Machine learning reveals the diversity of human 3D chromatin contact patterns.

Understanding variation in chromatin contact patterns across diverse humans is critical for interpreting non-coding variants and their effects on gene expression and phenotypes. However, experimental determination of chromatin contact patterns across large samples is prohibitively expensive. To overcome this challenge, we develop and validate a machine learning method to quantify the variation in 3D chromatin contacts at 2 kilobase resolution from genome sequence alone. We apply this approach to thousands of human genomes from the 1000 Genomes Project and the inferred hominin ancestral genome. While patterns of 3D contact divergence genome-wide are qualitatively similar to patterns of sequence divergence, we find substantial differences in 3D divergence and sequence divergence in local 1 megabase genomic windows. In particular, we identify 392 windows with significantly greater 3D divergence than expected from sequence. Moreover, for 31\% of genomic windows, a single individual has a rare divergent 3D contact map pattern. Using in silico mutagenesis we find that most single nucleotide sequence changes do not result in changes to 3D chromatin contacts. However, in windows with substantial 3D divergence just one or a few variants can lead to divergent 3D chromatin contacts without the individuals carrying those variants having high sequence divergence. In summary, inferring 3D chromatin contact maps across human populations reveals variable contact patterns. We anticipate that these genetically diverse maps of 3D chromatin contact will provide a reference for future work on the function and evolution of 3D chromatin contact variation across human populations.

Review and metabolomic profiling of unsolved case reveals newly reported autosomal dominant congenital disorder of glycosylation, type Iw formerly thought to only be an autosomal recessive condition.

Autosomal dominant congenital disorder of glycosylation (CDG) type Iw (OMIM# 619714) is caused by a heterozygous mutation in the STT3A gene. Most CDGs have an autosomal recessive (AR) mode of inheritance, but several cases with an autosomal dominant (AD) form of an AR CDG have been recently identified. This report describes a 17-year-old male who was referred to the Undiagnosed Diseases Network (UDN) with a history of macrocephaly, failure to thrive, short stature, epilepsy, autism, attention-deficit/hyperactivity disorder, mild developmental delay, intermittent hypotonia, dysmorphic features, and mildly enlarged aortic root. Trio exome sequencing was negative. His biochemical workup included normal plasma amino acids, ammonia, acylcarnitine profile and urine organic and amino acids. His UDN genome sequencing (GS) identified a previously unreported de novo STT3A variant (c.1631A > G: p.Asn544Ser). This variant removes a glycosylation site and was predicted to be destabilizing by structural biology modeling. The patient was formally diagnosed by the UDN Metabolomics Core as having an abnormal transferrin profile indicative of CDG type Iw through metabolomic profiling. We report here an affected male with phenotypic, molecular, and metabolic findings consistent with CDG type Iw due to a heterozygous STT3A variant. This case highlights the importance of further testing of individuals with the phenotypic and metabolic findings of an AR disorder who are heterozygous for a single disease-causing allele and can be shown to have a new AD form of the disorder that represents clinical heterogeneity.

Evolutionary origin and population diversity of a cryptic hybrid pathogen.

Cryptic fungal pathogens pose disease management challenges due to their morphological resemblance to known pathogens. Here, we investigated the genomes and phenotypes of 53 globally distributed isolates of Aspergillus section Nidulantes fungi and found 30 clinical isolates-including four isolated from COVID-19 patients-were A. latus, a cryptic pathogen that originated via allodiploid hybridization. Notably, all A. latus isolates were misidentified. A. latus hybrids likely originated via a single hybridization event during the Miocene and harbor substantial genetic diversity. Transcriptome profiling of a clinical isolate revealed that both parental subgenomes are actively expressed and respond to environmental stimuli. Characterizing infection-relevant traits-such as drug resistance and growth under oxidative stress-revealed distinct phenotypic profiles among A. latus hybrids compared to parental and closely related species. Moreover, we identified four features that could aid A. latus taxonomic identification. Together, these findings deepen our understanding of the origin of cryptic pathogens.

