Catalog Of Variants Research Articles

Comprehensive Catalog of Variants Potentially Associated with Hidradenitis Suppurativa, Including Newly Identified Variants from a Cohort of 100 Patients.

Hidradenitis suppurativa (HS) is a chronic skin disease characterized by painful, recurrent abscesses, nodules, and scarring, primarily in skin folds. The exact causes of HS are multifactorial, involving genetic, hormonal, and environmental factors. It is associated with systemic diseases such as metabolic syndrome and inflammatory bowel disease. Genetic studies have identified mutations in the γ-secretase complex that affect Notch signaling pathways critical for skin cell regulation. Despite its high heritability, most reported HS cases do not follow a simple genetic pattern. In this article, we performed whole-exome sequencing (WES) on a cohort of 100 individuals with HS, and we provide a comprehensive review of the variants known to be described or associated with HS. 91 variants were associated with the γ-secretase complex, and 78 variants were associated with other genes involved in the Notch pathway, keratinization, or immune response. Through this new genetic analysis, we have added ten new variants to the existing catalogs. All variants are available in a .vcf file and are provided as a resource for future studies.

Genetic regulation of ovulation rate and multiple births.

Ovulation rate in many mammalian species is controlled to regulate the numbers of offspring and maximise reproductive success. Pathways that regulate ovulation rate still respond to genetic and environmental factors and show considerable variation within and between species. Genetic segregation, positional cloning, and association studies have discovered numerous mutations and genetic risk factors that contribute to this variation. Notable among the discoveries has been the role of mutations in bone morphogenetic protein 15 (BMP15 ), growth differentiation factor 9 (GDF9 ) and bone morphogenetic protein receptor type 1B (BMPR1B ) from the intra-ovarian signalling pathway contributing to the evidence that signalling from the oocyte is the key driver in follicle regulation rather than circulating gonadotrophin concentrations. Multiple variants in different domains of BMP15 and GDF9 result in partial or complete loss of function of the proteins providing insights into their functional roles and differential regulation contributing to species differences in ovulation rate. Early success encouraged many more studies in prolific strains of sheep, cattle and goats providing a valuable catalogue of genetic variants of large effect increasing ovulation rate and litter size. More recently, genetic association studies are beginning to identify genetic risk factors with smaller effects. Most genes implicated are from pathways with defined roles in regulation of the ovarian function. However, some genomic regions suggest regulation by novel genes. Continuing genetic and related functional studies will add further to our understanding of the detailed regulation of ovulation rate and litter size with implications for health and animal production systems.

Genetic Markers of Spina Bifida in an Indian Cohort.

To identify the genetic markers of spina bifida through a systematic survey of the exome in an Indian cohort. Three consecutive patients (P1: 1 year, male; P2: 2.8 years, male; and P3: 10 years, female) with spina bifida (lumbosacral meningomyelocele) underwent whole-exome sequencing (libraries: SureSelect Human All Exon V8; sequencing: 2 * 150 bp paired-end run, 100×) with NovaSeq 6000. Data analysis was performed using SMART-One™ (secondary analysis) and SMARTer™ (tertiary analysis) for automated quality check, alignment (GRCh38/hg38), variant calling, annotation (ClinVar, OMIM, avsnp150, 1000 Genomes v5b, ExAC v0.3, gnomAD v4.0, and esp6500vi2all v0.0.25), v0.0.25), interpretation. The pathogenic and likely pathogenic (ClinVar/ InterVar), non-synonymous, exonic markers (read depth ≥ 5) were matched with the Familial Neural Tube Defects (Version 1.10) panel (FNTD panel). Pathogenic variants overlapping with the FNTD panel were MTRR, CC2D2A, and ZIC2 in P1 and P2, TGIF1 in P1 only, and none in P3. Novel pathogenic/likely pathogenic variants common to all three patients were PRUNE1, PKD1, PDZD2, and DAB2 in the homozygous state as well as in the heterozygous state, PLK1 and NLGN2. The possible role of such markers in etiopathogenesis was explored through a literatur search. The genetic landscape of the spina bifida in an Indian cohort is diverse compared to that reported from other parts of the world. A comprehensive catalog of single-nucleotide variants in the etiopathogenesis of the spina bifida on a background of the Familial Neural Tube Defects Panel has been generated.

Massively parallel characterization of regulatory elements in the developing human cortex.

