Low Read Depth Research Articles

Expanding the genomic diversity of human anelloviruses.

Anelloviruses are a group of small, circular, single-stranded DNA viruses that are found ubiquitously across mammalian hosts. Here, we explored a large number of publicly available human microbiome datasets and retrieved a total of 829 anellovirus genomes, substantially expanding the known diversity of these viruses. The majority of new genomes fall within the three major human anellovirus genera: Alphatorquevirus, Betatorquevirus, and Gammatorquevirus, while we also present new genomes of the under-sampled Hetorquevirus, Memtorquevirus, and Samektorquevirus genera. We performed recombination analysis and show evidence of extensive recombination across all human anelloviruses. Interestingly, more than 95% of the detected events are between members of the same genus and only 15 inter-genus recombination events were detected. The breakpoints of recombination cluster in hotspots at the ends and outside of the ORF1 gene, while a recombination coldspot was detected within the gene. Our analysis suggests that anellovirus evolution is governed by homologous recombination; however, events between distant viruses or ones producing chimaeric ORF1s likely lead to nonviable recombinants. The large number of genomes further allowed us to examine how essential genomic features vary across anelloviruses. These include functional domains in the ORF1 protein and the nucleotide motif of the replication loop region, required for the viruses' rolling-circle replication. A subset of the genomes assembled in both this and previous studies are completely lacking these essential elements, opening up the possibility that anellovirus intracellular populations contain nonstandard viral genomes. However, low-read depth of the metagenomically assembled contigs may partly explain the lack of some features. Overall, our study highlights key features of anellovirus genomics and evolution, a largely understudied group of viruses whose potential in virus-based therapeutics is recently being explored.

MDB-47. DEEP LEARNING DECODES NEW SITES OF RNA TRANSLATION IN MEDULLOBLASTOMA

Abstract BACKGROUND Medulloblastoma, a malignant brain cancer predominantly affecting children, possesses a high propensity for metastasis and is frequently fatal. Through studies on RNA translation, a core biological process, we aim to uncover the disease biology of cancer in order to design therapeutic targets. Yet, the exploration of canonical protein-coding genes has thus far yielded few viable targets in medulloblastoma, where non-canonical open reading frames (ORFs) are increasingly being investigated for their regulatory role. METHODS To address the significant challenge in delineating novel translated ORFs in individual cells or tissues, we have designed RIBO-former, a best-of-its-class machine learning model that leverages ribosome profiling data to detect translated open reading frames. Through RIBO-former, we expanded the proteome of healthy prenatal (n=30) and adult (n=42) samples, which are notoriously hard to process due to low read depth and noise, in addition to medulloblastoma cancer tissue (n=8) and cell line (n=15) data. RESULTS Across all medulloblastoma cell lines, we determine an initial selection of 3,638 non-canonical ORFs. Unsupervised clustering of the ribosome profiling read counts within these non-canonical ORF regions group samples according to the described subtypes of medulloblastoma cancer, hinting at the significant role these ncORFs play in protein homeostasis. Looking into distinct expression profiles between cell lines with high and low MYC expression, we revealed 201 non-canonical ORFs that are differentially expressed. We evaluate our data through various analyses including testing of which ORFs have a viable sequence context for translation, achieved through another in-house tool (TIS Transformer). CONCLUSIONS By taking advantage of advances in machine learning, we were able to uncover new sites of translation in medulloblastoma that can aid the future discovery of therapeutic targets. As such, we were able to find 22 highly promising non-canonical ORFs that show unique expression profiles in relation to MYC in medulloblastoma.

How low can you go? Short-read polishing of Oxford Nanopore bacterial genome assemblies.

It is now possible to assemble near-perfect bacterial genomes using Oxford Nanopore Technologies (ONT) long reads, but short-read polishing is usually required for perfection. However, the effect of short-read depth on polishing performance is not well understood. Here, we introduce Pypolca (with default and careful parameters) and Polypolish v0.6.0 (with a new careful parameter). We then show that: (1) all polishers other than Pypolca-careful, Polypolish-default and Polypolish-careful commonly introduce false-positive errors at low read depth; (2) most of the benefit of short-read polishing occurs by 25× depth; (3) Polypolish-careful almost never introduces false-positive errors at any depth; and (4) Pypolca-careful is the single most effective polisher. Overall, we recommend the following polishing strategies: Polypolish-careful alone when depth is very low (<5×), Polypolish-careful and Pypolca-careful when depth is low (5-25×), and Polypolish-default and Pypolca-careful when depth is sufficient (>25×).

