mice with the heterozygous loss-of-function mutation R878H, equivalent to the human hotspot mutation R882H. Partial transplantation with Dnmt3aR878H/+ bone marrow (BM) cells resulted in clonal expansion of mutant cells into both myeloid and lymphoid lineages and an elevated abundance of osteoclast precursors in the BM and osteoclastogenic macrophages in the periphery. DNMT3A-driven clonal hematopoiesis in recipient mice promoted naturally occurring periodontitis and aggravated experimentally induced periodontitis and arthritis, associated with enhanced osteoclastogenesis, IL-17-dependent inflammation and neutrophil responses, and impaired regulatory T cell immunosuppressive activity. DNMT3A-driven clonal hematopoiesis and, subsequently, periodontitis were suppressed by rapamycin treatment. DNMT3A-driven CHIP represents a treatable state of maladaptive hematopoiesis promoting inflammatory bone loss.

Evaluation of mutagenic susceptibility of different stages in germ cell development of Caenorhabditis elegans using whole genome sequencing.

In contrast to somatic mutations, mutations in germ cells affect every cell of any organism derived from the germ cell and therefore are related to numerous genetic diseases. However, there is no suitable assay to evaluate the mutagenic sensitivities of both male and female germ cells. The main type of Caenorhabditis elegans (C. elegans) is hermaphroditic, where spermatogenesis and oogenesis occur chronologically at specific stages, allowing induction of mutations in either sperm or eggs exclusively. In this study, we used the alkylating agent ethyl methanesulfonate and N-ethyl-N-nitrosourea to induce germline mutations in C. elegans at different developmental stages and analyzed mutation frequency and mutational spectrum from data gathered using next-generation sequencing (NGS) technology. Our results revealed low spontaneous mutation rates of C. elegans, along with distinct mutagenic effects elicited by the two mutagens. Our data show that the parental worms treated during germ cell mitosis, spermatogenesis, and oogenesis resulted in different mutation frequencies in their offspring, and female germ cells could be very susceptible to mutagen exposure during oogenesis. In summary, our study indicates that the use of C. elegans and its specific chronological hermaphroditism would be a promising way to explore the sensitivities of both male and female germ cells to mutagens.

Whole Exome Sequencing Reveals Genetic Variants in HLA Class II Genes Associated With Transplant-free Survival of Indeterminate Acute Liver Failure.

INTRODUCTION: Indeterminate acute liver failure (IND-ALF) is a rare clinical syndrome with a high mortality rate. Lacking a known etiology makes rapid evaluation and treatment difficult, with liver transplantation often considered as the only therapeutic option. Our aim was to identify genetic variants from whole exome sequencing data that might be associated with IND-ALF clinical outcomes. METHODS: Bioinformatics analysis was performed on whole exome sequencing data for 22 patients with IND-ALF. A 2-tier approach was used to identify significant single-nucleotide polymorphisms (SNPs) associated with IND-ALF clinical outcomes. Tier 1 identified the SNPs with a higher relative risk in the IND-ALF population compared with those identified in control populations. Tier 2 determined the SNPs connected to transplant-free survival and associated with model for end-stage liver disease serum sodium and Acute Liver Failure Study Group prognostic scores. RESULTS: Thirty-one SNPs were found associated with a higher relative risk in the IND-ALF population compared with those in controls, of which 11 belong to the human leukocyte antigen (HLA) class II genes but none for the class I. Further analysis showed that 5 SNPs: rs796202376, rs139189937, and rs113473719 of HLA-DRB5; rs9272712 of HLA-DQA1; and rs747397929 of IDO1 were associated with a higher probability of IND-ALF transplant-free survival. Using 3 selected SNPs, a model for the polygenic risk score was developed to predict IND-ALF prognoses, which are comparable with those by model for end-stage liver disease serum sodium and Acute Liver Failure Study Group prognostic scores. DISCUSSION: Certain gene variants in HLA-DRB5, HLA-DQA1, and IDO1 were found associated with IND-ALF transplant-free survival. Once validated, these identified SNPs may help elucidate the mechanism of IND-ALF and assist in its diagnosis and management.

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.

Hidden biases in germline structural variant detection.

