Analysis of genetic inheritance in a family quartet by whole-genome sequencing

A newly identified pathology of episodic angioedema with hypereosinophilia (Gleich syndrome) revealed by nultiomics analysis

Background

Episodic angioedema with eosinophilia (Gleich syndrome) is a rare disease marked by periodic angioedema, fever, and severe eosinophilia, with limited understanding of its pathogenesis.

Objective

We sought to identify pathogenic factors contributing to severe Gleich syndrome through a comprehensive multiomics approach, using whole-genome sequencing (WGS) and RNA sequencing (RNA-seq).

Methods

A multiomics analysis was conducted on a 16- to 20-year-old female patient with severe Gleich syndrome, presenting with periodic high fever, extensive urticaria/eczema, and marked eosinophilia. The analysis included WGS and RNA-seq of blood samples.

Results

WGS revealed high-impact pathogenic mutations that have the potential to significantly alter gene function in 16 genes, including PR domain containing 16 (gene involved in transcriptional regulation). RNA-seq identified differentially expressed genes linked to immune response regulation and viral defense. Combined z-score analysis of WGS and RNA-seq highlighted angiotensin-converting enzyme as a key gene, with significant downregulation during disease progression that normalized with treatment. IFNG was also implicated.

Conclusions

The findings suggest that decreased angiotensin-converting enzyme expression, driven by PR domain containing 16 (gene involved in transcriptional regulation) mutations and altered IFNG expression, may contribute to increased bradykinin levels and activation of the arachidonic acid cascade, leading to the severe inflammation and angioedema characteristic of Gleich syndrome. This study underscores the utility of integrating WGS and RNA-seq data in elucidating the molecular basis of rare diseases and offers a foundation for developing therapeutic strategies for hypereosinophilic syndromes.

Unveiling the Phenotypic Spectrum of Miller Syndrome: A Systematic Review

Miller syndrome is an extremely rare condition in the group of facial dysostosis syndromes. These syndromes have great phenotypic overlap and variability, even within families. To facilitate the differentiation of Miller syndrome from related facial dysostosis syndromes, such as Treacher Collins and Nager syndrome, this study aims to provide an overview of the phenotypic spectrum of the syndrome. A systematic literature search of Embase, MEDLINE/PubMed, Web of Science, and CINAHL was conducted until November 2024. Case reports and case series of patients with a clinical or genetic diagnosis of Miller syndrome in all languages were included. The quality of the included reports was assessed using the Joanna Briggs Institute critical appraisal tool and the Fichas de Lectura Critica 3.0 web application. In total, 44 cases of Miller syndrome were found, with only 18.2% having genetic confirmation. Craniofacial anomalies were prominent, including midface hypoplasia (72.7%) and micrognathia (75.0%), orofacial clefts (77.3%), eyelid anomalies (70.5%), and external ear anomalies (63.6%). Limb anomalies were present in all cases, primarily involving the hands (95.5%), forearms (52.3%), and feet (90.9%). Anomalies in other extracraniofacial tracts were also reported. Despite limitations, including limited genetic confirmation and reliance on literature, this study provides valuable insights into the phenotypic spectrum of Miller syndrome. Efforts for genetic confirmation, international collaboration, and comprehensive reporting are essential to advance research and care for rare conditions like Miller syndrome. Therefore, a detailed checklist for phenotypic evaluation in Miller syndrome cases is provided in this study.

Molecular characterization of doublesex and Mab-3 (DMRT) gene family in Ctenopharyngodon idella (grass carp)

Doublesex and Mab-3 (DMRT) gene family is a diverse group of transcriptional factors crucially involved in sex differentiation and biological processes such as body growth and differentiation in vertebrates. In this study, we analyzed DMRT genes structural characterization and physiochemical properties, and elucidated their functional role as a ligand of different gonadal receptors including androgen (AR), estrogen β (ER-β), estrogen γ (ER-γ), and progesterone (PR). All six genes of the DMRT gene family in grass carp (Ctenopharyngodon Idella Valenciennes, 1844) exhibited an acidic nature. These DMRT genes are primarily localized in the nucleus, where they play a role in DNA binding via doublesex DNA binding motif. All the DMRT gene pairs are under strong purifying selection with two segmental duplications envisaged about 18.30 (DMRT3a/DMRTA2) and 24.90 (DMRT2b/DMRT2a) million years ago (MYA). Recombination analysis revealed six potential recombinant breakpoints posing substantial evolutionary pressure for diverse cellular functioning of DMRT isoforms. Moreover, the DMRTA1 protein had a highest binding affinity of - 270.42 and - 267.16 for androgen receptors (AR) and progesterone receptors (PR), whereas, for estrogen receptors ER-β and ER-γ, the maximum binding affinity was observed with DMRT2a and DMRT2b proteins showing a docking score of - 254.22 and - 261.71, respectively. First time we studied the binding scores and interface residues of the DMRT genes as a ligand of gonadal receptors that play a crucial role in fish growth, sex development and differentiation, and spermatogenesis and oocyte maturation. The present study provides a molecular basis for DMRT genes in grass carp that may serve as a reference for in-depth phylogenomic study in other species.

Quantifying the effects of computational filter criteria on the accurate identification of de novo mutations at varying levels of sequencing coverage

The rate of spontaneous (de novo) germline mutation is a key parameter in evolutionary biology, impacting genetic diversity and contributing to the evolution of populations and species. Mutation rates themselves evolve over time but the mechanisms underlying the mutation rate variation observed across the Tree of Life remain largely to be elucidated. In recent years, whole genome sequencing has enabled the estimation of mutation rates for several organisms. However, due to a lack of community standards, many previous studies differ both empirically - most notably, in the depth of sequencing used to reliably identify de novo mutations - and computationally - utilizing different computational pipelines to detect germline mutations as well as different analysis strategies to mitigate technical artifacts - rendering comparisons between studies challenging. Using a pedigree of Western chimpanzees as an illustrative example, we here quantify the effects of commonly utilized quality metrics to reliably identify de novo mutations at different levels of sequencing coverage. We demonstrate that datasets with a mean depth of ≤ 30X are ill-suited for the detection of de novo mutations due to high false positive rates that can only be partially mitigated by computational filter criteria. In contrast, higher coverage datasets enable a comprehensive identification of de novo mutations at low false positive rates, with minimal benefits beyond a sequencing coverage of 60X, suggesting that future work should favor breadth (by sequencing additional individuals) over depth. Importantly, the simulation and analysis framework described here provides conceptual guidelines that will allow researchers to take study design and species-specific resources into account when determining computational filtering strategies for their organism of interest.

Estimating mutation rate and characterising single nucleotide de novo mutations in pigs

BACKGROUND

Direct estimates of mutation rates in humans have changed our understanding of evolutionary timing and de novo mutations (DNM) have been associated with several developmental disorders in humans. Livestock species, including pigs, can contribute to the study of DNM because of their ideal population structure and routine phenotype collection. In principle, there is the potential for livestock populations to quickly accumulate new genetic variants because of short generation intervals and high selection intensity. However, the impact of DNM on the fitness of individuals is not known and with current genomic selection programs they cannot contribute to estimated breeding values. The aims of our project were to detect and validate single nucleotide DNM in two commercial pig breeding lines, estimate the single nucleotide mutation rate, and characterise DNM.