Analytic optimization of Plasmodium falciparum marker gene haplotype recovery from amplicon deep sequencing of complex mixtures.

Molecular epidemiologic studies of malaria parasites and other pathogens commonly employ amplicon deep sequencing (AmpSeq) of marker genes derived from dried blood spots (DBS) to answer public health questions related to topics such as transmission and drug resistance. As these methods are increasingly employed to inform direct public health action, it is important to rigorously evaluate the risk of false positive and false negative haplotypes derived from clinically-relevant sample types. We performed a control experiment evaluating haplotype recovery from AmpSeq of 5 marker genes (ama1, csp, msp7, sera2, and trap) from DBS containing mixtures of DNA from 1 to 10 known P. falciparum reference strains across 3 parasite densities in triplicate (n = 270 samples). While false positive haplotypes were present across all parasite densities and mixtures, we optimized censoring criteria to remove 83% (148/179) of false positives while removing only 8% (67/859) of true positives. Post-censoring, the median pairwise Jaccard distance between replicates was 0.83. We failed to recover 35% (477/1365) of haplotypes expected to be present in the sample. Haplotypes were more likely to be missed in low-density samples with <1.5 genomes/μL (OR: 3.88, CI: 1.82-8.27, vs. high-density samples with ≥75 genomes/μL) and in samples with lower read depth (OR per 10,000 reads: 0.61, CI: 0.54-0.69). Furthermore, minority haplotypes within a sample were more likely to be missed than dominant haplotypes (OR per 0.01 increase in proportion: 0.96, CI: 0.96-0.97). Finally, in clinical samples the percent concordance across markers for multiplicity of infection ranged from 40%-80%. Taken together, our observations indicate that, with sufficient read depth, the majority of haplotypes can be successfully recovered from DBS while limiting the false positive rate.

Low-coverage sequencing and Wahlund effect severely bias estimates of inbreeding, heterozygosity and effective population size in North American wolves.

vonHoldt etal. ((2024), Molecular Ecology, 33, e17231) (vH24) used low-coverage (average ~ 7X read depth) restriction site-associated DNA sequence data to estimate individual inbreeding and heterozygosity, and recent effective population size (Ne), in Great Lakes (GL) and Northern Rocky Mountain (RM) wolves. They concluded that RM heterozygosity rapidly declined between 1991 and 2020, and that Ne declined substantially in GL and RM over the last 50 generations. Here, we evaluate the effects of low sequence coverage and sampling strategy on vH24's findings and provide general recommendations for using sequence data to evaluate inbreeding, heterozygosity and Ne. Low-coverage sequencing resulted in downwardly biased estimates of individual inbreeding and heterozygosity, and an erroneous large temporal decline in RM heterozygosity due to declining read depth through time. Additionally, vH24's sampling strategy-which combined individuals from several genetically differentiated populations and across at least eight wolf generations-is expected to have resulted in severe downward bias in estimates of recent Ne for RM. We recommend using high-coverage sequence data ( 15-20X) to estimate inbreeding and heterozygosity. Carefully filtering individuals, loci and genotypes, and using genotype imputation or likelihoods can help to minimise bias when low-coverage sequence data must be used. For estimation of contemporary Ne, the marginal benefits of using more than 103-104 loci are small, so aggressive filtering of loci with low average read depth potentially can retain most individuals without sacrificing much precision. Individuals are relatively more valuable than loci because analyses of contemporary Ne should focus on roughly single-generation samples from local breeding populations.

Biogeographical Ancestry Analyses Using the ForenSeqTM DNA Signature Prep Kit and Multiple Prediction Tools.

The inference of biogeographical ancestry (BGA) can assist in police investigations of serious crime cases and help to identify missing people and victims of mass disasters. In this study, we evaluated the typing performance of 56 ancestry-informative SNPs in 177 samples using the ForenSeq™ DNA Signature Prep Kit on the MiSeq FGx system. Furthermore, we compared the prediction accuracy of the tools Universal Analysis Software v1.2 (UAS), the FROG-kb, and GenoGeographer when inferring the ancestry of 503 Europeans, 22 non-Europeans, and 5 individuals with co-ancestry. The kit was highly sensitive with complete aiSNP profiles in samples with as low as 250pg input DNA. However, in line with others, we observed low read depth and occasional drop-out in some SNPs. Therefore, we suggest not using less than the recommended 1ng of input DNA. FROG-kb and GenoGeographer accurately predicted both Europeans (99.6% and 91.8% correct, respectively) and non-Europeans (95.4% and 90.9% correct, respectively). The UAS was highly accurate when predicting Europeans (96.0% correct) but performed poorer when predicting non-Europeans (40.9% correct). None of the tools were able to correctly predict individuals with co-ancestry. Our study demonstrates that the use of multiple prediction tools will increase the prediction accuracy of BGA inference in forensic casework.

