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

Population structure and mitogenomic analyses reveal dispersal routes of Macrobrachium nipponense in China

BACKGROUND

The oriental river prawn Macrobrachium nipponense is widely distributed in China, but its origin and distribution routes remain largely unknown. We collected 126 oriental river prawn specimens from four lakes and one river across China, and sequenced their mitochondrial cytochrome C oxidase subunit I (cox1) genes. We performed whole-genome resequencing of 100 samples and assembled mitogenomes for population analysis, these two types of mitochondrial markers (cox1 and all 13 protein-coding genes-13 PCGs), a nuclear marker (28S rRNA) and SNPs to infer the relationships between the five populations, the population structure, and migratory routes. We also assembled complete mitogenome per sampled population (5 in total) and used them to conduct comparative mitogenomic analyses.

RESULTS

The complete mitogenomes comprised 15,774-15,784 base pairs (bp). The average nucleotide diversity (π) of the populations, inferred using the cox1 gene data, was 0.03013 ± 0.00618, ranging from 0.00500 ± 0.00110 (Fuxian Lake) to 0.03562 ± 0.02538 (Khanka Lake). The identified haplotypes (33 cox1 and 101 13 PCGs) clustered into three main geographical lineages. Lineage A included Khanka Lake and one clade from the Haihe River. The specimens from Fuxian Lake constituted lineage B. Lineage C comprised a majority of specimens from the Haihe River, Taihu Lake, and Poyang Lake, and a minority of specimens from Khanka Lake and Fuxian Lake.

CONCLUSIONS

This study indicates that native M. nipponense prawns in China originated from East China, subsequently spreading northward and westward into the inland regions along the Grand Canal and the Yangtze River system, forming distinct lineages. This proposed route improves our understanding of the geographic distribution and origin of M. nipponense in China.

Investigating the shared genetic architecture between obesity and depression: a large-scale genomewide cross-trait analysis

Introduction

Increasing evidence suggests that individuals with obesity are at a higher risk of developing depression, and conversely, depression can contribute to the onset of obesity, creating a detrimental cycle. This study aims to investigate the potential shared biological pathways between obesity and depression by examining genetic correlations, identifying common polymorphisms, and conducting cross-trait genetic analyses.

Methods

We assessed the genetic correlation between obesity and depression using linkage disequilibrium score regression and high-density lipoprotein levels. We combined two different sources of obesity data using METAL and employed bidirectional Mendelian randomization to determine the causal relationship between obesity and depression. Additionally, we conducted multivariate trait analysis using the MTAG method to improve statistical robustness and identify novel genetic associations. Furthermore, we performed a thorough investigation of independent risk loci using GCTA-COJO, PLACO, MAGMA, POPS, and SMR, integrating different QTL information and methods to further identify risk genes and proteins.

Results

Our analysis revealed genetic correlations and bidirectional positive causal relationships between obesity and depression, highlighting shared risk SNP (rs10789340). We identified RPL31P12, NEGR1, and DCC as common risk genes for obesity and depression. Using the BLISS method, we identified SCG3 and FLRT2 as potential drug targets.

Limitation

Most of our data sources are from Europe, which may limit the generalization of our findings to other ethnic populations.

Conclusion

This study demonstrates the genetic causal relationship and common risk SNPs, genes, proteins, and pathways between obesity and depression. These findings contribute to a deeper understanding of their pathogenesis and the identification of potential therapeutic targets.

The effects of loss of Y chromosome on male health

Loss of Y chromosome (LOY) is the most commonly occurring post-zygotic (somatic) mutation in male individuals. The past decade of research suggests that LOY has important effects in shaping the activity of the immune system, and multiple studies have shown the effects of LOY on a range of diseases, including cancer, neurodegeneration, cardiovascular disease and acute infection. Epidemiological findings have been corroborated by functional analyses providing insights into the mechanisms by which LOY modulates the immune system; in particular, a causal role for LOY in cardiac fibrosis, bladder cancer and Alzheimer disease has been indicated. These insights show that LOY is a highly dynamic mutation (such that LOY clones expand and contract with time) and has pleiotropic, cell-type-specific effects. Here, we review the status of the field and highlight the potential of LOY as a biomarker and target of new therapeutics that aim to counteract its negative effects on the immune system.