BACKGROUND: Genomic structural variations (SV) are important determinants of genotypic and phenotypic changes in many organisms. However, the detection of SV from next-generation sequencing data remains challenging. RESULTS: In this study, DNA from a Chinese family quartet is sequenced at three different sequencing centers in triplicate. A total of 288 derivative data sets are generated utilizing different analysis pipelines and compared to identify sources of analytical variability. Mapping methods provide the major contribution to variability, followed by sequencing centers and replicates. Interestingly, SV supported by only one center or replicate often represent true positives with 47.02% and 45.44% overlapping the long-read SV call set, respectively. This is consistent with an overall higher false negative rate for SV calling in centers and replicates compared to mappers (15.72%). Finally, we observe that the SV calling variability also persists in a genotyping approach, indicating the impact of the underlying sequencing and preparation approaches. CONCLUSIONS: This study provides the first detailed insights into the sources of variability in SV identification from next-generation sequencing and highlights remaining challenges in SV calling for large cohorts. We further give recommendations on how to reduce SV calling variability and the choice of alignment methodology.

Informing selection of drugs for COVID-19 treatment through adverse events analysis.

Coronavirus disease 2019 (COVID-19) is an ongoing pandemic and there is an urgent need for safe and effective drugs for COVID-19 treatment. Since developing a new drug is time consuming, many approved or investigational drugs have been repurposed for COVID-19 treatment in clinical trials. Therefore, selection of safe drugs for COVID-19 patients is vital for combating this pandemic. Our goal was to evaluate the safety concerns of drugs by analyzing adverse events reported in post-market surveillance. We collected 296 drugs that have been evaluated in clinical trials for COVID-19 and identified 28,597,464 associated adverse events at the system organ classes (SOCs) level in the FDA adverse events report systems (FAERS). We calculated Z-scores of SOCs that statistically quantify the relative frequency of adverse events of drugs in FAERS to quantitatively measure safety concerns for the drugs. Analyzing the Z-scores revealed that these drugs are associated with different significantly frequent adverse events. Our results suggest that this safety concern metric may serve as a tool to inform selection of drugs with favorable safety profiles for COVID-19 patients in clinical practices. Caution is advised when administering drugs with high Z-scores to patients who are vulnerable to associated adverse events.

Identification of Epidemiological Traits by Analysis of SARS-CoV-2 Sequences.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the ongoing global COVID-19 pandemic that began in late December 2019. The rapid spread of SARS-CoV-2 is primarily due to person-to-person transmission. To understand the epidemiological traits of SARS-CoV-2 transmission, we conducted phylogenetic analysis on genome sequences from >54K SARS-CoV-2 cases obtained from two public databases. Hierarchical clustering analysis on geographic patterns in the resulting phylogenetic trees revealed a co-expansion tendency of the virus among neighboring countries with diverse sources and transmission routes for SARS-CoV-2. Pairwise sequence similarity analysis demonstrated that SARS-CoV-2 is transmitted locally and evolves during transmission. However, no significant differences were seen among SARS-CoV-2 genomes grouped by host age or sex. Here, our identified epidemiological traits provide information to better prevent transmission of SARS-CoV-2 and to facilitate the development of effective vaccines and therapeutics against the virus.

Mutagenicity of silver nanoparticles evaluated using whole-genome sequencing in mouse lymphoma cells.

The increasing medical and food applications of silver nanoparticles (AgNPs) raise concerns about their safety, including the potential health consequences of human exposure. Previous studies found that AgNPs were negative in the Ames test due to both their microbicidal activity and the inability of nanoparticles to penetrate bacterial cell walls. Thus, the mutagenicity of AgNPs is still not completely clear, though they do induce chromosome damage, as suggested by many previous genotoxicity studies. In this study, whole-genome sequencing (WGS) was used to analyze the mutagenicity of AgNPs in mouse lymphoma cells expanded from single-cell clones. The cells were treated with AgNPs, 4-nitroquinolone-1-oxide (4-NQO) as the positive control, and vehicle controls. Both AgNPs and 4-NQO significantly increased mutation frequencies over their concurrent controls by 1.12-fold and 4.89-fold with mutation rates at 4-fold and 130-fold, respectively. AgNP-induced mutations mainly occurred at G:C sites with G:C > T:A transversions, G:C > A:T transitions, and deletions as the most commonly observed mutations. AgNPs also induced higher fold changes in tandem mutations. The results suggest that the WGS mutation assay conducted here can detect the low-level mutagenicity of AgNPs, providing substantial support for the use of the WGS method as a possible alternative assay with respect to the mutagenic assessment of nanomaterials.