Using nanopore sequencing to identify bacterial infection in joint replacements: a preliminary study.

This project investigates if third-generation genomic sequencing can be used to identify the species of bacteria causing prosthetic joint infections (PJIs) at the time of revision surgery. Samples of prosthetic fluid were taken during revision surgery from patients with known PJIs. Samples from revision surgeries from non-infected patients acted as negative controls. Genomic sequencing was performed using the MinION device and the rapid sequencing kit from Oxford Nanopore Technologies. Bioinformatic analysis pipelines to identify bacteria included Basic Local Alignment Search Tool, Kraken2 and MinION Detection Software, and the results were compared with standard of care microbiological cultures. Furthermore, there was an attempt to predict antibiotic resistance using computational tools including ResFinder, AMRFinderPlus and Comprehensive Antibiotic Resistance Database. Bacteria identified using microbiological cultures were successfully identified using bioinformatic analysis pipelines. Nanopore sequencing and genomic classification could be completed in the time it takes to perform joint revision surgery (2-3h). Genomic sequencing in this study was not able to predict antibiotic resistance in this time frame, this is thought to be due to a short-read length and low read depth. It can be concluded that genomic sequencing can be useful to identify bacterial species in infected joint replacements. However, further work is required to investigate if it can be used to predict antibiotic resistance within clinically relevant timeframes.

Abstract 331: Ion TorrentTM NGS sequencing of the TERT promoter hotspots with Ion AmpliSeqTM HD technology

Abstract Introduction: Recurrent mutations C228T and C250T in the TERT gene promoter are prevalent in cancer and serve as important biomarkers for aggressive disease. Ion Torrent™ NGS sequencing, combined with Ion AmpliSeqTM HD technology, enables comprehensive genomic profiling with ultra-high sensitivity for low-frequency variants in cell-free DNA (cf-DNA) and highly heterogeneous solid tumor samples. However, the high GC content (&amp;gt;80%) and the presence of G repeats that are known to adopt a compact stacked three-G-quadruplex conformation in the TERT gene promoter region pose sequencing challenges such as low read depth and strand-bias, i.e. prematurely truncated reads on one strand. Methods: We designed nine AmpliSeqTM HD panels with amplicon sizes of 70 to 104 bp, ideal for cf-DNA and FFPE samples, to target the recurrent TERT promoter hotspots. The designs were tested alone and combined with a larger Ion AmpliSeqTM HD DNA research panel resulting in highly multiplexed libraries. The libraries were used for Ion 540TM chip template preparation on the Ion ChefTM instrument and subsequently sequenced using the Ion GeneStudioTM S5 System. Sequencing data was used to evaluate coverage of the target hotspots by each design for each condition, and additional panels were designed to test single amplicons covering both TERT promoter hotspots. Results: Through performance evaluation, we selected two overlapping amplicons, each effectively amplifying one of the two hotspots. Individually tested, these amplicons yielded approximately 3000 families each from a 10ng gDNA input and when combined into the larger Ion AmpliSeqTM HD DNA research panel, they produced several thousand reads across various libraries, providing molecular coverage of around 200 functional molecules. While capture efficiency was lower compared to TERT amplicon-only libraries, these improved amplicons allow downstream analysis of variants. A single-pool solution (single amplicon/s covering both hotspots) will be explored further using the second batch of amplicons/primers. Conclusions: The optimized amplicons in two pools developed in this study enable the detection of challenging yet clinically significant TERT promoter hotspot mutations using the ultra-sensitive Ion AmpliSeqTM HD technology. For Research Use Only. Not for use in diagnostic procedures. © 2023 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of Thermo Fisher Scientific and its subsidiaries unless otherwise specified. Citation Format: Anupma Sharma, Guobin Luo, Na Li, Giorgio Pea, Fiona Hyland. Ion TorrentTM NGS sequencing of the TERT promoter hotspots with Ion AmpliSeqTM HD technology [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 331.

Impact of genotype-calling methodologies on genome-wide association and genomic prediction in polyploids.