Nucleotide changes in gene regulatory elements are important determinants of neuronal development and diseases. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 open chromatin regions, including thousands of sequences with cell type-specific accessibility and variants associated with brain gene regulation. In primary cells, we identified 46,802 active enhancer sequences and 164 variants that alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development.

Diallel panel reveals a significant impact of low-frequency genetic variants on gene expression variation in yeast.

Unraveling the genetic sources of gene expression variation is essential to better understand the origins of phenotypic diversity in natural populations. Genome-wide association studies identified thousands of variants involved in gene expression variation, however, variants detected only explain part of the heritability. In fact, variants such as low-frequency and structural variants (SVs) are poorly captured in association studies. To assess the impact of these variants on gene expression variation, we explored a half-diallel panel composed of 323 hybrids originated from pairwise crosses of 26 natural Saccharomyces cerevisiae isolates. Using short- and long-read sequencing strategies, we established an exhaustive catalog of single nucleotide polymorphisms (SNPs) and SVs for this panel. Combining this dataset with the transcriptomes of all hybrids, we comprehensively mapped SNPs and SVs associated with gene expression variation. While SVs impact gene expression variation, SNPs exhibit a higher effect size with an overrepresentation of low-frequency variants compared to common ones. These results reinforce the importance of dissecting the heritability of complex traits with a comprehensive catalog of genetic variants at the population level.

Variant Classification Discordance: Contributing Factors and Predictive Models

An ever-growing catalog of human variants is hosted in the ClinVar database. In this database, submissions on a variant are combined into a multi-submitter record and in the case of discordance in variant classification between submitters, the record is labelled as conflicting. We used ClinVar data to identify characteristics that would make variants more likely to be associated with the conflict class of variants. Further, we used the Extreme Gradient Boosting (XGBoost) algorithm to train classifier models to provide prediction of classification discordance for single submission variants in ClinVar database.We showed that population allele frequency, the gene harboring the variant, variant type, consequence on protein, variant deleteriousness score, first submitter identity and submission count are associated with conflict in variant classification. Using such features, the optimized classifier showed accuracy on the test set of 88% with the weighted average of precision, recall and f1-score of 0.84, 0.88 and 0.85, respectively.There are pronounced associations between variant classification discordance and allele frequency, gene type, and the identity of the first submitter. We provide the predicted discordance status for single-submitter variants deposited in ClinVar. Our approach can be used to assess whether single-submitter variants are likely to be supported, or in conflict with, future entries; this knowledge might help laboratories with clinical variant assessment.

52 The Power of Pangenome Assemblies in Ruminants

Abstract High quality reference genomes are the bases of all genomic research and they have facilitated a wealth of discoveries and research tools for the improvement of livestock species. These works have enabled major advances in the fields of animal science and genetics and impacted livestock production and associated industries for the benefit of society. However, because a single reference genome fails to represent all of the genetic material present across populations, it inherently limits the ability to comprehensively evaluate all genomic variants within a species. A complete understanding of how small and large genomic variants, from single nucleotide polymorphisms (SNP) to larger structural variations (SV) including insertions/deletions (InDels) and copy number variation (CNVs), have been selected for over time for specific environments and phenotypes, remains elusive. To address this, it is necessary to generate a catalog of genomic variants in populations subjected to natural or artificial selection pressures and evaluate their relationship among phenotypic classes. The pangenome approach is a means to comprehensively identify and catalog genomic variation and representation that will make more suitable reference for mapping population sequence data for variant detection and frequency evaluation. The goal of the most pangenome projects is to provide genomic resources to represent the immense genetic diversity of this species more completely. This will increase our understanding of genetic variation and its role in dictating different phenomes, empowering scientists to predict the physiological outcomes more effectively from genomic variation towards the improvement of breeding strategies. These pangenomes can then be used to discover the underlying mechanism of biological traits and inform future breeding strategies and support sustainable production of this global source of food and fiber.

Clustering minimal inhibitory concentration data through Bayesian mixture models: An application to detect Mycobacterium tuberculosis resistance mutations.

Antimicrobial resistance is becoming a major threat to public health throughout the world. Researchers are attempting to contrast it by developing both new antibiotics and patient-specific treatments. In the second case, whole-genome sequencing has had a huge impact in two ways: first, it is becoming cheaper and faster to perform whole-genome sequencing, and this makes it competitive with respect to standard phenotypic tests; second, it is possible to statistically associate the phenotypic patterns of resistance to specific mutations in the genome. Therefore, it is now possible to develop catalogues of genomic variants associated with resistance to specific antibiotics, in order to improve prediction of resistance and suggest treatments. It is essential to have robust methods for identifying mutations associated to resistance and continuously updating the available catalogues. This work proposes a general method to study minimal inhibitory concentration distributions and to identify clusters of strains showing different levels of resistance to antimicrobials. Once the clusters are identified and strains allocated to each of them, it is possible to perform regression method to identify with high statistical power the mutations associated with resistance. The method is applied to a new 96-well microtiter plate used for testing Mycobacterium tuberculosis.

