Toward better understanding of artifacts in variant calling from high-coverage samples

Targeted panel sequencing of pharmacogenes and oncodrivers in colorectal cancer patients reveals genes with prognostic significance

BACKGROUND

Colorectal cancer is still the second leading cause of cancer-related deaths and thus biomarkers allowing prediction of the resistance of patients to therapy and estimating their prognosis are needed. We designed a panel of 558 genes with pharmacogenomics records related to 5-fluorouracil resistance, genes important for sensitivity to other frequently used drugs, major oncodrivers, and actionable genes. We performed a target enrichment sequencing of DNA from tumors and matched blood samples of patients, and compared the results with patient prognosis stratified by systemic adjuvant chemotherapy.

RESULTS

The median number of detected variants per tumor sample was 18.5 with 4 classified as having a high predicted functional effect and 14.5 moderate effect. APC, TP53, and KRAS were the most frequent mutated genes (64%, 59%, and 42% of mutated samples, respectively) followed by FAT4 (23%), FBXW7, and PIK3CA (16% for both). Patients with advanced stage III had more frequently APC, TP53, or KRAS mutations than those in stages I or II. KRAS mutation counts followed an increasing trend with grade (G1 < G2 < G3). The response to adjuvant therapy was worse in carriers of frameshift mutations in APC or 12D variant in KRAS, but none of these oncodrivers had prognostic value. Carriage of somatic mutations in any of the genes ABCA13, ANK2, COL7A1, NAV3, or UNC80 had prognostic relevance for worse overall survival (OS) of all patients. In contrast, mutations in FLG, GLI3, or UNC80 were prognostic in the same direction for patients untreated, and mutations in COL6A3, LRP1B, NAV3, RYR1, RYR3, TCHH, or TENM4 for patients treated with adjuvant therapy. The first association was externally validated. From all germline variants with high or moderate predicted functional effects (median 326 per patient), > 5% frequency and positive Manhattan plot based on 3-year RFS, rs72753407 in NFACS, rs34621071 in ERBB4, and rs2444274 in RIF1 were significantly associated with RFS, OS or both.

CONCLUSIONS

The present study identified several putative somatic and germline genetic events with prognostic potential for colorectal cancer that should undergo functional characterization.

Exome-wide evidence of compound heterozygous effects across common phenotypes in the UK Biobank

The phenotypic impact of compound heterozygous (CH) variation has not been investigated at the population scale. We phased rare variants (MAF ∼0.001%) in the UK Biobank (UKBB) exome-sequencing data to characterize recessive effects in 175,587 individuals across 311 common diseases. A total of 6.5% of individuals carry putatively damaging CH variants, 90% of which are only identifiable upon phasing rare variants (MAF < 0.38%). We identify six recessive gene-trait associations (p < 1.68 × 10-7) after accounting for relatedness, polygenicity, nearby common variants, and rare variant burden. Of these, just one is discovered when considering homozygosity alone. Using longitudinal health records, we additionally identify and replicate a novel association between bi-allelic variation in ATP2C2 and an earlier age at onset of chronic obstructive pulmonary disease (COPD) (p < 3.58 × 10-8). Genetic phase contributes to disease risk for gene-trait pairs: ATP2C2-COPD (p = 0.000238), FLG-asthma (p = 0.00205), and USH2A-visual impairment (p = 0.0084). We demonstrate the power of phasing large-scale genetic cohorts to discover phenome-wide consequences of compound heterozygosity.

Variant calling in polyploids for population and quantitative genetics

Advancements in genome assembly and sequencing technology have made whole genome sequence (WGS) data and reference genomes accessible to study polyploid species. Compared to popular reduced-representation sequencing approaches, the genome-wide coverage and greater marker density provided by WGS data can greatly improve our understanding of polyploid species and polyploid biology. However, biological features that make polyploid species interesting also pose challenges in read mapping, variant identification, and genotype estimation. Accounting for characteristics in variant calling like allelic dosage uncertainty, homology between subgenomes, and variance in chromosome inheritance mode can reduce errors. Here, I discuss the challenges of variant calling in polyploid WGS data and discuss where potential solutions can be integrated into a standard variant calling pipeline.

Genomic landscapes of divergence among island bird populations: Evidence of parallel adaptation but at different loci?

When populations colonise new environments, they may be exposed to novel selection pressures but also suffer from extensive genetic drift due to founder effects, small population sizes and limited interpopulation gene flow. Genomic approaches enable us to study how these factors drive divergence, and disentangle neutral effects from differentiation at specific loci due to selection. Here, we investigate patterns of genetic diversity and divergence using whole-genome resequencing (>22× coverage) in Berthelot's pipit (Anthus berthelotii), a passerine endemic to the islands of three north Atlantic archipelagos. Strong environmental gradients, including in pathogen pressure, across populations in the species range, make it an excellent system in which to explore traits important in adaptation and/or incipient speciation. First, we quantify how genomic divergence accumulates across the speciation continuum, that is, among Berthelot's pipit populations, between sub species across archipelagos, and between Berthelot's pipit and its mainland ancestor, the tawny pipit (Anthus campestris). Across these colonisation timeframes (2.1 million-ca. 8000 years ago), we identify highly differentiated loci within genomic islands of divergence and conclude that the observed distributions align with expectations for non-neutral divergence. Characteristic signatures of selection are identified in loci associated with craniofacial/bone and eye development, metabolism and immune response between population comparisons. Interestingly, we find limited evidence for repeated divergence of the same loci across the colonisation range but do identify different loci putatively associated with the same biological traits in different populations, likely due to parallel adaptation. Incipient speciation across these island populations, in which founder effects and selective pressures are strong, may therefore be repeatedly associated with morphology, metabolism and immune defence.

Novel Allelic Gene Variations in CmCLAVATA3 (CmCLV3) Were Identified in a Genetic Population of Melon (Cucumis melo L.)

Carpel number (CN) is an important trait affecting the fruit size and shape of melon, which plays a crucial role in determining the overall appearance and market value. A unique non-synonymous single nucleotide polymorphism (SNP) in CmCLAVATA3 (CmCLV3) is responsible for the variation of CN in C. melo ssp. agrestis (hereafter agrestis), but it has been unclear in C. melo ssp. melo (hereafter melo). In this study, one major locus controlling the polymorphism of 5-CN (multi-CN) and 3-CN (normal-CN) in melo was identified using bulked segregant analysis (BSA-seq). This locus was then fine-mapped to an interval of 1.8 Mb on chromosome 12 using a segregating population containing 1451 progeny. CmCLV3 is still present in the candidate region. A new allele of CmCLV3, which contains five other nucleotide polymorphisms, including a non-synonymous SNP in coding sequence (CDS), except the SNP reported in agrestis, was identified in melo. A cis-trans test confirmed that the candidate gene, CmCLV3, contributes to the variation of CNs in melo. The qRT-PCR results indicate that there is no significant difference in the expression level of CmCLV3 in the apical stem between the multi-CN plants and the normal-CN plants. Overall, this study provides a genetic resource for melon fruit development research and molecular breeding. Additionally, it suggests that melo has undergone similar genetic selection but evolved into an independent allele.

SNP-SVant: A Computational Workflow to Predict and Annotate Genomic Variants in Organisms Lacking Benchmarked Variants

Whole-genome sequencing is widely used to investigate population genomic variation in organisms of interest. Assorted tools have been independently developed to call variants from short-read sequencing data aligned to a reference genome, including single nucleotide polymorphisms (SNPs) and structural variations (SVs). We developed SNP-SVant, an integrated, flexible, and computationally efficient bioinformatic workflow that predicts high-confidence SNPs and SVs in organisms without benchmarked variants, which are traditionally used for distinguishing sequencing errors from real variants. In the absence of these benchmarked datasets, we leverage multiple rounds of statistical recalibration to increase the precision of variant prediction. The SNP-SVant workflow is flexible, with user options to tradeoff accuracy for sensitivity. The workflow predicts SNPs and small insertions and deletions using the Genome Analysis ToolKit (GATK) and predicts SVs using the Genome Rearrangement IDentification Software Suite (GRIDSS), and it culminates in variant annotation using custom scripts. A key utility of SNP-SVant is its scalability. Variant calling is a computationally expensive procedure, and thus, SNP-SVant uses a workflow management system with intermediary checkpoint steps to ensure efficient use of resources by minimizing redundant computations and omitting steps where dependent files are available. SNP-SVant also provides metrics to assess the quality of called variants and converts between VCF and aligned FASTA format outputs to ensure compatibility with downstream tools to calculate selection statistics, which are commonplace in population genomics studies. By accounting for both small and large structural variants, users of this workflow can obtain a wide-ranging view of genomic alterations in an organism of interest. Overall, this workflow advances our capabilities in assessing the functional consequences of different types of genomic alterations, ultimately improving our ability to associate genotypes with phenotypes. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Predicting single nucleotide polymorphisms and structural variations Support Protocol 1: Downloading publicly available sequencing data Support Protocol 2: Visualizing variant loci using Integrated Genome Viewer Support Protocol 3: Converting between VCF and aligned FASTA formats.