Discovery and analysis of genetic variants underlying agriculturally important traits are key to molecular breeding of crops. Reduced representation approaches have provided cost-efficient genotyping using next-generation sequencing. However, accurate genotype calling from next-generation sequencing data is challenging, particularly in polyploid species due to their genome complexity. Recently developed Bayesian statistical methods implemented in available software packages, polyRAD, EBG, and updog, incorporate error rates and population parameters to accurately estimate allelic dosage across any ploidy. We used empirical and simulated data to evaluate the three Bayesian algorithms and demonstrated their impact on the power of genome-wide association study (GWAS) analysis and the accuracy of genomic prediction. We further incorporated uncertainty in allelic dosage estimation by testing continuous genotype calls and comparing their performance to discrete genotypes in GWAS and genomic prediction. We tested the genotype-calling methods using data from two autotetraploid species, Miscanthus sacchariflorus and Vaccinium corymbosum, and performed GWAS and genomic prediction. In the empirical study, the tested Bayesian genotype-calling algorithms differed in their downstream effects on GWAS and genomic prediction, with some showing advantages over others. Through subsequent simulation studies, we observed that at low read depth, polyRAD was advantageous in its effect on GWAS power and limit of false positives. Additionally, we found that continuous genotypes increased the accuracy of genomic prediction, by reducing genotyping error, particularly at low sequencing depth. Our results indicate that by using the Bayesian algorithm implemented in polyRAD and continuous genotypes, we can accurately and cost-efficiently implement GWAS and genomic prediction in polyploid crops.

Abstract P1008: Characterizing Complex Tandem Repeat Variants And Their Contribution To Congenital Heart Disease

Congenital heart disease (CHD) is a major cause of childhood mortality and lifelong morbidity in children and adults. CHD has a strong genetic basis, with exome and short read whole genome sequencing (srWGS) identifying genetic contributions to CHD risk in around 45% of affected individuals, while the remaining 55% have not had a specific genetic risk identified. Variation in tandem repeats (TRs), defined as repeated sequences of base pairs, has been implicated in several diseases and can affect gene expression. TR polymorphism in coding or regulatory regions of CHD related genes can alter function and expression, thereby modifying risk of CHD in patients. Identifying variants in TRs has been a challenge due to multiple variants at each site, as well as difficulty resolving long expansions with short read sequencing technologies. New bioinformatic tools have enabled identification of high-confidence short-TR (STR) variants in srWGS. Additionally, long read whole genome sequencing (lrWGS), with read lengths of 10-20 kilobases, enables genotyping of longer TRs that are missed by srWGS. We hypothesized that patients with CHD will have a higher burden of de novo and transmitted TRs near known CHD genes. We identified de novo and transmitted STR variants near known CHD genes in srWGS data from 1900 CHD proband and their parents in the Pediatric Cardiac Genomics Consortium (PCGC), and 1611 non-CHD probands and their parents. Transmitted STR variants in CHD probands were enriched in 5’-UTR, introns, and promoters of CHD genes compared to non-CHD probands. We identified large de novo repeats near known CHD genes such as NOTCH2 and RBFOX2 . Additionally we used Pacbio HiFi lrWGS on 150 PCGC probands without an established etiology for CHD. Combining these analyses, we identified 3,243 repeat regions with low read depth in srWGS, and therefore unable to be resolved accurately, near known CHD genes and from lrWGS we assess length polymorphisms using Tandem Repeat Finder. TRs that harbor large variation in length were identified within intronic regions of CHD genes including FLT4 , NFATC1 , and PKD1 . We suggest that polymorphic repeat regions provide new candidate variants or altering gene transcription or splicing and thereby contribute to CHD.

Easy-to-use R functions to separate reduced-representation genomic datasets into sex-linkedand autosomal loci, and conduct sex assignment.

Identifying sex-linked markers in genomic datasets is important because their presence in supposedly neutral autosomal datasets can result in incorrect estimates of genetic diversity, population structure and parentage. However, detecting sex-linked loci can be challenging, and available scripts neglect some categories of sex-linked variation. Here, we present new R functions to (1) identify and separate sex-linked loci in ZW and XY sex determination systems and (2) infer the genetic sex of individuals based on these loci. We tested these functions on genomic data for two bird and one mammal species and compared the biological inferences made before and after removing sex-linked loci using our function. We found that our function identified autosomal loci with ≥98.8% accuracy and sex-linked loci with an average accuracy of 87.8%. We showed that standard filters, such as low read depth and call rate, failed to remove up to 54.7% of sex-linked loci. This led to (i) overestimation of population FIS by up to 24%, and the number of private alleles by up to 8%; (ii) wrongly inferring significant sex differences in heterozygosity; (iii) obscuring genetic population structure and (iv) inferring ~11% fewer correct parentages. We discuss how failure to remove sex-linked markers can lead to incorrect biological inferences (e.g. sex-biased dispersal and cryptic population structure) and misleading management recommendations. For reduced-representation datasets with at least 15 known-sex individuals of each sex, our functions offer convenient resources to remove sex-linked loci and to sex the remaining individuals (freely available at https://github.com/drobledoruiz/conservation_genomics).