RESULTS

We sequenced (150 bp paired end reads, 30X coverage) 46 pig trios from two commercial lines. Single nucleotide DNM were detected using a trio-aware method. We defined candidate DNM as single nucleotide variants (SNVs) found in heterozygous state in trio-offspring with both trio-parents homozygous for the reference allele. In this study, we estimate a lower threshold of the DNM rate in pigs of 6.3 × 10-9 per site per gamete. Our findings are consistent with those from other mammals and those published for a small number of livestock species. Most DNM we detected were in introns (47%) and intergenic regions (49%). The mutational spectrum in pigs differs from that in humans and we found several DNM predicted to have an effect on animal's fitness based on the base pair change and their location in the genome.

CONCLUSIONS

With this study, we have generated fundamental knowledge on mutation rate in a non-primate species and identified DNM that could have an impact on the fitness of individuals.

Common variation in meiosis genes shapes human recombination phenotypes and aneuploidy risk

The leading cause of human pregnancy loss is aneuploidy, often tracing to errors in chromosome segregation during female meiosis. While abnormal crossover recombination is known to confer risk for aneuploidy, limited data have hindered understanding of the potential shared genetic basis of these key molecular phenotypes. To address this gap, we performed retrospective analysis of preimplantation genetic testing data from 139,416 in vitro fertilized embryos from 22,850 sets of biological parents. By tracing transmission of haplotypes, we identified 3,656,198 crossovers, as well as 92,485 aneuploid chromosomes. Counts of crossovers were lower in aneuploid versus euploid embryos, consistent with their role in chromosome pairing and segregation. Our analyses further revealed that a common haplotype spanning the meiotic cohesin SMC1B is significantly associated with both crossover count and maternal meiotic aneuploidy, with evidence supporting a non-coding cis-regulatory mechanism. Transcriptome- and phenome-wide association tests also implicated variation in the synaptonemal complex component C14orf39 and crossover-regulating ubiquitin ligases CCNB1IP1 and RNF212 in meiotic aneuploidy risk. More broadly, recombination and aneuploidy possess a partially shared genetic basis that also overlaps with reproductive aging traits. Our findings highlight the dual role of recombination in generating genetic diversity, while ensuring meiotic fidelity.

A structured coalescent model reveals deep ancestral structure shared by all modern humans

Understanding the history of admixture events and population size changes leading to modern humans is central to human evolutionary genetics. Here we introduce a coalescence-based hidden Markov model, cobraa, that explicitly represents an ancestral population split and rejoin, and demonstrate its application on simulated and real data across multiple species. Using cobraa, we present evidence for an extended period of structure in the history of all modern humans, in which two ancestral populations that diverged ~1.5 million years ago came together in an admixture event ~300 thousand years ago, in a ratio of ~80:20%. Immediately after their divergence, we detect a strong bottleneck in the major ancestral population. We inferred regions of the present-day genome derived from each ancestral population, finding that material from the minority correlates strongly with distance to coding sequence, suggesting it was deleterious against the majority background. Moreover, we found a strong correlation between regions of majority ancestry and human-Neanderthal or human-Denisovan divergence, suggesting the majority population was also ancestral to those archaic humans.

Human deleterious mutation rate slows adaptation and implies high fitness variance

Each new human has an expectedU d = 2 - 10 new deleterious mutations. Using a novel approach to capture complex linkage disequilibria from highU d using genome-wide simulations, we confirm that fitness decline due to the fixation of many slightly deleterious mutations can be compensated by rarer beneficial mutations of larger effect. The evolution of increased genome size and complexity have previously been attributed to a similarly asymmetric pattern of fixations, but we propose that the cause might be highU d rather than the small population size posited as causal by drift barrier theory. High within-population variance in relative fitness is an inevitable consequence of highU d ∼ 2 - 10 combined with inferred human deleterious effect sizes; two individuals will typically differ in fitness by 15-40%. The need to compensate for the deluge of deleterious mutations slows net adaptation (i.e. to the external environment) by ~13%-55%. The rate of beneficial fixations is more sensitive to changes in the mutation rate than the rate of deleterious fixations is. As a surprising consequence of this, an increase (e.g. 10%) in overall mutation rate leads to faster adaptation; this puts to rest dysgenic fears about increasing mutation rates due to rising paternal age.

Characterizing the Rates and Patterns of De Novo Germline Mutations in the Aye-Aye (Daubentonia madagascariensis)

Given the many levels of biological variation in mutation rates observed to date in primates-spanning from species to individuals to genomic regions-future steps in our understanding of mutation rate evolution will not only be aided by a greater breadth of species coverage across the primate clade but also by a greater depth as afforded by an evaluation of multiple trios within individual species. In order to help bridge these gaps, we here present an analysis of a species representing one of the most basal splits on the primate tree (aye-ayes), combining whole-genome sequencing of seven parent-offspring trios from a three-generation pedigree with a novel computational pipeline that takes advantage of recently developed pan-genome graphs, thereby circumventing the application of (highly subjective) quality metrics that has previously been shown to result in notable differences in the detection of de novo mutations and ultimately estimates of mutation rates. This deep sampling has enabled both a detailed picture of parental age effects and sex dependency in mutation rates, which we here compare with previously studied primates, but has also provided unique insights into the nature of genetic variation in one of the most endangered primates on the planet.

A T2T-CHM13 recombination map and globally diverse haplotype reference panel improves phasing and imputation

The T2T-CHM13 complete human reference genome contains ~200 Mb of newly resolved sequence, improving read mapping and variant calling compared to GRCh38. However, the benefits of using complete reference genomes in other contexts are unclear. Here, we present a reference T2T-CHM13 recombination map and phased haplotype panel derived from 3202 samples from the 1000 Genomes Project (1KGP). Using published long-read based assemblies as a reference-neutral ground truth, we compared our T2T-CHM13 1KGP panel to the previously released GRCh38 1KGP phased callset. We find that alignment to T2T-CHM13 resulted in 38% fewer assembly-discordant genotypes and 16% fewer switch errors. The largest gains in panel accuracy are observed on chromosome X and in the regions flanking disease-causing CNVs. Simons Genome Diversity Project samples were more accurately imputed when using the T2T-CHM13 panel. Our study demonstrates that use of a T2T-native phased haplotype panel improves statistical phasing and imputation for samples from diverse human populations.

Expert consensus on classification and diagnosis of congenital orofacial cleft

Congenital orofacial cleft, the most common birth defect in the maxillofacial region, exhibits a wide range of prognosis depending on the severity of deformity and underlying etiology. Non-syndromic congenital orofacial clefts typically present with milder deformities and more favorable treatment outcomes, whereas syndromic congenital orofacial clefts often manifest with concomitant organ abnormalities, which pose greater challenges for treatment and result in poorer prognosis. This consensus provides an elaborate classification system for varying degrees of orofacial clefts along with corresponding diagnostic and therapeutic guidelines. Results serve as a crucial resource for families to navigate prenatal screening results or make informed decisions regarding treatment options while also contributing significantly to preventing serious birth defects within the development of population.