Strain heterogeneity in a non-pathogenic Aspergillus fungus highlights factors associated with virulence.

Fungal pathogens exhibit extensive strain heterogeneity, including variation in virulence. Whether closely related non-pathogenic species also exhibit strain heterogeneity remains unknown. Here, we comprehensively characterized the pathogenic potentials (i.e., the ability to cause morbidity and mortality) of 16 diverse strains of Aspergillus fischeri, a non-pathogenic close relative of the major pathogen Aspergillus fumigatus. In vitro immune response assays and in vivo virulence assays using a mouse model of pulmonary aspergillosis showed that A. fischeri strains varied widely in their pathogenic potential. Furthermore, pangenome analyses suggest that A. fischeri genomic and phenotypic diversity is even greater. Genomic, transcriptomic, and metabolic profiling identified several pathways and secondary metabolites associated with variation in virulence. Notably, strain virulence was associated with the simultaneous presence of the secondary metabolites hexadehydroastechrome and gliotoxin. We submit that examining the pathogenic potentials of non-pathogenic close relatives is key for understanding the origins of fungal pathogenicity.

Aspergillus fumigatus conidial surface-associated proteome reveals factors for fungal evasion and host immunity modulation.

Aspergillus fumigatus causes aspergillosis and relies on asexual spores (conidia) for initiating host infection. There is scarce information about A. fumigatus proteins involved in fungal evasion and host immunity modulation. Here we analysed the conidial surface proteome of A. fumigatus, two closely related non-pathogenic species, Aspergillus fischeri and Aspergillus oerlinghausenensis, as well as pathogenic Aspergillus lentulus, to identify such proteins. After identifying 62 proteins exclusively detected on the A. fumigatus conidial surface, we assessed null mutants for 42 genes encoding these proteins. Deletion of 33 of these genes altered susceptibility to macrophage, epithelial cells and cytokine production. Notably, a gene that encodes a putative glycosylasparaginase, modulating levels of the host proinflammatory cytokine IL-1ß, is important for infection in an immunocompetent murine model of fungal disease. These results suggest that A. fumigatus conidial surface proteins are important for evasion and modulation of the immune response at the onset of fungal infection.

VUStruct: a compute pipeline for high throughput and personalized structural biology.

Effective diagnosis and treatment of rare genetic disorders requires the interpretation of a patient's genetic variants of unknown significance (VUSs). Today, clinical decision-making is primarily guided by gene-phenotype association databases and DNA-based scoring methods. Our web-accessible variant analysis pipeline, VUStruct, supplements these established approaches by deeply analyzing the downstream molecular impact of variation in context of 3D protein structure. VUStruct's growing impact is fueled by the co-proliferation of protein 3D structural models, gene sequencing, compute power, and artificial intelligence. Contextualizing VUSs in protein 3D structural models also illuminates longitudinal genomics studies and biochemical bench research focused on VUS, and we created VUStruct for clinicians and researchers alike. We now introduce VUStruct to the broad scientific community as a mature, web-facing, extensible, High Performance Computing (HPC) software pipeline. VUStruct maps missense variants onto automatically selected protein structures and launches a broad range of analyses. These include energy-based assessments of protein folding and stability, pathogenicity prediction through spatial clustering analysis, and machine learning (ML) predictors of binding surface disruptions and nearby post-translational modification sites. The pipeline also considers the entire input set of VUS and identifies genes potentially involved in digenic disease. VUStruct's utility in clinical rare disease genome interpretation has been demonstrated through its analysis of over 175 Undiagnosed Disease Network (UDN) Patient cases. VUStruct-leveraged hypotheses have often informed clinicians in their consideration of additional patient testing, and we report here details from two cases where VUStruct was key to their solution. We also note successes with academic research collaborators, for whom VUStruct has informed research directions in both computational genomics and wet lab studies.

Strain heterogeneity in a non-pathogenic fungus highlights factors contributing to virulence.

