Detection of nonneutral substitution rates on mammalian phylogenies

Computational approaches and challenges in the analysis of circRNA data

Circular RNAs (circRNA) are a class of non-coding RNA, forming a single-stranded covalently closed loop structure generated via back-splicing. Advancements in sequencing methods and technologies in conjunction with algorithmic developments of bioinformatics tools have enabled researchers to characterise the origin and function of circRNAs, with practical applications as a biomarker of diseases becoming increasingly relevant. Computational methods developed for circRNA analysis are predicated on detecting the chimeric back-splice junction of circRNAs whilst mitigating false-positive sequencing artefacts. In this review, we discuss in detail the computational strategies developed for circRNA identification, highlighting a selection of tool strengths, weaknesses and assumptions. In addition to circRNA identification tools, we describe methods for characterising the role of circRNAs within the competing endogenous RNA (ceRNA) network, their interactions with RNA-binding proteins, and publicly available databases for rich circRNA annotation.

Evolutionary and functional analyses of LRP5 in archaic and extant modern humans

BACKGROUND

The human lineage has undergone a postcranial skeleton gracilization (i.e. lower bone mass and strength relative to body size) compared to other primates and archaic populations such as the Neanderthals. This gracilization has been traditionally explained by differences in the mechanical load that our ancestors exercised. However, there is growing evidence that gracilization could also be genetically influenced.

RESULTS

We have analyzed the LRP5 gene, which is known to be associated with high bone mineral density conditions, from an evolutionary and functional point of view. Taking advantage of the published genomes of archaic Homo populations, our results suggest that this gene has a complex evolutionary history both between archaic and living humans and within living human populations. In particular, we identified the presence of different selective pressures in archaics and extant modern humans, as well as evidence of positive selection in the African and South East Asian populations from the 1000 Genomes Project. Furthermore, we observed a very limited evidence of archaic introgression in this gene (only at three haplotypes of East Asian ancestry out of the 1000 Genomes), compatible with a general erasing of the fingerprint of archaic introgression due to functional differences in archaics compared to extant modern humans. In agreement with this hypothesis, we observed private mutations in the archaic genomes that we experimentally validated as putatively increasing bone mineral density. In particular, four of five archaic missense mutations affecting the first β-propeller of LRP5 displayed enhanced Wnt pathway activation, of which two also displayed reduced negative regulation.

CONCLUSIONS

In summary, these data suggest a genetic component contributing to the understanding of skeletal differences between extant modern humans and archaic Homo populations.

Large language models in plant biology

Large language models (LLMs), such as ChatGPT, have taken the world by storm. However, LLMs are not limited to human language and can be used to analyze sequential data, such as DNA, protein, and gene expression. The resulting foundation models can be repurposed to identify the complex patterns within the data, resulting in powerful, multipurpose prediction tools able to predict the state of cellular systems. This review outlines the different types of LLMs and showcases their recent uses in biology. Since LLMs have not yet been embraced by the plant community, we also cover how these models can be deployed for the plant kingdom.

Genetic susceptibility to optic neuropathy in patients with alcohol use disorder

BACKGROUND

The pathophysiology of toxico-nutritional optic neuropathies remains debated, with no clear understanding of the respective roles played by the direct alcohol toxicity, smoking and the often associated vitamin deficiencies, which are risk factors for optic neuropathy. Our aim was to investigate genetic susceptibility in patients with bilateral infraclinical optic neuropathy associated with chronic alcohol use disorder.

METHODS

This retrospective cohort study included 102 visually asymptomatic patients with documented alcohol use disorder from a French reference center. Optic neuropathy was identified with optical coherence tomography (OCT), after which genetic susceptibility in the group of affected patients was investigated. Genetic testing was performed using panel sequencing of 87 nuclear genes and complete mitochondrial DNA sequencing.

RESULTS

Optic neuropathy was detected in 36% (37/102) of the included patients. Genetic testing of affected patients disclosed two patients (2/30, 6.7%) with optic neuropathy associated with pathogenic variants affecting the SPG7 gene and five patients (5/30, 16.7%) who harbored variants of uncertain significance close to probable pathogenicity in the genes WFS1, LOXL1, MMP19, NR2F1 and PMPCA. No pathogenic mitochondrial DNA variants were found in this group.

CONCLUSIONS

OCT can detect presence of asymptomatic optic neuropathy in patients with chronic alcohol use disorder. Furthermore, genetic susceptibility to optic neuropathy in this setting is found in almost a quarter of affected patients. Further studies may clarify the role of preventative measures in patients who might be predisposed to avoidable visual loss and blindness.

Constitutional mismatch repair deficiency mimicking Lynch syndrome is associated with hypomorphic mismatch repair gene variants

Lynch syndrome (LS) and constitutional mismatch repair deficiency (CMMRD) are distinct cancer syndromes caused, respectively, by mono- and bi-allelic germline mismatch repair (MMR) variants. LS predisposes to mainly gastrointestinal and genitourinary cancers in adulthood. CMMRD predisposes to brain, haematological, and LS-spectrum cancers from childhood. Two suspected LS patients with first cancer diagnosis aged 27 or 38 years were found to be homozygous for an MMR (likely) pathogenic variant, MSH6 c.3226C>T (p.(Arg1076Cys)), or variant of uncertain significance (VUS), MLH1 c.306G>A (p.(Glu102=)). MLH1 c.306G>A was shown to cause leaky exon 3 skipping. The apparent genotype-phenotype conflict was resolved by detection of constitutional microsatellite instability in both patients, a hallmark feature of CMMRD. A hypomorphic effect of these and other variants found in additional late onset CMMRD cases, identified by literature review, likely explains a LS-like phenotype. CMMRD testing in carriers of compound heterozygous or homozygous MMR VUS may find similar cases and novel hypomorphic variants. Individualised management of mono- and bi-allelic carriers of hypomorphic MMR variants is needed until we better characterise the associated phenotypes.

Convergent accelerated evolution of mammal-specific conserved non-coding elements in hibernators

Mammals maintain their body temperature, yet hibernators can temporarily lower their metabolic rate as an energy-saving strategy. It has been proposed that hibernators evolved independently from homeotherms, and it is possible that the convergent evolution of hibernation involved common genomic changes among hibernator-lineages. Since hibernation is a seasonal trait, the evolution of gene regulatory regions in response to changes in season may have been important for the acquisition of hibernation traits. High-frequency accumulation of mutations in conserved non-coding elements (CNEs) could, in principle, alter the expression of neighboring genes and thereby contribute to the acquisition of new traits. To address this possibility, we performed a comparative genomic analysis of mammals to identify accelerated CNEs commonly associated with hibernation. We found that accelerated CNEs are common to hibernator-lineages and could be involved with hibernation. We also found that common factors of genes that located near accelerated CNEs and are differentially expressed between normal and hibernation periods related to gene regulation and cell-fate determination. It suggests that the molecular mechanisms controlling hibernation have undergone convergent evolution. These results help broaden our understanding of the genetic adaptations that facilitated hibernation in mammals and may offer insights pertaining to stress responses and energy conservation.

Predicting functional UTR variants by integrating region-specific features

The untranslated region (UTR) of messenger ribonucleic acid (mRNA), including the 5'UTR and 3'UTR, plays a critical role in regulating gene expression and translation. Variants within the UTR can lead to changes associated with human traits and diseases; however, computational prediction of UTR variant effect is challenging. Current noncoding variant prediction mainly focuses on the promoters and enhancers, neglecting the unique sequence of the UTR and thereby limiting their predictive accuracy. In this study, using consolidated datasets of UTR variants from disease databases and large-scale experimental data, we systematically analyzed more than 50 region-specific features of UTR, including functional elements, secondary structure, sequence composition and site conservation. Our analysis reveals that certain features, such as C/G-related sequence composition in 5'UTR and A/T-related sequence composition in 3'UTR, effectively differentiate between nonfunctional and functional variant sets, unveiling potential sequence determinants of functional UTR variants. Leveraging these insights, we developed two classification models to predict functional UTR variants using machine learning, achieving an area under the curve (AUC) value of 0.94 for 5'UTR and 0.85 for 3'UTR, outperforming all existing methods. Our models will be valuable for enhancing clinical interpretation of genetic variants, facilitating the prediction and management of disease risk.