Transgenerational effects of paternal exposures: the role of germline de novo mutations

Germline de novo mutations (DNMs) refer to spontaneous mutations arising during gametogenesis, resulting in genetic changes within germ cells that are subsequently transmitted to the next generation. While the impact of maternal exposures on germline DNMs has been extensively studied, more recent studies have begun to highlight the increasing importance of the effects of paternal factors. In this review, we have summarized the existing literature on how various exposures experienced by fathers affect the germline DNM burden in their spermatozoa, as well as their consequences for semen analysis parameters, pregnancy outcomes, and offspring health. A growing body of literature supports the conclusion that advanced paternal age (APA) correlates with a higher germline DNM rate in offspring. Furthermore, lifestyle choices, environmental toxins, assisted reproductive techniques (ART), and chemotherapy are associated with the accumulation of paternal DNMs in spermatozoa, with deleterious consequences for pregnancy outcomes and offspring health. Ultimately, our review highlights the clear importance of the germline DNM mode of inheritance, and the current understanding of how this is affected by various paternal factors. In addition, we explore conflicting reports or gaps of knowledge that should be addressed in future research.

How Have Massively Parallel Sequencing Technologies Furthered Our Understanding of Oncogenesis and Cancer Progression?

Massively parallel sequencing technologies have been a boon to many fields of biological science, including oncology. Cancer is an umbrella term for many diseases featuring abnormal cellular growth due to genetic and epigenetic aberrations. Advances in sequencing technology allow for interrogation of the DNA and RNA of cancer cells and other cells in the tumor microenvironment down to a single-base resolution. However, these strides come after a rich history of ground-breaking biological assays, like the discovery of the Philadelphia chromosome in the context of leukemia. Many specific genetic and epigenetic modifications have been implicated in oncogenesis, cancer progression, and response to treatment. Sequencing technologies have also helped to associate populations of bacteria in the microbiome to cancer development and prognosis. However, all this new information, especially when procured via high-throughput methods, comes at the cost of being more computationally and staff-resource intensive. There is also more risk to the privacy of the individuals with sequenced genomes. Notwithstanding, the overall benefit of sequencing technologies can greatly outweigh the risks with careful advancements and continued focus on the goal: helping those affected by cancer via precision medicine. Cancer biology has been and will continue to be elucidated by sequencing innovations in ways unimaginable without it.

Detection of De Novo Mutations by Sequencing Reduced Representation Libraries

De novo mutations (DNMs) are spontaneous genetic alterations not present in parents but occurring in the germline and transmitted to offspring. These mutations play a vital role in understanding evolutionary processes, genetic diversity, and impacts on species' fitness and survival. The identification of DNMs is especially crucial in the context of environmental stresses, such as those induced by nuclear accidents like Fukushima. This chapter describes recent advances in high-throughput sequencing technologies that have enhanced our capacity to detect DNMs within a single generation. Due to challenges associated with whole-genome resequencing in nonmodel organisms with high genetic and environmental heterogeneity, we proposed the use of genetic marker-based methods like Restriction site-Associated DNA Sequencing (RADSeq). RADSeq simplifies the detection of DNMs by using restriction enzymes to cut DNA at specific sites, producing manageable fragments for sequencing that represent the entire genome. This method allows for the targeted analysis of genetic variations across large populations and is particularly effective in detecting DNMs from wide range of populations, providing insight into damages and adaptations required for different biological conditions.

Estimating evolutionary and demographic parameters via ARG-derived IBD

Inference of evolutionary and demographic parameters from a sample of genome sequences often proceeds by first inferring identical-by-descent (IBD) genome segments. By exploiting efficient data encoding based on the ancestral recombination graph (ARG), we obtain three major advantages over current approaches: (i) no need to impose a length threshold on IBD segments, (ii) IBD can be defined without the hard-to-verify requirement of no recombination, and (iii) computation time can be reduced with little loss of statistical efficiency using only the IBD segments from a set of sequence pairs that scales linearly with sample size. We first demonstrate powerful inferences when true IBD information is available from simulated data. For IBD inferred from real data, we propose an approximate Bayesian computation inference algorithm and use it to show that even poorly-inferred short IBD segments can improve estimation. Our mutation-rate estimator achieves precision similar to a previously-published method despite a 4 000-fold reduction in data used for inference, and we identify significant differences between human populations. Computational cost limits model complexity in our approach, but we are able to incorporate unknown nuisance parameters and model misspecification, still finding improved parameter inference.

Characterizing the rates and patterns of de novo germline mutations in the aye-aye (Daubentonia madagascariensis)

Given the many levels of biological variation in mutation rates observed to date in primates - spanning from species to individuals to genomic regions - future steps in our understanding of mutation rate evolution will be aided by both a greater breadth of species coverage across the primate clade, but also by a greater depth as afforded by an evaluation of multiple trios within individual species. In order to help bridge these gaps, we here present an analysis of a species representing one of the most basal splits on the primate tree (aye-ayes), combining whole-genome sequencing of seven parent-offspring trios from a three-generation pedigree with a novel computational pipeline that takes advantage of recently developed pan-genome graphs, thereby circumventing the application of (highly subjective) quality metrics that has previously been shown to result in notable differences in the detection of de novo mutations, and ultimately estimates of mutation rates. This deep sampling has enabled both a detailed picture of parental age effects as well as sex dependency in mutation rates which we here compare with previously studied primates, but has also provided unique insights into the nature of genetic variation in one of the most endangered primates on the planet.

Characterization and distribution of de novo mutations in the zebra finch

Germline de novo mutations (DNMs) provide the raw material for evolution. The DNM rate varies considerably between species, sexes and chromosomes. Here, we identify DNMs in the zebra finch (Taeniopygia guttata) across 16 parent-offspring trios using two genome assemblies of different quality. Using an independent genotyping assay, we validate 82% of the 150 candidate DNMs. DNM rates are consistent between both assemblies, with estimates of 6.14 × 10-9 and 6.36 × 10-9 per site per generation. We observe a strong paternal bias in DNM rates (male-to-female ratio ɑ ≈ 4), but this bias is in transition mutations only, leading to a transition-to-transversion ratio of 3.18 and 3.57. Finally, we find that DNMs tend to be randomly distributed across chromosomes, not associated with recombination hotspots or genic regions. However, the sex chromosome chrZ shows a roughly fourfold increased DNM rate compared to autosomes, which is more than the expected increase due to chrZ spending two-thirds of its time in males. Overall, our results further enhance our understanding of DNMs in passerine songbirds.

Gonadal Mosaicism as a Rare Inheritance Pattern in Recessive Genodermatoses: Report of Two Cases with Pseudoxanthoma Elasticum and Literature Review

Germline mosaicism in autosomal recessive disorders is considered a rare disease mechanism with important consequences for diagnosis and patient counseling. In this report, we present two families with PXE in which paternal germline mosaicism for an ABCC6 whole-gene deletion was observed. The first family further illustrates the clinical challenges in PXE, with a typical PXE retinopathy in an apparently heterozygous carrier parent. A systematic review of the literature on gonadal mosaicism in autosomal recessive genodermatoses revealed 16 additional patients. As in most reported families, segregation analysis data are not mentioned, and this may still be an underrepresentation. Though rare, the possibility of germline mosaicism emphasizes the need for variant verification in parents and sibs of a newly diagnosed proband, as it has significant implications for genetic counseling and management.