Nanopore Direct RNA Sequencing for Modified Uridine Nucleotides Yields Signals Dependent on the Physical Properties of the Modified Base

Sequencing for RNA modifications with the nanopore direct RNA sequencing platform provides ionic current levels, helicase dwell times, and base call data that differentiate the modifications from the canonical form. Herein, model RNAs were synthesized with site-specific uridine (U) base modifications that enable the study of increasing an alkyl group size, halogen identity, or a change in base acidity to impact the nanopore data. The analysis concluded that increases in alkyl size trend with greater current blockage but a similar change in base-call error was not found. The addition of a halogen series to C5 of U revealed that the current levels recorded a trend with the water-octanol partition coefficient of the base, as well as the base call error. Studies with U modifications that are deprotonated (i.e., anionic) under the sequencing conditions gave broad current levels that influenced the base call error. Some modifications led to helicase dwell time changes. These insights provide design parameters for modification-specific chemical reagents that can shift nanopore signatures to minimize false positive reads, a known issue with this sequencing approach.

Exploring COVID-19 causal genes through disease-specific Cis-eQTLs

Genome-wide association study (GWAS) analysis has exposed that genetic factors play important roles in COVID-19. Whereas a deeper understanding of the underlying mechanism of COVID-19 was hindered by the lack of expression of quantitative trait loci (eQTL) data specific for disease. To this end, we identified COVID-19-specific cis-eQTLs by integrating nucleotide sequence variations and RNA-Seq data from COVID-19 samples. These identified eQTLs have different regulatory effect on genes between patients and controls, indicating that SARS-CoV-2 infection may cause alterations in the human body's internal environment. Individuals with the TT genotype in the rs1128320 region seemed more susceptible to SARS-CoV-2 infection and developed into severe COVID-19 due to the abnormal expression of IFITM1. We subsequently discovered potential causal genes, of the result, a total of 48 genes from six tissues were identified. siRNA-mediated depletion assays in SARS-CoV-2 infection proved that 14 causal genes were directly associated with SARS-CoV-2 infection. These results enriched existing research on COVID-19 causal genes and provided a new sight in the mechanism exploration for COVID-19.

Identifying distant relatives using benchtop-scale sequencing

The genetic component of forensic genetic genealogy (FGG) is an estimate of kinship, often conducted at genome scales between a great number of individuals. The promise of FGG is substantial: in concert with genealogical records and other nongenetic information, it can indirectly identify a person of interest. A downside of FGG is cost, as it is currently expensive and requires chemistries uncommon to forensic genetic laboratories (microarrays and high throughput sequencing). The more common benchtop sequencers can be coupled with a targeted PCR assay to conduct FGG, though such approaches have limited resolution for kinship. This study evaluates low-pass sequencing, an alternative strategy that is accessible to benchtop sequencers and can produce resolutions comparable to high-pass sequencing. Samples from a three-generation pedigree were augmented to include up to 7th degree relatives (using whole genome pedigree simulations) and the ability to recover the true kinship coefficient was assessed using algorithms qualitatively similar to those found in GEDmatch. We show that up to 7th degree relatives can be reliably inferred from 1 × whole genome sequencing obtainable from desktop sequencers.

Genomic insights into local adaptation and phenotypic diversity of Wenchang chickens

Wenchang chicken, a prized local breed in Hainan Province of China renowned for its exceptional adaptability to tropical environments and good meat quality, is deeply favored by the public. However, an insufficient understanding of its population architecture and the unclear genetic basis that governs its typical attributes have posed challenges in the protection and breeding of this precious breed. To address these gaps, we conducted whole-genome resequencing on 200 Wenchang chicken samples derived from 10 distinct strains, and we gathered data on an array of 21 phenotype traits. Population genomics analysis unveiled distinctive population structures in Wenchang chickens, primarily attributed to strong artificial selection for different feather colors. Selection sweep analysis identified a group of candidate genes, including PCDH9, DPF3, CDIN1, and SUGCT, closely linked to adaptations that enhance resilience in tropical island habitats. Genome-wide association studies (GWAS) highlighted potential candidate genes associated with diverse feather color traits, encompassing TYR, RAB38, TRPM1, GABARAPL2, CDH1, ZMIZ1, LYST, MC1R, and SASH1. Through the comprehensive analysis of high-quality genomic and phenotypic data across diverse Wenchang chicken resource groups, this study unveils the intricate genetic backgrounds and population structures of Wenchang chickens. Additionally, it identifies multiple candidate genes linked to environmental adaptation, feather color variations, and production traits. These insights not only provide genetic reference for the purification and breeding of Wenchang chickens but also broaden our understanding of the genetic basis of phenotypic diversity in chickens.

Genetic analysis of transcription factors in dopaminergic neuronal development in Parkinson's disease

BACKGROUND

Genetic variants of dopaminergic transcription factor-encoding genes are suggested to be Parkinson's disease (PD) risk factors; however, no comprehensive analyses of these genes in patients with PD have been undertaken. Therefore, we aimed to genetically analyze 16 dopaminergic transcription factor genes in Chinese patients with PD.

METHODS

Whole-exome sequencing (WES) was performed using a Chinese cohort comprising 1917 unrelated patients with familial or sporadic early-onset PD and 1652 controls. Additionally, whole-genome sequencing (WGS) was performed using another Chinese cohort comprising 1962 unrelated patients with sporadic late-onset PD and 1279 controls.

RESULTS

We detected 308 rare and 208 rare protein-altering variants in the WES and WGS cohorts, respectively. Gene-based association analyses of rare variants suggested that MSX1 is enriched in sporadic late-onset PD. However, the significance did not pass the Bonferroni correction. Meanwhile, 72 and 1730 common variants were found in the WES and WGS cohorts, respectively. Unfortunately, single-variant logistic association analyses did not identify significant associations between common variants and PD.

CONCLUSIONS

Variants of 16 typical dopaminergic transcription factors might not be major genetic risk factors for PD in Chinese patients. However, we highlight the complexity of PD and the need for extensive research elucidating its etiology.

Nosocomial surveillance of multidrug-resistant Acinetobacter baumannii: a genomic epidemiological study

Acinetobacter baumannii is a major opportunistic pathogen causing hospital-acquired infections, and it is imperative to comprehend its evolutionary and epidemiological dynamics in hospitals to prevent and control nosocomial transmission. Here, we present a comprehensive genomic epidemiological study involving the genomic sequencing and antibiotic resistance profiling of 634 A. baumannii strains isolated from seven intensive care units (ICUs) of a Chinese general hospital over 2 consecutive years. Our study reveals that ST2 is highly dominant (90.54%) in the ICUs, with 98.90% of the ST2 exhibiting multidrug resistant or extensively drug resistant. Phylogenetic analyses of newly sequenced genomes and public data suggest that nosocomial isolates originated outside the hospital but evolved inside. The major lineages appear to be stable, with 9 of the 28 identified nosocomial epidemic clones infecting over 60% of the affected patients. However, outbreaks of two highly evolved clones have been observed in different hospitals, suggesting significant inter-hospital transmission chains. By coupling patient medical records and genomic divergence of the ST2, we found that cross-ward patient transfer played a crucial role in pathogen's nosocomial transmission. Additionally, we identified 831 potential adaptive evolutionary loci and 44 associated genes by grouping and comparing the genomes of clones with different prevalence. Overall, our study provides a comprehensive and contemporary survey on the epidemiology and genomic evolution of A. baumannii in a large Chinese general hospital. These findings shed light on the nosocomial evolution and transmission of A. baumannii and offers valuable information for transmission prevention and antibiotic therapy.IMPORTANCEThis study delved into the genomic evolution and transmission of nosocomial Acinetobacter baumannii on a large scale, spanning both an extended time period and the largest sample size to date. Through molecular epidemiological investigations based on genomics, we can directly trace the origin of the pathogen, detecting and monitoring outbreaks of infectious diseases in a timely manner, and ensuring public health safety. In addition, this study also collects a large amount of genomic and antibiotic resistance detection data, which is helpful for phenotype prediction based on genomic sequencing. It enables patients to receive personalized antibiotic treatment quickly, helps doctors select antibiotics more accurately, and contributes to reducing the use of antibiotics and lowering the risk of antibiotic resistance development.