Haploinsufficiency underlies the neurodevelopmental consequences of SLC6A1 variants

Heterozygous variants in SLC6A1, encoding the GAT-1 GABA transporter, are associated with seizures, developmental delay, and autism. The majority of affected individuals carry missense variants, many of which are recurrent germline de novo mutations, raising the possibility of gain-of-function or dominant-negative effects. To understand the functional consequences, we performed an in vitro GABA uptake assay for 213 unique variants, including 24 control variants. De novo variants consistently resulted in a decrease in GABA uptake, in keeping with haploinsufficiency underlying all neurodevelopmental phenotypes. Where present, ClinVar pathogenicity reports correlated well with GABA uptake data; the functional data can inform future reports for the remaining 72% of unscored variants. Surface localization was assessed for 86 variants; two-thirds of loss-of-function missense variants prevented GAT-1 from being present on the membrane while GAT-1 was on the surface but with reduced activity for the remaining third. Surprisingly, recurrent de novo missense variants showed moderate loss-of-function effects that reduced GABA uptake with no evidence for dominant-negative or gain-of-function effects. Using linear regression across multiple missense severity scores to extrapolate the functional data to all potential SLC6A1 missense variants, we observe an abundance of GAT-1 residues that are sensitive to substitution. The extent of this missense vulnerability accounts for the clinically observed missense enrichment; overlap with hypermutable CpG sites accounts for the recurrent missense variants. Strategies to increase the expression of the wild-type SLC6A1 allele are likely to be beneficial across neurodevelopmental disorders, though the developmental stage and extent of required rescue remain unknown.

Comparative analysis of in-silico tools in identifying pathogenic variants in dominant inherited retinal diseases

Inherited retinal diseases (IRDs) are a group of rare genetic eye conditions that cause blindness. Despite progress in identifying genes associated with IRDs, improvements are necessary for classifying rare autosomal dominant (AD) disorders. AD diseases are highly heterogenous, with causal variants being restricted to specific amino acid changes within certain protein domains, making AD conditions difficult to classify. Here, we aim to determine the top-performing in-silico tools for predicting the pathogenicity of AD IRD variants. We annotated variants from ClinVar and benchmarked 39 variant classifier tools on IRD genes, split by inheritance pattern. Using area-under-the-curve (AUC) analysis, we determined the top-performing tools and defined thresholds for variant pathogenicity. Top-performing tools were assessed using genome sequencing on a cohort of participants with IRDs of unknown etiology. MutScore achieved the highest accuracy within AD genes, yielding an AUC of 0.969. When filtering for AD gain-of-function and dominant negative variants, BayesDel had the highest accuracy with an AUC of 0.997. Five participants with variants in NR2E3, RHO, GUCA1A, and GUCY2D were confirmed to have dominantly inherited disease based on pedigree, phenotype, and segregation analysis. We identified two uncharacterized variants in GUCA1A (c.428T>A, p.Ile143Thr) and RHO (c.631C>G, p.His211Asp) in three participants. Our findings support using a multi-classifier approach comprised of new missense classifier tools to identify pathogenic variants in participants with AD IRDs. Our results provide a foundation for improved genetic diagnosis for people with IRDs.

Interspecies regulatory landscapes and elements revealed by novel joint systematic integration of human and mouse blood cell epigenomes

Knowledge of locations and activities of cis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using epigenetic features in one species, making comparisons difficult between species. In contrast, we conducted an interspecies study defining epigenetic states and identifying cCREs in blood cell types to generate regulatory maps that are comparable between species, using integrative modeling of eight epigenetic features jointly in human and mouse in our Validated Systematic Integration (VISION) Project. The resulting catalogs of cCREs are useful resources for further studies of gene regulation in blood cells, indicated by high overlap with known functional elements and strong enrichment for human genetic variants associated with blood cell phenotypes. The contribution of each epigenetic state in cCREs to gene regulation, inferred from a multivariate regression, was used to estimate epigenetic state Regulatory Potential (esRP) scores for each cCRE in each cell type, which were used to categorize dynamic changes in cCREs. Groups of cCREs displaying similar patterns of regulatory activity in human and mouse cell types, obtained by joint clustering on esRP scores, harbored distinctive transcription factor binding motifs that were similar between species. An interspecies comparison of cCREs revealed both conserved and species-specific patterns of epigenetic evolution. Finally, we showed that comparisons of the epigenetic landscape between species can reveal elements with similar roles in regulation, even in the absence of genomic sequence alignment.

MultiSuSiE improves multi-ancestry fine-mapping in All of Us whole-genome sequencing data

Leveraging data from multiple ancestries can greatly improve fine-mapping power due to differences in linkage disequilibrium and allele frequencies. We propose MultiSuSiE, an extension of the sum of single effects model (SuSiE) to multiple ancestries that allows causal effect sizes to vary across ancestries based on a multivariate normal prior informed by empirical data. We evaluated MultiSuSiE via simulations and analyses of 14 quantitative traits leveraging whole-genome sequencing data in 47k African-ancestry and 94k European-ancestry individuals from All of Us. In simulations, MultiSuSiE applied to Afr47k+Eur47k was well-calibrated and attained higher power than SuSiE applied to Eur94k; interestingly, higher causal variant PIPs in Afr47k compared to Eur47k were entirely explained by differences in the extent of LD quantified by LD 4th moments. Compared to very recently proposed multi-ancestry fine-mapping methods, MultiSuSiE attained higher power and/or much lower computational costs, making the analysis of large-scale All of Us data feasible. In real trait analyses, MultiSuSiE applied to Afr47k+Eur94k identified 579 fine-mapped variants with PIP > 0.5, and MultiSuSiE applied to Afr47k+Eur47k identified 44% more fine-mapped variants with PIP > 0.5 than SuSiE applied to Eur94k. We validated MultiSuSiE results for real traits via functional enrichment of fine-mapped variants. We highlight several examples where MultiSuSiE implicates well-studied or biologically plausible fine-mapped variants that were not implicated by other methods.

Exome sequencing implicates ancestry-related Mendelian variation at SYNE1 in childhood-onset essential hypertension

Childhood-onset essential hypertension (COEH) is an uncommon form of hypertension that manifests in childhood or adolescence and, in the United States, disproportionately affects children of African ancestry. The etiology of COEH is unknown, but its childhood onset, low prevalence, high heritability, and skewed ancestral demography suggest the potential to identify rare genetic variation segregating in a Mendelian manner among affected individuals and thereby implicate genes important to disease pathogenesis. However, no COEH genes have been reported to date. Here, we identify recessive segregation of rare and putatively damaging missense variation in the spectrin domain of spectrin repeat containing nuclear envelope protein 1 (SYNE1), a cardiovascular candidate gene, in 3 of 16 families with early-onset COEH without an antecedent family history. By leveraging exome sequence data from an additional 48 COEH families, 1,700 in-house trios, and publicly available data sets, we demonstrate that compound heterozygous SYNE1 variation in these COEH individuals occurred more often than expected by chance and that this class of biallelic rare variation was significantly enriched among individuals of African genetic ancestry. Using in vitro shRNA knockdown of SYNE1, we show that reduced SYNE1 expression resulted in a substantial decrease in the elasticity of smooth muscle vascular cells that could be rescued by pharmacological inhibition of the downstream RhoA/Rho-associated protein kinase pathway. These results provide insights into the molecular genetics and underlying pathophysiology of COEH and suggest a role for precision therapeutics in the future.