Massively multiplex blocker displacement amplification (BDA) for the detection of measurable residual disease in acute myeloid leukemia.

e19045 Background: Next-generation sequencing (NGS) technologies, used to accomplish high throughput characterization of DNA, have an inherent error rate of between 0.1-1%. However, many important DNA sequences possess variant allele frequencies (VAFs) below this rate, potentially precluding their detection and identification by NGS. The previously published blocker displacement amplification (BDA) research technology has enabled selective amplification of sequences with variants, facilitating detection by NGS of these sequences with low VAFs at low read depths. Methods: Here we present the massively multiplex BDA library preparation method for the NGS-based detection of low VAF sequences. By optimizing our previously published Simulated Annealing Design using Dimer Likelihood Estimation (SADDLE) algorithm, we designed a 4 tube assay, comprising up to ~2400 amplicons in each tube, and ~8300 total amplicons. Tube 1 was designed with the highest likelihood of on-target amplification and the lowest likelihood of dimerization or non-specific amplification. While Tube 1 targeted ~1000 regions covering the most-frequently observed mutations in current public databases of patients with acute myeloid leukemia (AML) across more than 200 genes, Tubes 2-4 were designed for enrichment of the full coding sequence of 63 genes. To highlight the performances of SADDLE, coverage uniformity, primer dimerization, and non-specific amplification of tube 1 were compared to those of a naively designed tube. The panel was further tested with contrived and reference samples to demonstrate its analytical performance. Results: The SADDLE algorithm design decreased the first pass amplicon dropout rate more than 10-fold, from 30% to ~2%, and further improved the overall on-target rate compared to the naively designed panel. Through SADDLE, we were able to achieve an 80% median coverage of 63 genes. The resulting panel has a bulk limit of detection (LoD) of below 0.1% VAF. Conclusions: Massively multiplex BDA enabled the NGS characterization of DNA targets with VAFs suitable for detection of AML measurable residual disease (MRD). This technology represents a 100-fold increase in current plexity for the detection of low VAF alleles over our previously published multiplex BDA technology, demonstrating the ability to perform high throughput sequencing of rare mutations.

Low hybridization temperatures improve target capture success of invertebrate loci: a case study of leaf-footed bugs (Hemiptera: Coreoidea).

Target capture is widely used in phylogenomic, ecological and functional genomic studies. Bait sets that allow capture from a diversity of species can be advantageous, but high-sequence divergence from baits can limit yields. Currently, only four experimental comparisons of a critical target capture parameter, hybridization temperature, have been published. These have been in vertebrates, where bait divergences are typically low, and none include invertebrates where bait-target divergences may be higher. Most invertebrate capture studies use a fixed, high hybridization temperature to maximize the proportion of on-target data, but many report low locus recovery. Using leaf-footed bugs (Hemiptera: Coreoidea), we investigate the effect of hybridization temperature on capture success of ultraconserved elements targeted by (i) baits developed from divergent hemipteran genomes and (ii) baits developed from less divergent coreoid transcriptomes. Lower temperatures generally resulted in more contigs and improved recovery of targets despite a lower proportion of on-target reads, lower read depth and more putative paralogues. Hybridization temperatures had less of an effect when using transcriptome-derived baits, which is probably due to lower bait-target divergences and greater bait tiling density. Thus, accommodating low hybridization temperatures during target capture can provide a cost-effective, widely applicable solution to improve invertebrate locus recovery.