Disruption of the TP53 locus in osteosarcoma leads to TP53 promoter gene fusions and restoration of parts of the TP53 signalling pathway

TP53 is the most frequently mutated gene in human cancer. This gene shows not only loss-of-function mutations but also recurrent missense mutations with gain-of-function activity. We have studied the primary bone malignancy osteosarcoma, which harbours one of the most rearranged genomes of all cancers. This is odd since it primarily affects children and adolescents who have not lived the long life thought necessary to accumulate massive numbers of mutations. In osteosarcoma, TP53 is often disrupted by structural variants. Here, we show through combined whole-genome and transcriptome analyses of 148 osteosarcomas that TP53 structural variants commonly result in loss of coding parts of the gene while simultaneously preserving and relocating the promoter region. The transferred TP53 promoter region is fused to genes previously implicated in cancer development. Paradoxically, these erroneously upregulated genes are significantly associated with the TP53 signalling pathway itself. This suggests that while the classical tumour suppressor activities of TP53 are lost, certain parts of the TP53 signalling pathway that are necessary for cancer cell survival and proliferation are retained. In line with this, our data suggest that transposition of the TP53 promoter is an early event that allows for a new normal state of genome-wide rearrangements in osteosarcoma. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Bioinformatics of germline variant discovery for rare disease diagnostics: current approaches and remaining challenges

Next-generation sequencing (NGS) has revolutionized the field of rare disease diagnostics. Whole exome and whole genome sequencing are now routinely used for diagnostic purposes; however, the overall diagnosis rate remains lower than expected. In this work, we review current approaches used for calling and interpretation of germline genetic variants in the human genome, and discuss the most important challenges that persist in the bioinformatic analysis of NGS data in medical genetics. We describe and attempt to quantitatively assess the remaining problems, such as the quality of the reference genome sequence, reproducible coverage biases, or variant calling accuracy in complex regions of the genome. We also discuss the prospects of switching to the complete human genome assembly or the human pan-genome and important caveats associated with such a switch. We touch on arguably the hardest problem of NGS data analysis for medical genomics, namely, the annotation of genetic variants and their subsequent interpretation. We highlight the most challenging aspects of annotation and prioritization of both coding and non-coding variants. Finally, we demonstrate the persistent prevalence of pathogenic variants in the coding genome, and outline research directions that may enhance the efficiency of NGS-based disease diagnostics.

Choosing the Best Tissue and Technique to Detect Mosaicism in Fibrous Dysplasia/McCune-Albright Syndrome (FD/MAS)

GNAS-activating somatic mutations give rise to Fibrous Dysplasia/McCune-Albright syndrome (FD/MAS). The low specificity of extra-skeletal signs of MAS and the mosaic status of the mutations generate some difficulties for a proper diagnosis. We studied the clinical and molecular statuses of 40 patients referred with a clinical suspicion of FD/MAS to provide some clues. GNAS was sequenced using both Sanger and Next-Generation Sequencing (NGS). We were able to identify the pathogenic variants in 25% of the patients. Most of them were identified in the affected tissue, but not in blood. Additionally, NGS demonstrated the ability to detect more patients with mosaicism (8/34) than Sanger sequencing (4/39). Even if in some cases, the clinical information was not complete, we confirmed that, as in previous works, when the patients were young children with a single manifestation, such as hyperpigmented skin macules or precocious puberty, the molecular diagnosis was usually negative. In conclusion, as FD/MAS is caused by mosaic variants, it is essential to use sensitive techniques that allow for the detection of low percentages and to choose the right tissue to study. When not possible, and due to the low positive genetic rate, patients with FD/MAS should only be genetically tested when the clinical diagnosis is really uncertain.

Leveraging Tissue-Specific Enhancer-Target Gene Regulatory Networks Identifies Enhancer Somatic Mutations That Functionally Impact Lung Cancer

Enhancers are noncoding regulatory DNA regions that modulate the transcription of target genes, often over large distances along with the genomic sequence. Enhancer alterations have been associated with various pathological conditions, including cancer. However, the identification and characterization of somatic mutations in noncoding regulatory regions with a functional effect on tumorigenesis and prognosis remain a major challenge. Here, we present a strategy for detecting and characterizing enhancer mutations in a genome-wide analysis of patient cohorts, across three lung cancer subtypes. Lung tissue-specific enhancers were defined by integrating experimental data and public epigenomic profiles, and the genome-wide enhancer-target gene regulatory network of lung cells was constructed by integrating chromatin three-dimensional architecture data. Lung cancers possessed a similar mutation burden at tissue-specific enhancers and exons but with differences in their mutation signatures. Functionally relevant alterations were prioritized on the basis of the pathway-level integration of the effect of a mutation and the frequency of mutations on individual enhancers. The genes enriched for mutated enhancers converged on the regulation of key biological processes and pathways relevant to tumor biology. Recurrent mutations in individual enhancers also affected the expression of target genes, with potential relevance for patient prognosis. Together, these findings show that noncoding regulatory mutations have a potential relevance for cancer pathogenesis and can be exploited for patient classification.

SIGNIFICANCE

Mapping enhancer-target gene regulatory interactions and analyzing enhancer mutations at the level of their target genes and pathways reveal convergence of recurrent enhancer mutations on biological processes involved in tumorigenesis and prognosis.

A genomic mutational constraint map using variation in 76,156 human genomes

The depletion of disruptive variation caused by purifying natural selection (constraint) has been widely used to investigate protein-coding genes underlying human disorders1-4, but attempts to assess constraint for non-protein-coding regions have proved more difficult. Here we aggregate, process and release a dataset of 76,156 human genomes from the Genome Aggregation Database (gnomAD)-the largest public open-access human genome allele frequency reference dataset-and use it to build a genomic constraint map for the whole genome (genomic non-coding constraint of haploinsufficient variation (Gnocchi)). We present a refined mutational model that incorporates local sequence context and regional genomic features to detect depletions of variation. As expected, the average constraint for protein-coding sequences is stronger than that for non-coding regions. Within the non-coding genome, constrained regions are enriched for known regulatory elements and variants that are implicated in complex human diseases and traits, facilitating the triangulation of biological annotation, disease association and natural selection to non-coding DNA analysis. More constrained regulatory elements tend to regulate more constrained protein-coding genes, which in turn suggests that non-coding constraint can aid the identification of constrained genes that are as yet unrecognized by current gene constraint metrics. We demonstrate that this genome-wide constraint map improves the identification and interpretation of functional human genetic variation.

The genome of a globally invasive passerine, the common myna, Acridotheres tristis

In an era of global climate change, biodiversity conservation is receiving increased attention. Conservation efforts are greatly aided by genetic tools and approaches, which seek to understand patterns of genetic diversity and how they impact species health and their ability to persist under future climate regimes. Invasive species offer vital model systems in which to investigate questions regarding adaptive potential, with a particular focus on how changes in genetic diversity and effective population size interact with novel selection regimes. The common myna (Acridotheres tristis) is a globally invasive passerine and is an excellent model species for research both into the persistence of low-diversity populations and the mechanisms of biological invasion. To underpin research on the invasion genetics of this species, we present the genome assembly of the common myna. We describe the genomic landscape of this species, including genome wide allelic diversity, methylation, repeats, and recombination rate, as well as an examination of gene family evolution. Finally, we use demographic analysis to identify that some native regions underwent a dramatic population increase between the two most recent periods of glaciation, and reveal artefactual impacts of genetic bottlenecks on demographic analysis.