Negative Selection Allows DNA Mismatch Repair-Deficient Mouse Fibroblasts In Vitro to Tolerate High Levels of Somatic Mutations

Substantial numbers of somatic mutations have been found to accumulate with age in different human tissues. Clonal cellular amplification of some of these mutations can cause cancer and other diseases. However, it is as yet unclear if and to what extent an increased burden of random mutations can affect cellular function without clonal amplification. We tested this in cell culture, which avoids the limitation that an increased mutation burden in vivo typically leads to cancer. We performed single-cell whole-genome sequencing of primary fibroblasts from DNA mismatch repair (MMR) deficient Msh2 -/- mice and littermate control animals after long-term passaging. Apart from analyzing somatic mutation burden we analyzed clonality, mutational signatures, and hotspots in the genome, characterizing the complete landscape of somatic mutagenesis in normal and MMR-deficient mouse primary fibroblasts during passaging. While growth rate of Msh2 -/- fibroblasts was not significantly different from the controls, the number of de novo single-nucleotide variants (SNVs) increased linearly up until at least 30,000 SNVs per cell, with the frequency of small insertions and deletions (INDELs) plateauing in the Msh2 -/- fibroblasts to about 10,000 INDELS per cell. We provide evidence for negative selection and large-scale mutation-driven population changes, including significant clonal expansion of preexisting mutations and widespread cell-strain-specific hotspots. Overall, our results provide evidence that increased somatic mutation burden drives significant cell evolutionary changes in a dynamic cell culture system without significant effects on growth. Since similar selection processes against mutations preventing organ and tissue dysfunction during aging are difficult to envision, these results suggest that increased somatic mutation burden can play a causal role in aging and diseases other than cancer.

Behavioral screening of conserved RNA-binding proteins reveals CEY-1/YBX RNA-binding protein dysfunction leads to impairments in memory and cognition

RNA-binding proteins (RBPs) regulate translation and plasticity which are required for memory. RBP dysfunction has been linked to a range of neurological disorders where cognitive impairments are a key symptom. However, of the 2,000 RBPs in the human genome, many are uncharacterized with regards to neurological phenotypes. To address this, we used the model organism C. elegans to assess the role of 20 conserved RBPs in memory. We identified eight previously uncharacterized memory regulators, three of which are in the C. elegans Y-Box (CEY) RBP family. Of these, we determined that cey-1 is the closest ortholog to the mammalian Y-Box (YBX) RBPs. We found that CEY-1 is both necessary in the nervous system for memory ability and sufficient to increase memory. Leveraging human datasets, we found both copy number variation losses and single nucleotide variants in YBX1 and YBX3 in individuals with neurological symptoms. We identified one predicted deleterious YBX3 variant of unknown significance, p.Asn127Tyr, in two individuals with neurological symptoms. Introducing this variant into endogenous cey-1 locus caused memory deficits in the worm. We further generated two humanized worm lines expressing human YBX3 or YBX1 at the cey-1 locus to test evolutionary conservation of YBXs in memory and the potential functional significance of the p.Asn127Tyr variant. Both YBX1/3 can functionally replace cey-1, and introduction of p.Asn127Tyr into the humanized YBX3 locus caused memory deficits. Our study highlights the worm as a model to reveal memory regulators and identifies YBX dysfunction as a potential new source of rare neurological disease.

VARista: a free web platform for streamlined whole-genome variant analysis across T2T, hg38, and hg19

With the increasing importance of genomic data in understanding genetic diseases, there is an essential need for efficient and user-friendly tools that simplify variant analysis. Although multiple tools exist, many present barriers such as steep learning curves, limited reference genome compatibility, or costs. We developed VARista, a free web-based tool, to address these challenges and provide a streamlined solution for researchers, particularly those focusing on rare monogenic diseases. VARista offers a user-centric interface that eliminates much of the technical complexity typically associated with variant analysis. The tool directly supports VCF files generated using reference genomes hg19, hg38, and the emerging T2T, with seamless remapping capabilities between them. Features such as gene summaries and links, tissue and cell-specific gene expression data for both adults and fetuses, as well as automated PCR design and integration with tools such as SpliceAI and AlphaMissense, enable users to focus on the biology and the case itself. As we demonstrate, VARista proved effective in narrowing down potential disease-causing variants, prioritizing them effectively, and providing meaningful biological context, facilitating rapid decision-making. VARista stands out as a freely available and comprehensive tool that consolidates various aspects of variant analysis into a single platform that embraces the forefront of genomic advancements. Its design inherently supports a shift in focus from technicalities to critical thinking, thereby promoting better-informed decisions in genetic disease research. Given its unique capabilities and user-centric design, VARista has the potential to become an essential asset for the genomic research community. https://VARista.link.

Heterozygous THBS2 pathogenic variant causes Ehlers-Danlos syndrome with prominent vascular features in humans and mice

Ehlers-Danlos syndromes (EDS) are a group of connective tissue disorders caused by mutations in collagen and collagen-interacting genes. We delineate a novel form of EDS with vascular features through clinical and histopathological phenotyping and genetic studies of a three-generation pedigree, displaying an apparently autosomal dominant phenotype of joint hypermobility and frequent joint dislocations, atrophic scarring, prolonged bleeding time and age-related aortic dilatation and rupture. Coagulation tests as well as platelet counts and function were normal. Reticular dermis displayed highly disorganized collagen fibers and transmission electron microscopy (TEM) revealed abnormally shaped fibroblasts and endothelial cells, with high amount and irregular shape of extracellular matrix (ECM) substance, especially near blood vessels. Genetic analysis unraveled a heterozygous mutation in THBS2 (NM_003247.5:c.2686T>C, p.Cys896Arg). We generated CRISPR/Cas9 knock-in (KI) mice, bearing the heterozygous human mutation in the mouse ortholog. The KI mice demonstrated phenotypic traits correlating with those observed in the human subjects, as evidenced by morphologic, histologic, and TEM analyses, in conjunction with bleeding time assays. Our findings delineate a novel form of human EDS with classical-like elements combined with vascular features, caused by a heterozygous THBS2 missense mutation. We further demonstrate a similar phenotype in heterozygous THBS2Cys896Arg KI mice, in line with previous studies in Thbs2 homozygous null-mutant mice. Notably, THBS2 encodes Thrombospondin-2, a secreted homotrimeric matricellular protein that directly binds the ECM-shaping Matrix Metalloproteinase 2 (MMP2), mediating its clearance. THBS2 loss-of-function attenuates MMP2 clearance, enhancing MMP2-mediated proteoglycan cleavage, causing ECM abnormalities similar to those seen in the human and mouse disease we describe.

Emx2 underlies the development and evolution of marsupial gliding membranes

Phenotypic variation among species is a product of evolutionary changes to developmental programs1,2. However, how these changes generate novel morphological traits remains largely unclear. Here we studied the genomic and developmental basis of the mammalian gliding membrane, or patagium-an adaptative trait that has repeatedly evolved in different lineages, including in closely related marsupial species. Through comparative genomic analysis of 15 marsupial genomes, both from gliding and non-gliding species, we find that the Emx2 locus experienced lineage-specific patterns of accelerated cis-regulatory evolution in gliding species. By combining epigenomics, transcriptomics and in-pouch marsupial transgenics, we show that Emx2 is a critical upstream regulator of patagium development. Moreover, we identify different cis-regulatory elements that may be responsible for driving increased Emx2 expression levels in gliding species. Lastly, using mouse functional experiments, we find evidence that Emx2 expression patterns in gliders may have been modified from a pre-existing program found in all mammals. Together, our results suggest that patagia repeatedly originated through a process of convergent genomic evolution, whereby regulation of Emx2 was altered by distinct cis-regulatory elements in independently evolved species. Thus, different regulatory elements targeting the same key developmental gene may constitute an effective strategy by which natural selection has harnessed regulatory evolution in marsupial genomes to generate phenotypic novelty.