FRI457 Protein-coding Genetic Variation In Polycystic Ovary Syndrome

Abstract Disclosure: C. Parker: None. R. Bauer: None. C.K. Welt: None. R.S. Legro: None. M.G. Hayes: None. M. Urbanek: None. Background: Polycystic ovary syndrome (PCOS) is a multisystem endocrine disorder and is the most common form of anovulatory infertility of reproductive aged women (6-15%). PCOS is characterized by the presence of hyperandrogenemia, irregular menses, and polycystic ovarian morphology. A previous twin study has shown PCOS to be highly heritable (h2=0.72). Thus, we hypothesize that genetic variation is a major contributor to the etiology of PCOS. Objective: Our goal is to identify the genetic factors that contribute to the PCOS phenotype and how they define phenotypic subtypes of PCOS with the aim of better understanding PCOS pathology and optimizing treatment strategies for individual women. Methodology: We are performing whole exome sequencing (WES) supplemented with genomic regions mapping to PCOS GWAS loci on 772 subjects with PCOS and 300 age and ancestry-matched controls to generate a comprehensive catalog of PCOS-associated protein coding variants. We will use prediction tools to identify likely-to-be deleterious variants and in silico evidence of epigenetic modification to identify PCOS associated genes/pathways. We will then prioritize variants for molecular follow-up creating a comprehensive catalog of protein coding variants associated with PCOS. We expect the variants identified by WES to map to multiple genes and pathways including novel genes/pathways which have not previously been implicated in PCOS as well as genes/pathways that have previously been shown or predicted to play a major role in the etiology of PCOS by us or other groups. Results: To date we have obtained high quality sequencing data on 772 women with PCOS. Sequencing of 300 age and ancestry matched reproductively heathy women is being started. We have identified 81 rare protein coding genetic variants using targeted re-sequencing in three distinct pathways in an independent PCOS cohort. These genes are associated with insulin resistance, the gonadotropin signaling pathway and the Anti-Müllerian Hormone (AMH) signaling pathway. We identified 37 functionally validated deleterious variants in genes that encode AMH or its cognate receptor AMHR2, 7 rare variants that encode LMNA, 11 rare (MAF <0.1) variants that encode the insulin receptor, and 26 coding variants for the genes encoding the beta subunit of gonadotropins, LH and FSH, and their receptors, FSHR and LHCGR. Conclusion: We have identified 81 rare protein altering genetic variants in pathways that are predicted to be impaired in individuals with PCOS supporting a critical role for genetics in the etiology of PCOS. Our WES screen will allow us to generate a comprehensive catalog of likely to be deleterious PCOS associated variants. This catalog of variants will identify the genes/pathways that are mutated in PCOS leading to improved personalized phenotyping and treatment of PCOS. Presentation Date: Friday, June 16, 2023

Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer’s disease brains

BackgroundThe genetic underpinnings of late-onset Alzheimer’s disease (LOAD) are yet to be fully elucidated. Although numerous LOAD-associated loci have been discovered, the causal variants and their target genes remain largely unknown. Since the brain is composed of heterogenous cell subtypes, it is imperative to study the brain on a cell subtype specific level to explore the biological processes underlying LOAD.MethodsHere, we present the largest parallel single-nucleus (sn) multi-omics study to simultaneously profile gene expression (snRNA-seq) and chromatin accessibility (snATAC-seq) to date, using nuclei from 12 normal and 12 LOAD brains. We identified cell subtype clusters based on gene expression and chromatin accessibility profiles and characterized cell subtype-specific LOAD-associated differentially expressed genes (DEGs), differentially accessible peaks (DAPs) and cis co-accessibility networks (CCANs).ResultsIntegrative analysis defined disease-relevant CCANs in multiple cell subtypes and discovered LOAD-associated cell subtype-specific candidate cis regulatory elements (cCREs), their candidate target genes, and trans-interacting transcription factors (TFs), some of which, including ELK1, JUN, and SMAD4 in excitatory neurons, were also LOAD-DEGs. Finally, we focused on a subset of cell subtype-specific CCANs that overlap known LOAD-GWAS regions and catalogued putative functional SNPs changing the affinities of TF motifs within LOAD-cCREs linked to LOAD-DEGs, including APOE and MYO1E in a specific subtype of microglia and BIN1 in a subpopulation of oligodendrocytes.ConclusionsTo our knowledge, this study represents the most comprehensive systematic interrogation to date of regulatory networks and the impact of genetic variants on gene dysregulation in LOAD at a cell subtype resolution. Our findings reveal crosstalk between epigenetic, genomic, and transcriptomic determinants of LOAD pathogenesis and define catalogues of candidate genes, cCREs, and variants involved in LOAD genetic etiology and the cell subtypes in which they act to exert their pathogenic effects. Overall, these results suggest that cell subtype-specific cis–trans interactions between regulatory elements and TFs, and the genes dysregulated by these networks contribute to the development of LOAD.

