Neuronal DNA double-strand breaks lead to genome structural variations and 3D genome disruption in neurodegeneration.

Persistent DNA double-strand breaks (DSBs) in neurons are an early pathological hallmark of neurodegenerative diseases including Alzheimer's disease (AD), with the potential to disrupt genome integrity. We used single-nucleus RNA-seq in human postmortem prefrontal cortex samples and found that excitatory neurons in AD were enriched for somatic mosaic gene fusions. Gene fusions were particularly enriched in excitatory neurons with DNA damage repair and senescence gene signatures. In addition, somatic genome structural variations and gene fusions were enriched in neurons burdened with DSBs in the CK-p25 mouse model of neurodegeneration. Neurons enriched for DSBs also had elevated levels of cohesin along with progressive multiscale disruption of the 3D genome organization aligned with transcriptional changes in synaptic, neuronal development, and histone genes. Overall, this study demonstrates the disruption of genome stability and the 3D genome organization by DSBs in neurons as pathological steps in the progression of neurodegenerative diseases.

Circadian clock gene polymorphisms implicated in human pathologies.

Circadian rhythms, ~24 h cycles of physiological and behavioral processes, can be synchronized by external signals (e.g., light) and persist even in their absence. Consequently, dysregulation of circadian rhythms adversely affects the well-being of the organism. This timekeeping system is generated and sustained by a genetically encoded endogenous mechanism composed of interlocking transcriptional/translational feedback loops that generate rhythmic expression of core clock genes. Genome-wide association studies (GWAS) and forward genetic studies show that SNPs in clock genes influence gene regulation and correlate with the risk of developing various conditions. We discuss genetic variations in core clock genes that are associated with various phenotypes, their implications for human health, and stress the need for thorough studies in this domain of circadian regulation.

Splicing-specific transcriptome-wide association uncovers genetic mechanisms for schizophrenia.

Recent studies have highlighted the essential role of RNA splicing, a key mechanism of alternative RNA processing, in establishing connections between genetic variations and disease. Genetic loci influencing RNA splicing variations show considerable influence on complex traits, possibly surpassing those affecting total gene expression. Dysregulated RNA splicing has emerged as a major potential contributor to neurological and psychiatric disorders, likely due to the exceptionally high prevalence of alternatively spliced genes in the human brain. Nevertheless, establishing direct associations between genetically altered splicing and complex traits has remained an enduring challenge. We introduce Spliced-Transcriptome-Wide Associations (SpliTWAS) to integrate alternative splicing information with genome-wide association studies to pinpoint genes linked to traits through exon splicing events. We applied SpliTWAS to two schizophrenia (SCZ) RNA-sequencing datasets, BrainGVEX and CommonMind, revealing 137 and 88 trait-associated exons (in 84 and 67 genes), respectively. Enriched biological functions in the associated gene sets converged on neuronal function and development, immune cell activation, and cellular transport, which are highly relevant to SCZ. SpliTWAS variants impacted RNA-binding protein binding sites, revealing potential disruption of RNA-protein interactions affecting splicing. We extended the probabilistic fine-mapping method FOCUS to the exon level, identifying 36 genes and 48 exons as putatively causal for SCZ. We highlight VPS45 and APOPT1, where splicing of specific exons was associated with disease risk, eluding detection by conventional gene expression analysis. Collectively, this study supports the substantial role of alternative splicing in shaping the genetic basis of SCZ, providing a valuable approach for future investigations in this area.

Unified views on variant impact across many diseases.

Genomic studies of human disorders are often performed by distinct research communities (i.e., focused on rare diseases, common diseases, or cancer). Despite underlying differences in the mechanistic origin of different disease categories, these studies share the goal of identifying causal genomic events that are critical for the clinical manifestation of the disease phenotype. Moreover, these studies face common challenges, including understanding the complex genetic architecture of the disease, deciphering the impact of variants on multiple scales, and interpreting noncoding mutations. Here, we highlight these challenges in depth and argue that properly addressing them will require a more unified vocabulary and approach across disease communities. Toward this goal, we present a unified perspective on relating variant impact to various genomic disorders.

Comprehensive SMN1 and SMN2 profiling for spinal muscular atrophy analysis using long-read PacBio HiFi sequencing.