Evolution and Comparative Genomics of the Transforming Growth Factor-β-Related Proteins in Nile Tilapia

The members of the transforming growth factor β (TGF-β) family of cell signaling polypeptides have garnered a great deal of interest due to its capacity from nematodes to mammals to regulate cell-based activities which control the growth of embryos and sustain tissue homeostasis. The current study designed a computational analysis of the TGF-β protein family for understanding these proteins at the molecular level. This study determined the genomic structure of TGF-β gene family in Nile tilapia for the first time. We chose 33 TGF-β genes for identification and divided them into two subgroups, TGF-like and BMP-like. Moreover, the subcellular localization of the Nile tilapia TGF-β proteins have showed that majority of the members of TGF-β proteins family are present into extracellular matrix and plasma except BMP6, BMP7, and INHAC. All TGF-β proteins were thermostable excluding BMP1. Each protein exhibited basic nature, excluding of BMP1, BMP2, BMP7, BMP10, GDF2, GDF8, GDF11, AMH, INHA, INHBB, and NODAL M. All proteins gave impression of being unstable depending on the instability index, having values exceeding 40 excluding BMP1 and BMP2. Each TGF-β protein was found to be hydrophobic with lowered values of GRAVY. Moreover, every single one of the discovered TGF-β genes had a consistent evolutionary pattern. The TGF-β gene family had eight segmental duplications, and the Ka/Ks ratio demonstrated that purifying selection had an impact on the duplicated gene pairs which have experienced selection pressure. This study highlights important functionality of TGF-β and depicts the demand for further investigation to better understand the role and mechanism of transforming growth factor β in fishes and other species.

Study of the cyto- and genotoxic activity of water from the Kapshagai reservoir (Kazakhstan) on laboratory mice

Chemical compounds in the environment, which exhibit toxic and genotoxic activity, increase the mutational pressure on biota. This study aimed to investigate the genotoxic, mutagenic, and toxic effects of water from the Ile River and the Kapshagai Reservoir, both sites of active economic activities. Cytogenetic analysis of bone marrow from mice exposed to water samples from the Ile River and the Kapshagai Reservoir revealed a statistically significant increase in aberrant (p<0.05) and polyploid cells (p<0.01), as well as a decrease in the mitotic index (p<0.001), compared to the negative control. The water samples caused statistically significant increases in single- and double-strand DNA breaks in cells across various organs in the experimental mice compared to unexposed animals (p<0.001). These observations suggest the existence of chemical compounds within the water samples from the Kapshagai Reservoir and the Ile River, which exhibit genotoxic, mutagenic, and toxic properties.

Joint, multifaceted genomic analysis enables diagnosis of diverse, ultra-rare monogenic presentations

Genomics for rare disease diagnosis has advanced at a rapid pace due to our ability to perform "N-of-1" analyses on individual patients with ultra-rare diseases. The increasing sizes of ultra-rare disease cohorts internationally newly enables cohort-wide analyses for new discoveries, but well-calibrated statistical genetics approaches for jointly analyzing these patients are still under development.1,2 The Undiagnosed Diseases Network (UDN) brings multiple clinical, research and experimental centers under the same umbrella across the United States to facilitate and scale N-of-1 analyses. Here, we present the first joint analysis of whole genome sequencing data of UDN patients across the network. We introduce new, well-calibrated statistical methods for prioritizing disease genes with de novo recurrence and compound heterozygosity. We also detect pathways enriched with candidate and known diagnostic genes. Our computational analysis, coupled with a systematic clinical review, recapitulated known diagnoses and revealed new disease associations. We further release a software package, RaMeDiES, enabling automated cross-analysis of deidentified sequenced cohorts for new diagnostic and research discoveries. Gene-level findings and variant-level information across the cohort are available in a public-facing browser (https://dbmi-bgm.github.io/udn-browser/). These results show that N-of-1 efforts should be supplemented by a joint genomic analysis across cohorts.

Tracking of Ubiquitin Signaling through 3.5 Billion Years of Combinatorial Conjugation

Ubiquitination is an evolutionary, ancient system of post-translational modification of proteins that occurs through a cascade involving ubiquitin activation, transfer, and conjugation. The maturation of this system has followed two main pathways. The first is the conservation of a universal structural fold of ubiquitin and ubiquitin-like proteins, which are present in both Archaea and Bacteria, as well as in multicellular Eukaryotes. The second is the rise of the complexity of the superfamily of ligases, which conjugate ubiquitin-like proteins to substrates, in terms of an increase in the number of enzyme variants, greater variation in structural organization, and the diversification of their catalytic domains. Here, we examine the diversity of the ubiquitination system among different organisms, assessing the variety and conservation of the key domains of the ubiquitination enzymes and ubiquitin itself. Our data show that E2 ubiquitin-conjugating enzymes of metazoan phyla are highly conservative, whereas the homology of E3 ubiquitin ligases with human orthologues gradually decreases depending on "molecular clock" timing and evolutionary distance. Surprisingly, Chordata and Echinodermata, which diverged over 0.5 billion years ago during the Cambrian explosion, share almost the same homology with humans in the amino acid sequences of E3 ligases but not in their adaptor proteins. These observations may suggest that, firstly, the E2 superfamily already existed in its current form in the last common metazoan ancestor and was generally not affected by purifying selection in metazoans. Secondly, it may indicate convergent evolution of the ubiquitination system and highlight E3 adaptor proteins as the "upper deck" of the ubiquitination system, which plays a crucial role in chordate evolution.

Optimal Diagnostic and Treatment Practices for Facial Dysostosis Syndromes: A Clinical Consensus Statement Among European Experts

Facial dysostosis syndromes (FDS) are rare congenital conditions impacting facial development, often leading to diverse craniofacial abnormalities. This study addresses the scarcity of evidence on these syndromes about optimal diagnostic and treatment practices. To overcome this scarcity, European experts from ERN CRANIO collaborated to develop a clinical consensus statement through the Delphi consensus method. A systematic search of Embase, MEDLINE/PubMed, Cochrane, and Web of Science databases was conducted until February 2023. The quality of evidence was evaluated using various tools depending on the study design. Statements were subsequently formed based on literature and expert opinion, followed by a Delphi process with expert health care providers and patient representatives. In total, 92 experts from various specialties and three patient representatives were involved in the Delphi process. Over 3 voting rounds, consensus was achieved on 92 (46.9%), 58 (59.2%), and 19 (70.4%) statements, respectively. These statements cover the topics of general care; craniofacial reconstruction; the eyes and lacrimal system; upper airway management; genetics; hearing; speech; growth, feeding, and swallowing; dental treatment and orthodontics; extracranial anomalies; and psychology and cognition. The current clinical consensus statement provides valuable insights into optimal diagnostic and treatment practices and identifies key research opportunities for FDS. This consensus statement represents a significant advancement in FDS care, underlining the commitment of health care professionals to improve the understanding and management of these rare syndromes in Europe.

Exploring the clinical utility of exome sequencing/Mono, Duo, Trio in prenatal testing: a retrospective study in a tertiary care centre in South India

OBJECTIVES

With the availability of Next Generation Sequencing (NGS) diagnosis of genetic disorders has improved significantly. Its use is also applicable to ascertain diagnosis and management in a perinatal setting. The study aims to detect the genetic aetiology of various congenital structural and functional defects using NGS technology in the reproductive cohort at a tertiary centre. The secondary objective is to address challenges in the interpretation of variants.

METHODS

This was a retrospective study of couples who underwent exome sequencing (Mono-testing proband only or Duo-testing parents only or Trio-testing proband and parents) for suspected single gene disorders between years 2020-2022 at a tertiary care perinatal center in the South India. American College of Medical Genetics (ACMG) guidelines were followed to classify the pathogenicity of the variants identified by exome sequencing.