Innovative construction of the first reliable catalogue of bovine circular RNAs

The aim of this study was to compare the circular transcriptome of divergent tissues in order to understand: i) the presence of circular RNAs (circRNAs) that are not exonic circRNAs, i.e. originated from backsplicing involving known exons and, ii) the origin of artificial circRNA (artif_circRNA), i.e. circRNA not generated in-vivo. CircRNA identification is mostly an in-silico process, and the analysis of data from the BovReg project (https://www.bovreg.eu/) provided an opportunity to explore new ways to identify reliable circRNAs. By considering 117 tissue samples, we characterized 23,926 exonic circRNAs, 337 circRNAs from 273 introns (191 ciRNAs, 146 intron circles), 108 circRNAs from small non-coding genes and nearly 36.6K circRNAs classified as other_circRNAs. Furthermore, for 63 of those samples we analysed in parallel data from total-RNAseq (ribosomal RNAs depleted prior to library preparation) with paired mRNAseq (library prepared with poly(A)-selected RNAs). The high number of circRNAs detected in mRNAseq, and the significant number of novel circRNAs, mainly other_circRNAs, led us to consider all circRNAs detected in mRNAseq as artificial. This study provided evidence of 189 false entries in the list of exonic circRNAs: 103 artif_circRNAs identified by total RNAseq/mRNAseq comparison using two circRNA tools, 26 probable artif_circRNAs, and 65 identified by deep annotation analysis. Extensive benchmarking was performed (including analyses with CIRI2 and CIRCexplorer-2) and confirmed 94% of the 23,737 reliable exonic circRNAs. Moreover, this study demonstrates the effectiveness of a panel of highly expressed exonic circRNAs (5-8%) in analysing the tissue specificity of the bovine circular transcriptome.

Identification and high-throughput genotyping of single nucleotide polymorphism markers in a non-model conifer (Abies nordmanniana (Steven) Spach)

Single nucleotide polymorphism (SNP) markers are powerful tools for investigating population structures, linkage analysis, and genome-wide association studies, as well as for breeding and population management. The availability of SNP markers has been limited to the most commercially important timber species, primarily due to the cost of genome sequencing required for SNP discovery. In this study, a combination of reference-based and reference-free approaches were used to identify SNPs in Nordmann fir (Abies nordmanniana), a species previously lacking genomic sequence information. Using a combination of a genome assembly of the closely related Silver fir (Abies alba) species and a de novo assembly of low-copy regions of the Nordmann fir genome, we identified a high density of reliable SNPs. Reference-based approaches identified two million SNPs in common between the Silver fir genome and low-copy regions of Nordmann fir. A combination of one reference-free and two reference-based approaches identified 250 shared SNPs. A subset of 200 SNPs were used to genotype 342 individuals and thereby tested and validated in the context of identity analysis and/or clone identification. The tested SNPs successfully identified all ramets per clone and five mislabeled individuals via identity and genomic relatedness analysis. The identified SNPs will be used in ad hoc breeding of Nordmann fir in Denmark.

Multi-locus genome-wide association study and genomic prediction for flowering time in chrysanthemum

MAIN CONCLUSION

Multi-locus GWAS detected several known and candidate genes responsible for flowering time in chrysanthemum. The associations could greatly increase the predictive ability of genome selection that accelerates the possible application of GS in chrysanthemum breeding. Timely flowering is critical for successful reproduction and determines the economic value for ornamental plants. To investigate the genetic architecture of flowering time in chrysanthemum, a multi-locus genome-wide association study (GWAS) was performed using a collection of 200 accessions and 330,710 single-nucleotide polymorphisms (SNPs) via 3VmrMLM method. Five flowering time traits including budding (FBD), visible colouring (VC), early opening (EO), full-bloom (OF) and senescing (SF) stages, plus five derived conditional traits were recorded in two environments. Extensive phenotypic variations were observed for these flowering time traits with coefficients of variation ranging from 6.42 to 38.27%, and their broad-sense heritability ranged from 71.47 to 96.78%. GWAS revealed 88 stable quantitative trait nucleotides (QTNs) and 93 QTN-by-environment interactions (QEIs) associated with flowering time traits, accounting for 0.50-8.01% and 0.30-10.42% of the phenotypic variation, respectively. Amongst the genes around these stable QTNs and QEIs, 21 and 10 were homologous to known flowering genes in Arabidopsis; 20 and 11 candidate genes were mined by combining the functional annotation and transcriptomics data, respectively, such as MYB55, FRIGIDA-like, WRKY75 and ANT. Furthermore, genomic selection (GS) was assessed using three models and seven unique marker datasets. We found the prediction accuracy (PA) using significant SNPs identified by GWAS under SVM model exhibited the best performance with PA ranging from 0.90 to 0.95. Our findings provide new insights into the dynamic genetic architecture of flowering time and the identified significant SNPs and candidate genes will accelerate the future molecular improvement of chrysanthemum.

SMARCB1 loss activates patient-specific distal oncogenic enhancers in malignant rhabdoid tumors

Malignant rhabdoid tumor (MRT) is a highly malignant and often lethal childhood cancer. MRTs are genetically defined by bi-allelic inactivating mutations in SMARCB1, a member of the BRG1/BRM-associated factors (BAF) chromatin remodeling complex. Mutations in BAF complex members are common in human cancer, yet their contribution to tumorigenesis remains in many cases poorly understood. Here, we study derailed regulatory landscapes as a consequence of SMARCB1 loss in the context of MRT. Our multi-omics approach on patient-derived MRT organoids reveals a dramatic reshaping of the regulatory landscape upon SMARCB1 reconstitution. Chromosome conformation capture experiments subsequently reveal patient-specific looping of distal enhancer regions with the promoter of the MYC oncogene. This intertumoral heterogeneity in MYC enhancer utilization is also present in patient MRT tissues as shown by combined single-cell RNA-seq and ATAC-seq. We show that loss of SMARCB1 activates patient-specific epigenetic reprogramming underlying MRT tumorigenesis.

Improving the filtering of false positive single nucleotide variations by combining genomic features with quality metrics

MOTIVATION

Technical errors in sequencing or bioinformatics steps and difficulties in alignment at some genomic sites result in false positive (FP) variants. Filtering based on quality metrics is a common method for detecting FP variants, but setting thresholds to reduce FP rates may reduce the number of true positive variants by overlooking the more complex relationships between features. The goal of this study is to develop a machine learning-based model for identifying FPs that integrates quality metrics with genomic features and with the feature interpretability property to provide insights into model results.

RESULTS

We propose a random forest-based model that utilizes genomic features to improve identification of FPs. Further examination of the features shows that the newly introduced features have an important impact on the prediction of variants misclassified by VEF, GATK-CNN, and GARFIELD, recently introduced FP detection systems. We applied cost-sensitive training to avoid errors in misclassification of true variants and developed a model that provides a robust mechanism against misclassification of true variants while increasing the prediction rate of FP variants. This model can be easily re-trained when factors such as experimental protocols might alter the FP distribution. In addition, it has an interpretability mechanism that allows users to understand the impact of features on the model's predictions.

AVAILABILITY AND IMPLEMENTATION

The software implementation can be found at https://github.com/ideateknoloji/FPDetect.

Prognostic potential of whole exome sequencing in the clinical management of metachronous colorectal cancer liver metastases

BACKGROUND

Colorectal cancer is a highly prevalent and deadly. The most common metastatic site is the liver. We performed a whole exome sequencing analysis of a series of metachronous colorectal cancer liver metastases (mCLM) and matched non-malignant liver tissues to investigate the genomic profile of mCLM and explore associations with the patients' prognosis and therapeutic modalities.

METHODS

DNA samples from mCLM and non-malignant liver tissue pairs (n = 41) were sequenced using whole exome target enrichment and their germline and somatic genetic variability, copy number variations, and mutational signatures were assessed for associations with relapse-free (RFS) and overall survival (OS).

RESULTS

Our genetic analysis could stratify all patients into existing targeted therapeutic regimens. The most commonly mutated genes in mCLM were TP53, APC, and KRAS together with PIK3CA and several passenger genes like ABCA13, FAT4, PCLO, and UNC80. Patients with somatic alterations in genes from homologous recombination repair, Notch, and Hedgehog pathways had significantly prolonged RFS, while those with altered MYC pathway genes had poor RFS. Additionally, alterations in the JAK-STAT pathway were prognostic of longer OS. Patients bearing somatic variants in VIPR2 had significantly shorter OS and those with alterations in MUC16 prolonged OS. Carriage of the KRAS-12D variant was associated with shortened survival in our and external datasets. On the other hand, tumor mutation burden, mismatch repair deficiency, microsatellite instability, mutational signatures, or copy number variation in mCLM had no prognostic value.