Uncovering the Molecular Drivers of NHEJ DNA Repair-Implicated Missense Variants and Their Functional Consequences.

Variants in non-homologous end joining (NHEJ) DNA repair genes are associated with various human syndromes, including microcephaly, growth delay, Fanconi anemia, and different hereditary cancers. However, very little has been done previously to systematically record the underlying molecular consequences of NHEJ variants and their link to phenotypic outcomes. In this study, a list of over 2983 missense variants of the principal components of the NHEJ system, including DNA Ligase IV, DNA-PKcs, Ku70/80 and XRCC4, reported in the clinical literature, was initially collected. The molecular consequences of variants were evaluated using in silico biophysical tools to quantitatively assess their impact on protein folding, dynamics, stability, and interactions. Cancer-causing and population variants within these NHEJ factors were statistically analyzed to identify molecular drivers. A comprehensive catalog of NHEJ variants from genes known to be mutated in cancer was curated, providing a resource for better understanding their role and molecular mechanisms in diseases. The variant analysis highlighted different molecular drivers among the distinct proteins, where cancer-driving variants in anchor proteins, such as Ku70/80, were more likely to affect key protein-protein interactions, whilst those in the enzymatic components, such as DNA-PKcs, were likely to be found in intolerant regions undergoing purifying selection. We believe that the information acquired in our database will be a powerful resource to better understand the role of non-homologous end-joining DNA repair in genetic disorders, and will serve as a source to inspire other investigations to understand the disease further, vital for the development of improved therapeutic strategies.

Bioinformatics pipeline to guide post-GWAS studies in Alzheimer's: A new catalogue of disease candidate short structural variants.

Short structural variants (SSVs), including insertions/deletions (indels), are common in the human genome and impact disease risk. The role of SSVs in late-onset Alzheimer's disease (LOAD) has been understudied. In this study, we developed a bioinformatics pipeline of SSVs within LOAD-genome-wide association study (GWAS) regions to prioritize regulatory SSVs based on the strength of their predicted effect on transcription factor (TF) binding sites. The pipeline utilized publicly available functional genomics data sources including candidate cis-regulatory elements (cCREs) from ENCODE and single-nucleus (sn)RNA-seq data from LOAD patient samples. We catalogued 1581 SSVs in candidate cCREs in LOAD GWAS regions that disrupted 737 TF sites. That included SSVs that disrupted the binding of RUNX3, SPI1, and SMAD3, within the APOE-TOMM40, SPI1, and MS4A6A LOAD regions. The pipeline developed here prioritized non-coding SSVs in cCREs and characterized their putative effects on TF binding. The approach integrates multiomics datasets for validation experiments using disease models.

Genome-wide structural variant analysis identifies risk loci for non-Alzheimer’s dementias

We characterized the role of structural variants, a largely unexplored type of genetic variation, in two non-Alzheimer's dementias, namely Lewy body dementia (LBD) and frontotemporal dementia (FTD)/amyotrophic lateral sclerosis (ALS). To do this, we applied an advanced structural variant calling pipeline (GATK-SV) to short-read whole-genome sequence data from 5,213 European-ancestry cases and 4,132 controls. We discovered, replicated, and validated a deletion in TPCN1 as a novel risk locus for LBD and detected the known structural variants at the C9orf72 and MAPT loci as associated with FTD/ALS. We also identified rare pathogenic structural variants in both LBD and FTD/ALS. Finally, we assembled a catalog of structural variants that can be mined for new insights into the pathogenesis of these understudied forms of dementia.