Development of a Nicotinic Acetylcholine Receptor nAChR α7 Binding Activity Prediction Model.

Despite the well-known adverse health effects associated with tobacco use, addiction to nicotine found in tobacco products causes difficulty in quitting among users. Nicotinic acetylcholine receptors (nAChRs) are the physiological targets of nicotine and facilitate addiction to tobacco products. The nAChR-α7 subtype plays an important role in addiction; therefore, predicting the binding activity of tobacco constituents to nAChR-α7 is an important component for assessing addictive potential of tobacco constituents. We developed an α7 binding activity prediction model based on a large training data set of 843 chemicals with human α7 binding activity data extracted from PubChem and ChEMBL. The model was tested using 1215 chemicals with rat α7 binding activity data from the same databases. Based on the competitive docking results, the docking scores were partitioned to the key residues that play important roles in the receptor-ligand binding. A decision forest was used to train the human α7 binding activity prediction model based on the partition of docking scores. Five-fold cross validations were conducted to estimate the performance of the decision forest models. The developed model was used to predict the potential human α7 binding activity for 5275 tobacco constituents. The human α7 binding activity data for 84 of the 5275 tobacco constituents were experimentally measured to confirm and empirically validate the prediction results. The prediction accuracy, sensitivity, and specificity were 64.3, 40.0, and 81.6%, respectively. The developed prediction model of human α7 may be a useful tool for high-throughput screening of potential addictive tobacco constituents.

Elucidating Interactions Between SARS-CoV-2 Trimeric Spike Protein and ACE2 Using Homology Modeling and Molecular Dynamics Simulations.

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19). As of October 21, 2020, more than 41.4 million confirmed cases and 1.1 million deaths have been reported. Thus, it is immensely important to develop drugs and vaccines to combat COVID-19. The spike protein present on the outer surface of the virion plays a major role in viral infection by binding to receptor proteins present on the outer membrane of host cells, triggering membrane fusion and internalization, which enables release of viral ssRNA into the host cell. Understanding the interactions between the SARS-CoV-2 trimeric spike protein and its host cell receptor protein, angiotensin converting enzyme 2 (ACE2), is important for developing drugs and vaccines to prevent and treat COVID-19. Several crystal structures of partial and mutant SARS-CoV-2 spike proteins have been reported; however, an atomistic structure of the wild-type SARS-CoV-2 trimeric spike protein complexed with ACE2 is not yet available. Therefore, in our study, homology modeling was used to build the trimeric form of the spike protein complexed with human ACE2, followed by all-atom molecular dynamics simulations to elucidate interactions at the interface between the spike protein and ACE2. Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) and in silico alanine scanning were employed to characterize the interacting residues at the interface. Twenty interacting residues in the spike protein were identified that are likely to be responsible for tightly binding to ACE2, of which five residues (Val445, Thr478, Gly485, Phe490, and Ser494) were not reported in the crystal structure of the truncated spike protein receptor binding domain (RBD) complexed with ACE2. These data indicate that the interactions between ACE2 and the tertiary structure of the full-length spike protein trimer are different from those between ACE2 and the truncated monomer of the spike protein RBD. These findings could facilitate the development of drugs and vaccines to prevent SARS-CoV-2 infection and combat COVID-19.

Persistent Organic Pollutants in Food: Contamination Sources, Health Effects and Detection Methods.

Persistent organic pollutants (POPs) present in foods have been a major concern for food safety due to their persistence and toxic effects. To ensure food safety and protect human health from POPs, it is critical to achieve a better understanding of POP pathways into food and develop strategies to reduce human exposure. POPs could present in food in the raw stages, transferred from the environment or artificially introduced during food preparation steps. Exposure to these pollutants may cause various health problems such as endocrine disruption, cardiovascular diseases, cancers, diabetes, birth defects, and dysfunctional immune and reproductive systems. This review describes potential sources of POP food contamination, analytical approaches to measure POP levels in food and efforts to control food contamination with POPs.

Correction to: Similarities and differences between variants called with human reference genome HG19 or HG38.

After publication of this supplement article.

Similarities and differences between variants called with human reference genome HG19 or HG38.