Abstract 4272: Pan-cancer analysis of intra-tumor heterogeneity in 9,116 cancers using a novel regularized likelihood model

Abstract Subpopulations of tumor cells characterized by mutation profiles may confer differential fitness and consequently influence the prognosis of cancers. Understanding subclonal architecture has the potential to provide biological insight in tumor evolution and advance cancer precision treatment. Recent subclonal reconstruction methods require heavy computational resources, prior knowledge of the number of subclones, and extensive postprocessing. These drawbacks can be addressed by using a regularized likelihood modeling approach, which is novel to the field. Therefore, we propose a model-based method, Clonal structure identification through pair-wise Penalization, or CliP, to address these drawbacks. To evaluate the performance of CliP against other methods, we generated a benchmark dataset of 4,050 simulated samples with varied tumor purity, read depth, copy number alteration rate, and true numbers of clusters. Our results suggest that CliP outperforms popular methods such as PhyloWGS in accuracy and shows similar robustness in most scenarios. We further compared CliP performance against 10 other subclonal reconstruction methods to the consensus subclonal reconstruction results on whole-genome sequencing (WGS) data from the Pan-Cancer Analysis of Whole Genomes (PCAWG, n = 1,993). Our result shows that of all 11 methods, CliP achieves the highest correlation with the consensus calls. In terms of speed, CliP can finish running a sample with 5,000 SNVs within one minute, which is ~1,000 times faster than MCMC-based algorithms. Next, we profiled the subclonal structures of 7,711 patient samples with well-annotated clinical outcomes from The Cancer Genome Atlas (TCGA) across 32 cancer types applying CliP to the whole-exome sequencing (WES) data. This is the largest and most complete pan-cancer characterization of intratumor heterogeneity (ITH) through the lens of subclonal reconstruction. We further used CliP outputs to address a commonly asked question on which sequencing platform to use for cancer evolution studies: the cost-effect WES data at higher read depth versus the more comprehensive WGS data at lower read depth. There were a total of 588 tumor samples from 21 cancer types, for which both PCAWG and TCGA have profiled using the WGS and WES platform, respectively. Using both datasets to compare results from these samples as benchmark, we observed that for most cancer types, subclonal reconstruction from WES is as informative as that from the matched WGS data. In summary, our study represents a significant methodological advancement in subclonal reconstruction and highlights the importance of measuring tumor subclone structure. Citation Format: Yujie Jiang, Kaixian Yu, Matthew D. Montierth, Shuangxi Ji, Seung Jun Shin, Shuai Guo, Shaolong Cao, Yuxin Tang, Scott Kopetz, Pavlos Msaouel, Jennifer R. Wang, Marek Kimmel, Peter Van Loo, Hongtu Zhu, Wenyi Wang. Pan-cancer analysis of intra-tumor heterogeneity in 9,116 cancers using a novel regularized likelihood model. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4272.

Unwarranted Exclusion of Intermediate Lineage A-B SARS-CoV-2 Genomes Is Inconsistent with the Two-Spillover Hypothesis of the Origin of COVID-19

Pekar et al. (2022) propose that SARS-CoV-2 was a zoonotic spillover that first infected humans in the Huanan Seafood Market in Wuhan, China. They propose that there were two separate spillovers of the closely related lineages A and lineage B in a short period of time. The two lineages are differentiated by two SNVs; hence, a single-SNV A-B intermediate must have occurred in an unsampled animal host if the two-spillover hypothesis is correct. Consequently, confirmation of the existence of an intermediate A-B genome from humans would falsify their hypothesis of two spillovers. Pekar et al. identified and excluded 20 A-B intermediate genomes from their analysis. A variety of exclusion criteria were applied, including low read depth and the assertion of repeated erroneous base calls at lineage-defining positions 8782 and 28144. However, data from GISAID show that most of the genomes were sequenced to high average sequencing depth, appearing inconsistent with these criteria. The decision to exclude the majority of genomes was based on personal communications, with raw data unavailable for inspection. Multiple errors, biases, and inconsistencies were observed in the exclusion process. For example, 12 intermediate genomes from one study were excluded; however, 54 other genomes from the same study were included, indicating selection bias. Puzzlingly, two intermediate genomes from Beijing were discarded despite an average sequencing depth of 2175X; however, four genomes from the same sequencing study were included in the analysis. Lastly, we discuss 14 additional possible intermediate genomes not discussed by Pekar et al. and note that genome sequence filtration is inappropriate when considering the presence or absence of a specific SNV pair in an outbreak. Consequently, we find that the exclusion of many of the intermediate genomes is unfounded, leaving the conclusion of two natural zoonoses unsupported.

Rapid whole genome sequencing methods for RNA viruses.