RESULTS

The overall diagnostic yield as defined by pathogenic/likely pathogenic variants obtained was (23/43) 53.4 %. The individual subsets have the following diagnostic yield viz., Mono 5/6 (83 %); Carrier 16/32 (50 %); Trio 2/5 (40 %). Diagnostic yield was significantly higher in consanguineous couples. However, miscarriage history, and organ system involvement did not have a significant effect on the diagnostic yield. Prenatal diagnosis was offered for seven patients based on the exome result. One fetus was confirmed with a compound heterozygous pathogenic variant.

CONCLUSIONS

Diagnostic yield of exome sequencing in our cohort was 53 %. The detection of pathogenic variants was maximum in those cases undergoing Mono exome sequencing. In places where there is a high prevalence of consanguinity and endogamy, NGS may be offered as first line test in the context of prenatal diagnosis.

Naturally occurring genetic diseases caused by de novo variants in domestic animals

With the advent of next-generation sequencing, an increasing number of cases of de novo variants in domestic animals have been reported in scientific literature primarily associated with clinically severe phenotypes. The emergence of new variants at each generation is a crucial aspect in understanding the pathology of early-onset diseases in animals and can provide valuable insights into similar diseases in humans. With the aim of collecting deleterious de novo variants in domestic animals, we searched the scientific literature and compiled reports on 42 de novo variants in 31 genes in domestic animals. No clear disease-associated phenotype has been established in humans for three of these genes (NUMB, ANKRD28 and KCNG1). For the remaining 28 genes, a strong similarity between animal and human phenotypes was recognized from available information in OMIM and OMIA, revealing the importance of comparative studies and supporting the use of domestic animals as natural models for human diseases, in line with the One Health approach.

Estimating evolutionary and demographic parameters via ARG-derived IBD

Inference of demographic and evolutionary parameters from a sample of genome sequences often proceeds by first inferring identical-by-descent (IBD) genome segments. By exploiting efficient data encoding based on the ancestral recombination graph (ARG), we obtain three major advantages over current approaches: (i) no need to impose a length threshold on IBD segments, (ii) IBD can be defined without the hard-to-verify requirement of no recombination, and (iii) computation time can be reduced with little loss of statistical efficiency using only the IBD segments from a set of sequence pairs that scales linearly with sample size. We first demonstrate powerful inferences when true IBD information is available from simulated data. For IBD inferred from real data, we propose an approximate Bayesian computation inference algorithm and use it to show that poorly-inferred short IBD segments can improve estimation precision. We show estimation precision similar to a previously-published estimator despite a 4 000-fold reduction in data used for inference. Computational cost limits model complexity in our approach, but we are able to incorporate unknown nuisance parameters and model misspecification, still finding improved parameter inference.

Reconstructing the ancestral gene pool to uncover the origins and genetic links of Hmong-Mien speakers

BACKGROUND

Hmong-Mien (HM) speakers are linguistically related and live primarily in China, but little is known about their ancestral origins or the evolutionary mechanism shaping their genomic diversity. In particular, the lack of whole-genome sequencing data on the Yao population has prevented a full investigation of the origins and evolutionary history of HM speakers. As such, their origins are debatable.

RESULTS

Here, we made a deep sequencing effort of 80 Yao genomes, and our analysis together with 28 East Asian populations and 968 ancient Asian genomes suggested that there is a strong genetic basis for the formation of the HM language family. We estimated that the most recent common ancestor dates to 5800 years ago, while the genetic divergence between the HM and Tai-Kadai speakers was estimated to be 8200 years ago. We proposed that HM speakers originated from the Yangtze River Basin and spread with agricultural civilization. We identified highly differentiated variants between HM and Han Chinese, in particular, a deafness-related missense variant (rs72474224) in the GJB2 gene is in a higher frequency in HM speakers than in others.

CONCLUSIONS

Our results indicated complex gene flow and medically relevant variants involved in the HM speakers' evolution history.

Global research landscape on the contribution of de novo mutations to human genetic diseases over the past 20 years: bibliometric analysis

As the contribution of de novo mutations (DNMs) to human genetic diseases has been gradually uncovered, analyzing the global research landscape over the past 20 years is essential. Because of the large and rapidly increasing number of publications in this field, understanding the current landscape of the contribution of DNMs in the human genome to genetic diseases remains a challenge. Bibliometric analysis provides an approach for visualizing these studies using information in published records in a specific field. This study aimed to illustrate the current global research status and explore trends in the field of DNMs underlying genetic diseases. Bibliometric analyses were performed using the Bibliometrix Package based on the R language version 4.1.3 and CiteSpace version 6.1.R2 software for publications from 2000 to 2021 indexed under the Web of Science Core Collection (WoSCC) about DNMs underlying genetic diseases on 17 September 2022. We identified 3435 records, which were published in 731 journals by 26,538 authors from 6052 institutes in 66 countries. There was an upward trend in the number of publications since 2013. The USA, China, and Germany contributed the majority of the records included. The University of Washington, Columbia University, and Baylor College of Medicine were the top-producing institutions. Evan E Eichler of the University of Washington, Stephan J Sanders of the Yale University School of Medicine, and Ingrid E Scheffer of the University of Melbourne were the most high-ranked authors. Keyword co-occurrence analysis suggested that DNMs in neurodevelopmental disorders and intellectual disabilities were research hotspots and trends. In conclusion, our data show that DNMs have a significant effect on human genetic diseases, with a noticeable increase in annual publications over the last 5 years. Furthermore, potential hotspots are shifting toward understanding the causative role and clinical interpretation of newly identified or low-frequency DNMs observed in patients.

In silico molecular characterization of TGF-β gene family in Bufo bufo: genome-wide analysis

Bufo bufo is a living example of evolutionary processes due to its numerous physiological and ecological adaptations. This is the first study to genetically characterize the TGF-β gene family in B. bufo at the genome-wide level, and a total of 28 TGF-β gene family homologs are identified. Physicochemical characteristics of TGF-β homologs exhibit a basic nature except for BMP1, BMP4, BMP10, BMP15, AMH, INHA, NODAL Modulator and TGFB1. Phylogenetic analysis divided the TGF-β gene family homologs into 2 major clades along with other vertebrate species. In domain and motif composition analysis, the gene structure for all TGF-β homologs exhibited homogeneity except BMP1. We have identified the TGF-β propeptide domain together with the TGF-β in all family homologs of TGF-β superfamily. Gene structure comparisons indicated that the TGF-β gene family have arisen by gene duplications. We also identified 10 duplicated gene pairs, all of which were detected to be segmental duplications. The Ka/Ks test ratio findings for every pair of genes revealed that none of the ratios surpassed 1 except for one gene pair (INHA/BMP1), indicating that these proteins are under positive selection. Circos analysis showed that TGF-β gene family homologs are arranged in 11 dispersed clusters and all were segmentally arrayed in the genome. This study provides a molecular basis for TGF-β ligand protein functional analysis and may serve as a reference for in-depth phylogenomics and may promote the development of novel strategies.

Genomic vulnerability of a freshwater salmonid under climate change

Understanding the adaptive potential of populations and species is pivotal for minimizing the loss of biodiversity in this era of rapid climate change. Adaptive potential has been estimated in various ways, including based on levels of standing genetic variation, presence of potentially beneficial alleles, and/or the severity of environmental change. Kokanee salmon, the non-migratory ecotype of sockeye salmon (Oncorhynchus nerka), is culturally and economically important and has already been impacted by the effects of climate change. To assess its climate vulnerability moving forward, we integrated analyses of standing genetic variation, genotype-environment associations, and climate modeling based on sequence and structural genomic variation from 224 whole genomes sampled from 22 lakes in British Columbia and Yukon (Canada). We found that variables for extreme temperatures, particularly warmer temperatures, had the most pervasive signature of selection in the genome and were the strongest predictors of levels of standing variation and of putatively adaptive genomic variation, both sequence and structural. Genomic offset estimates, a measure of climate vulnerability, were significantly correlated with higher increases in extreme warm temperatures, further highlighting the risk of summer heat waves that are predicted to increase in frequency in the future. Levels of standing genetic variation, an important metric for population viability and resilience, were not correlated with genomic offset. Nonetheless, our combined approach highlights the importance of integrating different sources of information and genomic data to formulate more comprehensive and accurate predictions on the vulnerability of populations and species to future climate change.