Trans-ancestry GWAS identifies 59 loci and improves risk prediction and fine-mapping for kidney stone disease

Kidney stone disease is a multifactorial disease with increasing incidence worldwide. Trans-ancestry GWAS has become a popular strategy to dissect genetic structure of complex traits. Here, we conduct a large trans-ancestry GWAS meta-analysis on kidney stone disease with 31,715 cases and 943,655 controls in European and East Asian populations. We identify 59 kidney stone disease susceptibility loci, including 13 novel loci and show similar effects across populations. Using fine-mapping, we detect 1612 variants at these loci, and pinpoint 25 causal signals with a posterior inclusion probability >0.5 among them. At a novel locus, we pinpoint TRIOBP gene and discuss its potential link to kidney stone disease. We show that a cross-population polygenic risk score, PRS-CSxEAS&EUR, exhibits superior predictive performance for kidney stone disease than other polygenic risk scores constructed in our study. Relative to individuals in the third quintile of PRS-CSxEAS&EUR, those in the lowest and highest quintiles exhibit distinct kidney stone disease risks with odds ratios of 0.57 (0.51-0.63) and 1.83 (1.68-1.98), respectively. Our results suggest that kidney stone disease patients with higher polygenic risk scores are younger at onset. In summary, our study advances the understanding of kidney stone disease genetic architecture and improves its genetic predictability.

Genome-wide association study of dry eye disease reveals shared heritability with systemic comorbidities

Dry eye disease (DED) affects up to 25% of the adult population, with chronic symptoms of pain and dryness often negatively impacting quality of life. The genetic architecture of DED is largely unknown. Here, we develop and validate an algorithm for DED in the Million Veteran Program using a combination of diagnosis codes and prescription records, resulting in 132,657 cases and 352,201 controls. In a multi-ancestry genome-wide association study, we identify ten significant loci in nine susceptibility regions with largely consistent effects across ancestries, including loci linked to synapse maintenance (EPHA5, GRIA1, SYNGAP1) and autoimmunity (BLK). Phenome-wide scans for genetic pleiotropy indicate substantial genetic correlations of DED with comorbidities, including fibromyalgia, post-traumatic stress disorder, and Sjögren's disease. Finally, applying genomic structural equation modeling, we derive a latent factor underlying DED and other chronic pain traits which accounts for 51% of the genetic variance of DED.

Decoding omicron: Genetic insight into its transmission dynamics, severity spectrum and ever-evolving strategies of immune escape in comparison with other SARS-CoV-2 variants

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic, driven by the rapid evolution of the SARS-CoV-2 virus, has led to the emergence of multiple variants with significant impacts on global health. This study aims to analyze the evolutionary trends and mutational landscape of SARS-CoV-2 variants circulating in Pune, Maharashtra, India, from August 2022 to April 2024. Using comprehensive genomic surveillance data, we identified the predominance of variants such as BA.2.75, XBB.x, and the newly emerged subvariants JN.1, KP.1, and KP.2. These subvariants, belonging to the BA.2.86 lineage, have raised concerns owing to their potential for increased transmissibility and immune evasion.

RESULTS

Phylogenetic analysis of 84 sequenced samples from Pune revealed 18 distinct lineages, with JN.1 and KP.2 forming a novel branch compared with their ancestral lineage, BA.2. Detailed mutational analysis highlighted key mutations in the N-terminal domain (NTD) and receptor-binding domain (RBD) of the spike protein, affecting viral stability, ACE2 binding affinity, and neutralizing antibody escape. Our findings, along with the predictions of SpikePro, suggest that the combination of these mutations enhances the viral fitness of JN.1 and KP.2, contributing to their rapid emergence and spread.

CONCLUSION

This study underscores the importance of continuous genomic surveillance and advanced computational modeling to track and predict the evolutionary trajectories of SARS-CoV-2 variants. The insights gained from this research are crucial for informing public health strategies, vaccine updates, and therapeutic interventions to mitigate the impact of current and future SARS-CoV-2 variants.

