Modernizing reference genome assemblies

Stress increases sperm respiration and motility in mice and men

Semen quality and fertility has declined over the last 50 years, corresponding to ever-increasing environmental stressors. However, the cellular mechanisms involved and their impact on sperm functions remain unknown. In a repeated sampling human cohort study, we identify a significant effect of prior perceived stress to increase sperm motility 2-3 months following stress, timing that expands upon our previous studies revealing significant stress-associated changes in sperm RNA important for fertility. We mechanistically examine this post-stress timing in mice using an in vitro stress model in the epididymal epithelial cells responsible for sperm maturation and find 7282 differentially H3K27me3 bound DNA regions involving genes critical for mitochondrial and metabolic pathways. Further, prior stress exposure significantly changes the composition and size of epithelial cell-secreted extracellular vesicles that when incubated with mouse sperm, increase mitochondrial respiration and sperm motility, adding to our prior work showing impacts on embryo development. Together, these studies identify a time-dependent, translational signaling pathway that communicates stress experience to sperm, ultimately affecting reproductive functions.

Rare genomic copy number variants implicate new candidate genes for bicuspid aortic valve

Bicuspid aortic valve (BAV), the most common congenital heart defect, is a major cause of aortic valve disease requiring valve interventions and thoracic aortic aneurysms predisposing to acute aortic dissections. The spectrum of BAV ranges from early onset valve and aortic complications (EBAV) to sporadic late onset disease. Rare genomic copy number variants (CNVs) have previously been implicated in the development of BAV and thoracic aortic aneurysms. We determined the frequency and gene content of rare CNVs in EBAV probands (n = 272) using genome-wide SNP microarray analysis and three complementary CNV detection algorithms (cnvPartition, PennCNV, and QuantiSNP). Unselected control genotypes from the Database of Genotypes and Phenotypes were analyzed using identical methods. We filtered the data to select large genic CNVs that were detected by multiple algorithms. Findings were replicated in a BAV cohort with late onset sporadic disease (n = 5040). We identified 3 large and rare (< 1,1000 in controls) CNVs in EBAV probands. The burden of CNVs intersecting with genes known to cause BAV when mutated was increased in case-control analysis. CNVs intersecting with GATA4 and DSCAM were enriched in cases, recurrent in other datasets, and segregated with disease in families. In total, we identified potentially pathogenic CNVs in 9% of EBAV cases, implicating alterations of candidate genes at these loci in the pathogenesis of BAV.

Normalization of gene counts affects principal components-based exploratory analysis of RNA-sequencing data

Normalization of gene expression count data is an essential step of in the analysis of RNA-sequencing data. Its statistical analysis has been mostly addressed in the context of differential expression analysis, that is in the univariate setting. However, relationships among genes and samples are better explored and quantified using multivariate exploratory data analysis tools like Principal Component Analysis (PCA). In this study we investigate how normalization impacts the PCA model and its interpretation, considering twelve different widely used normalization methods that were applied on simulated and experimental data. Correlation patterns in the normalized data were explored using both summary statistics and Covariance Simultaneous Component Analysis. The impact of normalization on the PCA solution was assessed by exploring the model complexity, the quality of sample clustering in the low-dimensional PCA space and gene ranking in the model fit to normalized data. PCA models upon normalization were interpreted in the context gene enrichment pathway analysis. We found that although PCA score plots are often similar independently form the normalization used, biological interpretation of the models can depend heavily on the normalization method applied.

Comprehensive network modeling approaches unravel dynamic enhancer-promoter interactions across neural differentiation

BACKGROUND

Increasing evidence suggests that a substantial proportion of disease-associated mutations occur in enhancers, regions of non-coding DNA essential to gene regulation. Understanding the structures and mechanisms of the regulatory programs this variation affects can shed light on the apparatuses of human diseases.

RESULTS

We collect epigenetic and gene expression datasets from seven early time points during neural differentiation. Focusing on this model system, we construct networks of enhancer-promoter interactions, each at an individual stage of neural induction. These networks serve as the base for a rich series of analyses, through which we demonstrate their temporal dynamics and enrichment for various disease-associated variants. We apply the Girvan-Newman clustering algorithm to these networks to reveal biologically relevant substructures of regulation. Additionally, we demonstrate methods to validate predicted enhancer-promoter interactions using transcription factor overexpression and massively parallel reporter assays.

CONCLUSIONS

Our findings suggest a generalizable framework for exploring gene regulatory programs and their dynamics across developmental processes; this includes a comprehensive approach to studying the effects of disease-associated variation on transcriptional networks. The techniques applied to our networks have been published alongside our findings as a computational tool, E-P-INAnalyzer. Our procedure can be utilized across different cellular contexts and disorders.

Prior Fc receptor activation primes macrophages for increased sensitivity to IgG via long-term and short-term mechanisms

Macrophages measure the "eat-me" signal immunoglobulin G (IgG) to identify targets for phagocytosis. We tested whether prior encounters with IgG influence macrophage appetite. IgG is recognized by the Fc receptor. To temporally control Fc receptor activation, we engineered an Fc receptor that is activated by the light-induced oligomerization of Cry2, triggering phagocytosis. Using this tool, we demonstrate that subthreshold Fc receptor activation primes mouse bone-marrow-derived macrophages to be more sensitive to IgG in future encounters. Macrophages that have previously experienced subthreshold Fc receptor activation eat more IgG-bound human cancer cells. Increased phagocytosis occurs by two discrete mechanisms-a short- and long-term priming. Long-term priming requires new protein synthesis and Erk activity. Short-term priming does not require new protein synthesis and correlates with an increase in Fc receptor mobility. Our work demonstrates that IgG primes macrophages for increased phagocytosis, suggesting that therapeutic antibodies may become more effective after initial priming doses.

Beyond the Human Genome Project: The Age of Complete Human Genome Sequences and Pangenome References

The Human Genome Project was an enormous accomplishment, providing a foundation for countless explorations into the genetics and genomics of the human species. Yet for many years, the human genome reference sequence remained incomplete and lacked representation of human genetic diversity. Recently, two major advances have emerged to address these shortcomings: complete gap-free human genome sequences, such as the one developed by the Telomere-to-Telomere Consortium, and high-quality pangenomes, such as the one developed by the Human Pangenome Reference Consortium. Facilitated by advances in long-read DNA sequencing and genome assembly algorithms, complete human genome sequences resolve regions that have been historically difficult to sequence, including centromeres, telomeres, and segmental duplications. In parallel, pangenomes capture the extensive genetic diversity across populations worldwide. Together, these advances usher in a new era of genomics research, enhancing the accuracy of genomic analysis, paving the path for precision medicine, and contributing to deeper insights into human biology.

Metagenome-wide characterization of shared antimicrobial resistance genes in sympatric people and lemurs in rural Madagascar

Background

Tracking the spread of antibiotic resistant bacteria is critical to reduce global morbidity and mortality associated with human and animal infections. There is a need to understand the role that wild animals in maintenance and transfer of antibiotic resistance genes (ARGs).

Methods

This study used metagenomics to identify and compare the abundance of bacterial species and ARGs detected in the gut microbiomes from sympatric humans and wild mouse lemurs in a forest-dominated, roadless region of Madagascar near Ranomafana National Park. We examined the contribution of human geographic location toward differences in ARG abundance and compared the genomic similarity of ARGs between host source microbiomes.

Results

Alpha and beta diversity of species and ARGs between host sources were distinct but maintained a similar number of detectable ARG alleles. Humans were differentially more abundant for four distinct tetracycline resistance-associated genes compared to lemurs. There was no significant difference in human ARG diversity from different locations. Human and lemur microbiomes shared 14 distinct ARGs with highly conserved in nucleotide identity. Synteny of ARG-associated assemblies revealed a distinct multidrug-resistant gene cassette carrying dfrA1 and aadA1 present in human and lemur microbiomes without evidence of geographic overlap, suggesting that these resistance genes could be widespread in this ecosystem. Further investigation into intermediary processes that maintain drug-resistant bacteria in wildlife settings is needed.