Abstract 673: CHROMR Governs Interferon Signaling And Cholesterol Homeostasis In Human Atherosclerotic Plaque

Long noncoding RNAs (lncRNA) have emerged as critical regulators of gene expression, yet their potential contribution to human disease remains poorly understood. We previously identified the primate-specific lncRNA CHROMR as a key regulator of cholesterol homeostasis. Here, we report a novel function for CHROMR in controlling interferon signaling, which is known to regulate innate and adaptive immune responses that drive atherosclerosis. Using single cell RNA-sequencing of human atheroma, we observed robust expression of CHROMR in plaque immune cell populations, which correlated strongly with the expression of two subsets of interferon-stimulated genes (ISG). Interrogation of these genesets using DisGeNET, a comprehensive catalogue of genes and variants associated to human diseases, revealed associations with atherosclerosis and coronary artery disease. Differential expression analysis of CHROMR -expressing versus non-expressing immune cells showed higher levels of ISGs particularly in the monocyte-macrophage cluster. To assess the impact of CHROMR depletion on inflammatory gene expression, we knocked down CHROMR in THP1 macrophages using GapmeR antisense oligonucleotides (or controls) and treated with the TLR3 agonist poly(I:C) to stimulate the interferon response. Transcriptome profiling and unsupervised hierarchical clustering of genes differentially expressed in CHROMR -sufficient and -depleted macrophages revealed that CHROMR silencing markedly repressed expression of key ISGs, including MX1 , IFI44L , STAT1 , and CXCL and CCL family chemokines ( CXCL10 , CXCL11, CCL2 ). Conversely, overexpression of CHROMR in THP1 macrophages increased expression of these ISGs. Furthermore, CHROMR depletion in macrophages reduced histone acetylation at regulatory regions of ISG loci. Mechanistically, we showed that CHROMR sequesters the interferon regulatory factor (IRF)-2-dependent transcriptional co-repressor IRF2BP2, thereby licensing IRF-dependent signaling and transcription of the ISG network. Taken together, our work unveils a critical role for CHROMR in coordinating interferon signaling responses in macrophages and suggests that targeting this lncRNA may reduce inflammation in atherosclerotic plaques.

A genomic timescale for placental mammal evolution

The precise pattern and timing of speciation events that gave rise to all living placental mammals remain controversial. We provide a comprehensive phylogenetic analysis of genetic variation across an alignment of 241 placental mammal genome assemblies, addressing prior concerns regarding limited genomic sampling across species. We compared neutral genome-wide phylogenomic signals using concatenation and coalescent-based approaches, interrogated phylogenetic variation across chromosomes, and analyzed extensive catalogs of structural variants. Interordinal relationships exhibit relatively low rates of phylogenomic conflict across diverse datasets and analytical methods. Conversely, X-chromosome versus autosome conflicts characterize multiple independent clades that radiated during the Cenozoic. Genomic time trees reveal an accumulation of cladogenic events before and immediately after the Cretaceous-Paleogene (K-Pg) boundary, implying important roles for Cretaceous continental vicariance and the K-Pg extinction in the placental radiation.

Resolution of structural variation in diverse mouse genomes reveals chromatin remodeling due to transposable elements

Diverse inbred mouse strains are important biomedical research models, yet genome characterization of many strains is fundamentally lacking in comparison with humans. In particular, catalogs of structural variants (SVs) (variants ≥ 50bp) are incomplete, limiting the discovery of causative alleles for phenotypic variation. Here, we resolve genome-wide SVs in 20 genetically distinct inbred mice with long-read sequencing. We report 413,758 site-specific SVs affecting 13% (356 Mbp) of the mouse reference assembly, including 510 previously unannotated coding variants. We substantially improve the Mus musculus transposable element (TE) callset, and we find that TEs comprise 39% of SVs and account for 75% of altered bases. We further utilize this callset to investigate how TE heterogeneity affects mouse embryonic stem cells and find multiple TE classes that influence chromatin accessibility. Our work provides a comprehensive analysis of SVs found in diverse mouse genomes and illustrates the role of TEs in epigenetic differences.