Spinal muscular atrophy, a leading cause of early infant death, is caused by bi-allelic mutations of SMN1. Sequence analysis of SMN1 is challenging due to high sequence similarity with its paralog SMN2. Both genes have variable copy numbers across populations. Furthermore, without pedigree information, it is currently not possible to identify silent carriers (2+0) with two copies of SMN1 on one chromosome and zero copies on the other. We developed Paraphase, an informatics method that identifies full-length SMN1 and SMN2 haplotypes, determines the gene copy numbers, and calls phased variants using long-read PacBio HiFi data. The SMN1 and SMN2 copy-number calls by Paraphase are highly concordant with orthogonal methods (99.2% for SMN1 and 100% for SMN2). We applied Paraphase to 438 samples across 5 ethnic populations to conduct a population-wide haplotype analysis of these highly homologous genes. We identified major SMN1 and SMN2 haplogroups and characterized their co-segregation through pedigree-based analyses. We identified two SMN1 haplotypes that form a common two-copy SMN1 allele in African populations. Testing positive for these two haplotypes in an individual with two copies of SMN1 gives a silent carrier risk of 88.5%, which is significantly higher than the currently used marker (1.7%-3.0%). Extending beyond simple copy-number testing, Paraphase can detect pathogenic variants and enable potential haplotype-based screening of silent carriers through statistical phasing of haplotypes into alleles. Future analysis of larger population data will allow identification of more diverse haplotypes and genetic markers for silent carriers.

A perspective on genetic and polygenic risk scores-advances and limitations and overview of associated tools.

Polygenetic Risk Scores are used to evaluate an individual's vulnerability to developing specific diseases or conditions based on their genetic composition, by taking into account numerous genetic variations. This article provides an overview of the concept of Polygenic Risk Scores (PRS). We elucidate the historical advancements of PRS, their advantages and shortcomings in comparison with other predictive methods, and discuss their conceptual limitations in light of the complexity of biological systems. Furthermore, we provide a survey of published tools for computing PRS and associated resources. The various tools and software packages are categorized based on their technical utility for users or prospective developers. Understanding the array of available tools and their limitations is crucial for accurately assessing and predicting disease risks, facilitating early interventions, and guiding personalized healthcare decisions. Additionally, we also identify potential new avenues for future bioinformatic analyzes and advancements related to PRS.

Genomic Copy-Number Loss Is Rescued by Self-Limiting Production of DNA Circles.

Copy-number changes generate phenotypic variability in health and disease. Whether organisms protect against copy-number changes is largely unknown. Here, we show that Saccharomyces cerevisiae monitors the copy number of its ribosomal DNA (rDNA) and rapidly responds to copy-number loss with the clonal amplification of extrachromosomal rDNA circles (ERCs) from chromosomal repeats. ERC formation is replicative, separable from repeat loss, and reaches a dynamic steady state that responds to the addition of exogenous rDNA copies. ERC levels are also modulated by RNAPI activity and diet, suggesting that rDNA copy number is calibrated against the cellular demand for rRNA. Last, we show that ERCs reinsert into the genome in a dosage-dependent manner, indicating that they provide a reservoir for ultimately increasing rDNA array length. Our results reveal a DNA-based mechanism for rapidly restoring copy number in response to catastrophic gene loss that shares fundamental features with unscheduled copy-number amplifications in cancer cells.

Lateralized Functional Connectivity of the Sensorimotor Cortex and its Variations During Complex Visuomotor Tasks.

Previous studies have shown that the left hemisphere dominates motor function, often observed through homotopic activation measurements. Using a functional connectivity approach, this study investigated the lateralization of the sensorimotor cortex during handwriting and drawing, two complex visuomotor tasks with varying contextual demands. We found that both left- and right-lateralized connectivity in the primary motor cortex (M1), dorsal premotor cortex (PMd), somatosensory cortex, and visual regions were evident in adults (males and females), primarily in an interhemispheric integrative fashion. Critically, these lateralization tendencies remained highly invariant across task contexts, representing a task-invariant neural architecture for encoding fundamental motor programs consistently implemented in different task contexts. Additionally, the PMd exhibited a slight variation in lateralization degree between task contexts, reflecting the ability of the high-order motor system to adapt to varying task demands. However, connectivity-based lateralization of the sensorimotor cortex was not detected in 10-year-old children (males and females), suggesting that the maturation of connectivity-based lateralization requires prolonged development. In summary, this study demonstrates both task-invariant and task-sensitive connectivity lateralization in sensorimotor cortices that support the resilience and adaptability of skilled visuomotor performance. These findings align with the hierarchical organization of the motor system and underscore the significance of the functional connectivity-based approach in studying functional lateralization.

Shared genetic risk between major orofacial cleft phenotypes in an African population.

Nonsyndromic orofacial clefts (NSOFCs) represent a large proportion (70%-80%) of all OFCs. They can be broadly categorized into nonsyndromic cleft lip with or without cleft palate (NSCL/P) and nonsyndromic cleft palate only (NSCPO). Although NSCL/P and NSCPO are considered etiologically distinct, recent evidence suggests the presence of shared genetic risks. Thus, we investigated the genetic overlap between NSCL/P and NSCPO using African genome-wide association study (GWAS) data on NSOFCs. These data consist of 814 NSCL/P, 205 NSCPO cases, and 2159 unrelated controls. We generated common single-nucleotide variants (SNVs) association summary statistics separately for each phenotype (NSCL/P and NSCPO) under an additive genetic model. Subsequently, we employed the pleiotropic analysis under the composite null (PLACO) method to test for genetic overlap. Our analysis identified two loci with genome-wide significance (rs181737795 [p = 2.58E-08] and rs2221169 [p = 4.5E-08]) and one locus with marginal significance (rs187523265 [p = 5.22E-08]). Using mouse transcriptomics data and information from genetic phenotype databases, we identified MDN1, MAP3k7, KMT2A, ARCN1, and VADC2 as top candidate genes for the associated SNVs. These findings enhance our understanding of genetic variants associated with NSOFCs and identify potential candidate genes for further exploration.