IGLoo: Profiling the Immunoglobulin Heavy chain locus in Lymphoblastoid Cell Lines with PacBio High-Fidelity Sequencing reads

New high-quality human genome assemblies derived from lymphoblastoid cell lines (LCLs) provide reference genomes and pangenomes for genomics studies. However, the characteristics of LCLs pose technical challenges to profiling immunoglobulin (IG) genes. IG loci in LCLs contain a mixture of germline and somatically recombined haplotypes, making them difficult to genotype or assemble accurately. To address these challenges, we introduce IGLoo, a software tool that implements novel methods for analyzing sequence data and genome assemblies derived from LCLs. IGLoo characterizes somatic V(D)J recombination events in the sequence data and identifies the breakpoints and missing IG genes in the LCL-based assemblies. Furthermore, IGLoo implements a novel reassembly framework to improve germline assembly quality by integrating information about somatic events and population structural variantions in the IG loci. We applied IGLoo to study the assemblies from the Human Pangenome Reference Consortium, providing new insights into the mechanisms, gene usage, and patterns of V(D)J recombination, causes of assembly fragmentation in the IG heavy chain (IGH) locus, and improved representation of the IGH assemblies.

Impact of genome build on RNA-seq interpretation and diagnostics

Transcriptomics is a powerful tool for unraveling the molecular effects of genetic variants and disease diagnosis. Prior studies have demonstrated that choice of genome build impacts variant interpretation and diagnostic yield for genomic analyses. To identify the extent genome build also impacts transcriptomics analyses, we studied the effect of the hg19, hg38, and CHM13 genome builds on expression quantification and outlier detection in 386 rare disease and familial control samples from both the Undiagnosed Diseases Network and Genomics Research to Elucidate the Genetics of Rare Disease Consortium. Across six routinely collected biospecimens, 61% of quantified genes were not influenced by genome build. However, we identified 1,492 genes with build-dependent quantification, 3,377 genes with build-exclusive expression, and 9,077 genes with annotation-specific expression across six routinely collected biospecimens, including 566 clinically relevant and 512 known OMIM genes. Further, we demonstrate that between builds for a given gene, a larger difference in quantification is well correlated with a larger change in expression outlier calling. Combined, we provide a database of genes impacted by build choice and recommend that transcriptomics-guided analyses and diagnoses are cross referenced with these data for robustness.

Three-dimensional genome architecture persists in a 52,000-year-old woolly mammoth skin sample

Analyses of ancient DNA typically involve sequencing the surviving short oligonucleotides and aligning to genome assemblies from related, modern species. Here, we report that skin from a female woolly mammoth (†Mammuthus primigenius) that died 52,000 years ago retained its ancient genome architecture. We use PaleoHi-C to map chromatin contacts and assemble its genome, yielding 28 chromosome-length scaffolds. Chromosome territories, compartments, loops, Barr bodies, and inactive X chromosome (Xi) superdomains persist. The active and inactive genome compartments in mammoth skin more closely resemble Asian elephant skin than other elephant tissues. Our analyses uncover new biology. Differences in compartmentalization reveal genes whose transcription was potentially altered in mammoths vs. elephants. Mammoth Xi has a tetradic architecture, not bipartite like human and mouse. We hypothesize that, shortly after this mammoth's death, the sample spontaneously freeze-dried in the Siberian cold, leading to a glass transition that preserved subfossils of ancient chromosomes at nanometer scale.

Vaginal and rectal microbiome contribute to genital inflammation in chronic pelvic pain

BACKGROUND

Chronic pelvic pain (CPP) is a multifactorial syndrome that can substantially affect a patient's quality of life. Endometriosis is one cause of CPP, and alterations of the immune and microbiome profiles have been observed in patients with endometriosis. The objective of this pilot study was to investigate differences in the vaginal and gastrointestinal microbiomes and cervicovaginal immune microenvironment in patients with CPP and endometriosis diagnosis compared to those with CPP without endometriosis and no CPP.

METHODS

Vaginal swabs, rectal swabs, and cervicovaginal lavages (CVL) were collected among individuals undergoing gynecologic laparoscopy. Participants were grouped based on patients seeking care for chronic pain and/or pathology results: CPP and endometriosis (CPP-Endo) (n = 35), CPP without endometriosis (n = 23), or patients without CPP or endometriosis (controls) (n = 15). Sensitivity analyses were performed on CPP with endometriosis location, stage, and co-occurring gynecologic conditions (abnormal uterine bleeding, fibroids). 16S rRNA sequencing was performed to profile the microbiome, and a panel of soluble immune mediators was quantified using a multiplex assay. Statistical analysis was conducted with SAS, R, MicrobiomeAnalyst, MetaboAnalyst, and QIIME 2.

RESULTS

Significant differences were observed between participants with CPP alone, CPP-Endo, and surgical controls for body mass index, ethnicity, diagnosis of ovarian cysts, and diagnosis of fibroids. In rectal microbiome analysis, both CPP alone and CPP-Endo exhibited lower alpha diversity than controls, and both CPP groups revealed enrichment of irritable bowel syndrome-associated bacteria. CPP-Endo exhibited an increased abundance of vaginal Streptococcus anginosus and rectal Ruminococcus. Patients with CPP and endometrioma (s) demonstrated increased vaginal Streptococcus, Lactobacillus, and Prevotella compared to other endometriosis sites. Further, abnormal uterine bleeding was associated with an increased abundance of bacterial vaginosis-associated bacteria. Immunoproteomic profiles were distinctly clustered by CPP alone and CPP-Endo compared to controls. CPP-Endo was enriched in TNF⍺, MDC, and IL-1⍺.

CONCLUSIONS

Vaginal and rectal microbiomes were observed to differ between patients with CPP alone and CPP with endometriosis, which may be useful in personalized treatment for individuals with CPP and endometriosis from those with other causes of CPP. Further investigation is warranted in patients with additional co-occurring conditions, such as AUB/fibroids, which add additional complexity to these conditions and reveal the enrichment of distinct pathogenic bacteria in both mucosal sites. This study provides foundational microbiome-immunoproteomic knowledge related to chronic pelvic pain, endometriosis, and co-occurring gynecologic conditions that can help improve the treatment of patients seeking care for pain.

Insights into non-crossover recombination from long-read sperm sequencing

Meiotic recombination is a fundamental process that generates genetic diversity by creating new combinations of existing alleles. Although human crossovers have been studied at the pedigree, population and single-cell level, the more frequent non-crossover events that lead to gene conversion are harder to study, particularly at the individual level. Here we show that single high-fidelity long sequencing reads from sperm can capture both crossovers and non-crossovers, allowing effectively arbitrary sample sizes for analysis from one male. Using fifteen sperm samples from thirteen donors we demonstrate variation between and within donors for the rates of different types of recombination. Intriguingly, we observe a tendency for non-crossover gene conversions to occur upstream of nearby PRDM9 binding sites, whereas crossover locations have a slight downstream bias. We further provide evidence for two distinct non-crossover processes. One gives rise to the vast majority of non-crossovers with mean conversion tract length under 50bp, which we suggest is an outcome of standard PRDM9-induced meiotic recombination. In contrast ~2% of non-crossovers have much longer mean tract length, and potentially originate from the same process as complex events with more than two haplotype switches, which is not associated with PRDM9 binding sites and is also seen in somatic cells.

Every CFTR variant counts - Target-capture based next-generation-sequencing for molecular diagnosis in the German CF Registry

BACKGROUND

In times of genotype guided therapy options, a total of 3.2 % of people with CF (pwCF) in the German CF Registry[1] only have one or no CFTR-variant detected after genetic analysis. Additionally, genetic data in the Registry can be documented as free text and can therefore be prone to error. In order to allow the greatest possible amount of pwCF access to modern therapies, we conducted a re-evaluation of free text entries and established a custom-whole-CFTR-locus NGS-approach for all pwCF who remained without genetic confirmation afterwards.

METHODS

To this end, we assembled 731 free text variants of 655 pwCF in the German CF Registry. All variants were evaluated using ClinVar, HGMD and CFTR1/2, corrected in the Registries' database and uploaded to ClinVar. PwCF whose diagnosis remained uncertain as well as additional pwCF or pwCFTR-RD that were assembled through a nationwide call for testing of unclear cases were offered genetic analysis. Samples were analysed using a target-capture based NGS-custom-design-panel covering the entire CFTR-locus.

RESULTS

Evaluation of free text variants led to the discovery of 43 variants not formerly reported in the context of CF. The Registries' dropdown list was extended by 497 variants and over 500 pwCF were provided with their most up-to-date genotype. Samples of 47 pwCF/pwCFTR-RD were sequenced via NGS with an overall success rate of 61.7 %, resulting in implementation of entire CFTR-genotyping into routine diagnostics.