An update on clinical presentation and responses to therapy of patients with hereditary hypophosphatemic rickets with hypercalciuria (HHRH)

Pathogenic variants in solute carrier family 34, member 3 (SLC34A3), the gene encoding the sodium-dependent phosphate cotransporter 2c (NPT2c), cause hereditary hypophosphatemic rickets with hypercalciuria (HHRH). Here, we report a pooled analysis of clinical and laboratory records of 304 individuals from 145 kindreds, including 20 previously unreported HHRH kindreds, in which two novel SLC34A3 pathogenic variants were identified. Compound heterozygous/homozygous carriers show above 90% penetrance for kidney and bone phenotypes. The biochemical phenotype for heterozygous carriers is intermediate with decreased serum phosphate, tubular reabsorption of phosphate (TRP (%)), fibroblast growth factor 23, and intact parathyroid hormone, but increased serum 1,25-dihydroxy vitamin D, and urine calcium excretion causing idiopathic hypercalciuria in 38%, with bone phenotypes still observed in 23% of patients. Oral phosphate supplementation is the current standard of care, which typically normalizes serum phosphate. However, although in more than half of individuals this therapy achieves correction of hypophosphatemia it fails to resolve the other outcomes. The American College of Medical Genetics and Genomics score correlated with functional analysis of frequent SLC34A3 pathogenic variants in vitro and baseline disease severity. The number of mutant alleles and baseline TRP (%) were identified as predictors for kidney and bone phenotypes, baseline TRP (%) furthermore predicted response to therapy. Certain SLC34A3/NPT2c pathogenic variants can be identified with partial responses to therapy, whereas with some overlap, others present only with kidney phenotypes and a third group present only with bone phenotypes. Thus, our report highlights important novel clinical aspects of HHRH and heterozygous carriers, raises awareness to this rare group of disorders and can be a foundation for future studies urgently needed to guide therapy of HHRH.

High number of mitochondrial DNA alterations in postmortem brain tissue of patients with schizophrenia compared to healthy controls

Previous studies have shown mitochondrial dysfunction in schizophrenia (SZ) patients, which may be caused by mitochondrial DNA (mtDNA) alterations. However, there are few studies in SZ that have analyzed mtDNA in brain samples by next-generation sequencing (NGS). To address this gap, we used mtDNA-targeted NGS and qPCR to characterize mtDNA alterations in brain samples from patients with SZ (n = 40) and healthy controls (HC) (n = 40). 35 % of SZ patients showed mtDNA alterations, a significantly higher prevalence compared to 10 % of HC. Specifically, SZ patients had a significantly higher frequency of deletions (35 vs. 5 in HC), with a mean number of deletions of 3.8 in SZ vs. 1.0 in HC. Likely pathogenic missense variants were also significantly more frequent in patients with SZ than in HC (10 vs. three HC), encompassing 14 variants in patients and three in HC. The pathogenic tRNA variant m.3243A>G was identified in one SZ patient with a high heteroplasmy level of 32.2 %. While no significant differences in mtDNA copy number (mtDNA-CN) were observed between SZ and HC, antipsychotic users had significantly higher mtDNA-CN than non-users. These findings suggest a potential role for mtDNA alterations in the pathophysiology of SZ that require further validation and functional studies.

The Influence of a Genetic Variant in CCDC78 on LMNA-Associated Skeletal Muscle Disease

Mutations in the LMNA gene-encoding A-type lamins can cause Limb-Girdle muscular dystrophy Type 1B (LGMD1B). This disease presents with weakness and wasting of the proximal skeletal muscles and has a variable age of onset and disease severity. This variability has been attributed to genetic background differences among individuals; however, such variants have not been well characterized. To identify such variants, we investigated a multigeneration family in which affected individuals are diagnosed with LGMD1B. The primary genetic cause of LGMD1B in this family is a dominant mutation that activates a cryptic splice site, leading to a five-nucleotide deletion in the mature mRNA. This results in a frame shift and a premature stop in translation. Skeletal muscle biopsies from the family members showed dystrophic features of variable severity, with the muscle fibers of some family members possessing cores, regions of sarcomeric disruption, and a paucity of mitochondria, not commonly associated with LGMD1B. Using whole genome sequencing (WGS), we identified 21 DNA sequence variants that segregate with the family members possessing more profound dystrophic features and muscle cores. These include a relatively common variant in coiled-coil domain containing protein 78 (CCDC78). This variant was given priority because another mutation in CCDC78 causes autosomal dominant centronuclear myopathy-4, which causes cores in addition to centrally positioned nuclei. Therefore, we analyzed muscle biopsies from family members and discovered that those with both the LMNA mutation and the CCDC78 variant contain muscle cores that accumulated both CCDC78 and RyR1. Muscle cores containing mislocalized CCDC78 and RyR1 were absent in the less profoundly affected family members possessing only the LMNA mutation. Taken together, our findings suggest that a relatively common variant in CCDC78 can impart profound muscle pathology in combination with a LMNA mutation and accounts for variability in skeletal muscle disease phenotypes.

Differences in 5'untranslated regions highlight the importance of translational regulation of dosage sensitive genes

BACKGROUND

Untranslated regions (UTRs) are important mediators of post-transcriptional regulation. The length of UTRs and the composition of regulatory elements within them are known to vary substantially across genes, but little is known about the reasons for this variation in humans. Here, we set out to determine whether this variation, specifically in 5'UTRs, correlates with gene dosage sensitivity.

RESULTS

We investigate 5'UTR length, the number of alternative transcription start sites, the potential for alternative splicing, the number and type of upstream open reading frames (uORFs) and the propensity of 5'UTRs to form secondary structures. We explore how these elements vary by gene tolerance to loss-of-function (LoF; using the LOEUF metric), and in genes where changes in dosage are known to cause disease. We show that LOEUF correlates with 5'UTR length and complexity. Genes that are most intolerant to LoF have longer 5'UTRs, greater TSS diversity, and more upstream regulatory elements than their LoF tolerant counterparts. We show that these differences are evident in disease gene-sets, but not in recessive developmental disorder genes where LoF of a single allele is tolerated.

CONCLUSIONS

Our results confirm the importance of post-transcriptional regulation through 5'UTRs in tight regulation of mRNA and protein levels, particularly for genes where changes in dosage are deleterious and lead to disease. Finally, to support gene-based investigation we release a web-based browser tool, VuTR, that supports exploration of the composition of individual 5'UTRs and the impact of genetic variation within them.

CRISPR Screening Uncovers a Long-Range Enhancer for ONECUT1 in Pancreatic Differentiation and Links a Diabetes Risk Variant

Functional enhancer annotation is a valuable first step for understanding tissue-specific transcriptional regulation and prioritizing disease-associated non-coding variants for investigation. However, unbiased enhancer discovery in physiologically relevant contexts remains a major challenge. To discover regulatory elements pertinent to diabetes, we conducted a CRISPR interference (CRISPRi) screen in the human pluripotent stem cell (hPSC) pancreatic differentiation system. Among the enhancers uncovered, we focused on a long-range enhancer ∼664 kb from the ONECUT1 promoter, as coding mutations in ONECUT1 cause pancreatic hypoplasia and neonatal diabetes. Homozygous enhancer deletion in hPSCs was associated with a near-complete loss of ONECUT1 gene expression and compromised pancreatic differentiation. This enhancer contains a confidently fine-mapped type 2 diabetes (T2D) associated variant (rs528350911) which disrupts a GATA motif. Introduction of the risk variant into hPSCs revealed substantially reduced binding of key pancreatic transcription factors (GATA4, GATA6 and FOXA2) on the edited allele, accompanied by a slight reduction of ONECUT1 transcription, supporting a causal role for this risk variant in metabolic disease. This work expands our knowledge about transcriptional regulation in pancreatic development through the characterization of a long-range enhancer and highlights the utility of enhancer discovery in disease-relevant settings for understanding monogenic and complex disease.

Improved estimation of functional enrichment in SNP heritability using feasible generalized least squares

Functional enrichment results typically implicate tissue or cell-type-specific biological pathways in disease pathogenesis and as therapeutic targets. We propose generalized linkage disequilibrium score regression (g-LDSC) that requires only genome-wide association studies (GWASs) summary-level data to estimate functional enrichment. The method adopts the same assumptions and regression model formulation as stratified linkage disequilibrium score regression (s-LDSC). Although s-LDSC only partially uses LD information, our method uses the whole LD matrix, which accounts for possible correlated error structure via a feasible generalized least-squares estimation. We demonstrate through simulation studies under various scenarios that g-LDSC provides more precise estimates of functional enrichment than s-LDSC, regardless of model misspecification. In an application to GWAS summary statistics of 15 traits from the UK Biobank, estimates of functional enrichment using g-LDSC were lower and more realistic than those obtained from s-LDSC. In addition, g-LDSC detected more significantly enriched functional annotations among 24 functional annotations for the 15 traits than s-LDSC (118 vs. 51).