BACKGROUND: Reference genome selection is a prerequisite for successful analysis of next generation sequencing (NGS) data. Current practice employs one of the two most recent human reference genome versions: HG19 or HG38. To date, the impact of genome version on SNV identification has not been rigorously assessed. METHODS: We conducted analysis comparing the SNVs identified based on HG19 vs HG38, leveraging whole genome sequencing (WGS) data from the genome-in-a-bottle (GIAB) project. First, SNVs were called using 26 different bioinformatics pipelines with either HG19 or HG38. Next, two tools were used to convert the called SNVs between HG19 and HG38. Lastly we calculated conversion rates, analyzed discordant rates between SNVs called with HG19 or HG38, and characterized the discordant SNVs. RESULTS: The conversion rates from HG38 to HG19 (average 95%) were lower than the conversion rates from HG19 to HG38 (average 99%). The conversion rates varied slightly among the various calling pipelines. Around 1.5% SNVs were discordantly converted between HG19 or HG38. The conversions from HG38 to HG19 had more SNVs which failed conversion and more discordant SNVs than the opposite conversion (HG19 to HG38). Most of the discordant SNVs had low read depth, were low confidence SNVs as defined by GIAB, and/or were predominated by G/C alleles (52% observed versus 42% expected). CONCLUSION: A significant number of SNVs could not be converted between HG19 and HG38. Based on careful review of our comparisons, we recommend HG38 (the newer version) for NGS SNV analysis. To summarize, our findings suggest caution when translating identified SNVs between different versions of the human reference genome.

Draft genome of the cotton aphid Aphis gossypii.

The cotton aphid Aphis gossypii Glover is a worldwide agricultural pest that feeds on cotton, melon, and other landscape plants, causing a high level of economic loss. In addition to the common characteristics shared with other aphids, Ap. gossypii has evolved multiple biotypes that present substantial differences in host adaption. These intriguing biological features are of interest from both a fundamental and applied perspective. However, the molecular studies of Ap. gossypii have been restrained by the lack of a reference genome. Furthermore, in order to establish a platform for the development of novel and sustainable control methods, it is necessary to generate genomic resources for Ap. gossypii. Here, we present a 294 Mb draft genome sequence of Ap. gossypii, which consists of 4,724 scaffolds with an N50 size of 438 kb. Compared to other aphid species with published genomes, Ap. gossypii presents the most compact genome size. A total of 14,694 protein-coding genes were predicted and annotated in the consensus gene set, 98.03% of CEGMA genes and 93.5% of BUSCO genes were captured respectively. Genome-wide selection analyses revealed that significantly evolving pathways in the genus Aphis are related to biological processes of detoxification, steroid biosynthesis, and ethylbenzene degradation. The acquisition of the genome of Ap. gossypii makes it possible to understand the molecular mechanism of intricate biological traits of this species, and will further facilitate the study of aphid evolution.

Whole genome sequencing analysis of small and large colony mutants from the mouse lymphoma assay.

The Thymidine kinase (Tk) gene forward mutation assay, known as the mouse lymphoma assay (MLA), has been widely used for evaluating the genotoxicity of chemical agents. A striking morphological feature of Tk mutant colonies is the bimodal distribution of their sizes, with cells from the large colonies growing at a normal rate and cells from the small colonies growing at a slower rate than normal. To understand the molecular distinction for the different growth rates, we performed whole genome sequencing (WGS) analysis of the large and small colony mutants generated from the MLA. Three large colony and three small colony mutants generated from cells treated with 4-nitroquinoline 1-oxide (4-NQO) or the vehicle control were selected for analysis. The WGS data were analyzed for loss of heterozygosity (LOH) and chromosome copy number along chromosome 11, where the Tk gene is located. Although there were LOH alterations in both large and small colony mutants, copy number changes near Tk locus were found only in small colony mutants produced by the vehicle control and 4-NQO treatments. The chromosome copy number in the regions near the Tk locus increased from two to three or four in the spontaneous small colony mutants and decreased from two to one in the 4-NQO-induced small colony mutants. These results suggest that chromosome damage was repaired differently in the large and small colony mutants, resulting in significant chromosome alterations in the small colony mutants, but not in the large colony mutants. Thus, chromosome alterations near the Tk locus may play a major role in the inhibition of cell growth in the Tk small colony mutants.