CONCLUSION

Entire CFTR-genotyping can greatly increase the genetic diagnostic rate of pwCF/pwCFTR-RD and should be considered after inconspicuous CFTR screening panels in CFTR-diagnostics.

LINC01432 binds to CELF2 in newly diagnosed multiple myeloma promoting short progression-free survival to standard therapy

Multiple Myeloma (MM) is a highly prevalent and incurable form of cancer that arises from malignant plasma cells, with over 35,000 new cases diagnosed annually in the United States. While there are a growing number of approved therapies, MM remains incurable and nearly all patients will relapse and exhaust all available treatment options. Mechanisms for disease progression are unclear and in particular, little is known regarding the role of long non-coding RNAs (lncRNA) in mediating disease progression and response to treatment. In this study, we used transcriptome sequencing to compare newly diagnosed MM patients who had short progression-free survival (PFS) to standard first-line treatment (PFS < 24 months) to patients who had prolonged PFS (PFS > 24 months). We identified 157 differentially upregulated lncRNAs with short PFS and focused our efforts on characterizing the most upregulated lncRNA, LINC01432. We investigated LINC01432 overexpression and CRISPR/Cas9 knockdown in MM cell lines to show that LINC01432 overexpression significantly increases cell viability and reduces apoptosis, while knockdown significantly reduces viability and increases apoptosis, supporting the clinical relevance of this lncRNA. Next, we used individual-nucleotide resolution cross-linking immunoprecipitation with RT-qPCR to show that LINC01432 directly interacts with the RNA binding protein, CELF2. Lastly, we showed that LINC01432-targeted locked nucleic acid antisense oligonucleotides reduce viability and increases apoptosis. In summary, this fundamental study identified lncRNAs associated with short PFS to standard NDMM treatment and further characterized LINC01432, which inhibits apoptosis.

Phasing Diploid Genome Assembly Graphs with Single-Cell Strand Sequencing

Haplotype information is crucial for biomedical and population genetics research. However, current strategies to produce de-novo haplotype-resolved assemblies often require either difficult-to-acquire parental data or an intermediate haplotype-collapsed assembly. Here, we present Graphasing, a workflow which synthesizes the global phase signal of Strand-seq with assembly graph topology to produce chromosome-scale de-novo haplotypes for diploid genomes. Graphasing readily integrates with any assembly workflow that both outputs an assembly graph and has a haplotype assembly mode. Graphasing performs comparably to trio-phasing in contiguity, phasing accuracy, and assembly quality, outperforms Hi-C in phasing accuracy, and generates human assemblies with over 18 chromosome-spanning haplotypes.

The role of GPD1L, a sodium channel interacting gene, in the pathogenesis of Brugada Syndrome

Background

Brugada Syndrome (BrS) is an inherited arrhythmia syndrome in which mutations in the cardiac sodium channel SCN5A (NaV1.5) account for approximately 20% of cases. Mutations in sodium channel-modifying genes may account for additional BrS cases, though BrS may be polygenic given common SNPs associated with BrS have been identified. Recent analysis, however, has suggested that SCN5A should be regarded as the sole monogenic cause of BrS.

Objective

We sought to re-assess the genetic underpinnings of BrS in a large mutligenerational family with a putative mutation in GPD1L that affects surface membrane expression of NaV1.5 in vitro.

Methods

Fine linkage mapping was performed in the family using the Illumina Global Screening Array. Whole exome sequencing of the proband was performed to identify rare variants and mutations, and Sanger sequencing was used to assay previously-reported risk single nucleotide polymorphsims (SNPs) for BrS.

Results

Linkage analysis decreased the size of the previously-reported microsatellite linkage region to approximately 3 Mb. GPD1L-A280V was the only coding non-synonymous variation present at less than 1% allele frequency in the proband within the linkage region. No rare non-synonymous variants were present outside the linkage area in affected individuals in genes associated with BrS. Risk SNPs known to predispose to BrS were overrepresented in affected members of the family.

Conclusion

Together, our data suggest GPD1L-A280V remains the most likely cause of BrS in this large multigenerational family. While care should be taken in interpreting variant pathogenicity given the genetic uncertainty of BrS, our data support inclusion of other putative BrS genes in clinical genetic panels.

SwissGenVar: A Platform for Clinical-Grade Interpretation of Genetic Variants to Foster Personalized Healthcare in Switzerland

Large-scale next-generation sequencing (NGS) germline testing is technically feasible today, but variant interpretation represents a major bottleneck in analysis workflows. This includes extensive variant prioritization, annotation, and time-consuming evidence curation. The scale of the interpretation problem is massive, and variants of uncertain significance (VUSs) are a challenge to personalized medicine. This challenge is further compounded by the complexity and heterogeneity of the standards used to describe genetic variants and the associated phenotypes when searching for relevant information to support clinical decision making. To address this, all five Swiss academic institutions for Medical Genetics joined forces with the Swiss Institute of Bioinformatics (SIB) to create SwissGenVar as a user-friendly nationwide repository and sharing platform for genetic variant data generated during routine diagnostic procedures and research sequencing projects. Its aim is to provide a protected environment for expert evidence sharing about individual variants to harmonize and upscale their significance interpretation at the clinical grade according to international standards. To corroborate the clinical assessment, the variant-related data will be combined with consented high-quality clinical information. Broader visibility will be achieved by interfacing with international databases, thus supporting global initiatives in personalized healthcare.

The clock-like accumulation of germline and somatic mutations can arise from the interplay of DNA damage and repair

The rates at which mutations accumulate across human cell types vary. To identify causes of this variation, mutations are often decomposed into a combination of the single-base substitution (SBS) "signatures" observed in germline, soma, and tumors, with the idea that each signature corresponds to one or a small number of underlying mutagenic processes. Two such signatures turn out to be ubiquitous across cell types: SBS signature 1, which consists primarily of transitions at methylated CpG sites thought to be caused by spontaneous deamination, and the more diffuse SBS signature 5, which is of unknown etiology. In cancers, the number of mutations attributed to these 2 signatures accumulates linearly with age of diagnosis, and thus the signatures have been termed "clock-like." To better understand this clock-like behavior, we develop a mathematical model that includes DNA replication errors, unrepaired damage, and damage repaired incorrectly. We show that mutational signatures can exhibit clock-like behavior because cell divisions occur at a constant rate and/or because damage rates remain constant over time, and that these distinct sources can be teased apart by comparing cell lineages that divide at different rates. With this goal in mind, we analyze the rate of accumulation of mutations in multiple cell types, including soma as well as male and female germline. We find no detectable increase in SBS signature 1 mutations in neurons and only a very weak increase in mutations assigned to the female germline, but a significant increase with time in rapidly dividing cells, suggesting that SBS signature 1 is driven by rounds of DNA replication occurring at a relatively fixed rate. In contrast, SBS signature 5 increases with time in all cell types, including postmitotic ones, indicating that it accumulates independently of cell divisions; this observation points to errors in DNA repair as the key underlying mechanism. Thus, the two "clock-like" signatures observed across cell types likely have distinct origins, one set by rates of cell division, the other by damage rates.

Comprehensive network modeling approaches unravel dynamic enhancer-promoter interactions across neural differentiation

Background

Increasing evidence suggests that a substantial proportion of disease-associated mutations occur in enhancers, regions of non-coding DNA essential to gene regulation. Understanding the structures and mechanisms of regulatory programs this variation affects can shed light on the apparatuses of human diseases.

Results

We collected epigenetic and gene expression datasets from seven early time points during neural differentiation. Focusing on this model system, we constructed networks of enhancer-promoter interactions, each at an individual stage of neural induction. These networks served as the base for a rich series of analyses, through which we demonstrated their temporal dynamics and enrichment for various disease-associated variants. We applied the Girvan-Newman clustering algorithm to these networks to reveal biologically relevant substructures of regulation. Additionally, we demonstrated methods to validate predicted enhancer-promoter interactions using transcription factor overexpression and massively parallel reporter assays.

Conclusions

Our findings suggest a generalizable framework for exploring gene regulatory programs and their dynamics across developmental processes. This includes a comprehensive approach to studying the effects of disease-associated variation on transcriptional networks. The techniques applied to our networks have been published alongside our findings as a computational tool, E-P-INAnalyzer. Our procedure can be utilized across different cellular contexts and disorders.