CONCLUSIONS

The results encourage further molecular profiling for personalized treatment of colorectal cancer liver metastases discerning metachronous from synchronous scenarios.

Mutation of key signaling regulators of cerebrovascular development in vein of Galen malformations

To elucidate the pathogenesis of vein of Galen malformations (VOGMs), the most common and most severe of congenital brain arteriovenous malformations, we performed an integrated analysis of 310 VOGM proband-family exomes and 336,326 human cerebrovasculature single-cell transcriptomes. We found the Ras suppressor p120 RasGAP (RASA1) harbored a genome-wide significant burden of loss-of-function de novo variants (2042.5-fold, p = 4.79 x 10-7). Rare, damaging transmitted variants were enriched in Ephrin receptor-B4 (EPHB4) (17.5-fold, p = 1.22 x 10-5), which cooperates with p120 RasGAP to regulate vascular development. Additional probands had damaging variants in ACVRL1, NOTCH1, ITGB1, and PTPN11. ACVRL1 variants were also identified in a multi-generational VOGM pedigree. Integrative genomic analysis defined developing endothelial cells as a likely spatio-temporal locus of VOGM pathophysiology. Mice expressing a VOGM-specific EPHB4 kinase-domain missense variant (Phe867Leu) exhibited disrupted developmental angiogenesis and impaired hierarchical development of arterial-capillary-venous networks, but only in the presence of a "second-hit" allele. These results illuminate human arterio-venous development and VOGM pathobiology and have implications for patients and their families.

Advantages and challenges associated with bisulfite-assisted nanopore direct RNA sequencing for modifications

Nanopore direct RNA sequencing is a technology that allows sequencing for epitranscriptomic modifications with the possibility of a quantitative assessment. In the present work, pseudouridine (Ψ) was sequenced with the nanopore before and after the pH 7 bisulfite reaction that yields stable ribose adducts at C1' of Ψ. The adducted sites produced greater base call errors in the form of deletion signatures compared to Ψ. Sequencing studies on E. coli rRNA and tmRNA before and after the pH 7 bisulfite reaction demonstrated that using chemically-assisted nanopore sequencing has distinct advantages for minimization of false positives and false negatives in the data. The rRNA from E. coli has 19 known U/C sequence variations that give similar base call signatures as Ψ, and therefore, are false positives when inspecting base call data; however, these sites are refractory to reacting with bisulfite as is easily observed in nanopore data. The E. coli tmRNA has a low occupancy Ψ in a pyrimidine-rich sequence context that is called a U representing a false negative; partial occupancy by Ψ is revealed after the bisulfite reaction. In a final study, 5-methylcytidine (m5C) in RNA can readily be observed after the pH 5 bisulfite reaction in which the parent C deaminates to U and the modified site does not react. This locates m5C when using bisulfite-assisted nanopore direct RNA sequencing, which is otherwise challenging to observe. The advantages and challenges of the overall approach are discussed.

Heat shock response in Sulfolobus acidocaldarius and first implications for cross-stress adaptation

Sulfolobus acidocaldarius, a thermoacidophilic crenarchaeon, frequently encounters temperature fluctuations, oxidative stress, and nutrient limitations in its environment. Here, we employed a high-throughput transcriptomic analysis to examine how the gene expression of S. acidocaldarius changes when exposed to high temperatures (92 °C). The data obtained was subsequently validated using quantitative reverse transcription-PCR (qRT-PCR) analysis. Our particular focus was on genes that are involved in the heat shock response, type-II Toxin-Antitoxin systems, and putative transcription factors. To investigate how S. acidocaldarius adapts to multiple stressors, we assessed the expression of these selected genes under oxidative and nutrient stresses using qRT-PCR analysis. The results demonstrated that the gene thβ encoding the β subunit of the thermosome, as well as hsp14 and hsp20, play crucial roles in the majority of stress conditions. Furthermore, we observed overexpression of at least eight different TA pairs belonging to the type II TA systems under all stress conditions. Additionally, four common transcription factors: FadR, TFEβ, CRISPR loci binding protein, and HTH family protein were consistently overexpressed across all stress conditions, indicating their significant role in managing stress. Overall, this work provides the first insight into molecular players involved in the cross-stress adaptation of S. acidocaldarius.

Invasive Californian death caps develop mushrooms unisexually and bisexually

Canonical sexual reproduction among basidiomycete fungi involves the fusion of two haploid individuals of different mating types, resulting in a heterokaryotic mycelial body made up of genetically different nuclei. Using population genomics data and experiments, we discover mushrooms of the invasive and deadly Amanita phalloides can also be homokaryotic; evidence of sexual reproduction by single, unmated individuals. In California, genotypes of homokaryotic mushrooms are also found in heterokaryotic mushrooms, implying nuclei of homokaryotic mycelia are also involved in outcrossing. We find death cap mating is controlled by a single mating type locus, but the development of homokaryotic mushrooms appears to bypass mating type gene control. Ultimately, sporulation is enabled by nuclei able to reproduce alone as well as with others, and nuclei competent for both unisexuality and bisexuality have persisted in invaded habitats for at least 17 but potentially as long as 30 years. The diverse reproductive strategies of invasive death caps are likely facilitating its rapid spread, suggesting a profound similarity between plant, animal and fungal invasions.

Super-enhancer hijacking drives ectopic expression of hedgehog pathway ligands in meningiomas

Hedgehog signaling mediates embryologic development of the central nervous system and other tissues and is frequently hijacked by neoplasia to facilitate uncontrolled cellular proliferation. Meningiomas, the most common primary brain tumor, exhibit Hedgehog signaling activation in 6.5% of cases, triggered by recurrent mutations in pathway mediators such as SMO. In this study, we find 35.6% of meningiomas that lack previously known drivers acquired various types of somatic structural variations affecting chromosomes 2q35 and 7q36.3. These cases exhibit ectopic expression of Hedgehog ligands, IHH and SHH, respectively, resulting in Hedgehog signaling activation. Recurrent tandem duplications involving IHH permit de novo chromatin interactions between super-enhancers within DIRC3 and a locus containing IHH. Our work expands the landscape of meningioma molecular drivers and demonstrates enhancer hijacking of Hedgehog ligands as a route to activate this pathway  in neoplasia.

Genetic and cultural adaptations underlie the establishment of dairy pastoralism in the Tibetan Plateau

BACKGROUND

Domestication and introduction of dairy animals facilitated the permanent human occupation of the Tibetan Plateau. Yet the history of dairy pastoralism in the Tibetan Plateau remains poorly understood. Little is known how Tibetans adapted to milk and dairy products.

RESULTS

We integrated archeological evidence and genetic analysis to show the picture that the dairy ruminants, together with dogs, were introduced from West Eurasia into the Tibetan Plateau since ~ 3600 years ago. The genetic admixture between the exotic and indigenous dogs enriched the candidate lactase persistence (LP) allele 10974A > G of West Eurasian origin in Tibetan dogs. In vitro experiments demonstrate that - 13838G > A functions as a LP allele in Tibetans. Unlike multiple LP alleles presenting selective signatures in West Eurasians and South Asians, the de novo origin of Tibetan-specific LP allele - 13838G > A with low frequency (~ 6-7%) and absence of selection corresponds - 13910C > T in pastoralists across eastern Eurasia steppe.

CONCLUSIONS

Results depict a novel scenario of genetic and cultural adaptations to diet and expand current understanding of the establishment of dairy pastoralism in the Tibetan Plateau.