An FM-Index Based High-Throughput Memory-Efficient FPGA Accelerator for Paired-End Short-Read Mapping

This article presents an Ferragina-Manzini index (FM-index) based paired-end short-read mapping hardware accelerator. Four techniques are proposed to significantly reduce the number of memory accesses and operations to improve the throughput. First, an interleaved data structure is proposed to reduce the processing time by 51.8% by leveraging the data locality. Second, the boundaries of possible mapping location candidates can be retrieved within only one memory access by constructing a lookup table along with the FM-index. This reduces the number of DRAM accesses by 60% with only a 64 MB memory overhead. Third, an additional step is added to skip the time-consuming repetitive location candidates filtering conditionally, avoiding unnecessary operations. Lastly, an early termination method is proposed to terminate the mapping process if any location candidate with a high enough alignment score is detected, greatly decreasing the execution time. Overall, the computation time is reduced by 92.6% with only a 2% memory overhead in DRAM. The proposed methods are realized on a Xilinx Alveo U250 FPGA. The proposed FPGA accelerator processes 1,085,812,766 short-reads from the U.S. Food and Drug Administration (FDA) dataset within 35.4 minutes at 200 MHz. It achieves a 1.7-to-18.6× higher throughput and the highest 99.3% accuracy by exploiting the paired-end short-read mapping, compared to state-of-the-art FPGA-based designs.

Validation of machine learning approach for direct mutation rate estimation

Mutations are the primary source of all genetic variation. Knowledge about their rates is critical for any evolutionary genetic analyses, but for a long time, that knowledge has remained elusive and indirectly inferred. In recent years, parent-offspring comparisons have yielded the first direct mutation rate estimates. The analyses are, however, challenging due to high rate of false positives and no consensus regarding standardized filtering of candidate de novo mutations. Here, we validate the application of a machine learning approach for such a task and estimate the mutation rate for the guppy (Poecilia reticulata), a model species in eco-evolutionary studies. We sequenced 4 parents and 20 offspring, followed by screening their genomes for de novo mutations. The initial large number of candidate de novo mutations was hard-filtered to remove false-positive results. These results were compared with mutation rate estimated with a supervised machine learning approach. Both approaches were followed by molecular validation of all candidate de novo mutations and yielded similar results. The ML method uniquely identified three mutations, but overall required more hands-on curation and had higher rates of false positives and false negatives. Both methods concordantly showed no difference in mutation rates between families. Estimated here the guppy mutation rate is among the lowest directly estimated mutation rates in vertebrates; however, previous research has also found low estimated rates in other teleost fishes. We discuss potential explanations for such a pattern, as well as future utility and limitations of machine learning approaches.

A novel rare variants association test for binary traits in family-based designs via copulas

With the cost-effectiveness technology in whole-genome sequencing, more sophisticated statistical methods for testing genetic association with both rare and common variants are being investigated to identify the genetic variation between individuals. Several methods which group variants, also called gene-based approaches, are developed. For instance, advanced extensions of the sequence kernel association test, which is a widely used variant-set test, have been proposed for unrelated samples and extended for family data. Family data have been shown to be powerful when analyzing rare variants. However, most of such methods capture familial relatedness using a random effect component within the generalized linear mixed model framework. Therefore, there is a need to develop unified and flexible methods to study the association between a set of genetic variants and a trait, especially for a binary outcome. Copulas are multivariate distribution functions with uniform margins on the [ 0 , 1 ] interval and they provide suitable models to capture familial dependence structure. In this work, we propose a flexible family-based association test for both rare and common variants in the presence of binary traits. The method, termed novel rare variant association test (NRVAT), uses a marginal logistic model and a Gaussian Copula. The latter is employed to model the dependence between relatives. An analytic score-type test is derived. Through simulations, we show that our method can achieve greater power than existing approaches. The proposed model is applied to investigate the association between schizophrenia and bipolar disorder in a family-based cohort consisting of 17 extended families from Eastern Quebec.

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.

Genome-wide identification and evolutionary analysis of the FGF gene family in buffalo

Fibroblast growth factors (FGFs) are important polypeptide growth factors that play a critical role in many developmental processes, including differentiation, cell proliferation, and migration in mammals. This study employs in silico analyses to characterize the FGF gene family in buffalo, investigating their genome-wide identification, physicochemical properties, and evolutionary patterns. For this purpose, genomic and proteomic sequences of buffalo, cattle, goat, and sheep were retrieved from NCBI database. We identified a total of 22 FGF genes in buffalo. Physicochemical properties observed through ProtParam tool showed notable features of these proteins including in-vitro instability, thermostability, hydrophilicity, and basic nature. Phylogenetic analysis grouped 22 identified genes into nine sub-families based on evolutionary relationships. Additionally, analysis of gene structure, motif patterns, and conserved domains using TBtools revealed the remarkable conservation of this gene family across selected species throughout the course of evolution. Comparative amino acid analysis performed through ClustalW demonstrated significant conservation between buffalo and cattle FGF proteins. Mutational analysis showed three non-synonymous mutations at positions R103 > G, P7 > L, and E98 > Q in FGF4, FGF6, and FGF19, respectively in buffalo. Duplication events revealed only one segmental duplication (FGF10/FGF22) in buffalo and two in cattle (FGF10/FGF22 and FGF13/FGF13-like) with Ka/Ks values <1 indicating purifying selection pressure for these duplications. Comparison of protein structures of buffalo, goat, and sheep exhibited more similarities in respective structures. In conclusion, our study highlights the conservation of the FGF gene family in buffalo during evolution. Furthermore, the identified non-synonymous mutations may have implications for the selection of animals with better performance.Communicated by Ramaswamy H. Sarma.

Extensive variation in germline de novo mutations in Poecilia reticulata

The rate of germline mutation is fundamental to evolutionary processes, as it generates the variation upon which selection acts. The guppy, Poecilia reticulata, is a model of rapid adaptation, however the relative contribution of standing genetic variation versus de novo mutation (DNM) to evolution in this species remains unclear. Here, we use pedigree-based approaches to quantify and characterize germline DNMs in three large guppy families. Our results suggest germline mutation rate in the guppy varies substantially across individuals and families. Most DNMs are shared across multiple siblings, suggesting they arose during early embryonic development. DNMs are randomly distributed throughout the genome, and male-biased mutation rate is low, as would be expected from the short guppy generation time. Overall, our study shows remarkable variation in germline mutation rate and provides insights into rapid evolution of guppies.

Two germline mutations can serve as genetic susceptibility screening makers for a lung adenocarcinoma family

OBJECTIVES

Lung cancer is the most common form of cancer and the leading cause of cancer death. For familial lung cancer, identification of causing genetic factors is essential for prevention and control of non-lung cancer in carriers.