Fungal pathogens exhibit extensive strain heterogeneity, including variation in virulence. Whether closely related non-pathogenic species also exhibit strain heterogeneity remains unknown. Here, we comprehensively characterized the pathogenic potentials (i.e., the ability to cause morbidity and mortality) of 16 diverse strains of Aspergillus fischeri, a non-pathogenic close relative of the major pathogen Aspergillus fumigatus. In vitro immune response assays and in vivo virulence assays using a mouse model of pulmonary aspergillosis showed that A. fischeri strains varied widely in their pathogenic potential. Furthermore, pangenome analyses suggest that A. fischeri genomic and phenotypic diversity is even greater. Genomic, transcriptomic, and metabolomic profiling identified several pathways and secondary metabolites associated with variation in virulence. Notably, strain virulence was associated with the simultaneous presence of the secondary metabolites hexadehydroastechrome and gliotoxin. We submit that examining the pathogenic potentials of non-pathogenic close relatives is key for understanding the origins of fungal pathogenicity.

Archaic Introgression Shaped Human Circadian Traits.

When the ancestors of modern Eurasians migrated out of Africa and interbred with Eurasian archaic hominins, namely, Neanderthals and Denisovans, DNA of archaic ancestry integrated into the genomes of anatomically modern humans. This process potentially accelerated adaptation to Eurasian environmental factors, including reduced ultraviolet radiation and increased variation in seasonal dynamics. However, whether these groups differed substantially in circadian biology and whether archaic introgression adaptively contributed to human chronotypes remain unknown. Here, we traced the evolution of chronotype based on genomes from archaic hominins and present-day humans. First, we inferred differences in circadian gene sequences, splicing, and regulation between archaic hominins and modern humans. We identified 28 circadian genes containing variants with potential to alter splicing in archaics (e.g., CLOCK, PER2, RORB, and RORC) and 16 circadian genes likely divergently regulated between present-day humans and archaic hominins, including RORA. These differences suggest the potential for introgression to modify circadian gene expression. Testing this hypothesis, we found that introgressed variants are enriched among expression quantitative trait loci for circadian genes. Supporting the functional relevance of these regulatory effects, we found that many introgressed alleles have associations with chronotype. Strikingly, the strongest introgressed effects on chronotype increase morningness, consistent with adaptations to high latitude in other species. Finally, we identified several circadian loci with evidence of adaptive introgression or latitudinal clines in allele frequency. These findings identify differences in circadian gene regulation between modern humans and archaic hominins and support the contribution of introgression via coordinated effects on variation in human chronotype.

Spatial Distribution of Missense Variants within Complement Proteins Associates with Age Related Macular Degeneration.