Quantitative Analysis of RNA Polymerase Slippages for Production of P3N-PIPO Trans-frame Fusion Proteins in Potyvirids

Potyvirids, members of the family Potyviridae, produce the P3N-PIPO protein, which is crucial for the cell-to-cell transport of viral genomic RNAs. The production of P3N-PIPO requires an adenine (A) insertion caused by RNA polymerase slippage at a conserved GAAAAAA (GA6) sequence preceding the PIPO open reading frame. Presently, the slippage rate of RNA polymerase has been estimated in only a few potyvirids, ranging from 0.8 to 2.1%. In this study, we analyzed publicly available plant RNA-seq data and identified 19 genome contigs from 13 distinct potyvirids. We further investigated the RNA polymerase slippage rates at the GA6 motif. Our analysis revealed that the frequency of the A insertion variant ranges from 0.53 to 4.07% in 11 potyviruses (genus Potyvirus). For the two macluraviruses (genus Macluravirus), the frequency of the A insertion variant was found to be 0.72% and 10.96% respectively. Notably, the estimated RNA polymerase slippage rates for 12 out of the 13 investigated potyvirids were reported for the first time in this study. Our findings underscore the value of plant RNA-seq data for quantitative analysis of potyvirid genome variants, specifically at the GA6 slippage site, and contribute to a more comprehensive understanding of the RNA polymerase slippage phenomenon in potyvirids.

Clinical trio genome sequencing facilitates the interpretation of variants in cancer predisposition genes in paediatric tumour patients

The prevalence of pathogenic and likely pathogenic (P/LP) variants in genes associated with cancer predisposition syndromes (CPS) is estimated to be 8-18% for paediatric cancer patients. In more than half of the carriers, the family history is unsuspicious for CPS. Therefore, broad genetic testing could identify germline predisposition in additional children with cancer resulting in important implications for themselves and their families. We thus evaluated clinical trio genome sequencing (TGS) in a cohort of 72 paediatric patients with solid cancers other than retinoblastoma or CNS-tumours. The most prevalent cancer types were sarcoma (n = 26), neuroblastoma (n = 15), and nephroblastoma (n = 10). Overall, P/LP variants in CPS genes were identified in 18.1% of patients (13/72) and P/LP variants in autosomal-dominant CPS genes in 9.7% (7/72). Genetic evaluation would have been recommended for the majority of patients with P/LP variants according to the Jongmans criteria. Four patients (5.6%, 4/72) carried P/LP variants in autosomal-dominant genes known to be associated with their tumour type. With the immediate information on variant inheritance, TGS facilitated the identification of a de novo P/LP in NF1, a gonadosomatic mosaic in WT1 and two pathogenic variants in one patient (DICER1 and PALB2). TGS allows a more detailed characterization of structural variants with base-pair resolution of breakpoints which can be relevant for the interpretation of copy number variants. Altogether, TGS allows comprehensive identification of children with a CPS and supports the individualised clinical management of index patients and high-risk relatives.

Identifying crossovers and shared genetic material in whole genome sequencing data from families

Large, whole-genome sequencing (WGS) data sets containing families provide an important opportunity to identify crossovers and shared genetic material in siblings. However, the high variant calling error rates of WGS in some areas of the genome can result in spurious crossover calls, and the special inheritance status of the X Chromosome presents challenges. We have developed a hidden Markov model that addresses these issues by modeling the inheritance of variants in families in the presence of error-prone regions and inherited deletions. We call our method PhasingFamilies. We validate PhasingFamilies using the platinum genome family NA1281 (precision: 0.81; recall: 0.97), as well as simulated genomes with known crossover positions (precision: 0.93; recall: 0.92). Using 1925 quads from the Simons Simplex Collection, we found that PhasingFamilies resolves crossovers to a median resolution of 3527.5 bp. These crossovers recapitulate existing recombination rate maps, including for the X Chromosome; produce sibling pair IBD that matches expected distributions; and are validated by the haplotype estimation tool SHAPEIT. We provide an efficient, open-source implementation of PhasingFamilies that can be used to identify crossovers from family sequencing data.

The pig pangenome provides insights into the roles of coding structural variations in genetic diversity and adaptation

Structural variations have emerged as an important driving force for genome evolution and phenotypic variation in various organisms, yet their contributions to genetic diversity and adaptation in domesticated animals remain largely unknown. Here we constructed a pangenome based on 250 sequenced individuals from 32 pig breeds in Eurasia and systematically characterized coding sequence presence/absence variations (PAVs) within pigs. We identified 308.3-Mb nonreference sequences and 3438 novel genes absent from the current reference genome. Gene PAV analysis showed that 16.8% of the genes in the pangene catalog undergo PAV. A number of newly identified dispensable genes showed close associations with adaptation. For instance, several novel swine leukocyte antigen (SLA) genes discovered in nonreference sequences potentially participate in immune responses to productive and respiratory syndrome virus (PRRSV) infection. We delineated previously unidentified features of the pig mobilome that contained 490,480 transposable element insertion polymorphisms (TIPs) resulting from recent mobilization of 970 TE families, and investigated their population dynamics along with influences on population differentiation and gene expression. In addition, several candidate adaptive TE insertions were detected to be co-opted into genes responsible for responses to hypoxia, skeletal development, regulation of heart contraction, and neuronal cell development, likely contributing to local adaptation of Tibetan wild boars. These findings enhance our understanding on hidden layers of the genetic diversity in pigs and provide novel insights into the role of SVs in the evolutionary adaptation of mammals.

Illuminating the oral microbiome and its host interactions: recent advancements in omics and bioinformatics technologies in the context of oral microbiome research

The oral microbiota has an enormous impact on human health, with oral dysbiosis now linked to many oral and systemic diseases. Recent advancements in sequencing, mass spectrometry, bioinformatics, computational biology, and machine learning are revolutionizing oral microbiome research, enabling analysis at an unprecedented scale and level of resolution using omics approaches. This review contains a comprehensive perspective of the current state-of-the-art tools available to perform genomics, metagenomics, phylogenomics, pangenomics, transcriptomics, proteomics, metabolomics, lipidomics, and multi-omics analysis on (all) microbiomes, and then provides examples of how the techniques have been applied to research of the oral microbiome, specifically. Key findings of these studies and remaining challenges for the field are highlighted. Although the methods discussed here are placed in the context of their contributions to oral microbiome research specifically, they are pertinent to the study of any microbiome, and the intended audience of this includes researchers would simply like to get an introduction to microbial omics and/or an update on the latest omics methods. Continued research of the oral microbiota using omics approaches is crucial and will lead to dramatic improvements in human health, longevity, and quality of life.

Mapinsights: deep exploration of quality issues and error profiles in high-throughput sequence data

High-throughput sequencing (HTS) has revolutionized science by enabling super-fast detection of genomic variants at base-pair resolution. Consequently, it poses the challenging problem of identification of technical artifacts, i.e. hidden non-random error patterns. Understanding the properties of sequencing artifacts holds the key in separating true variants from false positives. Here, we develop Mapinsights, a toolkit that performs quality control (QC) analysis of sequence alignment files, capable of detecting outliers based on sequencing artifacts of HTS data at a deeper resolution compared with existing methods. Mapinsights performs a cluster analysis based on novel and existing QC features derived from the sequence alignment for outlier detection. We applied Mapinsights on community standard open-source datasets and identified various quality issues including technical errors related to sequencing cycles, sequencing chemistry, sequencing libraries and across various orthogonal sequencing platforms. Mapinsights also enables identification of anomalies related to sequencing depth. A logistic regression-based model built on the features of Mapinsights shows high accuracy in detecting 'low-confidence' variant sites. Quantitative estimates and probabilistic arguments provided by Mapinsights can be utilized in identifying errors, bias and outlier samples, and also aid in improving the authenticity of variant calls.

Circulating Tumor DNA Analysis on Metastatic Prostate Cancer with Disease Progression

The positivity rate of circulating tumor DNA (ctDNA) next-generation sequencing (NGS) varies among patients with metastatic prostate cancer (mPC), complicating its incorporation into regular practice. This retrospective study analyzed the ctDNA sequencing results of 100 mPC patients from May 2021 to March 2023 to identify the factors associated with positive ctDNA. Three custom gene panels were used for sequencing. Overall, 63% of the patients exhibited tier I/II somatic alterations, while 12% had pathogenic/likely pathogenic germline alterations. The key genes that were altered included AR, TP53, RB1, PTEN, and APC. Mutations in BRCA1/2, either germline or somatic, were observed in 21% of the patients. Among the metastatic castration-resistant prostate cancer (mCRPC) patients, the ctDNA-positive samples generally showed higher median prostate-specific antigen (PSA) levels and were more likely to be at the radiographic and clinical progressive disease stages, although they were not significantly associated with PSA progression. Our results suggest that ctDNA analysis could detect meaningful genetic changes in mPC patients, especially during disease progression.