Combining DNA and protein alignments to improve genome annotation with LiftOn

As the number and variety of assembled genomes continues to grow, the number of annotated genomes is falling behind, particularly for eukaryotes. DNA-based mapping tools help to address this challenge, but they are only able to transfer annotation between closely-related species. Here we introduce LiftOn, a homology-based software tool that integrates DNA and protein alignments to enhance the accuracy of genome-scale annotation and to allow mapping between relatively distant species. LiftOn's protein-centric algorithm considers both types of alignments, chooses optimal open reading frames, resolves overlapping gene loci, and finds additional gene copies where they exist. LiftOn can reliably transfer annotation between genomes representing members of the same species, as we demonstrate on human, mouse, honey bee, rice, and Arabidopsis thaliana. It can further map annotation effectively across species pairs as far apart as mouse and rat or Drosophila melanogaster and D. erecta.

Understanding the genomic heterogeneity of North African Imazighen: from broad to microgeographical perspectives

The strategic location of North Africa has led to cultural and demographic shifts, shaping its genetic structure. Historical migrations brought different genetic components that are evident in present-day North African genomes, along with autochthonous components. The Imazighen (plural of Amazigh) are believed to be the descendants of autochthonous North Africans and speak various Amazigh languages, which belong to the Afro-Asiatic language family. However, the arrival of different human groups, especially during the Arab conquest, caused cultural and linguistic changes in local populations, increasing their heterogeneity. We aim to characterize the genetic structure of the region, using the largest Amazigh dataset to date and other reference samples. Our findings indicate microgeographical genetic heterogeneity among Amazigh populations, modeled by various admixture waves and different effective population sizes. A first admixture wave is detected group-wide around the twelfth century, whereas a second wave appears in some Amazigh groups around the nineteenth century. These events involved populations with higher genetic ancestry from south of the Sahara compared to the current North Africans. A plausible explanation would be the historical trans-Saharan slave trade, which lasted from the Roman times to the nineteenth century. Furthermore, our investigation shows that assortative mating in North Africa has been rare.

Mind the gap: the relevance of the genome reference to resolve rare and pathogenic inversions

Both long-read genome sequencing (lrGS) and the recently published Telomere to Telomere (T2T) reference genome provide increased coverage and resolution across repetitive regions promising heightened structural variant detection and improved mapping. Inversions (INV), intrachromosomal segments which are rotated 180° and inserted back into the same chromosome, are a class of structural variants particularly challenging to detect due to their copy-number neutral state and association with repetitive regions. Inversions represent about 1/20 of all balanced structural chromosome aberrations and can lead to disease by gene disruption or altering regulatory regions of dosage sensitive genes in cis . Here we remapped the genome data from six individuals carrying unsolved cytogenetically detected inversions. An INV6 and INV10 were resolved using GRCh38 and T2T-CHM13. Finally, an INV9 required optical genome mapping, de novo assembly of lrGS data and T2T-CHM13. This inversion disrupted intron 25 of EHMT1, confirming a diagnosis of Kleefstra syndrome 1 (MIM#610253). These three inversions, only mappable in specific references, prompted us to investigate the presence and population frequencies of differential reference regions (DRRs) between T2T-CHM13, GRCh37, GRCh38, the chimpanzee and bonobo, and hundreds of megabases of DRRs were identified. Our results emphasize the significance of the chosen reference genome and the added benefits of lrGS and optical genome mapping in solving rearrangements in challenging regions of the genome. This is particularly important for inversions and may impact clinical diagnostics.

Epithelial-derived interleukin-23 promotes oral mucosal immunopathology

At mucosal surfaces, epithelial cells provide a structural barrier and an immune defense system. However, dysregulated epithelial responses can contribute to disease states. Here, we demonstrated that epithelial cell-intrinsic production of interleukin-23 (IL-23) triggers an inflammatory loop in the prevalent oral disease periodontitis. Epithelial IL-23 expression localized to areas proximal to the disease-associated microbiome and was evident in experimental models and patients with common and genetic forms of disease. Mechanistically, flagellated microbial species of the periodontitis microbiome triggered epithelial IL-23 induction in a TLR5 receptor-dependent manner. Therefore, unlike other Th17-driven diseases, non-hematopoietic-cell-derived IL-23 served as an initiator of pathogenic inflammation in periodontitis. Beyond periodontitis, analysis of publicly available datasets revealed the expression of epithelial IL-23 in settings of infection, malignancy, and autoimmunity, suggesting a broader role for epithelial-intrinsic IL-23 in human disease. Collectively, this work highlights an important role for the barrier epithelium in the induction of IL-23-mediated inflammation.

Survival-Associated Cellular Response Maintained in Pancreatic Ductal Adenocarcinoma (PDAC) Switched Between Soft and Stiff 3D Microgel Culture

Pancreatic ductal adenocarcinoma (PDAC) accounts for about 90% of all pancreatic cancer cases. Five-year survival rates have remained below 12% since the 1970s, in part due to the difficulty in detection prior to metastasis (migration and invasion into neighboring organs and glands). Mechanical memory is a concept that has emerged over the past decade that may provide a path toward understanding how invading PDAC cells "remember" the mechanical properties of their diseased ("stiff", elastic modulus, E ≈ 10 kPa) microenvironment even while invading a healthy ("soft", E ≈ 1 kPa) microenvironment. Here, we investigated the role of mechanical priming by culturing a dilute suspension of PDAC (FG) cells within a 3D, rheologically tunable microgel platform from hydrogels with tunable mechanical properties. We conducted a suite of acute (short-term) priming studies where we cultured PDAC cells in either a soft (E ≈ 1 kPa) or stiff (E ≈ 10 kPa) environment for 6 h, then removed and placed them into a new soft or stiff 3D environment for another 18 h. Following these steps, we conducted RNA-seq analyses to quantify gene expression. Initial priming in the 3D culture showed persistent gene expression for the duration of the study, regardless of the subsequent environments (stiff or soft). Stiff 3D culture was associated with the downregulation of tumor suppressors (LATS1, BCAR3, CDKN2C), as well as the upregulation of cancer-associated genes (RAC3). Immunofluorescence staining (BCAR3, RAC3) further supported the persistence of this cellular response, with BCAR3 upregulated in soft culture and RAC3 upregulated in stiff-primed culture. Stiff-primed genes were stratified against patient data found in The Cancer Genome Atlas (TCGA). Upregulated genes in stiff-primed 3D culture were associated with decreased survival in patient data, suggesting a link between patient survival and mechanical priming.

Machine learning on alignment features for parent-of-origin classification of simulated hybrid RNA-seq

BACKGROUND

Parent-of-origin allele-specific gene expression (ASE) can be detected in interspecies hybrids by virtue of RNA sequence variants between the parental haplotypes. ASE is detectable by differential expression analysis (DEA) applied to the counts of RNA-seq read pairs aligned to parental references, but aligners do not always choose the correct parental reference.

RESULTS

We used public data for species that are known to hybridize. We measured our ability to assign RNA-seq read pairs to their proper transcriptome or genome references. We tested software packages that assign each read pair to a reference position and found that they often favored the incorrect species reference. To address this problem, we introduce a post process that extracts alignment features and trains a random forest classifier to choose the better alignment. On each simulated hybrid dataset tested, our machine-learning post-processor achieved higher accuracy than the aligner by itself at choosing the correct parent-of-origin per RNA-seq read pair.

CONCLUSIONS

For the parent-of-origin classification of RNA-seq, machine learning can improve the accuracy of alignment-based methods. This approach could be useful for enhancing ASE detection in interspecies hybrids, though RNA-seq from real hybrids may present challenges not captured by our simulations. We believe this is the first application of machine learning to this problem domain.

SingleQ: a comprehensive database of single-cell expression quantitative trait loci (sc-eQTLs) cross human tissues

Mapping of expression quantitative trait loci (eQTLs) and other molecular QTLs can help characterize the modes of action of disease-associated genetic variants. However, current eQTL databases present data from bulk RNA-seq approaches, which cannot shed light on the cell type- and environment-specific regulation of disease-associated genetic variants. Here, we introduce our Single-cell eQTL Interactive Database which collects single-cell eQTL (sc-eQTL) datasets and provides online visualization of sc-eQTLs across different cell types in a user-friendly manner. Although sc-eQTL mapping is still in its early stage, our database curates the most comprehensive summary statistics of sc-eQTLs published to date. sc-eQTL studies have revolutionized our understanding of gene regulation in specific cellular contexts, and we anticipate that our database will further accelerate the research of functional genomics. Database URL: http://www.sqraolab.com/scqtl.