Human gene regulatory evolution is driven by the divergence of regulatory element function in both cis and trans

Gene regulatory divergence between species can result from cis-acting local changes to regulatory element DNA sequences or global trans-acting changes to the regulatory environment. Understanding how these mechanisms drive regulatory evolution has been limited by challenges in identifying trans-acting changes. We present a comprehensive approach to directly identify cis- and trans-divergent regulatory elements between human and rhesus macaque lymphoblastoid cells using assay for transposase-accessible chromatin coupled to self-transcribing active regulatory region (ATAC-STARR) sequencing. In addition to thousands of cis changes, we discover an unexpected number (∼10,000) of trans changes and show that cis and trans elements exhibit distinct patterns of sequence divergence and function. We further identify differentially expressed transcription factors that underlie ∼37% of trans differences and trace how cis changes can produce cascades of trans changes. Overall, we find that most divergent elements (67%) experienced changes in both cis and trans, revealing a substantial role for trans divergence-alone and together with cis changes-in regulatory differences between species.

Bayesian estimation of gene constraint from an evolutionary model with gene features

Measures of selective constraint on genes have been used for many applications including clinical interpretation of rare coding variants, disease gene discovery, and studies of genome evolution. However, widely-used metrics are severely underpowered at detecting constraint for the shortest ∼25% of genes, potentially causing important pathogenic mutations to be overlooked. We developed a framework combining a population genetics model with machine learning on gene features to enable accurate inference of an interpretable constraint metric, shet. Our estimates outperform existing metrics for prioritizing genes important for cell essentiality, human disease, and other phenotypes, especially for short genes. Our new estimates of selective constraint should have wide utility for characterizing genes relevant to human disease. Finally, our inference framework, GeneBayes, provides a flexible platform that can improve estimation of many gene-level properties, such as rare variant burden or gene expression differences.

GPN-MSA: an alignment-based DNA language model for genome-wide variant effect prediction

Whereas protein language models have demonstrated remarkable efficacy in predicting the effects of missense variants, DNA counterparts have not yet achieved a similar competitive edge for genome-wide variant effect predictions, especially in complex genomes such as that of humans. To address this challenge, we here introduce GPN-MSA, a novel framework for DNA language models that leverages whole-genome sequence alignments across multiple species and takes only a few hours to train. Across several benchmarks on clinical databases (ClinVar, COSMIC, OMIM), experimental functional assays (DMS, DepMap), and population genomic data (gnomAD), our model for the human genome achieves outstanding performance on deleteriousness prediction for both coding and non-coding variants.

Prioritizing genomic variants pathogenicity via DNA, RNA, and protein-level features based on extreme gradient boosting

Genetic diseases are mostly implicated with genetic variants, including missense, synonymous, non-sense, and copy number variants. These different kinds of variants are indicated to affect phenotypes in various ways from previous studies. It remains essential but challenging to understand the functional consequences of these genetic variants, especially the noncoding ones, due to the lack of corresponding annotations. While many computational methods have been proposed to identify the risk variants. Most of them have only curated DNA-level and protein-level annotations to predict the pathogenicity of the variants, and others have been restricted to missense variants exclusively. In this study, we have curated DNA-, RNA-, and protein-level features to discriminate disease-causing variants in both coding and noncoding regions, where the features of protein sequences and protein structures have been shown essential for analyzing missense variants in coding regions while the features related to RNA-splicing and RBP binding are significant for variants in noncoding regions and synonymous variants in coding regions. Through the integration of these features, we have formulated the Multi-level feature Genomic Variants Predictor (ML-GVP) using the gradient boosting tree. The method has been trained on more than 400,000 variants in the Sherloc-training set from the 6th critical assessment of genome interpretation with superior performance. The method is one of the two best-performing predictors on the blind test in the Sherloc assessment, and is further confirmed by another independent test dataset of de novo variants.

Extensive Loss and Gain of Conserved Noncoding Elements During Early Teleost Evolution

Conserved noncoding elements in vertebrates are enriched around transcription factor loci associated with development. However, loss and rapid divergence of conserved noncoding elements has been reported in teleost fish, albeit taking only few genomes into consideration. Taking advantage of the recent increase in high-quality teleost genomes, we focus on studying the evolution of teleost conserved noncoding elements, carrying out targeted genomic alignments and comparisons within the teleost phylogeny to detect conserved noncoding elements and reconstruct the ancestral teleost conserved noncoding elements repertoire. This teleost-centric approach confirms previous observations of extensive vertebrate conserved noncoding elements loss early in teleost evolution, but also reveals massive conserved noncoding elements gain in the teleost stem-group over 300 million years ago. Using synteny-based association to link conserved noncoding elements to their putatively regulated target genes, we show the most teleost gained conserved noncoding elements are found in the vicinity of orthologous loci involved in transcriptional regulation and embryonic development that are also associated with conserved noncoding elements in other vertebrates. Moreover, teleost and vertebrate conserved noncoding elements share a highly similar motif and transcription factor binding site vocabulary. We suggest that early teleost conserved noncoding element gains reflect a restructuring of the ancestral conserved noncoding element repertoire through both extreme divergence and de novo emergence. Finally, we support newly identified pan-teleost conserved noncoding elements have potential for accurate resolution of teleost phylogenetic placements in par with coding sequences, unlike ancestral only elements shared with spotted gar. This work provides new insight into conserved noncoding element evolution with great value for follow-up work on phylogenomics, comparative genomics, and the study of gene regulation evolution in teleosts.

A phylogenetic method linking nucleotide substitution rates to rates of continuous trait evolution

Genomes contain conserved non-coding sequences that perform important biological functions, such as gene regulation. We present a phylogenetic method, PhyloAcc-C, that associates nucleotide substitution rates with changes in a continuous trait of interest. The method takes as input a multiple sequence alignment of conserved elements, continuous trait data observed in extant species, and a background phylogeny and substitution process. Gibbs sampling is used to assign rate categories (background, conserved, accelerated) to lineages and explore whether the assigned rate categories are associated with increases or decreases in the rate of trait evolution. We test our method using simulations and then illustrate its application using mammalian body size and lifespan data previously analyzed with respect to protein coding genes. Like other studies, we find processes such as tumor suppression, telomere maintenance, and p53 regulation to be related to changes in longevity and body size. In addition, we also find that skeletal genes, and developmental processes, such as sprouting angiogenesis, are relevant.

Genetic modifiers of cognitive decline in PSEN1 E280A Alzheimer's disease

INTRODUCTION

Rate of cognitive decline (RCD) in Alzheimer's disease (AD) determines the degree of impairment for patients and of burden for caretakers. We studied the association of RCD with genetic variants in AD.

METHODS

RCD was evaluated in 62 familial AD (FAD) and 53 sporadic AD (SAD) cases, and analyzed by whole-exome sequencing for association with common exonic functional variants. Findings were validated in post mortem brain tissue.

RESULTS

One hundred seventy-two gene variants in FAD, and 227 gene variants in SAD associated with RCD. In FAD, performance decline of the immediate recall of the Rey-Osterrieth figure test associated with 122 genetic variants. Olfactory receptor OR51B6 showed the highest number of associated variants. Its expression was detected in temporal cortex neurons.

DISCUSSION

Impaired olfactory function has been associated with cognitive impairment in AD. Genetic variants in these or other genes could help to identify risk of faster memory decline in FAD and SAD patients.

Auriculocondylar syndrome 2 caused by a novel PLCB4 variant in a male Chinese neonate: A case report and review of the literature

BACKGROUND

Auriculocondylar syndrome (ARCND) is a rare congenital craniofacial developmental malformation syndrome of the first and second pharyngeal arches with external ear malformation at the junction between the lobe and helix, micromaxillary malformation, and mandibular condylar hypoplasia. Four subtypes of ARCND have been described so far, that is, ARCND1 (OMIM # 602483), ARCND2 (ARCND2A, OMIM # 614669; ARCND2B, OMIM # 620458), ARCND3 (OMIM # 615706), and ARCND4 (OMIM # 620457).

METHODS

This study reports a case of ARCND2 resulting from a novel pathogenic variant in the PLCB4 gene, and summarizes PLCB4 gene mutation sites and phenotypes of ARCND2.