An allelic-series rare-variant association test for candidate-gene discovery

Allelic series are of candidate therapeutic interest because of the existence of a dose-response relationship between the functionality of a gene and the degree or severity of a phenotype. We define an allelic series as a collection of variants in which increasingly deleterious mutations lead to increasingly large phenotypic effects, and we have developed a gene-based rare-variant association test specifically targeted to identifying genes containing allelic series. Building on the well-known burden test and sequence kernel association test (SKAT), we specify a variety of association models covering different genetic architectures and integrate these into a Coding-Variant Allelic-Series Test (COAST). Through extensive simulations, we confirm that COAST maintains the type I error and improves the power when the pattern of coding-variant effect sizes increases monotonically with mutational severity. We applied COAST to identify allelic-series genes for four circulating-lipid traits and five cell-count traits among 145,735 subjects with available whole-exome sequencing data from the UK Biobank. Compared with optimal SKAT (SKAT-O), COAST identified 29% more Bonferroni-significant associations with circulating-lipid traits, on average, and 82% more with cell-count traits. All of the gene-trait associations identified by COAST have corroborating evidence either from rare-variant associations in the full cohort (Genebass, n = 400,000) or from common-variant associations in the GWAS Catalog. In addition to detecting many gene-trait associations present in Genebass by using only a fraction (36.9%) of the sample, COAST detects associations, such as that between ANGPTL4 and triglycerides, that are absent from Genebass but that have clear common-variant support.

Short-read aligner performance in germline variant identification

MOTIVATION

Read alignment is an essential first step in the characterization of DNA sequence variation. The accuracy of variant-calling results depends not only on the quality of read alignment and variant-calling software but also on the interaction between these complex software tools.

RESULTS

In this review, we evaluate short-read aligner performance with the goal of optimizing germline variant-calling accuracy. We examine the performance of three general-purpose short-read aligners-BWA-MEM, Bowtie 2, and Arioc-in conjunction with three germline variant callers: DeepVariant, FreeBayes, and GATK HaplotypeCaller. We discuss the behavior of the read aligners with regard to the data elements on which the variant callers rely, and illustrate how the runtime configurations of these software tools combine to affect variant-calling performance.

AVAILABILITY AND IMPLEMENTATION

The quick brown fox jumps over the lazy dog.

Fine-mapping across diverse ancestries drives the discovery of putative causal variants underlying human complex traits and diseases

Genome-wide association studies (GWAS) of human complex traits or diseases often implicate genetic loci that span hundreds or thousands of genetic variants, many of which have similar statistical significance. While statistical fine-mapping in individuals of European ancestries has made important discoveries, cross-population fine-mapping has the potential to improve power and resolution by capitalizing on the genomic diversity across ancestries. Here we present SuSiEx, an accurate and computationally efficient method for cross-population fine-mapping, which builds on the single-population fine-mapping framework, Sum of Single Effects (SuSiE). SuSiEx integrates data from an arbitrary number of ancestries, explicitly models population-specific allele frequencies and LD patterns, accounts for multiple causal variants in a genomic region, and can be applied to GWAS summary statistics. We comprehensively evaluated SuSiEx using simulations, a range of quantitative traits measured in both UK Biobank and Taiwan Biobank, and schizophrenia GWAS across East Asian and European ancestries. In all evaluations, SuSiEx fine-mapped more association signals, produced smaller credible sets and higher posterior inclusion probability (PIP) for putative causal variants, and captured population-specific causal variants.

Exome-wide evidence of compound heterozygous effects across common phenotypes in the UK Biobank

Exome-sequencing association studies have successfully linked rare protein-coding variation to risk of thousands of diseases. However, the relationship between rare deleterious compound heterozygous (CH) variation and their phenotypic impact has not been fully investigated. Here, we leverage advances in statistical phasing to accurately phase rare variants (MAF ~ 0.001%) in exome sequencing data from 175,587 UK Biobank (UKBB) participants, which we then systematically annotate to identify putatively deleterious CH coding variation. We show that 6.5% of individuals carry such damaging variants in the CH state, with 90% of variants occurring at MAF < 0.34%. Using a logistic mixed model framework, systematically accounting for relatedness, polygenic risk, nearby common variants, and rare variant burden, we investigate recessive effects in common complex diseases. We find six exome-wide significant (P < 1.68 × 10 - 7 ) and 17 nominally significant (P < 5.25 × 10 - 5 ) gene-trait associations. Among these, only four would have been identified without accounting for CH variation in the gene. We further incorporate age-at-diagnosis information from primary care electronic health records, to show that genetic phase influences lifetime risk of disease across 20 gene-trait combinations (FDR < 5%). Using a permutation approach, we find evidence for genetic phase contributing to disease susceptibility for a collection of gene-trait pairs, including FLG-asthma (P = 0.00205 ) and USH2A-visual impairment (P = 0.0084 ). Taken together, we demonstrate the utility of phasing large-scale genetic sequencing cohorts for robust identification of the phenome-wide consequences of compound heterozygosity.

Target capture sequencing for the first Nigerian genotype I ASFV genome

African swine fever (ASF) is a contagious viral disease that affects domestic pigs and wild boars, causing significant economic losses globally. After the first Nigerian outbreak in 1997, there have been frequent reports of ASF in pig-producing regions in the country. To facilitate control, it is important to understand the genotype and phylogenetic relationship of ASF viruses (ASFVs). Recent genetic analysis of Nigerian ASFV isolates has revealed the presence of both genotypes I and II; this is based on analysis of a few selected genes. Phylogenetic analysis of ASFV whole genomes highlights virus origins and evolution in greater depth. However, there is currently no information on the ASFV genome from Nigerian isolates. Two ASFV-positive samples were detected during a random survey of 150 Nigerian indigenous pig samples collected in 2016. We assembled near-complete genomes of the two ASFV-positive samples using in-solution hybrid capture sequencing. The genome-wide phylogenetic tree assigned these two genomes into p72 genotype I, particularly close to the virulent Benin 97/1 strain. The two ASFVs share 99.94 and 99.92 % genomic sequence identity to Benin97/1. This provides insight into the origin and relationship of ASFV strains from Nigeria and Italy. The study reports for the first time the determination of near-complete genomes of ASFV using in-solution hybrid capture sequencing, which represents an important advance in understanding the global evolutionary landscape of ASFVs.

Development of a Next-generation Sequencing-based Gene Panel Test to Detect Measurable Residual Disease in Acute Myeloid Leukemia

Background

AML is a heterogeneous disease, and despite intensive therapy, recurrence is still high in AML patients who achieve the criterion for cytomorphologic remission (residual tumor burden [measurable residual disease, MRD]<5%). This study aimed to develop a targeted next-generation sequencing (NGS) panel to detect MRD in AML patients and validate its performance.

Methods

We designed an error-corrected, targeted MRD-NGS panel without using physical molecular barcodes, including 24 genes. Fifty-four bone marrow and peripheral blood samples from 23 AML patients were sequenced using the panel. The panel design was validated using reference material, and accuracy was assessed using droplet digital PCR.

Results

Dilution tests showed excellent linearity and a strong correlation between expected and observed clonal frequencies (R>0.99). The test reproducibly detected MRD in three dilution series samples, with a sensitivity of 0.25% for single-nucleotide variants. More than half of samples from patients with morphologic remission after one month of chemotherapy had detectable mutations. NGS-MRD positivity for samples collected after one month of chemotherapy tended to be associated with poor overall survival and progression-free survival.

Conclusions

Our highly sensitive and accurate NGS-MRD panel can be readily used to monitor most AML patients in clinical practice, including patients without gene rearrangement. In addition, this NGS-MRD panel may allow the detection of newly emerging clones during clinical relapse, leading to more reliable prognoses of AML.

The Sapria himalayana genome provides new insights into the lifestyle of endoparasitic plants

BACKGROUND

Sapria himalayana (Rafflesiaceae) is an endoparasitic plant characterized by a greatly reduced vegetative body and giant flowers; however, the mechanisms underlying its special lifestyle and greatly altered plant form remain unknown. To illustrate the evolution and adaptation of S. himalayasna, we report its de novo assembled genome and key insights into the molecular basis of its floral development, flowering time, fatty acid biosynthesis, and defense responses.