Where Are the Formerly Y-linked Genes in the Ryukyu Spiny Rat that has Lost its Y Chromosome?

It has been predicted that the highly degenerate mammalian Y chromosome will be lost eventually. Indeed, Y was lost in the Ryukyu spiny rat Tokudaia osimensis, but the fate of the formerly Y-linked genes is not completely known. We looked for all 12 ancestrally Y-linked genes in a draft T. osimensis genome sequence. Zfy1, Zfy2, Kdm5d, Eif2s3y, Usp9y, Uty, and Ddx3y are putatively functional and are now located on the X chromosome, whereas Rbmy, Uba1y, Ssty1, Ssty2, and Sry are missing or pseudogenized. Tissue expressions of the mouse orthologs of the retained genes are significantly broader/higher than those of the lost genes, suggesting that the destinies of the formerly Y-linked genes are related to their original expressions. Interestingly, patterns of gene retention/loss are significantly more similar than by chance across four rodent lineages where Y has been independently lost, indicating a level of certainty in the fate of Y-linked genes even when the chromosome is gone.

Activation of recombinases at specific DNA loci by zinc-finger domain insertions

Recombinases have several potential advantages as genome editing tools compared to nucleases and other editing enzymes, but the process of engineering them to efficiently recombine predetermined DNA targets demands considerable investment of time and labor. Here we sought to harness zinc-finger DNA-binding domains (ZFDs) to program recombinase binding by developing fusions, in which ZFDs are inserted into recombinase coding sequences. By screening libraries of hybrid proteins, we optimized the insertion site, linker length, spacing and ZFD orientation and generated Cre-type recombinases that remain dormant unless the insertionally fused ZFD binds its target site placed in the vicinity of the recombinase binding site. The developed fusion improved targeted editing efficiencies of recombinases by four-fold and abolished measurable off-target activity in mammalian cells. The ZFD-dependent activity is transferable to a recombinase with relaxed specificity, providing the means for developing fully programmable recombinases. Our engineered recombinases provide improved genome editing tools with increased precision and efficiency.

A chromosome-level genome for the nudibranch gastropod Berghia stephanieae helps parse clade-specific gene expression in novel and conserved phenotypes

BACKGROUND

How novel phenotypes originate from conserved genes, processes, and tissues remains a major question in biology. Research that sets out to answer this question often focuses on the conserved genes and processes involved, an approach that explicitly excludes the impact of genetic elements that may be classified as clade-specific, even though many of these genes are known to be important for many novel, or clade-restricted, phenotypes. This is especially true for understudied phyla such as mollusks, where limited genomic and functional biology resources for members of this phylum have long hindered assessments of genetic homology and function. To address this gap, we constructed a chromosome-level genome for the gastropod Berghia stephanieae (Valdés, 2005) to investigate the expression of clade-specific genes across both novel and conserved tissue types in this species.

RESULTS

The final assembled and filtered Berghia genome is comparable to other high-quality mollusk genomes in terms of size (1.05 Gb) and number of predicted genes (24,960 genes) and is highly contiguous. The proportion of upregulated, clade-specific genes varied across tissues, but with no clear trend between the proportion of clade-specific genes and the novelty of the tissue. However, more complex tissue like the brain had the highest total number of upregulated, clade-specific genes, though the ratio of upregulated clade-specific genes to the total number of upregulated genes was low.

CONCLUSIONS

Our results, when combined with previous research on the impact of novel genes on phenotypic evolution, highlight the fact that the complexity of the novel tissue or behavior, the type of novelty, and the developmental timing of evolutionary modifications will all influence how novel and conserved genes interact to generate diversity.

Impact of genome build on RNA-seq interpretation and diagnostics

Transcriptomics is a powerful tool for unraveling the molecular effects of genetic variants and disease diagnosis. Prior studies have demonstrated that choice of genome build impacts variant interpretation and diagnostic yield for genomic analyses. To identify the extent genome build also impacts transcriptomics analyses, we studied the effect of the hg19, hg38, and CHM13 genome builds on expression quantification and outlier detection in 386 rare disease and familial control samples from both the Undiagnosed Diseases Network (UDN) and Genomics Research to Elucidate the Genetics of Rare Disease (GREGoR) Consortium. We identified 2,800 genes with build-dependent quantification across six routinely-collected biospecimens, including 1,391 protein-coding genes and 341 known rare disease genes. We further observed multiple genes that only have detectable expression in a subset of genome builds. Finally, we characterized how genome build impacts the detection of outlier transcriptomic events. Combined, we provide a database of genes impacted by build choice, and recommend that transcriptomics-guided analyses and diagnoses are cross-referenced with these data for robustness.

BCFtools/liftover: an accurate and comprehensive tool to convert genetic variants across genome assemblies

MOTIVATION

Many genetics studies report results tied to genomic coordinates of a legacy genome assembly. However, as assemblies are updated and improved, researchers are faced with either realigning raw sequence data using the updated coordinate system or converting legacy datasets to the updated coordinate system to be able to combine results with newer datasets. Currently available tools to perform the conversion of genetic variants have numerous shortcomings, including poor support for indels and multi-allelic variants, that lead to a higher rate of variants being dropped or incorrectly converted. As a result, many researchers continue to work with and publish using legacy genomic coordinates.

RESULTS

Here we present BCFtools/liftover, a tool to convert genomic coordinates across genome assemblies for variants encoded in the variant call format with improved support for indels represented by different reference alleles across genome assemblies and full support for multi-allelic variants. It further supports variant annotation fields updates whenever the reference allele changes across genome assemblies. The tool has the lowest rate of variants being dropped with an order of magnitude less indels dropped or incorrectly converted and is an order of magnitude faster than other tools typically used for the same task. It is particularly suited for converting variant callsets from large cohorts to novel telomere-to-telomere assemblies as well as summary statistics from genome-wide association studies tied to legacy genome assemblies.

AVAILABILITY AND IMPLEMENTATION

The tool is written in C and freely available under the MIT open source license as a BCFtools plugin available at http://github.com/freeseek/score.

Pleiotropic effects of extracellular vesicles from induced pluripotent stem cell-derived cardiomyocytes on ischemic cardiomyopathy: A preclinical study

BACKGROUND

Stem cell-secreted extracellular vesicles (EVs) play essential roles in intercellular communication and restore cardiac function in animal models of ischemic heart disease. However, few studies have used EVs derived from clinical-grade stem cells and their derivatives with stable quality. Moreover, there is little information on the mechanism and time course of the multifactorial effect of EV therapy from the acute to the chronic phase, the affected cells, and whether the effects are direct or indirect.

METHODS

Induced pluripotent stem cell-derived cardiomyocytes (iPSCM) were produced using a clinical-grade differentiation induction system. EVs were isolated from the conditioned medium by ultracentrifugation and characterized in silico, in vitro, and in vivo. A rat model of myocardial infarction was established by left anterior descending artery ligation and treated with iPSCM-derived EVs.

RESULTS

iPSCM-derived EVs contained microRNAs and proteins associated with angiogenesis, antifibrosis, promotion of M2 macrophage polarization, cell proliferation, and antiapoptosis. iPSCM-derived EV treatment improved left ventricular function and reduced mortality in the rat model by improving vascularization and suppressing fibrosis and chronic inflammation in the heart. EVs were uptaken by cardiomyocytes, endothelial cells, fibroblasts, and macrophages in the cardiac tissues. The pleiotropic effects occurred due to the direct effects of microRNAs and proteins encapsulated in EVs and indirect paracrine effects on M2 macrophages.

CONCLUSIONS

Clinical-grade iPSCM-derived EVs improve cardiac function by regulating various genes and pathways in various cell types and may have clinical potential for treating ischemic heart disease.