RESULTS

The proband, a 5-day-old male neonate, was referred to our hospital for respiratory distress. Micrognathia, microstomia, distinctive question mark ears, as well as mandibular condyle hypoplasia were identified. Trio-based whole-exome sequencing identified a novel missense variant of NM_001377142.1:c.1928C>T (NP_001364071.1:p.Ser643Phe) in the PLCB4 gene, which was predicted to impair the local structural stability with a result that the protein function might be affected. From a review of the literature, only 36 patients with PLCB4 gene mutations were retrieved.

CONCLUSION

As with other studies examining familial cases of ARCND2, incomplete penetrance and variable expressivity were observed within different families' heterozygous mutations in PLCB4 gene. Although, motor and intellectual development are in the normal range in the vast majority of patients with ARCND2, long-term follow-up and assessment are still required.

Vocal learning-associated convergent evolution in mammalian proteins and regulatory elements

Vocal production learning ("vocal learning") is a convergently evolved trait in vertebrates. To identify brain genomic elements associated with mammalian vocal learning, we integrated genomic, anatomical, and neurophysiological data from the Egyptian fruit bat (Rousettus aegyptiacus) with analyses of the genomes of 215 placental mammals. First, we identified a set of proteins evolving more slowly in vocal learners. Then, we discovered a vocal motor cortical region in the Egyptian fruit bat, an emergent vocal learner, and leveraged that knowledge to identify active cis-regulatory elements in the motor cortex of vocal learners. Machine learning methods applied to motor cortex open chromatin revealed 50 enhancers robustly associated with vocal learning whose activity tended to be lower in vocal learners. Our research implicates convergent losses of motor cortex regulatory elements in mammalian vocal learning evolution.

Menke-Hennekam syndrome; delineation of domain-specific subtypes with distinct clinical and DNA methylation profiles

CREB-binding protein (CBP, encoded by CREBBP) and its paralog E1A-associated protein (p300, encoded by EP300) are involved in histone acetylation and transcriptional regulation. Variants that produce a null allele or disrupt the catalytic domain of either protein cause Rubinstein-Taybi syndrome (RSTS), while pathogenic missense and in-frame indel variants in parts of exons 30 and 31 cause phenotypes recently described as Menke-Hennekam syndrome (MKHK). To distinguish MKHK subtypes and define their characteristics, molecular and extended clinical data on 82 individuals (54 unpublished) with variants affecting CBP (n = 71) or p300 (n = 11) (NP_004371.2 residues 1,705-1,875 and NP_001420.2 residues 1,668-1,833, respectively) were summarized. Additionally, genome-wide DNA methylation profiles were assessed in DNA extracted from whole peripheral blood from 54 individuals. Most variants clustered closely around the zinc-binding residues of two zinc-finger domains (ZZ and TAZ2) and within the first α helix of the fourth intrinsically disordered linker (ID4) of CBP/p300. Domain-specific methylation profiles were discerned for the ZZ domain in CBP/p300 (found in nine out of 10 tested individuals) and TAZ2 domain in CBP (in 14 out of 20), while a domain-specific diagnostic episignature was refined for the ID4 domain in CBP/p300 (in 21 out of 21). Phenotypes including intellectual disability of varying degree and distinct physical features were defined for each of the regions. These findings demonstrate existence of at least three MKHK subtypes, which are domain specific (MKHK-ZZ, MKHK-TAZ2, and MKHK-ID4) rather than gene specific (CREBBP/EP300). DNA methylation episignatures enable stratification of molecular pathophysiologic entities within a gene or across a family of paralogous genes.

DrivR-Base: a feature extraction toolkit for variant effect prediction model construction

MOTIVATION

Recent advancements in sequencing technologies have led to the discovery of numerous variants in the human genome. However, understanding their precise roles in diseases remains challenging due to their complex functional mechanisms. Various methodologies have emerged to predict the pathogenic significance of these genetic variants. Typically, these methods employ an integrative approach, leveraging diverse data sources that provide important insights into genomic function. Despite the abundance of publicly available data sources and databases, the process of navigating, extracting, and pre-processing features for machine learning models can be highly challenging and time-consuming. Furthermore, researchers often invest substantial effort in feature extraction, only to later discover that these features lack informativeness.

RESULTS

In this article, we introduce DrivR-Base, an innovative resource that efficiently extracts and integrates molecular information (features) related to single nucleotide variants. These features encompass information about the genomic positions and the associated protein positions of a variant. They are derived from a wide array of databases and tools, including structural properties obtained from AlphaFold, regulatory information sourced from ENCODE, and predicted variant consequences from Variant Effect Predictor. DrivR-Base is easily deployable via a Docker container to ensure reproducibility and ease of access across diverse computational environments. The resulting features can be used as input for machine learning models designed to predict the pathogenic impact of human genome variants in disease. Moreover, these feature sets have applications beyond this, including haploinsufficiency prediction and the development of drug repurposing tools. We describe the resource's development, practical applications, and potential for future expansion and enhancement.

AVAILABILITY AND IMPLEMENTATION

DrivR-Base source code is available at https://github.com/amyfrancis97/DrivR-Base.

Divergent composition and transposon-silencing activity of small RNAs in mammalian oocytes

BACKGROUND

Small RNAs are essential for germ cell development and fertilization. However, fundamental questions remain, such as the level of conservation in small RNA composition between species and whether small RNAs control transposable elements in mammalian oocytes.

RESULTS

Here, we use high-throughput sequencing to profile small RNAs and poly(A)-bearing long RNAs in oocytes of 12 representative vertebrate species (including 11 mammals). The results show that miRNAs are generally expressed in the oocytes of each representative species (although at low levels), whereas endo-siRNAs are specific to mice. Notably, piRNAs are predominant in oocytes of all species (except mice) and vary widely in length. We find PIWIL3-associated piRNAs are widespread in mammals and generally lack 3'-2'-O-methylation. Additionally, sequence identity is low between homologous piRNAs in different species, even among those present in syntenic piRNA clusters. Despite the species-specific divergence, piRNAs retain the capacity to silence younger TE subfamilies in oocytes.

CONCLUSIONS

Collectively, our findings illustrate a high level of diversity in the small RNA populations of mammalian oocytes. Furthermore, we identify sequence features related to conserved roles of small RNAs in silencing TEs, providing a large-scale reference for future in-depth study of small RNA functions in oocytes.

Construction of single-cell cross-species chromatin accessibility landscapes with combinatorial-hybridization-based ATAC-seq

Despite recent advances in single-cell genomics, the lack of maps for single-cell candidate cis-regulatory elements (cCREs) in non-mammal species has limited our exploration of conserved regulatory programs across vertebrates and invertebrates. Here, we developed a combinatorial-hybridization-based method for single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) named CH-ATAC-seq, enabling the construction of single-cell accessible chromatin landscapes for zebrafish, Drosophila, and earthworms (Eisenia andrei). By integrating scATAC censuses of humans, monkeys, and mice, we systematically identified 152 distinct main cell types and around 0.8 million cell-type-specific cCREs. Our analysis provided insights into the conservation of neural, muscle, and immune lineages across species, while epithelial cells exhibited a higher organ-origin heterogeneity. Additionally, a large-scale gene regulatory network (GRN) was constructed in four vertebrates by integrating scRNA-seq censuses. Overall, our study provides a valuable resource for comparative epigenomics, identifying the evolutionary conservation and divergence of gene regulation across different species.

DISP1 deficiency: Monoallelic and biallelic variants cause a spectrum of midline craniofacial malformations

PURPOSE

DISP1 encodes a transmembrane protein that regulates the secretion of the morphogen, Sonic hedgehog, a deficiency of which is a major cause of holoprosencephaly (HPE). This disorder covers a spectrum of brain and midline craniofacial malformations. The objective of the present study was to better delineate the clinical phenotypes associated with division transporter dispatched-1 (DISP1) variants.

METHODS

This study was based on the identification of at least 1 pathogenic variant of the DISP1 gene in individuals for whom detailed clinical data were available.