MATERIALS AND METHODS

We studied two generations of a family with suspected inherited lung cancer susceptibility. Four individuals in this family had lung adenocarcinoma. To identify the gene(s) that cause the lung cancer in this pedigree, we extracted DNA from the peripheral blood of four cancer individuals and blood from three cancer-free family members as the control and performed whole-genome sequencing. Our filtering strategy includes, assessment of allele frequency, functional affection on amino acids, mutation accumulation, phased blocks and evolution analysis towards the alterations.

RESULTS

We identified two possible mutations, including PLEKHM2 (D134N) and MCC (R448Q) in all affected family members but did not found in the control group. Then, we performed a genetic susceptibility screening for 10 non-lung cancer relatives and found two individuals with PLEKHM2 (D134N) mutation, two with MCC (R448Q) mutation and one carrying both mutations. 3 carriers performed LDCT scan and 2 of them carried MCC (R448Q) also had ground-glass opacity (GGO) lesion in their lung.

CONCLUSION

Our data suggested that WGS together with our filtering strategy was successful in identifying PLEKHM2 (D134N) and MCC (R448Q) as the possible driver mutations in this family. Genetic susceptibility screening of non-lung cancer carriers will be a useful approach to prevent and control lung cancer in families with high-risk for the disease.

Genome sequencing-based discovery of a novel deep intronic APC pathogenic variant causing exonization

Familial adenomatous polyposis (FAP) is a hereditary cancer syndrome that occurs as a result of germline mutations in the APC gene. Despite a clear clinical diagnosis of FAP, a certain proportion of the APC variants are not readily detectable through conventional genotyping routines. We accomplished genome sequencing in duo of the disease-affected proband and non-affected sibling followed by in silico predictions and a series of RNA-based assays clarifying variant functionality. By prioritizing variants obtained by genome sequencing, we discovered the novel deep intronic alteration APC:c.531 + 1482 A > G that was demonstrated to cause out-of-frame exonization of 56 base pairs from intron 5 of the gene. Further cDNA assays confirmed, that the aberrant splicing event was complete and its splice product was subject to nonsense-mediated decay. Co-segregation was observed between the variant carrier status and the disease phenotype. Cumulative evidence confirmed that APC:c.531 + 1482 A > G is a pathogenic variant causative of the disease.

SNV/indel hypermutator phenotype in biallelic RAD51C variant: Fanconi anemia

We previously reported a fetus with Fanconi anemia (FA), complementation group O due to compound heterozygous variants involving RAD51C. Interestingly, the trio exome sequencing analysis also detected eight apparent de novo mosaic variants with variant allele fraction (VAF) ranging between 11.5 and 37%. Here, using whole genome sequencing and a 'home-brew' variant filtering pipeline and DeepMosaic module, we investigated the number and signature of de novo heterozygous and mosaic variants and the hypothesis of a rare phenomenon of hypermutation. Eight-hundred-thirty apparent de novo SNVs and 21 de novo indels had VAFs below 37.41% and were considered postzygotic somatic mosaic variants. The VAFs showed a bimodal distribution, with one component having an average VAF of 25% (range: 18.7-37.41%) (n = 446), representing potential postzygotic first mitotic events, and the other component with an average VAF of 12.5% (range 9.55-18.69%) (n = 384), describing potential second mitotic events. No increased rate of CNV formation was observed. The mutational pattern analysis for somatic single base substitution showed SBS40, SBS5, and SBS3 as the top recognized signatures. SBS3 is a known signature associated with homologous recombination-based DNA damage repair error. Our data demonstrate that biallelic RAD51C variants show evidence for defective genomic DNA damage repair and thereby result in a hypermutator phenotype with the accumulation of postzygotic de novo mutations, at least in the prenatal period. This 'genome hypermutator phenomenon' might contribute to the observed hematological manifestations and the predisposition to tumors in patients with FA. We propose that other FA groups should be investigated for genome-wide de novo variants.

Assessment of a novel variation in DHODH gene causing Miller syndrome: The first report in Chinese population

BACKGROUND

Miller syndrome is a rare type of postaxial acrofacial dysostosis caused by biallelic mutations in the DHODH gene, which is characterized mainly by craniofacial malformations of micrognathia, orofacial clefts, cup-shaped ears, and malar hypoplasia, combined with postaxial limb deformities like the absence of fifth digits.

METHODS

In this study, a prenatal case with multiple orofacial-limb abnormities was enrolled, and a thorough clinical and imaging examination was performed. Subsequently, genetic detection with karyotyping, chromosomal microarray analysis (CMA) and whole-exome sequencing (WES) was carried out. In vitro splicing analysis was also conducted to clarify the impact of one novel variant.

RESULTS

The affected fetus displayed typical manifestations of Miller syndrome, and WES identified a diagnostic compound heterozygous variation in DHODH, consisting of two variants: exon(1-3)del and c.819 + 5G > A. We conducted a further in vitro validation with minigene system, and the result indicated that the c.819 + 5G > A variant would lead to an exon skipping in mRNA splicing.

CONCLUSIONS

These findings provided with the first exonic deletion and first splice site variant in DHODH, which expanded the mutation spectrum of Miller syndrome and offered reliable evidence for genetic counseling to the affected family.

The origins and functional effects of postzygotic mutations throughout the human life span

Postzygotic mutations (PZMs) begin to accrue in the human genome immediately after fertilization, but how and when PZMs affect development and lifetime health remain unclear. To study the origins and functional consequences of PZMs, we generated a multitissue atlas of PZMs spanning 54 tissue and cell types from 948 donors. Nearly half the variation in mutation burden among tissue samples can be explained by measured technical and biological effects, and 9% can be attributed to donor-specific effects. Through phylogenetic reconstruction of PZMs, we found that their type and predicted functional impact vary during prenatal development, across tissues, and through the germ cell life cycle. Thus, methods for interpreting effects across the body and the life span are needed to fully understand the consequences of genetic variants.

Comparing inference under the multispecies coalescent with and without recombination

Accurate inference of population parameters plays a pivotal role in unravelling evolutionary histories. While recombination has been universally accepted as a fundamental process in the evolution of sexually reproducing organisms, it remains challenging to model it exactly. Thus, existing coalescent-based approaches make different assumptions or approximations to facilitate phylogenetic inference, which can potentially bring about biases in estimates of evolutionary parameters when recombination is present. In this article, we evaluate the performance of population parameter estimation using three methods-StarBEAST2, SNAPP, and diCal2-that represent three different types of inference. We performed whole-genome simulations in which recombination rates, mutation rates, and levels of incomplete lineage sorting were varied. We show that StarBEAST2 using short or medium-sized loci is robust to realistic rates of recombination, which is in agreement with previous studies. SNAPP, as expected, is generally unaffected by recombination events. Most surprisingly, diCal2, a method that is designed to explicitly account for recombination, performs considerably worse than other methods under comparison.