Chronological and genetic analysis of an Upper Palaeolithic female infant burial from Borsuka Cave, Poland

Six infant human teeth and 112 animal tooth pendants from Borsuka Cave were identified as the oldest burial in Poland. However, uncertainties around the dating and the association of the teeth to the pendants have precluded their association with an Upper Palaeolithic archaeological industry. Using <67 mg per tooth, we combined dating and genetic analyses of two human teeth and six herbivore tooth pendants to address these questions. Our interdisciplinary approach yielded informative results despite limited sampling material, and high levels of degradation and contamination. Our results confirm the Palaeolithic origin of the human remains and herbivore pendants, and permit us to identify the infant as female and discuss the association of the assemblage with different Palaeolithic industries. This study exemplifies the progress that has been made toward minimally destructive methods and the benefits of integrating methods to maximize data retrieval from precious but highly degraded and contaminated prehistoric material.

Rapid intestinal and systemic metabolic reprogramming in an immunosuppressed environment

Intrinsic metabolism shapes the immune environment associated with immune suppression and tolerance in settings such as organ transplantation and cancer. However, little is known about the metabolic activities in an immunosuppressive environment. In this study, we employed metagenomic, metabolomic, and immunological approaches to profile the early effects of the immunosuppressant drug tacrolimus, antibiotics, or both in gut lumen and circulation using a murine model. Tacrolimus induced rapid and profound alterations in metabolic activities within two days of treatment, prior to alterations in gut microbiota composition and structure. The metabolic profile and gut microbiome after seven days of treatment was distinct from that after two days of treatment, indicating continuous drug effects on both gut microbial ecosystem and host metabolism. The most affected taxonomic groups are Clostriales and Verrucomicrobiae (i.e., Akkermansia muciniphila), and the most affected metabolic pathways included a group of interconnected amino acids, bile acid conjugation, glucose homeostasis, and energy production. Highly correlated metabolic changes were observed between lumen and serum metabolism, supporting their significant interactions. Despite a small sample size, this study explored the largely uncharacterized microbial and metabolic events in an immunosuppressed environment and demonstrated that early changes in metabolic activities can have significant implications that may serve as antecedent biomarkers of immune activation or quiescence. To understand the intricate relationships among gut microbiome, metabolic activities, and immune cells in an immune suppressed environment is a prerequisite for developing strategies to monitor and optimize alloimmune responses that determine transplant outcomes.

Downregulated NPAS4 in multiple brain regions is associated with major depressive disorder

Major Depressive Disorder (MDD) is a commonly observed psychiatric disorder that affects more than 2% of the world population with a rising trend. However, disease-associated pathways and biomarkers are yet to be fully comprehended. In this study, we analyzed previously generated RNA-seq data across seven different brain regions from three distinct studies to identify differentially and co-expressed genes for patients with MDD. Differential gene expression (DGE) analysis revealed that NPAS4 is the only gene downregulated in three different brain regions. Furthermore, co-expressing gene modules responsible for glutamatergic signaling are negatively enriched in these regions. We used the results of both DGE and co-expression analyses to construct a novel MDD-associated pathway. In our model, we propose that disruption in glutamatergic signaling-related pathways might be associated with the downregulation of NPAS4 and many other immediate-early genes (IEGs) that control synaptic plasticity. In addition to DGE analysis, we identified the relative importance of KEGG pathways in discriminating MDD phenotype using a machine learning-based approach. We anticipate that our study will open doors to developing better therapeutic approaches targeting glutamatergic receptors in the treatment of MDD.

Molecular and Metabolic Analysis of Arsenic-Exposed Humanized AS3MT Mice

BACKGROUND

Chronic exposure to inorganic arsenic (iAs) has been associated with type 2 diabetes (T2D). However, potential sex divergence and the underlying mechanisms remain understudied. iAs is not metabolized uniformly across species, which is a limitation of typical exposure studies in rodent models. The development of a new "humanized" mouse model overcomes this limitation. In this study, we leveraged this model to study sex differences in the context of iAs exposure.

OBJECTIVES

The aim of this study was to determine if males and females exhibit different liver and adipose molecular profiles and metabolic phenotypes in the context of iAs exposure.

METHODS

Our study was performed on wild-type (WT) 129S6/SvEvTac and humanized arsenic + 3 methyl transferase (human AS3MT) 129S6/SvEvTac mice treated with 400   ppb of iAs via drinking water ad libitum. After 1 month, mice were sacrificed and the liver and gonadal adipose depots were harvested for iAs quantification and sequencing-based microRNA and gene expression analysis. Serum blood was collected for fasting blood glucose, fasting plasma insulin, and homeostatic model assessment for insulin resistance (HOMA-IR).

RESULTS

We detected sex divergence in liver and adipose markers of diabetes (e.g., miR-34a, insulin signaling pathways, fasting blood glucose, fasting plasma insulin, and HOMA-IR) only in humanized (not WT) mice. In humanized female mice, numerous genes that promote insulin sensitivity and glucose tolerance in both the liver and adipose are elevated compared to humanized male mice. We also identified Klf11 as a putative master regulator of the sex divergence in gene expression in humanized mice.

DISCUSSION

Our study underscored the importance of future studies leveraging the humanized mouse model to study iAs-associated metabolic disease. The findings suggested that humanized males are at increased risk for metabolic dysfunction relative to humanized females in the context of iAs exposure. Future investigations should focus on the detailed mechanisms that underlie the sex divergence. https://doi.org/10.1289/EHP12785.

Long-range RNA structures in the human transcriptome beyond evolutionarily conserved regions

RNA structure has been increasingly recognized as a critical player in the biogenesis and turnover of many transcripts classes. In eukaryotes, the prediction of RNA structure by thermodynamic modeling meets fundamental limitations due to the large sizes and complex, discontinuous organization of eukaryotic genes. Signatures of functional RNA structures can be found by detecting compensatory substitutions in homologous sequences, but a comparative approach is applicable only within conserved sequence blocks. Here, we developed a computational pipeline called PHRIC, which is not limited to conserved regions and relies on RNA contacts derived from RNA in situ conformation sequencing (RIC-seq) experiments. It extracts pairs of short RNA fragments surrounded by nested clusters of RNA contacts and predicts long, nearly perfect complementary base pairings formed between these fragments. In application to a panel of RIC-seq experiments in seven human cell lines, PHRIC predicted ~12,000 stable long-range RNA structures with equilibrium free energy below -15 kcal/mol, the vast majority of which fall outside of regions annotated as conserved among vertebrates. These structures, nevertheless, show some level of sequence conservation and remarkable compensatory substitution patterns in other clades. Furthermore, we found that introns have a higher propensity to form stable long-range RNA structures between each other, and moreover that RNA structures tend to concentrate within the same intron rather than connect adjacent introns. These results for the first time extend the application of proximity ligation assays to RNA structure prediction beyond conserved regions.

Diverse African genomes reveal selection on ancient modern human introgressions in Neanderthals

Comparisons of Neanderthal genomes to anatomically modern human (AMH) genomes show a history of Neanderthal-to-AMH introgression stemming from interbreeding after the migration of AMHs from Africa to Eurasia. All non-sub-Saharan African AMHs have genomic regions genetically similar to Neanderthals that descend from this introgression. Regions of the genome with Neanderthal similarities have also been identified in sub-Saharan African populations, but their origins have been unclear. To better understand how these regions are distributed across sub-Saharan Africa, the source of their origin, and what their distribution within the genome tells us about early AMH and Neanderthal evolution, we analyzed a dataset of high-coverage, whole-genome sequences from 180 individuals from 12 diverse sub-Saharan African populations. In sub-Saharan African populations with non-sub-Saharan African ancestry, as much as 1% of their genomes can be attributed to Neanderthal sequence introduced by recent migration, and subsequent admixture, of AMH populations originating from the Levant and North Africa. However, most Neanderthal homologous regions in sub-Saharan African populations originate from migration of AMH populations from Africa to Eurasia ∼250 kya, and subsequent admixture with Neanderthals, resulting in ∼6% AMH ancestry in Neanderthals. These results indicate that there have been multiple migration events of AMHs out of Africa and that Neanderthal and AMH gene flow has been bi-directional. Observing that genomic regions where AMHs show a depletion of Neanderthal introgression are also regions where Neanderthal genomes show a depletion of AMH introgression points to deleterious interactions between introgressed variants and background genomes in both groups-a hallmark of incipient speciation.