Purpose: Genetic variants in complement genes are associated with age-related macular degeneration (AMD). However, many rare variants have been identified in these genes, but have an unknown significance, and their impact on protein function and structure is still unknown. We set out to address this issue by evaluating the spatial placement and impact on protein structureof these variants by developing an analytical pipeline and applying it to the International AMD Genomics Consortium (IAMDGC) dataset (16,144 AMD cases, 17,832 controls). Methods: The IAMDGC dataset was imputed using the Haplotype Reference Consortium (HRC), leading to an improvement of over 30% more imputed variants, over the original 1000 Genomes imputation. Variants were extracted for the CFH , CFI , CFB , C9 , and C3 genes, and filtered for missense variants in solved protein structures. We evaluated these variants as to their placement in the three-dimensional structure of the protein (i.e. spatial proximity in the protein), as well as AMD association. We applied several pipelines to a) calculate spatial proximity to known AMD variants versus gnomAD variants, b) assess a variant's likelihood of causing protein destabilization via calculation of predicted free energy change (ddG) using Rosetta, and c) whole gene-based testing to test for statistical associations. Gene-based testing using seqMeta was performed using a) all variants b) variants near known AMD variants or c) with a ddG >|2|. Further, we applied a structural kernel adaptation of SKAT testing (POKEMON) to confirm the association of spatial distributions of missense variants to AMD. Finally, we used logistic regression on known AMD variants in CFI to identify variants leading to >50% reduction in protein expression from known AMD patient carriers of CFI variants compared to wild type (as determined by in vitro experiments) to determine the pipeline's robustness in identifying AMD-relevant variants. These results were compared to functional impact scores, ie CADD values > 10, which indicate if a variant may have a large functional impact genomewide, to determine if our metrics have better discriminative power than existing variant assessment methods. Once our pipeline had been validated, we then performed a priori selection of variants using this pipeline methodology, and tested AMD patient cell lines that carried those selected variants from the EUGENDA cohort (n=34). We investigated complement pathway protein expression in vitro , looking at multiple components of the complement factor pathway in patient carriers of bioinformatically identified variants. Results: Multiple variants were found with a ddG>|2| in each complement gene investigated. Gene-based tests using known and novel missense variants identified significant associations of the C3 , C9 , CFB , and CFH genes with AMD risk after controlling for age and sex (P=3.22×10 -5 ;7.58×10 -6 ;2.1×10 -3 ;1.2×10 -31 ). ddG filtering and SKAT-O tests indicate that missense variants that are predicted to destabilize the protein, in both CFI and CFH, are associated with AMD (P=CFH:0.05, CFI:0.01, threshold of 0.05 significance). Our structural kernel approach identified spatial associations for AMD risk within the protein structures for C3, C9, CFB, CFH, and CFI at a nominal p-value of 0.05. Both ddG and CADD scores were predictive of reduced CFI protein expression, with ROC curve analyses indicating ddG is a better predictor (AUCs of 0.76 and 0.69, respectively). A priori in vitro analysis of variants in all complement factor genes indicated that several variants identified via bioinformatics programs PathProx/POKEMON in our pipeline via in vitro experiments caused significant change in complement protein expression (P=0.04) in actual patient carriers of those variants, via ELISA testing of proteins in the complement factor pathway, and were previously unknown to contribute to AMD pathogenesis. Conclusion: We demonstrate for the first time that missense variants in complement genes cluster together spatially and are associated with AMD case/control status. Using this method, we can identify CFI and CFH variants of previously unknown significance that are predicted to destabilize the proteins. These variants, both in and outside spatial clusters, can predict in-vitro tested CFI protein expression changes, and we hypothesize the same is true for CFH . A priori identification of variants that impact gene expression allow for classification for previously classified as VUS. Further investigation is needed to validate the models for additional variants and to be applied to all AMD-associated genes.

Integrating Computational Approaches to Predict the Effect of Genetic Variants on Protein Stability in Retinal Degenerative Disease.

Protein function can be impacted by changes in protein structure stability, but determining which change has impact is complex. Stability can be affected by a large change in the tertiary (3D) structure of the protein or due to free-energy changes caused by single amino acid substitutions. Changes in the DNA sequence can have minor or major impact on protein stability, which can lead to disease. Inherited retinal degenerations are generally caused by single mutations which are mostly located in protein-coding regions, while age-related macular degeneration (AMD) is a complex disorder that can be influenced by some genetic variants impacting proteins involved in the disease, although not all AMD risk variants lead to amino acid changes. Here, we review ways that proteins may be affected, the identification and understanding of these changes, and how to identify causal changes that can be targeted to develop treatments to alleviate retinal degenerative disease.

Evolutionary origin, population diversity, and diagnostics for a cryptic hybrid pathogen.