RNA viruses are the etiological agents of many infectious diseases. Since RNA viruses are error-prone during genome replication, rapid, accurate and economical whole RNA viral genome sequence determination is highly demanded. Next-generation sequencing (NGS) techniques perform whole viral genome sequencing due to their high-throughput sequencing capacity. However, the NGS techniques involve a significant burden for sample preparation. Since to generate complete viral genome coverage, genomic nucleic acid enrichment is required by reverse transcription PCR using virus-specific primers or by viral particle concentration. Furthermore, conventional NGS techniques cannot determine the 5' and 3' terminal sequences of the RNA viral genome. Therefore, the terminal sequences are determined one by one using rapid amplification of cDNA ends (RACE). However, since some RNA viruses have segmented genomes, the burden of the determination using RACE is proportional to the number of segments. To date, there is only one study attempting whole genome sequencing of multiple RNA viruses without using above mentioned methods, but the generated sequences' accuracy compared to the reference sequences was up to 97% and did not reach 100% due to the low read depth. Hence, we established novel methods, named PCR-NGS and RCA-NGS, that were optimized for an NGS machine, MinION. These methods do not require nucleic acid amplification with virus-specific PCR primers, physical viral particle enrichment, and RACE. These methods enable whole RNA viral genome sequencing by combining the following techniques: (1) removal of unwanted DNA and RNA other than the RNA viral genome by nuclease treatment; (2) the terminal of viral genome sequence determination by barcoded linkers ligation; (3) amplification of the viral genomic cDNA using ligated linker sequences-specific PCR or an isothermal DNA amplification technique, such as rolling circle amplification (RCA). The established method was evaluated using isolated RNA viruses with single-stranded, double-stranded, positive-stranded, negative-stranded, non-segmented or multi-segmented genomes. As a result, all the viral genome sequences could be determined with 100% accuracy, and these mean read depths were greater than 2,500×, at least using either of the methods. This method should allow for easy and economical determination of accurate RNA viral genomes.

Ultra-Low Level Somatic Mutations and Structural Variations in Focal Cortical Dysplasia Type II.

Brain somatic mutations in mTOR pathway genes are a major genetic etiology of focal cortical dysplasia type II (FCDII). Despite a greater ability to detect low-level somatic mutations in the brain by deep sequencing and analytics, about 40% of cases remain genetically unexplained. We included 2 independent cohorts consisting of 21 patients with mutation-negative FCDII without apparent mutations on conventional deep sequencing of bulk brain. To find ultra-low level somatic variants or structural variants, we isolated cells exhibiting phosphorylation of the S6 ribosomal protein (p-S6) in frozen brain tissues using fluorescence-activated cell sorting (FACS). We then performed deep whole-genome sequencing (WGS; >90×) in p-S6+ cells in a cohort of 11 patients with mutation-negative. Then, we simplified the method to whole-genome amplification and target gene sequencing of p-S6+ cells in independent cohort of 10 patients with mutation-negative followed by low-read depth WGS (10×). We found that 28.6% (6 of 21) of mutation-negative FCDII carries ultra-low level somatic mutations (less than 0.2% of variant allele frequency [VAF]) in mTOR pathway genes. Our method showed ~34 times increase of the average mutational burden in FACS mediated enrichment of p-S6+ cells (average VAF=5.84%) than in bulky brain tissues (average VAF=0.17%). We found that 19% (4 of 21) carried germline structural variations in GATOR1 complex undetectable in whole exome or targeted gene sequencing. Our method facilitates the detection of ultra-low level somatic mutations, in specifically p-S6+ cells, and germline structural variations and increases the genetic diagnostic rate up to ~80% for the entire FCDII cohort. ANN NEUROL 2023;93:1082-1093.

Freshwater Mussels Show Elevated Viral Richness and Intensity during a Mortality Event.

Freshwater mussels (Unionida) are among the world's most imperiled taxa, but the relationship between freshwater mussel mortality events and infectious disease is largely unstudied. We surveyed viromes of a widespread and abundant species (mucket, Actinonaias ligamentina; syn: Ortmanniana ligamentina) experiencing a mortality event of unknown etiology in the Huron River, Michigan, in 2019-2020 and compared them to viromes from mucket in a healthy population in the St. Croix River, Wisconsin and a population from the Clinch River, Virginia and Tennessee, where a mortality event was affecting the congeneric pheasantshell (Actinonaias pectorosa; syn: Ortmanniana pectorosa) population. We identified 38 viruses, most of which were associated with mussels collected during the Huron River mortality event. Viral richness and cumulative viral read depths were significantly higher in moribund mussels from the Huron River than in healthy controls from each of the three populations. Our results demonstrate significant increases in the number and intensity of viral infections for freshwater mussels experiencing mortality events, whereas individuals from healthy populations have a substantially reduced virome comprising a limited number of species at low viral read depths.

DETexT: An SNV detection enhancement for low read depth by integrating mutational signatures into TextCNN.