Genomic Markers Associated with Cytomegalovirus DNAemia in Kidney Transplant Recipients

Human cytomegalovirus (CMV) is a major pathogen after solid organ transplantation, leading to high morbidity and mortality. Transplantation from a CMV-seropositive donor to a CMV-seronegative recipient (D+/R-) is associated with high risk of CMV disease. However, that risk is not uniform, suggesting a role for host factors in immune control of CMV. To identify host genetic factors that control CMV DNAemia post transplantation, we performed a whole-exome association study in two cohorts of D+/R- kidney transplant recipients. Quantitative CMV DNA was measured for at least one year following transplantation. Several CMV-protective single-nucleotide polymorphisms (SNPs) were identified in the first cohort (72 patients) but were not reproducible in the second cohort (126 patients). A meta-analysis of both cohorts revealed several SNPs that were significantly associated with protection from CMV DNAemia. The copy number variation of several genes was significantly different between recipients with and without CMV DNAemia. Amongst patients with CMV DNAemia in the second cohort, several variants of interest (p < 5 × 10-5), the most common of which was NLRC5, were associated with peak viral load. We provide new predictive genetic markers for protection of CMV DNAemia. These markers should be validated in larger cohorts.

The shared genetic architecture and evolution of human language and musical rhythm

Rhythm and language-related traits are phenotypically correlated, but their genetic overlap is largely unknown. Here, we leveraged two large-scale genome-wide association studies performed to shed light on the shared genetics of rhythm (N=606,825) and dyslexia (N=1,138,870). Our results reveal an intricate shared genetic and neurobiological architecture, and lay groundwork for resolving longstanding debates about the potential co-evolution of human language and musical traits.

Non-invasive monitoring of neoadjuvant radiation therapy response in soft tissue sarcomas by multiparametric MRI and quantification of circulating tumor DNA-A study protocol

BACKGROUND

Wide resection remains the cornerstone of localized soft-tissue sarcomas (STS) treatment. Neoadjuvant radiation therapy (NRT) may decrease the risk of local recurrences; however, its effectiveness for different histological STS subtypes has not been systematically investigated. The proposed prospective study evaluates the NRT response in STS using liquid biopsies and the correlation of multiparametric magnetic resonance imaging (mpMRI) with histopathology and immunohistochemistry.

METHODS

Patients with localized high-grade STS, who qualify for NRT, are included in this study.

LIQUID BIOPSIES

Quantification of circulating tumor DNA (ctDNA) in patient blood samples is performed by targeted next-generation sequencing. Soft-tissue sarcoma subtype-specific panel sequencing in combination with patient-specific exome sequencing allows the detection of individual structural variants and point mutations. Circulating free DNA is isolated from peritherapeutically collected patient plasma samples and ctDNA quantified therein. Identification of breakpoints is carried out using FACTERA. Bioinformatic analysis is performed using samtools, picard, fgbio, and the MIRACUM Pipeline.

MPMRI

Combination of conventional MRI sequences with diffusion-weighted imaging, intravoxel-incoherent motion, and dynamic contrast enhancement. Multiparametric MRI is performed before, during, and after NRT. We aim to correlate mpMRI data with the resected specimen's macroscopical, histological, and immunohistochemical findings.

RESULTS

Preliminary data support the notion that quantification of ctDNA in combination with tumor mass characterization through co-registration of mpMRI and histopathology can predict NRT response of STS.

CLINICAL RELEVANCE

The methods presented in this prospective study are necessary to assess therapy response in heterogeneous tumors and lay the foundation of future patient- and tumor-specific therapy concepts. These methods can be applied to various tumor entities. Thus, the participation and support of a wider group of oncologic surgeons are needed to validate these findings on a larger patient cohort.

O-GlcNAcylation determines the translational regulation and phase separation of YTHDF proteins

N6-methyladenosine (m6A) is the most abundant internal mRNA nucleotide modification in mammals, regulating critical aspects of cell physiology and differentiation. The YTHDF proteins are the primary readers of m6A modifications and exert physiological functions of m6A in the cytosol. Elucidating the regulatory mechanisms of YTHDF proteins is critical to understanding m6A biology. Here we report a mechanism that protein post-translational modifications control the biological functions of the YTHDF proteins. We find that YTHDF1 and YTHDF3, but not YTHDF2, carry high levels of nutrient-sensing O-GlcNAc modifications. O-GlcNAcylation attenuates the translation-promoting function of YTHDF1 and YTHDF3 by blocking their interactions with proteins associated with mRNA translation. We further demonstrate that O-GlcNAc modifications on YTHDF1 and YTHDF3 regulate the assembly, stability and disassembly of stress granules to enable better recovery from stress. Therefore, our results discover an important regulatory pathway of YTHDF functions, adding an additional layer of complexity to the post-transcriptional regulation function of mRNA m6A.

Rare Genomic Copy Number Variants Implicate New Candidate Genes for Bicuspid Aortic Valve

Bicuspid aortic valve (BAV), the most common congenital heart defect, is a major cause of aortic valve disease requiring valve interventions and thoracic aortic aneurysms predisposing to acute aortic dissections. The spectrum of BAV ranges from early onset valve and aortic complications (EBAV) to sporadic late onset disease. Rare genomic copy number variants (CNVs) have previously been implicated in the development of BAV and thoracic aortic aneurysms. We determined the frequency and gene content of rare CNVs in EBAV probands (n = 272) using genome-wide SNP microarray analysis and three complementary CNV detection algorithms (cnvPartition, PennCNV, and QuantiSNP). Unselected control genotypes from the Database of Genotypes and Phenotypes were analyzed using identical methods. We filtered the data to select large genic CNVs that were detected by multiple algorithms. Findings were replicated in cohorts with late onset sporadic disease (n = 5040). We identified 34 large and rare (< 1:1000 in controls) CNVs in EBAV probands. The burden of CNVs intersecting with genes known to cause BAV when mutated was increased in case-control analysis. CNVs intersecting with GATA4 and DSCAM were enriched in cases, recurrent in other datasets, and segregated with disease in families. In total, we identified potentially pathogenic CNVs in 8% of EBAV cases, implicating alterations of candidate genes at these loci in the pathogenesis of BAV.

Rational probe design for efficient rRNA depletion and improved metatranscriptomic analysis of human microbiomes

The microbiota that colonize the human gut and other tissues are dynamic, varying both in composition and functional state between individuals and over time. Gene expression measurements can provide insights into microbiome composition and function. However, efficient and unbiased removal of microbial ribosomal RNA (rRNA) presents a barrier to acquiring metatranscriptomic data. Here we describe a probe set that achieves efficient enzymatic rRNA removal of complex human-associated microbial communities. We demonstrate that the custom probe set can be further refined through an iterative design process to efficiently deplete rRNA from a range of human microbiome samples. Using synthetic nucleic acid spike-ins, we show that the rRNA depletion process does not introduce substantial quantitative error in gene expression profiles. Successful rRNA depletion allows for efficient characterization of taxonomic and functional profiles, including during the development of the human gut microbiome. The pan-human microbiome enzymatic rRNA depletion probes described here provide a powerful tool for studying the transcriptional dynamics and function of the human microbiome.

Genome sizes and repeatome evolution in zoantharians (Cnidaria: Hexacorallia: Zoantharia)

Across eukaryotes, large variations of genome sizes have been observed even between closely related species. Transposable elements as part of the repeated DNA have been proposed and confirmed as one of the most important contributors to genome size variation. However, the evolutionary implications of genome size variation and transposable element dynamics are not well understood. Together with phenotypic traits, they are commonly referred to as the "C-value enigma". The order Zoantharia are benthic cnidarians found from intertidal zones to the deep sea, and some species are particularly abundant in coral reefs. Despite their high ecological relevance, zoantharians have yet to be largely studied from the genomic point of view. This study aims at investigating the role of the repeatome (total content of repeated elements) in genome size variations across the order Zoantharia. To this end, whole-genomes of 32 zoantharian species representing five families were sequenced. Genome sizes were estimated and the abundances of different repeat classes were assessed. In addition, the repeat overlap between species was assessed by a sequence clustering method. The genome sizes in the dataset varied up to 2.4 fold magnitude. Significant correlations between genome size, repeated DNA content and transposable elements, respectively (Pearson's correlation test R2 = 0.47, p = 0.0016; R2 = 0.22, p = 0.05) were found, suggesting their involvement in the dynamics of genome expansion and reduction. In all species, long interspersed nuclear elements and DNA transposons were the most abundant identified elements. These transposable elements also appeared to have had a recent expansion event. This was in contrast to the comparative clustering analysis which revealed species-specific patterns of satellite elements' amplification. In summary, the genome sizes of zoantharians likely result from the complex dynamics of repeated elements. Finally, the majority of repeated elements (up to 70%) could not be annotated to a known repeat class, highlighting the need to further investigate non-model cnidarian genomes. More research is needed to understand how repeated DNA dynamics relate to zoantharian evolution and their biology.