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

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

Landscape analysis of m6A modification reveals the dysfunction of bone metabolism in osteoporosis mice

Osteoporosis (OP) is a prevalent chronic bone metabolic disorder that affects the elderly population, leading to an increased susceptibility to bone fragility. Despite extensive research on the onset and progression of OP, the precise mechanisms underlying this condition remain elusive. The m6A modification, a prevalent form of chemical RNA modification, primarily regulates posttranscriptional processes, including RNA stability, splicing, and translation. Numerous studies have underscored the crucial functions of m6A regulators in OP. This study aimed to explore the relationship between OP and RNA m6A methylation, investigating its underlying mechanisms through comprehensive bioinformatic analysis and experimental validation. The mRNA sequencing (mRNA-seq) and methylated RNA immunoprecipitation sequencing (MeRIP-seq) were performed on control mice as well as ovariectomized mice to discover differentially expressed genes (DEGs) and m6A regulators in OP. The results revealed dysregulation of a majority of bone metabolism-related genes and m6A regulators in ovariectomized mice, indicating a closely linked relationship between them. Our research findings indicated that m6A modification is essential in regulating OP, offering potential insights for prevention and treatment.

GWAShug: a comprehensive platform for decoding the shared genetic basis between complex traits based on summary statistics

The shared genetic basis offers very valuable insights into the etiology, diagnosis and therapy of complex traits. However, a comprehensive resource providing shared genetic basis using the accessible summary statistics is currently lacking. It is challenging to analyze the shared genetic basis due to the difficulty in selecting parameters and the complexity of pipeline implementation. To address these issues, we introduce GWAShug, a platform featuring a standardized best-practice pipeline with four trait level methods and three molecular level methods. Based on stringent quality control, the GWAShug resource module includes 539 high-quality GWAS summary statistics for European and East Asian populations, covering 54 945 pairs between a measurement-based and a disease-based trait and 43 902 pairs between two disease-based traits. Users can easily search for shared genetic basis information by trait name, MeSH term and category, and access detailed gene information across different trait pairs. The platform facilitates interactive visualization and analysis of shared genetic basic results, allowing users to explore data dynamically. Results can be conveniently downloaded via FTP links. Additionally, we offer an online analysis module that allows users to analyze their own summary statistics, providing comprehensive tables, figures and interactive visualization and analysis. GWAShug is freely accessible at http://www.gwashug.com.

miRStart 2.0: enhancing miRNA regulatory insights through deep learning-based TSS identification

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression by binding to the 3'-untranslated regions of target mRNAs, influencing various biological processes at the post-transcriptional level. Identifying miRNA transcription start sites (TSSs) and transcription factors' (TFs) regulatory roles is crucial for elucidating miRNA function and transcriptional regulation. miRStart 2.0 integrates over 4500 high-throughput datasets across five data types, utilizing a multi-modal approach to annotate 28 828 putative TSSs for 1745 human and 1181 mouse miRNAs, supported by sequencing-based signals. Over 6 million tissue-specific TF-miRNA interactions, integrated from ChIP-seq data, are supplemented by DNase hypersensitivity and UCSC conservation data, with network visualizations. Our deep learning-based model outperforms existing tools in miRNA TSS prediction, achieving the most overlaps with both cell-specific and non-cell-specific validated TSSs. The user-friendly web interface and visualization tools make miRStart 2.0 easily accessible to researchers, enabling efficient identification of miRNA upstream regulatory elements in relation to their TSSs. This updated database provides systems-level insights into gene regulation and disease mechanisms, offering a valuable resource for translational research, facilitating the discovery of novel therapeutic targets and precision medicine strategies. miRStart 2.0 is now accessible at https://awi.cuhk.edu.cn/∼miRStart2.

Dog10K: an integrated Dog10K database summarizing canine multi-omics

The diversity observed in canine breed phenotypes, together with their risk for heritabily disorders of relevance to dogs and humans, makes the species an ideal subject for studies aimed at understanding the genetic basis of complex traits and human biomedical models. Dog10K is an ongoing international collaboration that aims to uncover the genetic basis of phenotypic diversity, disease, behavior, and domestication history of dogs. To best present and make the extensive data accessible and user friendly, we have established the Dog10K (http://dog10k.kiz.ac.cn/) database, a comprehensive-omics resource summarizing multiple types of data. This database integrates single nucleotide variants (SNVs) from 1987 canine genomes, de-novo mutations (DNMs) from 43 dog breeds with >40× sequence, RNA-seq data of 105057 single nuclei from hippocampus, 74067 single cells from leukocytes and 30 blood samples from published canid studies. We provide clear visualization, statistics, browse, searching, and downloading functions for all data. We have integrated three analysis tools, Selscan, LiftOver and AgeConversion, to aid researchers in custom exploration of the comprehensive-omics data. The Dog10K database will serve as a foundational platform for analyzing, presenting and utilizing canine multi-omics data.