RESULTS

A total of 23 DISP1 variants were identified in heterozygous, compound heterozygous or homozygous states in 25 individuals with midline craniofacial defects. Most cases were minor forms of HPE, with craniofacial features such as orofacial cleft, solitary median maxillary central incisor, and congenital nasal pyriform aperture stenosis. These individuals had either monoallelic loss-of-function variants or biallelic missense variants in DISP1. In individuals with severe HPE, the DISP1 variants were commonly found associated with a variant in another HPE-linked gene (ie, oligogenic inheritance).

CONCLUSION

The genetic findings we have acquired demonstrate a significant involvement of DISP1 variants in the phenotypic spectrum of midline defects. This underlines its importance as a crucial element in the efficient secretion of Sonic hedgehog. We also demonstrated that the very rare solitary median maxillary central incisor and congenital nasal pyriform aperture stenosis combination is part of the DISP1-related phenotype. The present study highlights the clinical risks to be flagged up during genetic counseling after the discovery of a pathogenic DISP1 variant.

Hypomagnesaemia with varying degrees of extrarenal symptoms as a consequence of heterozygous CNNM2 variants

Variants in the CNNM2 gene are causative for hypomagnesaemia, seizures and intellectual disability, although the phenotypes can be variable. This study aims to understand the genotype-phenotype relationship in affected individuals with CNNM2 variants by phenotypic, functional and structural analysis of new as well as previously reported variants. This results in the identification of seven variants that significantly affect CNNM2-mediated Mg2+ transport. Pathogenicity of these variants is further supported by structural modelling, which predicts CNNM2 structure to be affected by all of them. Strikingly, seizures and intellectual disability are absent in 4 out of 7 cases, indicating these phenotypes are caused either by specific CNNM2 variant only or by additional risk factors. Moreover, in line with sporadic observations from previous reports, CNNM2 variants might be associated with disturbances in parathyroid hormone and Ca2+ homeostasis.

Structural atlas of human primary microRNAs generated by SHAPE-MaP

MicroRNA (miRNA) maturation is critically dependent on structural features of primary transcripts (pri-miRNAs). However, the scarcity of determined pri-miRNA structures has limited our understanding of miRNA maturation. Here, we employed selective 2'-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP), a high-throughput RNA structure probing method, to unravel the secondary structures of 476 high-confidence human pri-miRNAs. Our SHAPE-based structures diverge substantially from those inferred solely from computation, particularly in the apical loop and basal segments, underlining the need for experimental data in RNA structure prediction. By comparing the structures with high-throughput processing data, we determined the optimal structural features of pri-miRNAs. The sequence determinants are influenced substantially by their structural contexts. Moreover, we identified an element termed the bulged GWG motif (bGWG) with a 3' bulge in the lower stem, which promotes processing. Our structure-function mapping better annotates the determinants of pri-miRNA processing and offers practical implications for designing small hairpin RNAs and predicting the impacts of miRNA mutations.

Tgfbr1 controls developmental plasticity between the hindlimb and external genitalia by remodeling their regulatory landscape

The hindlimb and external genitalia of present-day tetrapods are thought to derive from an ancestral common primordium that evolved to generate a wide diversity of structures adapted for efficient locomotion and mating in the ecological niche occupied by the species. We show that despite long evolutionary distance from the ancestral condition, the early primordium of the mouse external genitalia preserved the capacity to take hindlimb fates. In the absence of Tgfbr1, the pericloacal mesoderm generates an extra pair of hindlimbs at the expense of the external genitalia. It has been shown that the hindlimb and the genital primordia share many of their key regulatory factors. Tgfbr1 controls the response to those factors by modulating the accessibility status of regulatory elements that control the gene regulatory networks leading to the formation of genital or hindlimb structures. Our work uncovers a remarkable tissue plasticity with potential implications in the evolution of the hindlimb/genital area of tetrapods, and identifies an additional mechanism for Tgfbr1 activity that might also contribute to the control of other physiological or pathological processes.

A comparative medical genomics approach may facilitate the interpretation of rare missense variation

PURPOSE

To determine the degree to which likely causal missense variants of single-locus traits in domesticated species have features suggestive of pathogenicity in a human genomic context.

METHODS

We extracted missense variants from the Online Mendelian Inheritance in Animals database for nine animals (cat, cattle, chicken, dog, goat, horse, pig, rabbit and sheep), mapped coordinates to the human reference genome and annotated variants using genome analysis tools. We also searched a private commercial laboratory database of genetic testing results from >400 000 individuals with suspected rare disorders.

RESULTS

Of 339 variants that were mappable to the same residue and gene in the human genome, 56 had been previously classified with respect to pathogenicity: 31 (55.4%) pathogenic/likely pathogenic, 1 (1.8%) benign/likely benign and 24 (42.9%) uncertain/other. The odds ratio for a pathogenic/likely pathogenic classification in ClinVar was 7.0 (95% CI 4.1 to 12.0, p<0.0001), compared with all other germline missense variants in these same 220 genes. The remaining 283 variants disproportionately had allele frequencies and REVEL scores that supported pathogenicity.

CONCLUSION

Cross-species comparisons could facilitate the interpretation of rare missense variation. These results provide further support for comparative medical genomics approaches that connect big data initiatives in human and veterinary genetics.

A second hotspot for pathogenic exon-skipping variants in CDC45

Biallelic pathogenic variants in CDC45 are associated with Meier-Gorlin syndrome with craniosynostosis (MGORS type 7), which also includes short stature and absent/hypoplastic patellae. Identified variants act through a hypomorphic loss of function mechanism, to reduce CDC45 activity and impact DNA replication initiation. In addition to missense and premature termination variants, several pathogenic synonymous variants have been identified, most of which cause increased exon skipping of exon 4, which encodes an essential part of the RecJ-orthologue's DHH domain. Here we have identified a second cohort of families segregating CDC45 variants, where patients have craniosynostosis and a reduction in height, alongside common facial dysmorphisms, including thin eyebrows, consistent with MGORS7. Skipping of exon 15 is a consequence of two different variants, including a shared synonymous variant that is enriched in individuals of East Asian ancestry, while other variants in trans are predicted to alter key intramolecular interactions in α/β domain II, or cause retention of an intron within the 3'UTR. Our cohort and functional data confirm exon skipping is a relatively common pathogenic mechanism in CDC45, and highlights the need for alternative splicing events, such as exon skipping, to be especially considered for variants initially predicted to be less likely to cause the phenotype, particularly synonymous variants.

Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations

In both statistical genetics and phylogenetics, a major goal is to identify correlations between genetic loci or other aspects of the phenotype or environment and a focal trait. In these two fields, there are sophisticated but disparate statistical traditions aimed at these tasks. The disconnect between their respective approaches is becoming untenable as questions in medicine, conservation biology, and evolutionary biology increasingly rely on integrating data from within and among species, and once-clear conceptual divisions are becoming increasingly blurred. To help bridge this divide, we derive a general model describing the covariance between the genetic contributions to the quantitative phenotypes of different individuals. Taking this approach shows that standard models in both statistical genetics (e.g., Genome-Wide Association Studies; GWAS) and phylogenetic comparative biology (e.g., phylogenetic regression) can be interpreted as special cases of this more general quantitative-genetic model. The fact that these models share the same core architecture means that we can build a unified understanding of the strengths and limitations of different methods for controlling for genetic structure when testing for associations. We develop intuition for why and when spurious correlations may occur using analytical theory and conduct population-genetic and phylogenetic simulations of quantitative traits. The structural similarity of problems in statistical genetics and phylogenetics enables us to take methodological advances from one field and apply them in the other. We demonstrate this by showing how a standard GWAS technique-including both the genetic relatedness matrix (GRM) as well as its leading eigenvectors, corresponding to the principal components of the genotype matrix, in a regression model-can mitigate spurious correlations in phylogenetic analyses. As a case study of this, we re-examine an analysis testing for co-evolution of expression levels between genes across a fungal phylogeny, and show that including covariance matrix eigenvectors as covariates decreases the false positive rate while simultaneously increasing the true positive rate. More generally, this work provides a foundation for more integrative approaches for understanding the genetic architecture of phenotypes and how evolutionary processes shape it.