SNV/indel hypermutator phenotype in biallelic RAD51C variant - Fanconi anemia

We previously reported a fetus with Fanconi anemia (FA), complementation group O due to compound heterozygous variants involving RAD51C . Interestingly, the trio exome sequencing analysis also detected eight apparent de novo mosaic variants with variant allele fraction (VAF) ranging between 11.5%-37%. Here, using whole genome sequencing and a 'home-brew' variant filtering pipeline and DeepMosaic module, we investigated the number and signature of de novo heterozygous and mosaic variants and the rare phenomenon of hypermutation. Eight-hundred-thirty apparent dnSNVs and 21 de novo indels had VAFs below 37.41% and were considered postzygotic somatic mosaic variants. The VAFs showed a bimodal distribution, with one component with an average VAF of 25% (range: 18.7-37.41%) (n=446), representing potential postzygotic first mitotic events, and the other component with an average VAF of 12.5% (range: 9.55-18.69%) (n=384), describing potential second mitotic events. No increased rate of CNV formation was observed. The mutational pattern analysis for somatic single base substitution showed SBS40, SBS5, and SBS3 as the top recognized signatures. SBS3 is a known signature associated with homologous recombination-based DNA damage repair error. Our data demonstrate that biallelic RAD51C variants show evidence for defective genomic DNA damage repair and thereby result in a hypermutator phenotype with the accumulation of postzygotic de novo mutations, at least in the prenatal period. This 'genome hypermutator phenomenon' might contribute to the observed hematological manifestations and the predisposition to tumors in patients with FA, and pregnancy loss in general. We propose that other FA groups should be investigated for genome-wide de novo variants.

Genetics of Kidney Disease: The Unexpected Role of Rare Disorders

Hundreds of different genetic causes of chronic kidney disease are now recognized, and while individually rare, taken together they are significant contributors to both adult and pediatric diseases. Traditional genetics approaches relied heavily on the identification of large families with multiple affected members and have been fundamental to the identification of genetic kidney diseases. With the increased utilization of massively parallel sequencing and improvements to genotype imputation, we can analyze rare variants in large cohorts of unrelated individuals, leading to personalized care for patients and significant research advancements. This review evaluates the contribution of rare disorders to patient care and the study of genetic kidney diseases and highlights key advancements that utilize new techniques to improve our ability to identify new gene-disease associations.

Methods to improve the accuracy of next-generation sequencing

Next-generation sequencing (NGS) is present in all fields of life science, which has greatly promoted the development of basic research while being gradually applied in clinical diagnosis. However, the cost and throughput advantages of next-generation sequencing are offset by large tradeoffs with respect to read length and accuracy. Specifically, its high error rate makes it extremely difficult to detect SNPs or low-abundance mutations, limiting its clinical applications, such as pharmacogenomics studies primarily based on SNP and early clinical diagnosis primarily based on low abundance mutations. Currently, Sanger sequencing is still considered to be the gold standard due to its high accuracy, so the results of next-generation sequencing require verification by Sanger sequencing in clinical practice. In order to maintain high quality next-generation sequencing data, a variety of improvements at the levels of template preparation, sequencing strategy and data processing have been developed. This study summarized the general procedures of next-generation sequencing platforms, highlighting the improvements involved in eliminating errors at each step. Furthermore, the challenges and future development of next-generation sequencing in clinical application was discussed.

From Genomics to Metagenomics in the Era of Recent Sequencing Technologies

Metagenomics, also known as environmental genomics, is the study of the genomic content of a sample of organisms obtained from a common habitat. Metagenomics and other "omics" disciplines have captured the attention of researchers for several decades. The effect of microbes in our body is a relevant concern for health studies. Through sampling the sequences of microbial genomes within a certain environment, metagenomics allows study of the functional metabolic capacity of a community as well as its structure based upon distribution and richness of species. Exponentially increasing number of microbiome literatures illustrate the importance of sequencing techniques which have allowed the expansion of microbial research into areas, including the human gut, antibiotics, enzymes, and more. This chapter illustrates how metagenomics field has evolved with the progress of sequencing technologies.Further, from this chapter, researchers will be able to learn about all current options for sequencing techniques and comparison of their cost and read statistics, which will be helpful for planning their own studies.

Chromosome-level genome and recombination map of the male buffalo

BACKGROUND

The swamp buffalo (Bubalus bubalis carabanesis) is an economically important livestock supplying milk, meat, leather, and draft power. Several female buffalo genomes have been available, but the lack of high-quality male genomes hinders studies on chromosome evolution, especially Y, as well as meiotic recombination.

RESULTS

Here, a chromosome-level genome with a contig N50 of 72.2 Mb and a fine-scale recombination map of male buffalo were reported. We found that transposable elements (TEs) and structural variants (SVs) may contribute to buffalo evolution by influencing adjacent gene expression. We further found that the pseudoautosomal region (PAR) of the Y chromosome is subject to stronger purification selection. The meiotic recombination map showed that there were 2 obvious recombination hotspots on chromosome 8, and the genes around them were mainly related to tooth development, which may have helped to enhance the adaption of buffalo to inferior feed. Among several genomic features, TE density has the strongest correlation with recombination rates. Moreover, the TE subfamily, SINE/tRNA, is likely to play a role in driving recombination into SVs.

CONCLUSIONS

The male genome and sperm sequencing will facilitate the understanding of the buffalo genomic evolution and functional research.

Estimating the genome-wide mutation rate from thousands of unrelated individuals

We provide a method for estimating the genome-wide mutation rate from sequence data on unrelated individuals by using segments of identity by descent (IBD). The length of an IBD segment indicates the time to shared ancestor of the segment, and mutations that have occurred since the shared ancestor result in discordances between the two IBD haplotypes. Previous methods for IBD-based estimation of mutation rate have required the use of family data for accurate phasing of the genotypes. This has limited the scope of application of IBD-based mutation rate estimation. Here, we develop an IBD-based method for mutation rate estimation from population data, and we apply it to whole-genome sequence data on 4,166 European American individuals from the TOPMed Framingham Heart Study, 2,996 European American individuals from the TOPMed My Life, Our Future study, and 1,586 African American individuals from the TOPMed Hypertension Genetic Epidemiology Network study. Although mutation rates may differ between populations as a result of genetic factors, demographic factors such as average parental age, and environmental exposures, our results are consistent with equal genome-wide average mutation rates across these three populations. Our overall estimate of the average genome-wide mutation rate per 10⁸ base pairs per generation for single-nucleotide variants is 1.24 (95% CI 1.18-1.33).

Analysis of the Whole-Genome Sequences from an Equus Parent-Offspring Trio Provides Insight into the Genomic Incompatibilities in the Hybrid Mule

Interspecific hybridization often shows negative effects on hybrids. However, only a few multicellular species, limited to a handful of plants and animals, have shown partial genetic mechanisms by which hybridization leads to low fitness in hybrids. Here, to explore the outcome of combining the two genomes of a horse and donkey, we analyzed the whole-genome sequences from an Equus parent-offspring trio using Illumina platforms. We generated 41.39× and 46.21× coverage sequences for the horse and mule, respectively. For the donkey, a 40.38× coverage sequence was generated and stored in our laboratory. Approximately 24.86 million alleles were discovered that varied from the reference genome. Single nucleotide polymorphisms were used as polymorphic markers for assigning alleles to their parental genomic inheritance. We identified 25,703 Mendelian inheritance error single nucleotide polymorphisms in the mule genome that were not inherited from the parents through Mendelian inheritance. A total of 555 de novo single nucleotide polymorphisms were also identified. The rate of de novo single nucleotide polymorphisms was 2.21 × 10^-7 in the mule from the Equus parent-offspring trio. This rate is obviously higher than the natural mutation rate for Equus, which is also consistent with the previous hypothesis that interracial crosses may have a high mutation rate. The genes associated with these single nucleotide polymorphisms are mainly involved in immune processes, DNA repair, and cancer processes. The results of the analysis of three genomes from an Equus parent-offspring trio improved our knowledge of the consequences of the integration of parental genomes in mules.