Detecting SNV at very low read depths helps to reduce sequencing requirements, lowers sequencing costs, and aids in the early screening, diagnosis, and treatment of cancer. However, the accuracy of SNV detection is significantly reduced at read depths below ×34 due to the lack of a sufficient number of read pairs to help filter out false positives. Many recent studies have revealed the potential of mutational signature (MS) in detecting true SNV, understanding the mutational processes that lead to the development of human cancers, and analyzing the endogenous and exogenous causes. Here, we present DETexT, an SNV detection method better suited to low read depths, which classifies false positive variants by combining MS with deep learning algorithms to mine correlation information around bases in individual reads without relying on the support of duplicate read pairs. We have validated the effectiveness of DETexT on simulated and real datasets and conducted comparative experiments. The source code has been uploaded to https://github.com/TrinaZ/extra-lowRD for academic use only.

First Report of Cowpea Polerovirus 2 and Southern Cowpea Mosaic Virus Infecting Cowpea in Nepal.

Cowpea (Vigna unguiculata L. Walp) is one of the important legume crops of Nepal, which is consumed as a green vegetable or a dried pulse. In recent years, virus diseases have caused significant yield and quality losses in cowpea. In September 2019, five cowpea plants showing virus-like symptoms of mosaic, yellow mosaic, vein clearing, chlorotic spots, (Fig. S1) were collected in Chitwan, Nepal. The incidence of symptomatic plants in the three kitchen gardens was about 10-20%. To identify the viruses associated with the disease, a pooled sample from all five plants was screened initially by next generation sequencing (NGS). Total RNA was extracted from the symptomatic leaves using RNeasy Plant Mini Kit (Qiagen, Germany) and a transcriptome library was generated using the TruSeq Stranded Total RNA LT Sample Prep kit (Illumina, San Diego, CA) according to the standard protocol. NGS was performed using an Illumina NovaSeq 6000 system (Macrogen Inc. Korea). A total of 324,807 contigs in the range of 201-14,645 nucleotides (nt) were obtained and analyzed against the viral reference genome database in GenBank by BLASTn and BLASTx search. Among the analyzed contigs, two large contigs showed homologies to cowpea polerovirus 2 (CPPV2) and southern cowpea mosaic virus (SCPMV. The CPPV2 contig (361,121 mapped reads, mean read coverage of 9,206.4 times) had a nearly complete genome sequence of 5,923 nt and showed 96% identity (99% coverage) with CPPV2 isolate BE179 (GenBank Acc. No. KY364847) isolaed from cowpea in Burkina Faso (Palanga et al. 2017). The SCPMV contig (10,612 mapped reads, mean read coverage of 384.1 times) had a nearly complete genome sequence of 4,172 nt and showed 90% identity (100% coverage) with SCPMV isolate C (GenBank Acc. No. M23021) isolated from cowpea in the USA (Wu et al. 1987). Additionally, mungbean yellow mosaic India virus (MYMIV, genus Begomovirus) and bean common mosaic virus (BCMV, genus Potyvirus) were detected at very low read depths. To confirm the presence of these viruses, total RNA was extracted from individual leaf samples, and reverse transcription PCR (RT-PCR) was performed using specific primers for each virus (Table S1). Three of five cowpea samples were positive for CPPV2, and they were co-infected with one other virus; SCPMV, MYMIV, or BCMV (Fig. S1). One cowpea sample was positive for the remaining one with symptom of overall chlorosis was negative for all four viruses. The amplified products of 1,205 bp for CPPV2 isolates, CPPV2-NP10, -NP12, and -NP24 were sequenced and deposited in GenBank under accession nos. MZ318692-93. These Sanger sequences shared 99% nt identity with the NGS-derived sequence. The amplified product of 1,394 bp for SCPMV isolate SCPMV-NP12 (GenBank acc. no. MZ355623) shared 100% nt identity with the NGS-derived sequence. CPPV2 is a member of the genus Polerovirus and it was first identified and characterized by molecular assays in Burkina Faso (Palanga et al. 2016; 2017). SCPMV is a member of the genus Sobemovirus and it has been reported in the USA, China, and Burkina Faso (Hull et al. 2000; Lee et al. 2001; Wu et al. 1987). In Nepal, MYMIV has been reported in legumes, such as kidney bean, black gram, and mungbean, and BCMV in common bean (Acharya and Regmi 2020). To our knowledge, this is the first report of CPPV2 and SCPMV in cowpea in Nepal. Further work is required to determine the distribution, pathological properties, and economic impact of these two viruses.