Cryptic fungal pathogens pose significant identification and disease management challenges due to their morphological resemblance to known pathogenic species while harboring genetic and (often) infectionrelevant trait differences. The cryptic fungal pathogen Aspergillus latus, an allodiploid hybrid originating from Aspergillus spinulosporus and an unknown close relative of Aspergillus quadrilineatus within section Nidulantes, remains poorly understood. The absence of accurate diagnostics for A. latus has led to misidentifications, hindering epidemiological studies and the design of effective treatment plans. We conducted an in-depth investigation of the genomes and phenotypes of 44 globally distributed isolates (41 clinical isolates and three type strains) from Aspergillus section Nidulantes. We found that 21 clinical isolates were A. latus; notably, standard methods of pathogen identification misidentified all A. latus isolates. The remaining isolates were identified as A. spinulosporus (8), A. quadrilineatus (1), or A. nidulans (11). Phylogenomic analyses shed light on the origin of A. latus, indicating one or two hybridization events gave rise to the species during the Miocene, approximately 15.4 to 8.8 million years ago. Characterizing the A. latus pangenome uncovered substantial genetic diversity within gene families and biosynthetic gene clusters. Transcriptomic analysis revealed that both parental genomes are actively expressed in nearly equal proportions and respond to environmental stimuli. Further investigation into infection-relevant chemical and physiological traits, including drug resistance profiles, growth under oxidative stress conditions, and secondary metabolite biosynthesis, highlight distinct phenotypic profiles of the hybrid A. latus compared to its parental and closely related species. Leveraging our comprehensive genomic and phenotypic analyses, we propose five genomic and phenotypic markers as diagnostics for A. latus species identification. These findings provide valuable insights into the evolutionary origin, genomic outcome, and phenotypic implications of hybridization in a cryptic fungal pathogen, thus enhancing our understanding of the underlying processes contributing to fungal pathogenesis. Furthermore, our study underscores the effectiveness of extensive genomic and phenotypic analyses as a promising approach for developing diagnostics applicable to future investigations of cryptic and emerging pathogens.

The contribution of mosaicism to genetic diseases and de novo pathogenic variants.

The contribution of mosaicism to diagnosed genetic disease and presumed de novo variants (DNV) is under investigated. We determined the contribution of mosaic genetic disease (MGD) and diagnosed parental mosaicism (PM) in parents of offspring with reported DNV (in the same variant) in the (1) Undiagnosed Diseases Network (UDN) (N = 1946) and (2) in 12,472 individuals electronic health records (EHR) who underwent genetic testing at an academic medical center. In the UDN, we found 4.51% of diagnosed probands had MGD, and 2.86% of parents of those with DNV exhibited PM. In the EHR, we found 6.03% and 2.99% and (of diagnosed probands) had MGD detected on chromosomal microarray and exome/genome sequencing, respectively. We found 2.34% (of those with a presumed pathogenic DNV) had a parent with PM for the variant. We detected mosaicism (regardless of pathogenicity) in 4.49% of genetic tests performed. We found a broad phenotypic spectrum of MGD with previously unknown phenotypic phenomena. MGD is highly heterogeneous and provides a significant contribution to genetic diseases. Further work is required to improve the diagnosis of MGD and investigate how PM contributes to DNV risk.

Archaic Introgression Shaped Human Circadian Traits.

Introduction: When the ancestors of modern Eurasians migrated out of Africa and interbred with Eurasian archaic hominins, namely Neanderthals and Denisovans, DNA of archaic ancestry integrated into the genomes of anatomically modern humans. This process potentially accelerated adaptation to Eurasian environmental factors, including reduced ultra-violet radiation and increased variation in seasonal dynamics. However, whether these groups differed substantially in circadian biology, and whether archaic introgression adaptively contributed to human chronotypes remains unknown. Results: Here we traced the evolution of chronotype based on genomes from archaic hominins and present-day humans. First, we inferred differences in circadian gene sequences, splicing, and regulation between archaic hominins and modern humans. We identified 28 circadian genes containing variants with potential to alter splicing in archaics (e.g., CLOCK, PER2, RORB, RORC), and 16 circadian genes likely divergently regulated between present-day humans and archaic hominins, including RORA. These differences suggest the potential for introgression to modify circadian gene expression. Testing this hypothesis, we found that introgressed variants are enriched among eQTLs for circadian genes. Supporting the functional relevance of these regulatory effects, we found that many introgressed alleles have associations with chronotype. Strikingly, the strongest introgressed effects on chronotype increase morningness, consistent with adaptations to high latitude in other species. Finally, we identified several circadian loci with evidence of adaptive introgression or latitudinal clines in allele frequency. Conclusions: These findings identify differences in circadian gene regulation between modern humans and archaic hominins and support the contribution of introgression via coordinated effects on variation in human chronotype.