Genome sequences of BCG Pasteur ATCC 35734 and its derivative, the vaccine candidate BCGΔBCG1419c

Background:Bacillus Calmette–Guérin (BCG) remains the only vaccine to prevent tuberculosis (TB) during childhood, with relatively low to no efficacy against pulmonary TB in adolescents and adults. BCG consists of close to 15 different substrains, where genetic variations among them might contribute to the variable protective efficacy afforded against pulmonary TB. We have shown that the vaccine candidate, BCGΔBCG1419c, which is based on BCG Pasteur, improved protection against chronic TB in murine models, as well as against pulmonary and extrapulmonary TB in guinea pigs. Here, to confirm deletion of the BCG1419c gene and to detect possible genetic variations occurring as a consequence of the spontaneous mutations that may arise during in vitro culture of mycobacteria, the genomes of BCG Pasteur ATCC 35734 and its isogenic derivative, BCGΔBCG1419c, were sequenced and subjected to a comparative analysis between them and against BCG Pasteur 1173P2.Results:The complete catalog of variants in genes relative to the reference genome BCG Pasteur 1173P2 (GenBank NC008769) showed that the parental strain BCG Pasteur ATCC 35734, from which the mutant BCGΔBCG1419c originated, showed five synonymous mutations, three missense mutations, and five codon insertions, whereas the BCGΔBCG1419c mutant reported the same changes. When BCG Pasteur ATCC 35734 and BCGΔBCG1419c were compared, we confirmed that the latter was devoid of the BCG1419c gene, with only one unanticipated SNP at position 2, 828, 791 which we consider has no role in vaccine properties reported thus far.Conclusion:We provide evidence that the mutagenesis performed to remove BCG1419c from BCG Pasteur ATCC 35734 solely deleted this gene, and that compared with the reference strain BCG Pasteur 1173P2, few changes were present confirming that they are BCG Pasteur strains, and that changes in immunogenicity or efficacy observed thus far in BCGΔBCG1419c are most likely derived solely from the elimination of the BCG1419c gene.

Using species richness calculations to model the global profile of unsampled pathogenic variants: Examples from BRCA1 and BRCA2.

There have been many surveys of genetic variation in BRCA1 and BRCA2 to identify variant prevalence and catalogue population specific variants, yet none have evaluated the magnitude of unobserved variation. We applied species richness estimation methods from ecology to estimate "variant richness" and determine how many germline pathogenic BRCA1/2 variants have yet to be identified and the frequency of these missing variants in different populations. We also estimated the prevalence of germline pathogenic BRCA1/2 variants and identified those expected to be most common. Data was obtained from a literature search including studies conducted globally that tested the entirety of BRCA1/2 for pathogenic variation. Across countries, 45% to 88% of variants were estimated to be missing, i.e., present in the population but not observed in study data. Estimated variant frequencies in each country showed a higher proportion of rare variants compared to recurrent variants. The median prevalence estimate of BRCA1/2 pathogenic variant carriers was 0.64%. BRCA1 c.68_69del is likely the most recurrent BRCA1/2 variant globally due to its estimated prevalence in India. Modeling variant richness using ecology methods may assist in evaluating clinical targeted assays by providing a picture of what is observed with estimates of what is still unknown.

High-throughput splicing assays identify missense and silent splice-disruptive POU1F1 variants underlying pituitary hormone deficiency

Brief Summary: This study reports splice-disruptive variants in POU1F1 in 4 families with hypopituitarism and uses a high-throughput splicing reporter assay to create a comprehensive catalogue of such variants in or near exon 2 of the gene. The catalogue paves the way for identifying synonymous but splice-disruptive POU1F1 variants in additional patients with hypopituitarism, which underscores the importance of evaluating defective splicing as a disease mechanism.

Assembly of a pangenome for global cattle reveals missing sequences and novel structural variations, providing new insights into their diversity and evolutionary history.

A cattle pangenome representation was created based on the genome sequences of 898 cattle representing 57 breeds. The pangenome identified 83 Mb of sequence not found in the cattle reference genome, representing 3.1% novel sequence compared with the 2.71-Gb reference. A catalog of structural variants developed from this cattle population identified 3.3 million deletions, 0.12 million inversions, and 0.18 million duplications. Estimates of breed ancestry and hybridization between cattle breeds using insertion/deletions as markers were similar to those produced by single nucleotide polymorphism-based analysis. Hundreds of deletions were observed to have stratification based on subspecies and breed. For example, an insertion of a Bov-tA1 repeat element was identified in the first intron of the APPL2 gene and correlated with cattle breed geographic distribution. This insertion falls within a segment overlapping predicted enhancer and promoter regions of the gene, and could affect important traits such as immune response, olfactory functions, cell proliferation, and glucose metabolism in muscle. The results indicate that pangenomes are a valuable resource for studying diversity and evolutionary history, and help to delineate how domestication, trait-based breeding, and adaptive introgression have shaped the cattle genome.