Structural Changes Due to Antagonist Binding in Ligand Binding Pocket of Androgen Receptor Elucidated Through Molecular Dynamics Simulations.

When a small molecule binds to the androgen receptor (AR), a conformational change can occur which impacts subsequent binding of co-regulator proteins and DNA. In order to accurately study this mechanism, the scientific community needs a crystal structure of the Wild type AR (WT-AR) ligand binding domain, bound with antagonist. To address this open need, we leveraged molecular docking and molecular dynamics (MD) simulations to construct a structure of the WT-AR ligand binding domain bound with antagonist bicalutamide. The structure of mutant AR (Mut-AR) bound with this same antagonist informed this study. After molecular docking analysis pinpointed the suitable binding orientation of a ligand in AR, the model was further optimized through 1 µs of MD simulations. Using this approach, three molecular systems were studied: (1) WT-AR bound with agonist R1881, (2) WT-AR bound with antagonist bicalutamide, and (3) Mut-AR bound with bicalutamide. Our structures were very similar to the experimentally determined structures of both WT-AR with R1881 and Mut-AR with bicalutamide, demonstrating the trustworthiness of this approach. In our model, when WT-AR is bound with bicalutamide, Val716/Lys720/Gln733, or Met734/Gln738/Glu897 move and thus disturb the positive and negative charge clumps of the AF2 site. This disruption of the AF2 site is key for understanding the impact of antagonist binding on subsequent co-regulator binding. In conclusion, the antagonist induced structural changes in WT-AR detailed in this study will enable further AR research and will facilitate AR targeting drug discovery.

Competitive docking model for prediction of the human nicotinic acetylcholine receptor α7 binding of tobacco constituents.

The detrimental health effects associated with tobacco use constitute a major public health concern. The addiction associated with nicotine found in tobacco products has led to difficulty in quitting among users. Nicotinic acetylcholine receptors (nAChRs) are the targets of nicotine and are responsible for addiction to tobacco products. However, it is unknown if the other >8000 tobacco constituents are addictive. Since it is time-consuming and costly to experimentally assess addictive potential of such larger number of chemicals, computationally predicting human nAChRs binding is important for in silico evaluation of addiction potential of tobacco constituents and needs structures of human nAChRs. Therefore, we constructed three-dimensional structures of the ligand binding domain of human nAChR α7 subtype and then developed a predictive model based on the constructed structures to predict human nAChR α7 binding activity of tobacco constituents. The predictive model correctly predicted 11 out of 12 test compounds to be binders of nAChR α7. The model is a useful tool for high-throughput screening of potential addictive tobacco constituents. These results could inform regulatory science research by providing a new validated predictive tool using cutting-edge computational methodology to high-throughput screen tobacco additives and constituents for their binding interaction with the human α7 nicotinic receptor. The tool represents a prediction model capable of screening thousands of chemicals found in tobacco products for addiction potential, which improves the understanding of the potential effects of additives.

Computational prediction models for assessing endocrine disrupting potential of chemicals.

Endocrine disrupting chemicals (EDCs) mimic natural hormones and disrupt endocrine function. Humans and wildlife are exposed to EDCs might alter endocrine functions through various mechanisms and lead to an adverse effects. Hence, EDCs identification is important to protect the ecosystem and to promote the public health. Leveraging in-vitro and in-vivo experiments to identify potential EDCs is time consuming and expensive. Hence, quantitative structure-activity relationship is applied to screen the potential EDCs. Here, we summarize the predictive models developed using various algorithms to forecast the binding activity of chemicals to the estrogen and androgen receptors, alpha-fetoprotein, and sex hormone binding globulin.

Evaluation of chemical mutagenicity using next generation sequencing: A review.

Mutations are heritable changes in the nucleotide sequence of DNA that can lead to many adverse effects. Genotoxicity assays have been used to identify chemical mutagenicity. Recently, next generation sequencing (NGS) has been used for this purpose. In this review, we present the progress in NGS application for assessing mutagenicity of chemicals, including the methods used for detecting the induced mutations, bioinformatics tools for analyzing the sequencing data, and chemicals whose mutagenicity has been evaluated using NGS. Available information suggests that NGS technology has unparalleled advantages for evaluating mutagenicity of chemicals can be applied for the next generation of mutagenicity tests.