Shared genetic architecture and bidirectional clinical risks within the psycho-metabolic nexus

BACKGROUND

Increasing evidence suggests a complex interplay between psychiatric disorders and metabolic dysregulations. However, most research has been limited to specific disorder pairs, leaving a significant gap in our understanding of the broader psycho-metabolic nexus.

METHODS

This study leveraged large-scale cohort data and genome-wide association study (GWAS) summary statistics, covering 8 common psychiatric disorders and 43 metabolic traits. We introduced a comprehensive analytical strategy to identify shared genetic bases sequentially, from key genetic correlation regions to local pleiotropy and pleiotropic genes. Finally, we developed polygenic risk score (PRS) models to translate these findings into clinical applications.

FINDINGS

We identified significant bidirectional clinical risks between psychiatric disorders and metabolic dysregulations among 310,848 participants from the UK Biobank. Genetic correlation analysis confirmed 104 robust trait pairs, revealing 1088 key genomic regions, including critical hotspots such as chr3: 47588462-50387742. Cross-trait meta-analysis uncovered 388 pleiotropic single nucleotide variants (SNVs) and 126 shared causal variants. Among variants, 45 novel SNVs were associated with psychiatric disorders and 75 novel SNVs were associated with metabolic traits, shedding light on new targets to unravel the mechanism of comorbidity. Notably, RBM6, a gene involved in alternative splicing and cellular stress response regulation, emerged as a key pleiotropic gene. When psychiatric and metabolic genetic information were integrated, PRS models demonstrated enhanced predictive power.

INTERPRETATION

The study highlights the intertwined genetic and clinical relationships between psychiatric disorders and metabolic dysregulations, emphasising the need for integrated approaches in diagnosis and treatment.

FUNDING

The National Key Research and Development Program of China (2023YFC2506200, SHH). The National Natural Science Foundation of China (82273741, SY).

Sappanone A alleviates metabolic dysfunction-associated steatohepatitis by decreasing hepatocyte lipotoxicity via targeting Mup3 in mice

BACKGROUND AND PURPOSE

Metabolic dysfunction-associated steatohepatitis (MASH) is an inflammatory lipotoxic disorder marked by hepatic steatosis, hepatocyte damage, inflammation, and varying stages of fibrosis. Sappanone A (SA), a flavonoid, exhibits anti-inflammatory and hepatoprotection activities. Nevertheless, the effects of SA on MASH remain ambiguous. We evaluated the effects of SA on hepatocyte lipotoxicity, inflammation, and fibrosis conditions in MASH mice, as well as the underlying mechanisms.

METHODS

A conventional murine MASH model fed a methionine-choline-deficient (MCD) diet was utilized to assess the role of SA on MASH in vivo. Drug target prediction and liver transcriptomics were employed to elucidate the potential actions of SA. AML12 cells were applied to further explore the effects and mechanisms of SA in vitro.

RESULTS

The in silico prediction indicated that SA could modulate inflammation, insulin resistance, lipid metabolism, and collagen catabolic process. Treating with SA dose-dependently lessened the elevated levels of serum ALT and AST in mice with diet-triggered MASH, and high-dose SA treatment exhibited a similar effect to silymarin. Additionally, SA treatment significantly reduced lipid deposition, inflammation, and fibrosis subjected to metabolic stress in a dose-dependent manner. Besides, SA mitigated palmitate-triggered lipotoxicity in hepatocytes. Liver transcriptomics further confirmed the aforementioned findings. Of note, mRNA-sequencing analysis and molecular biology experiments demonstrated that SA statistically up-regulated the hepatic expression of major urinary protein 3 (Mup3), thereby facilitating lipid transportation and inhibiting lipotoxicity. Furthermore, Mup3 knockdown in hepatocytes significantly abolished the hepatoprotection provided by SA.

CONCLUSION

SA alleviates MASH by decreasing lipid accumulation and lipotoxicity in hepatocytes, at least partially by targeting Mup3, and subsequently blocks MASH process. Therefore, SA could be a promising hepatoprotective agent in the context of MASH.