Machine learning reveals the diversity of human 3D chromatin contact patterns.

Understanding variation in chromatin contact patterns across human populations is critical for interpreting non-coding variants and their ultimate effects on gene expression and phenotypes. However, experimental determination of chromatin contacts at a population-scale is prohibitively expensive. To overcome this challenge, we develop and validate a machine learning method to quantify the diversity 3D chromatin contacts at 2 kilobase resolution from genome sequence alone. We then apply this approach to thousands of diverse modern humans and the inferred human-archaic hominin ancestral genome. While patterns of 3D contact divergence genome-wide are qualitatively similar to patterns of sequence divergence, we find that 3D divergence in local 1-megabase genomic windows does not follow sequence divergence. In particular, we identify 392 windows with significantly greater 3D divergence than expected from sequence. Moreover, 26% of genomic windows have rare 3D contact variation observed in a small number of individuals. Using in silico mutagenesis we find that most sequence changes to do not result in changes to 3D chromatin contacts. However in windows with substantial 3D divergence, just one or a few variants can lead to divergent 3D chromatin contacts without the individuals carrying those variants having high sequence divergence. In summary, inferring 3D chromatin contact maps across human populations reveals diverse contact patterns. We anticipate that these genetically diverse maps of 3D chromatin contact will provide a reference for future work on the function and evolution of 3D chromatin contact variation across human populations.

Genomic and Molecular Identification of Genes Contributing to the Caspofungin Paradoxical Effect in Aspergillus fumigatus.

Aspergillus fumigatus is a deadly opportunistic fungal pathogen responsible for ~100,000 annual deaths. Azoles are the first line antifungal agent used against A. fumigatus, but azole resistance has rapidly evolved making treatment challenging. Caspofungin is an important second-line therapy against invasive pulmonary aspergillosis, a severe A. fumigatus infection. Caspofungin functions by inhibiting ß-1,3-glucan synthesis, a primary and essential component of the fungal cell wall. A phenomenon termed the caspofungin paradoxical effect (CPE) has been observed in several fungal species where at higher concentrations of caspofungin, chitin replaces ß-1,3-glucan, morphology returns to normal, and growth rate increases. CPE appears to occur in vivo, and it is therefore clinically important to better understand the genetic contributors to CPE. We applied genomewide association (GWA) analysis and molecular genetics to identify and validate candidate genes involved in CPE. We quantified CPE across 67 clinical isolates and conducted three independent GWA analyses to identify genetic variants associated with CPE. We identified 48 single nucleotide polymorphisms (SNPs) associated with CPE. We used a CRISPR/Cas9 approach to generate gene deletion mutants for seven genes harboring candidate SNPs. Two null mutants, ΔAfu3g13230 and ΔAfu4g07080 (dscP), resulted in reduced basal growth rate and a loss of CPE. We further characterized the dscP phosphatase-null mutant and observed a significant reduction in conidia production and extremely high sensitivity to caspofungin at both low and high concentrations. Collectively, our work reveals the contribution of Afu3g13230 and dscP in CPE and sheds new light on the complex genetic interactions governing this phenotype. IMPORTANCE This is one of the first studies to apply genomewide association (GWA) analysis to identify genes involved in an Aspergillus fumigatus phenotype. A. fumigatus is an opportunistic fungal pathogen that causes hundreds of thousands of infections and ~100,000 deaths each year, and antifungal resistance has rapidly evolved in this species. A phenomenon called the caspofungin paradoxical effect (CPE) occurs in some isolates, where high concentrations of the drug lead to increased growth rate. There is clinical relevance in understanding the genetic basis of this phenotype, since caspofungin concentrations could lead to unintended adverse clinical outcomes in certain cases. Using GWA analysis, we identified several interesting candidate polymorphisms and genes and then generated gene deletion mutants to determine whether these genes were important for CPE. Two of these mutant strains (ΔAfu3g13230 and ΔAfu4g07080/ΔdscP) displayed a loss of the CPE. This study sheds light on the genes involved in clinically important phenotype CPE.