Genotyping of the rare Para-Bombay blood group in southern Thailand

INTRODUCTION

The para-Bombay phenotype, or H-deficient secretor, results from different mutations of the FUT1, with or without the FUT2 mutation. Consequently, there is an absent or weak expression of the H antigen on red blood cells (RBCs). Routine ABO blood grouping for two siblings with blood group O showed discrepant results with their parental blood group AB. Fragments encompassing the entire coding region of the FUT1 and FUT2 genes were investigated.

METHODS

Blood and saliva specimens were collected to verify the correct ABO grouping by cell grouping, serum grouping and the hemagglutination inhibition (HI) test, respectively. The FUT1 and FUT2 genomes were identified using the whole-exome sequencing (WES) in two children's DNA blood specimens and may have caused, or been relative to, their blood group. Genetic variations of the FUT1 and FUT2 genes have been investigated in the other family members using the Sanger sequencing.

RESULTS

The serologic reaction results of the proband revealed that A, B and H antigens were absent on RBCs, and that the serum contained anti-H. However, ABH and AH antigens were present in the saliva PB1 and PB2, respectively. The probands PB1 and PB2 were assigned as AB and A blood groups, respectively. Blood genotyping confirmed that heterozygous mutations of the FUT1 gene, c.551_552delAG, were identified. Three family members, PB3, PB, and PB8, also showed normal ABO blood groups, but their genotypes were also the FUT1 mutation c.551_552delAG.

CONCLUSIONS

The FUT1 mutation c.551_552delAG may result in the reduced or absent H antigen production on RBCs, which characterizes the para-Bombay phenotypes. Blood genotyping is essential if these individuals need a blood transfusion or are planning to donate blood.

Reproducible Bioinformatics Analysis Workflows for Detecting IGH Gene Fusions in B-Cell Acute Lymphoblastic Leukaemia Patients

B-cell acute lymphoblastic leukaemia (B-ALL) is characterised by diverse genomic alterations, the most frequent being gene fusions detected via transcriptomic analysis (mRNA-seq). Due to its hypervariable nature, gene fusions involving the Immunoglobulin Heavy Chain (IGH) locus can be difficult to detect with standard gene fusion calling algorithms and significant computational resources and analysis times are required. We aimed to optimize a gene fusion calling workflow to achieve best-case sensitivity for IGH gene fusion detection. Using Nextflow, we developed a simplified workflow containing the algorithms FusionCatcher, Arriba, and STAR-Fusion. We analysed samples from 35 patients harbouring IGH fusions (IGH::CRLF2 n = 17, IGH::DUX4 n = 15, IGH::EPOR n = 3) and assessed the detection rates for each caller, before optimizing the parameters to enhance sensitivity for IGH fusions. Initial results showed that FusionCatcher and Arriba outperformed STAR-Fusion (85-89% vs. 29% of IGH fusions reported). We found that extensive filtering in STAR-Fusion hindered IGH reporting. By adjusting specific filtering steps (e.g., read support, fusion fragments per million total reads), we achieved a 94% reporting rate for IGH fusions with STAR-Fusion. This analysis highlights the importance of filtering optimization for IGH gene fusion events, offering alternative workflows for difficult-to-detect high-risk B-ALL subtypes.

Rapid intestinal and systemic metabolic reprogramming in an immunosuppressed environment

Intrinsic metabolism shapes the immune environment associated with immune suppression and tolerance in settings such as organ transplantation and cancer. However, little is known about the metabolic activities in an immunosuppressive environment. In this study, we employed metagenomic, metabolomic, and immunological approaches to profile the early effects of the immunosuppressant drug tacrolimus, antibiotics, or both in gut lumen and circulation using a murine model. Tacrolimus induced rapid and profound alterations in metabolic activities within two days of treatment, prior to alterations in gut microbiota composition and structure. The metabolic profile and gut microbiome after seven days of treatment was distinct from that after two days of treatment, indicating continuous drug effects on both gut microbial ecosystem and host metabolism. The most affected taxonomic groups are Clostriales and Verrucomicrobiae (i.e., Akkermansia muciniphila), and the most affected metabolic pathways included a group of interconnected amino acids, bile acid conjugation, glucose homeostasis, and energy production. Highly correlated metabolic changes were observed between lumen and serum metabolism, supporting their significant interactions. Despite a small sample size, this study explored the largely uncharacterized microbial and metabolic events in an immunosuppressed environment and demonstrated that early changes in metabolic activities can have significant implications that may serve as antecedent biomarkers of immune activation or quiescence. To understand the intricate relationships among gut microbiome, metabolic activities, and immune cells in an immune suppressed environment is a prerequisite for developing strategies to monitor and optimize alloimmune responses that determine transplant outcomes.

Morbidity and treatment costs of cystic fibrosis in a middle-income country

Introduction

: Asian children with cystic fibrosis (CF) managed in Malaysia have significant morbidity with limited access to life-sustaining treatments. We determined the morbidity and treatment cost of CF in a resource-limited country.

Methods

This cross-sectional study included all children diagnosed with CF in our centre. Data on clinical presentation, genetic mutation, serial spirometry results and complications were collected. Out-of-pocket (OOP) and healthcare costs over 1 year were retrieved for patients who were alive. Cohen's d and odds ratio (OR) were used to determine the effect size.

Results

Twenty-four patients were diagnosed with CF. Five patients died at a median (range) age of 18 (0.3-22) years. F508deletion (c. 1521_1523delCTT) was found in 20% of the alleles, while 89% of the variants were detected in nine patients. Body mass index (BMI) Z score was >-1.96 in 70.6% of patients. Two thirds (68%) were colonised with Pseudomonas aeruginosa, and this was associated with lower weight (P = 0.009) and BMI (P = 0.02) Z scores. Only 18% had FEV1 Z scores >-1.96. Early symptom onset (d = 0.74), delayed diagnosis (d = 2.07), a low FEF25-75 Z score (d = 0.82) and a high sweat conductance (d = 1.19) were associated with death. Inpatient cost was mainly from diagnostic tests, while medications contributed to half of the outpatient cost.

Healthcare utilisation cost was catastrophic, amounting to 20% of the total income.

Conclusion

Asian children with CF suffer significant complications such as low weight, low lung function and shortened lifespan. P. aeruginosa colonisation was frequent and associated with poor growth. Healthcare cost to parents was catastrophic.

Disentangling sources of clock-like mutations in germline and soma

The rates of mutations vary across cell types. To identify causes of this variation, mutations are often decomposed into a combination of the single base substitution (SBS) "signatures" observed in germline, soma and tumors, with the idea that each signature corresponds to one or a small number of underlying mutagenic processes. Two such signatures turn out to be ubiquitous across cell types: SBS signature 1, which consists primarily of transitions at methylated CpG sites caused by spontaneous deamination, and the more diffuse SBS signature 5, which is of unknown etiology. In cancers, the number of mutations attributed to these two signatures accumulates linearly with age of diagnosis, and thus the signatures have been termed "clock-like." To better understand this clock-like behavior, we develop a mathematical model that includes DNA replication errors, unrepaired damage, and damage repaired incorrectly. We show that mutational signatures can exhibit clock-like behavior because cell divisions occur at a constant rate and/or because damage rates remain constant over time, and that these distinct sources can be teased apart by comparing cell lineages that divide at different rates. With this goal in mind, we analyze the rate of accumulation of mutations in multiple cell types, including soma as well as male and female germline. We find no detectable increase in SBS signature 1 mutations in neurons and only a very weak increase in mutations assigned to the female germline, but a significant increase with time in rapidly-dividing cells, suggesting that SBS signature 1 is driven by rounds of DNA replication occurring at a relatively fixed rate. In contrast, SBS signature 5 increases with time in all cell types, including post-mitotic ones, indicating that it accumulates independently of cell divisions; this observation points to errors in DNA repair as the key underlying mechanism. Thus, the two "clock-like" signatures observed across cell types likely have distinct origins, one set by rates of cell division, the other by damage rates.