Genome-wide Machine Learning Analysis of Anosmia and Ageusia with COVID-19

The COVID-19 pandemic has caused substantial worldwide disruptions in health, economy, and society, manifesting symptoms such as loss of smell (anosmia) and loss of taste (ageusia), that can result in prolonged sensory impairment. Establishing the host genetic etiology of anosmia and ageusia in COVID-19 will aid in the overall understanding of the sensorineural aspect of the disease and contribute to possible treatments or cures. By using human genome sequencing data from the University of Iowa (UI) COVID-19 cohort (N=187) and the National Institute of Health All of Us (AoU) Research Program COVID-19 cohort (N=947), we investigated the genetics of anosmia and/or ageusia by employing feature selection techniques to construct a novel variant and gene prioritization pipeline, utilizing machine learning methods for the classification of patients. Models were assessed using a permutation-based variable importance (PVI) strategy for final prioritization of candidate variants and genes. The highest held-out test set area under the receiver operating characteristic (AUROC) curve for models and datasets from the UI cohort was 0.735 and 0.798 for the variant and gene analysis respectively and for the AoU cohort was 0.687 for the variant analysis. Our analysis prioritized several novel and known candidate host genetic factors involved in immune response, neuronal signaling, and calcium signaling supporting previously proposed hypotheses for anosmia/ageusia in COVID-19.

A reference quality, fully annotated diploid genome from a Saudi individual

We have used multiple sequencing approaches to sequence the genome of a volunteer from Saudi Arabia. We use the resulting data to generate a de novo assembly of the genome, and use different computational approaches to refine the assembly. As a consequence, we provide a contiguous assembly of the complete genome of an individual from Saudi Arabia for all chromosomes except chromosome Y, and label this assembly KSA001. We transferred genome annotations from reference genomes to fully annotate KSA001, and we make all primary sequencing data, the assembly, and the genome annotations freely available in public databases using the FAIR data principles. KSA001 is the first telomere-to-telomere-assembled genome from a Saudi individual that is freely available for any purpose.

Shared genetic architecture between COVID-19 and irritable bowel syndrome: a large-scale genome-wide cross-trait analysis

BACKGROUND

It has been reported that COVID-19 patients have an increased risk of developing IBS; however, the underlying genetic mechanisms of these associations remain largely unknown. The aim of this study was to investigate potential shared SNPs, genes, proteins, and biological pathways between COVID-19 and IBS by assessing pairwise genetic correlations and cross-trait genetic analysis.

MATERIALS AND METHODS

We assessed the genetic correlation between three COVID-19 phenotypes and IBS using linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL) methods. Two different sources of IBS data were combined using METAL, and the Multi-trait analysis of GWAS (MTAG) method was applied for multi-trait analysis to enhance statistical robustness and discover new genetic associations. Independent risk loci were examined using genome-wide complex trait analysis (GCTA)-conditional and joint analysis (COJO), multi-marker analysis of genomic annotation (MAGMA), and functional mapping and annotation (FUMA), integrating various QTL information and methods to further identify risk genes and proteins. Gene set variation analysis (GSVA) was employed to compute pleiotropic gene scores, and combined with immune infiltration algorithms, IBS patients were categorized into high and low immune infiltration groups.

RESULTS

We found a positive genetic correlation between COVID-19 infection, COVID-19 hospitalization, and IBS. Subsequent multi-trait analysis identified nine significantly associated genomic loci. Among these, eight genetic variants were closely related to the comorbidity of IBS and COVID-19. The study also highlighted four genes and 231 proteins associated with the susceptibility to IBS identified through various analytical strategies and a stratification approach for IBS risk populations.

CONCLUSIONS

Our study reveals a shared genetic architecture between these two diseases, providing new insights into potential biological mechanisms and laying the groundwork for more effective interventions.

Identifying Common Genetic Etiologies Between Inflammatory Bowel Disease and Related Immune-Mediated Diseases

BACKGROUND

Patients with inflammatory bowel disease (IBD) have an increased risk of developing immune-mediated diseases. However, the genetic basis of IBD is complex, and an integrated approach should be used to elucidate the complex genetic relationship between IBD and immune-mediated diseases.

METHODS

The genetic relationship between IBD and 16 immune-mediated diseases was examined using linkage disequilibrium score regression. GWAS data were synthesized from two IBD databases using the METAL, and multi-trait analysis of genome-wide association studies was performed to enhance statistical robustness and identify novel genetic associations. Independent risk loci were meticulously examined using conditional and joint genome-wide multi-trait analysis, multi-marker analysis of genomic annotation, and functional mapping and annotation of significant genetic loci, integrating the information of quantitative trait loci and different methodologies to identify risk-related genes and proteins.