The immune deficiency and c-Jun N-terminal kinase pathways drive the functional integration of the immune and circulatory systems of mosquitoes.

The immune and circulatory systems of animals are functionally integrated. In mammals, the spleen and lymph nodes filter and destroy microbes circulating in the blood and lymph, respectively. In insects, immune cells that surround the heart valves (ostia), called periostial haemocytes, destroy pathogens in the areas of the body that experience the swiftest haemolymph (blood) flow. An infection recruits additional periostial haemocytes, amplifying heart-associated immune responses. Although the structural mechanics of periostial haemocyte aggregation have been defined, the genetic factors that regulate this process remain less understood. Here, we conducted RNA sequencing in the African malaria mosquito, Anopheles gambiae, and discovered that an infection upregulates multiple components of the immune deficiency (IMD) and c-Jun N-terminal kinase (JNK) pathways in the heart with periostial haemocytes. This upregulation is greater in the heart with periostial haemocytes than in the circulating haemocytes or the entire abdomen. RNA interference-based knockdown then showed that the IMD and JNK pathways drive periostial haemocyte aggregation and alter phagocytosis and melanization on the heart, thereby demonstrating that these pathways regulate the functional integration between the immune and circulatory systems. Understanding how insects fight infection lays the foundation for novel strategies that could protect beneficial insects and harm detrimental ones.

A novel, likely pathogenic variant in UBTF-related neurodegeneration with brain atrophy is associated with a severe divergent neurodevelopmental phenotype.

BACKGROUND: A de novo, pathogenic, missense variant in UBTF, c.628G>A p.Glu210Lys, has been described as the cause of an emerging neurodegenerative disorder, Childhood-Onset Neurodegeneration with Brain Atrophy (CONDBA). The p.Glu210Lys alteration yields a positively charged stretch of three lysine residues. Functional studies confirmed this change results in a stronger interaction with negatively charged DNA and gain-of-function activity when compared to the wild-type sequence. The CONDBA phenotype reported in association with p.Glu210Lys consists of normal early-neurodevelopment followed by progressive motor, cognitive, and behavioral regression in early-to-middle childhood. METHODS AND RESULTS: The current proband presented at 9 months of age with baseline developmental delay and more extensive neuroradiological findings, including pontine hypoplasia, thalamic volume loss and signal abnormality, and hypomyelination. Like the recurrent CONDBA p.Glu210Lys variant, this novel variant, c.608A>G p.(Gln203Arg) lies within the highly conserved second HMG-box homology domain and involves the replacement of the wild-type residue with a positively charged residue, arginine. Computational structural modeling demonstrates that this amino acid substitution potentiates the interaction between UBTF and DNA, likely resulting in a gain-of-function effect for the UBTF protein, UBF. CONCLUSION: Here we present a new divergent phenotype associated with a novel, likely pathogenic, missense variant at a different position in the UBTF gene, c.608A>G p.(Gln203Arg).

Personalized structural biology reveals the molecular mechanisms underlying heterogeneous epileptic phenotypes caused by de novo KCNC2 variants.

Whole-exome sequencing (WES) in the clinic has identified several rare monogenic developmental and epileptic encephalopathies (DEE) caused by ion channel variants. However, WES often fails to provide actionable insight for rare diseases, such as DEEs, due to the challenges of interpreting variants of unknown significance (VUS). Here, we describe a "personalized structural biology" (PSB) approach that leverages recent innovations in the analysis of protein 3D structures to address this challenge. We illustrate this approach in an Undiagnosed Diseases Network (UDN) individual with DEE symptoms and a de novo VUS in KCNC2 (p.V469L), the Kv3.2 voltage-gated potassium channel. A nearby KCNC2 variant (p.V471L) was recently suggested to cause DEE-like phenotypes. Computational structural modeling suggests that both affect protein function. However, despite their proximity, the p.V469L variant is likely to sterically block the channel pore, while the p.V471L variant is likely to stabilize the open state. Biochemical and electrophysiological analyses demonstrate heterogeneous loss-of-function and gain-of-function effects, as well as differential response to 4-aminopyridine treatment. Molecular dynamics simulations illustrate that the pore of the p.V469L variant is more constricted, increasing the energetic barrier for K+ permeation, whereas the p.V471L variant stabilizes the open conformation. Our results implicate variants in KCNC2 as causative for DEE and guide the interpretation of a UDN individual. They further delineate the molecular basis for the heterogeneous clinical phenotypes resulting from two proximal pathogenic variants. This demonstrates how the PSB approach can provide an analytical framework for individualized hypothesis-driven interpretation of protein-coding VUS.