RESULTS

The genome of S. himalayana is ~ 1.92 Gb with 13,670 protein-coding genes, indicating remarkable gene loss (~ 54%), especially genes involved in photosynthesis, plant body, nutrients, and defense response. Genes specifying floral organ identity and controlling organ size were identified in S. himalayana and Rafflesia cantleyi, and showed analogous spatiotemporal expression patterns in both plant species. Although the plastid genome had been lost, plastids likely biosynthesize essential fatty acids and amino acids (aromatic amino acids and lysine). A set of credible and functional horizontal gene transfer (HGT) events (involving genes and mRNAs) were identified in the nuclear and mitochondrial genomes of S. himalayana, most of which were under purifying selection. Convergent HGTs in Cuscuta, Orobanchaceae, and S. himalayana were mainly expressed at the parasite-host interface. Together, these results suggest that HGTs act as a bridge between the parasite and host, assisting the parasite in acquiring nutrients from the host.

CONCLUSIONS

Our results provide new insights into the flower development process and endoparasitic lifestyle of Rafflesiaceae plants. The amount of gene loss in S. himalayana is consistent with the degree of reduction in its body plan. HGT events are common among endoparasites and play an important role in their lifestyle adaptation.

Hidden species diversity and mito-nuclear discordance within the Mediterranean cone snail, Lautoconus ventricosus

The Mediterranean cone snail, Lautoconus ventricosus, is currently considered a single species inhabiting the whole Mediterranean basin and the adjacent Atlantic coasts. Yet, no population genetic study has assessed its taxonomic status. Here, we collected 245 individuals from 75 localities throughout the Mediterranean Sea and used cox1 barcodes, complete mitochondrial genomes, and genome skims to test whether L. ventricosus represents a complex of cryptic species. The maximum likelihood phylogeny based on complete mitochondrial genomes recovered six main clades (hereby named blue, brown, green, orange, red, and violet) with sufficient sequence divergence to be considered putative species. On the other hand, phylogenomic analyses based on 437 nuclear genes only recovered four out of the six clades: blue and orange clades were thoroughly mixed and the brown one was not recovered. This mito-nuclear discordance revealed instances of incomplete lineage sorting and introgression, and may have caused important differences in the dating of main cladogenetic events. Species delimitation tests proposed the existence of at least three species: green, violet, and red+blue+orange (i.e., cyan). Green plus cyan (with sympatric distributions) and violet, had West and East Mediterranean distributions, respectively, mostly separated by the Siculo-Tunisian biogeographical barrier. Morphometric analyses of the shell using species hypotheses as factor and shell length as covariate showed that the discrimination power of the studied parameters was only 70.2%, reinforcing the cryptic nature of the uncovered species, and the importance of integrative taxonomic approaches considering morphology, ecology, biogeography, and mitochondrial and nuclear population genetic variation.

The genetic and phenotypic spectra of adult genetic leukoencephalopathies in a cohort of 309 patients

Genetic leukoencephalopathies (gLEs) are a highly heterogeneous group of rare genetic disorders. The spectrum of gLEs varies among patients of different ages. Distinct from the relatively more abundant studies of gLEs in children, only a few studies that explore the spectrum of adult gLEs have been published, and it should be noted that the majority of these excluded certain gLEs. Thus, to date, no large study has been designed and conducted to characterize the genetic and phenotypic spectra of gLEs in adult patients. We recruited a consecutive series of 309 adult patients clinically suspected of gLEs from Beijing Tiantan Hospital between January 2014 and December 2021. Whole-exome sequencing, mitochondrial DNA sequencing and repeat analysis of NOTCH2NLC, FMR1, DMPK and ZNF9 were performed for patients. We describe the genetic and phenotypic spectra of the set of patients with a genetically confirmed diagnosis and summarize their clinical and radiological characteristics. A total of 201 patients (65%) were genetically diagnosed, while 108 patients (35%) remained undiagnosed. The most frequent diseases were leukoencephalopathies related to NOTCH3 (25%), NOTCH2NLC (19%), ABCD1 (9%), CSF1R (7%) and HTRA1 (5%). Based on a previously proposed pathological classification, the gLEs in our cohort were divided into leukovasculopathies (35%), leuko-axonopathies (31%), myelin disorders (21%), microgliopathies (7%) and astrocytopathies (6%). Patients with NOTCH3 mutations accounted for 70% of the leukovasculopathies, followed by HTRA1 (13%) and COL4A1/2 (9%). The leuko-axonopathies contained the richest variety of associated genes, of which NOTCH2NLC comprised 62%. Among myelin disorders, demyelinating leukoencephalopathies (61%)-mainly adrenoleukodystrophy and Krabbe disease-accounted for the majority, while hypomyelinating leukoencephalopathies (2%) were rare. CSF1R was the only mutated gene detected in microgliopathy patients. Leukoencephalopathy with vanishing white matter disease due to mutations in EIF2B2-5 accounted for half of the astrocytopathies. We characterized the genetic and phenotypic spectra of adult gLEs in a large Chinese cohort. The most frequently mutated genes were NOTCH3, NOTCH2NLC, ABCD1, CSF1R and HTRA1.

C4S DB: Comprehensive Collection and Comparison for ChIP-Seq Database

Combining multiple binding profiles, such as transcription factors and histone modifications, is a crucial step in revealing the functions of complex biological systems. Although a massive amount of chromatin immunoprecipitation followed by sequencing (ChIP-seq) data is available, existing ChIP-seq databases or repositories focus on individual experiments, and it is difficult to elucidate orchestrated regulation by DNA-binding elements. We developed the Comprehensive Collection and Comparison for ChIP-Seq Database (C4S DB) to provide researchers with insights into the combination of DNA binding elements based on quality-assessed public ChIP-seq data. The C4S DB is based on > 16,000 human ChIP-seq experiments and provides two main web interfaces to discover the relationships between ChIP-seq data. "Gene browser" illustrates the landscape of distributions of binding elements around a specified gene, and "global similarity," a hierarchical clustering heatmap based on a similarity between two ChIP-seq experiments, gives an overview of genome-wide relations of regulatory elements. These functions promote the identification or evaluation of both gene-specific and genome-wide colocalization or mutually exclusive localization. Modern web technologies allow users to search for and aggregate large-scale experimental data through interactive web interfaces with quick responses. The C4S DB is available at https://c4s.site.

Improving variant calling using population data and deep learning

Large-scale population variant data is often used to filter and aid interpretation of variant calls in a single sample. These approaches do not incorporate population information directly into the process of variant calling, and are often limited to filtering which trades recall for precision. In this study, we develop population-aware DeepVariant models with a new channel encoding allele frequencies from the 1000 Genomes Project. This model reduces variant calling errors, improving both precision and recall in single samples, and reduces rare homozygous and pathogenic clinvar calls cohort-wide. We assess the use of population-specific or diverse reference panels, finding the greatest accuracy with diverse panels, suggesting that large, diverse panels are preferable to individual populations, even when the population matches sample ancestry. Finally, we show that this benefit generalizes to samples with different ancestry from the training data even when the ancestry is also excluded from the reference panel.

Allele-aware chromosome-level genome assembly of the autohexaploid Diospyros kaki Thunb

Artificially improving persimmon (Diospyros kaki Thunb.), one of the most important fruit trees, remains challenging owing to the lack of reference genomes. In this study, we generated an allele-aware chromosome-level genome assembly for the autohexaploid persimmon 'Xiaoguotianshi' (Chinese-PCNA type) using PacBio CCS and Hi-C technology. The final assembly contained 4.52 Gb, with a contig N50 value of 5.28 Mb and scaffold N50 value of 44.01 Mb, of which 4.06 Gb (89.87%) of the assembly were anchored onto 90 chromosome-level pseudomolecules comprising 15 homologous groups with 6 allelic chromosomes in each. A total of 153,288 protein-coding genes were predicted, of which 98.60% were functionally annotated. Repetitive sequences accounted for 64.02% of the genome; and 110,480 rRNAs, 12,297 tRNAs, 1,483 miRNAs, and 3,510 snRNA genes were also identified. This genome assembly fills the knowledge gap in the autohexaploid persimmon genome, which is conducive in the study on the regulatory mechanisms underlying the major economically advantageous traits of persimmons and promoting breeding programs.