RESULTS

The results revealed four immune-mediated diseases (AS, psoriasis, iridocyclitis, and PsA) with a significant relationship with IBD. The multi-trait analysis revealed 909 gene loci of statistical significance. Of these loci, 28 genetic variants were closely related to IBD, and 7 single-nucleotide polymorphisms represented novel independent risk loci. In addition, 14 genes and 514 proteins were found to be associated with susceptibility to immune-mediated diseases. Notably, IL1RL1 emerged as a key player, present within pleiotropic genes across multiple protein databases, highlighting its potential as a therapeutic target.

CONCLUSIONS

This study suggests that the common polygenic determinants between IBD and immune-mediated diseases are widely distributed across the genome. The findings not only support a shared genetic relationship between IBD and immune-mediated diseases but also provide novel therapeutic targets for these diseases.

StableLift: Optimized Germline and Somatic Variant Detection Across Genome Builds

Reference genomes are foundational to modern genomics. Our growing understanding of genome structure leads to continual improvements in reference genomes and new genome "builds" with incompatible coordinate systems. We quantified the impact of genome build on germline and somatic variant calling by analyzing tumour-normal whole-genome pairs against the two most widely used human genome builds. The average individual had a build-discordance of 3.8% for germline SNPs, 8.6% for germline SVs, 25.9% for somatic SNVs and 49.6% for somatic SVs. Build-discordant variants are not simply false-positives: 47% were verified by targeted resequencing. Build-discordant variants were associated with specific genomic and technical features in variant- and algorithm-specific patterns. We leveraged these patterns to create StableLift, an algorithm that predicts cross-build stability with AUROCs of 0.934 ± 0.029. These results call for significant caution in cross-build analyses and for use of StableLift as a computationally efficient solution to mitigate inter-build artifacts.

Giant polyketide synthase enzymes in the biosynthesis of giant marine polyether toxins

Prymnesium parvum are harmful haptophyte algae that cause massive environmental fish kills. Their polyketide polyether toxins, the prymnesins, are among the largest nonpolymeric compounds in nature and have biosynthetic origins that have remained enigmatic for more than 40 years. In this work, we report the "PKZILLAs," massive P. parvum polyketide synthase (PKS) genes that have evaded previous detection. PKZILLA-1 and -2 encode giant protein products of 4.7 and 3.2 megadaltons that have 140 and 99 enzyme domains. Their predicted polyene product matches the proposed pre-prymnesin precursor of the 90-carbon-backbone A-type prymnesins. We further characterize the variant PKZILLA-B1, which is responsible for the shorter B-type analog prymnesin-B1, from P. parvum RCC3426 and thus establish a general model of haptophyte polyether biosynthetic logic. This work expands expectations of genetic and enzymatic size limits in biology.

A multi-ancestry GWAS of Fuchs corneal dystrophy highlights the contributions of laminins, collagen, and endothelial cell regulation

Fuchs endothelial corneal dystrophy (FECD) is a leading indication for corneal transplantation, but its molecular etiology remains poorly understood. We performed genome-wide association studies (GWAS) of FECD in the Million Veteran Program followed by multi-ancestry meta-analysis with the previous largest FECD GWAS, for a total of 3970 cases and 333,794 controls. We confirm the previous four loci, and identify eight novel loci: SSBP3, THSD7A, LAMB1, PIDD1, RORA, HS3ST3B1, LAMA5, and COL18A1. We further confirm the TCF4 locus in GWAS for admixed African and Hispanic/Latino ancestries and show an enrichment of European-ancestry haplotypes at TCF4 in FECD cases. Among the novel associations are low frequency missense variants in laminin genes LAMA5 and LAMB1 which, together with previously reported LAMC1, form laminin-511 (LM511). AlphaFold 2 protein modeling, validated through homology, suggests that mutations at LAMA5 and LAMB1 may destabilize LM511 by altering inter-domain interactions or extracellular matrix binding. Finally, phenome-wide association scans and colocalization analyses suggest that the TCF4 CTG18.1 trinucleotide repeat expansion leads to dysregulation of ion transport in the corneal endothelium and has pleiotropic effects on renal function.