Comparative Genomics Reveals a Single Nucleotide Deletion in pksP That Results in White-Spore Phenotype in Natural Variants of Aspergillus fumigatus.

Aspergillus fumigatus is a potentially deadly opportunistic human pathogen. A. fumigatus has evolved a variety of mechanisms to evade detection by the immune system. For example, the conidium surface is covered in a layer of 1,8-dihydroxynaphthalene (DHN) melanin which masks the antigen macrophages use for recognition. DHN melanin also protects conidia from ultraviolet radiation and gives A. fumigatus conidia their characteristic green-grayish color. Here, we conducted genomic analysis of two closely related white-spore natural variants of A. fumigatus in comparison to two closely related green-spore isolates to identify a genetic basis of the white-spore phenotype. Illumina whole-genome resequencing data of the four isolates was used to identify variants that were shared in the white-spore isolates and different from both the green-spore isolates and the Af293 reference genome (which is also a green-spore isolate). We identified 4,279 single nucleotide variants and 1,785 insertion/deletions fitting this pattern. Among these, we identified 64 variants predicted to be high impact, loss-of-function mutations. One of these variants is a single nucleotide deletion that results in a frameshift in pksP (Afu2g17600), the core biosynthetic gene in the DHN melanin encoding gene cluster. The frameshift mutation in the white-spore isolates leads to a truncated protein in which a phosphopantetheine attachment site (PP-binding domain) is interrupted and an additional PP-binding domain and a thioesterase domain are omitted. Growth rate analysis of white-spore and green-spore isolates at 37°C and 48°C revealed that white-spore isolates are thermosensitive. Growth rate of A. fumigatus Af293 and a pksP null mutant in the Af293 background suggests pksP is not directly involved in the thermosensitivity phenotype. Further, our study identified a mutation in a gene (Afu4g04740) associated with thermal sensitivity in yeasts which could also be responsible for the thermosensitivity of the white-spore mutants. Overall, we used comparative genomics to identify the mutation and protein alterations responsible for the white-spore phenotype of environmental isolates of A. fumigatus.

Transcriptome profiles of Anopheles gambiae harboring natural low-level Plasmodium infection reveal adaptive advantages for the mosquito.

Anopheline mosquitoes are the sole vectors for the Plasmodium pathogens responsible for malaria, which is among the oldest and most devastating of human diseases. The continuing global impact of malaria reflects the evolutionary success of a complex vector-pathogen relationship that accordingly has been the long-term focus of both debate and study. An open question in the biology of malaria transmission is the impact of naturally occurring low-level Plasmodium infections of the vector on the mosquito's health and longevity as well as critical behaviors such as host-preference/seeking. To begin to answer this, we have completed a comparative RNAseq-based transcriptome profile study examining the effect of biologically salient, salivary gland transmission-stage Plasmodium infection on the molecular physiology of Anopheles gambiae s.s. head, sensory appendages, and salivary glands. When compared with their uninfected counterparts, Plasmodium infected mosquitoes exhibit increased transcript abundance of genes associated with olfactory acuity as well as a range of synergistic processes that align with increased fitness based on both anti-aging and reproductive advantages. Taken together, these data argue against the long-held paradigm that malaria infection is pathogenic for anophelines and, instead suggests there are biological and evolutionary advantages for the mosquito that drive the preservation of its high vectorial capacity.