GUANinE v1.0: Benchmark Datasets for Genomic AI Sequence-to-Function Models

Computational genomics increasingly relies on machine learning methods for genome interpretation, and the recent adoption of neural sequence-to-function models highlights the need for rigorous model specification and controlled evaluation, problems familiar to other fields of AI. Research strategies that have greatly benefited other fields - including benchmarking, auditing, and algorithmic fairness - are also needed to advance the field of genomic AI and to facilitate model development. Here we propose a genomic AI benchmark, GUANinE, for evaluating model generalization across a number of distinct genomic tasks. Compared to existing task formulations in computational genomics, GUANinE is large-scale, de-noised, and suitable for evaluating pretrained models. GUANinE v1.0 primarily focuses on functional genomics tasks such as functional element annotation and gene expression prediction, and it also draws upon connections to evolutionary biology through sequence conservation tasks. The current GUANinE tasks provide insight into the performance of existing genomic AI models and non-neural baselines, with opportunities to be refined, revisited, and broadened as the field matures. Finally, the GUANinE benchmark allows us to evaluate new self-supervised T5 models and explore the tradeoffs between tokenization and model performance, while showcasing the potential for self-supervision to complement existing pretraining procedures.

DVA: predicting the functional impact of single nucleotide missense variants

BACKGROUND

In the past decade, single nucleotide variants (SNVs) have been identified as having a significant relationship with the development and treatment of diseases. Among them, prioritizing missense variants for further functional impact investigation is an essential challenge in the study of common disease and cancer. Although several computational methods have been developed to predict the functional impacts of variants, the predictive ability of these methods is still insufficient in the Mendelian and cancer missense variants.

RESULTS

We present a novel prediction method called the disease-related variant annotation (DVA) method that predicts the effect of missense variants based on a comprehensive feature set of variants, notably, the allele frequency and protein-protein interaction network feature based on graph embedding. Benchmarked against datasets of single nucleotide missense variants, the DVA method outperforms the state-of-the-art methods by up to 0.473 in the area under receiver operating characteristic curve. The results demonstrate that the proposed method can accurately predict the functional impact of single nucleotide missense variants and substantially outperforms existing methods.

CONCLUSIONS

DVA is an effective framework for identifying the functional impact of disease missense variants based on a comprehensive feature set. Based on different datasets, DVA shows its generalization ability and robustness, and it also provides innovative ideas for the study of the functional mechanism and impact of SNVs.

Identification of Pancreatic Cancer Germline Risk Variants With Effects That Are Modified by Smoking

PURPOSE

Pancreatic cancer (PC) is a deadly disease most often diagnosed in late stages. Identification of high-risk subjects could both contribute to preventative measures and help diagnose the disease at earlier timepoints. However, known risk factors, assessed independently, are currently insufficient for accurately stratifying patients. We use large-scale data from the UK Biobank (UKB) to identify genetic variant-smoking interaction effects and show their importance in risk assessment.

METHODS

We draw data from 15,086,830 genetic variants and 315,512 individuals in the UKB. There are 765 cases of PC. Crucially, robust resampling corrections are used to overcome well-known challenges in hypothesis testing for interactions. Replication analysis is conducted in two independent cohorts totaling 793 cases and 570 controls. Integration of functional annotation data and construction of polygenic risk scores (PRS) demonstrate the additional insight provided by interaction effects.

RESULTS

We identify the genome-wide significant variant rs77196339 on chromosome 2 (per minor allele odds ratio in never-smokers, 2.31 [95% CI, 1.69 to 3.15]; per minor allele odds ratio in ever-smokers, 0.53 [95% CI, 0.30 to 0.91]; P = 3.54 × 10-8) as well as eight other loci with suggestive evidence of interaction effects (P < 5 × 10-6). The rs77196339 region association is validated (P < .05) in the replication sample. PRS incorporating interaction effects show improved discriminatory ability over PRS of main effects alone.

CONCLUSION

This study of genome-wide germline variants identified smoking to modify the effect of rs77196339 on PC risk. Interactions between known risk factors can provide critical information for identifying high-risk subjects, given the relative inadequacy of models considering only main effects, as demonstrated in PRS. Further studies are necessary to advance toward comprehensive risk prediction approaches for PC.

Detection of evolutionary conserved and accelerated genomic regions related to adaptation to thermal niches in Anolis lizards

Understanding the genetic basis for adapting to thermal environments is important due to serious effects of global warming on ectothermic species. Various genes associated with thermal adaptation in lizards have been identified mainly focusing on changes in gene expression or the detection of positively selected genes using coding regions. Only a few comprehensive genome-wide analyses have included noncoding regions. This study aimed to identify evolutionarily conserved and accelerated genomic regions using whole genomes of eight Anolis lizard species that have repeatedly adapted to similar thermal environments in multiple lineages. Evolutionarily conserved genomic regions were extracted as regions with overall sequence conservation (regions with fewer base substitutions) across all lineages compared with the neutral model. Genomic regions that underwent accelerated evolution in the lineage of interest were identified as those with more base substitutions in the target branch than in the entire background branch. Conserved elements across all branches were relatively abundant in "intergenic" genomic regions among noncoding regions. Accelerated regions (ARs) of each lineage contained a significantly greater proportion of noncoding RNA genes than the entire multiple alignment. Common genes containing ARs within 5 kb of their vicinity in lineages with similar thermal habitats were identified. Many genes associated with circadian rhythms and behavior were found in hot-open and cool-shaded habitat lineages. These genes might play a role in contributing to thermal adaptation and assist future studies examining the function of genes involved in thermal adaptation via genome editing.

An mRNA profiling assay incorporating coding region InDels for body fluid identification and the inference of the donor in mixed samples

Biological traces discovered at crime scenes hold significant significance in forensic investigations. In cases involving mixed body fluid stains, the evidentiary value of DNA profiles depends on the type of body fluid from which the DNA was obtained. Recently, coding region polymorphism analysis has proved to be a promising method for directly linking specific body fluids to their respective DNA contributors in mixtures, which may help to avoid "association fallacy" between separate DNA and RNA evidence. In this study, we present an update on previously reported coding region Single Nucleotide Polymorphisms (cSNPs) by exploring the potential application of coding region Insertion/Deletion polymorphisms (cInDels). Nine promising cInDels, selected from 70 mRNA markers based on stringent screening criteria, were integrated into an existing mRNA profiling assay. Subsequently, the body fluid specificity of our cInDel assay and the genotyping consistency between complementary DNA (cDNA) and genomic DNA (gDNA) were examined. Our study demonstrates that cInDels can function as important multifunctional genetic markers, as they provide not only the ability to confirm the presence of forensically relevant body fluids, but also the ability to associate/dissociate specific body fluids with particular donors.

Brief Communication: The Predictable Network Topology of Evolutionary Genomic Constraint

Large-scale comparative genomics studies offer valuable resources for understanding both functional and evolutionary rate constraints. It is suggested that constraint aligns with the topology of genomic networks, increasing toward the center, with intermediate nodes combining relaxed constraint with higher contributions to the phenotype due to pleiotropy. However, this pattern has yet to be demonstrated in vertebrates. This study shows that constraint intensifies toward the network's center in placental mammals. Genes with rate changes associated with emergence of hibernation cluster mostly toward intermediate positions, with higher constraint in faster-evolving genes, which is indicative of a "sweet spot" for adaptation. If this trend holds universally, network node metrics could predict high-constraint regions even in clades lacking empirical constraint data.

Graphylo: A deep learning approach for predicting regulatory DNA and RNA sites from whole-genome multiple alignments

This study focuses on enhancing the prediction of regulatory functional sites in DNA and RNA sequences, a crucial aspect of gene regulation. Current methods, such as motif overrepresentation and machine learning, often lack specificity. To address this issue, the study leverages evolutionary information and introduces Graphylo, a deep-learning approach for predicting transcription factor binding sites in the human genome. Graphylo combines Convolutional Neural Networks for DNA sequences with Graph Convolutional Networks on phylogenetic trees, using information from placental mammals' genomes and evolutionary history. The research demonstrates that Graphylo consistently outperforms both single-species deep learning techniques and methods that incorporate inter-species conservation scores on a wide range of datasets. It achieves this by utilizing a species-based attention model for evolutionary insights and an integrated gradient approach for nucleotide-level model interpretability. This innovative approach offers a promising avenue for improving the accuracy of regulatory site prediction in genomics.