Five Priorities of African Genomics Research: The Next Frontier.

To embrace the prospects of accurately diagnosing thousands of monogenic conditions, predicting disease risks for complex traits or diseases, tailoring treatment to individuals' pharmacogenetic profiles, and potentially curing some diseases, research into African genomic variation is a scientific imperative. African genomes harbor millions of uncaptured variants accumulated over 300,000 years of modern humans' evolutionary history, with successive waves of admixture, migration, and natural selection combining with extensive ecological diversity to create a broad and exceptional genomic complexity. Harnessing African genomic complexity, therefore, will require sustained commitment and equitable collaboration from the scientific community and funding agencies. African governments must support academic public research and industrial partnerships that build the necessary genetic medicine workforce, utilize the emerging genomic big data to develop expertise in computer science and bioinformatics, and evolve national and globalgovernance frameworks that recognize the ethical implications of data-driven genomic research and empower its application in African social, cultural, economic, and religious contexts.

GWAS of longitudinal trajectories at biobank scale.

Biobanks linked to massive, longitudinal electronic health record (EHR) data make numerous new genetic research questions feasible. One among these is the study of biomarker trajectories. For example, high blood pressure measurements over visits strongly predict stroke onset, and consistently high fasting glucose and Hb1Ac levels define diabetes. Recent research reveals that not only the mean level of biomarker trajectories but also their fluctuations, or within-subject (WS) variability, are risk factors for many diseases. Glycemic variation, for instance, is recently considered an important clinical metric in diabetes management. It is crucial to identify the genetic factors that shift the mean or alter the WS variability of a biomarker trajectory. Compared to traditional cross-sectional studies, trajectory analysis utilizes more data points and captures a complete picture of the impact of time-varying factors, including medication history and lifestyle. Currently, there are no efficient tools for genome-wide association studies (GWASs) of biomarker trajectories at the biobank scale, even for just mean effects. We propose TrajGWAS, a linear mixed effect model-based method for testing genetic effects that shift the mean or alter the WS variability of a biomarker trajectory. It is scalable to biobank data with 100,000 to 1,000,000 individuals and many longitudinal measurements and robust to distributional assumptions. Simulation studies corroborate that TrajGWAS controls the type I error rate and is powerful. Analysis of eleven biomarkers measured longitudinally and extracted from UK Biobank primary care data for more than 150,000 participants with 1,800,000 observations reveals loci that significantly alter the mean or WS variability.

Identify gestational diabetes mellitus by deep learning model from cell-free DNA at the early gestation stage.

Gestational diabetes mellitus (GDM) is a common complication of pregnancy, which has significant adverse effects on both the mother and fetus. The incidence of GDM is increasing globally, and early diagnosis is critical for timely treatment and reducing the risk of poor pregnancy outcomes. GDM is usually diagnosed and detected after 24 weeks of gestation, while complications due to GDM can occur much earlier. Copy number variations (CNVs) can be a possible biomarker for GDM diagnosis and screening in the early gestation stage. In this study, we proposed a machine-learning method to screen GDM in the early stage of gestation using cell-free DNA (cfDNA) sequencing data from maternal plasma. Five thousand and eighty-five patients from north regions of Mainland China, including 1942 GDM, were recruited. A non-overlapping sliding window method was applied for CNV coverage screening on low-coverage (~0.2×) sequencing data. The CNV coverage was fed to a convolutional neural network with attention architecture for the binary classification. The model achieved a classification accuracy of 88.14%, precision of 84.07%, recall of 93.04%, F1-score of 88.33% and AUC of 96.49%. The model identified 2190 genes associated with GDM, including DEFA1, DEFA3 and DEFB1. The enriched gene ontology (GO) terms and KEGG pathways showed that many identified genes are associated with diabetes-related pathways. Our study demonstrates the feasibility of using cfDNA sequencing data and machine-learning methods for early diagnosis of GDM, which may aid in early intervention and prevention of adverse pregnancy outcomes.

Regional Active Transcription Associates with Homoeologous Exchange Breakpoints in Synthetic Brassica Tetraploids.

Polyploidization plays a crucial role in plant evolution and is becoming increasingly important in breeding. Structural variations and epigenomic repatterning have been observed in synthetic polyploidizations. However, the mechanisms underlying the occurrence and their effects on gene expression and phenotype remain unknown. Here, we investigated genome-wide large deletion/duplication regions (DelDups) and genomic methylation dynamics in leaf organs of progeny from the first eight generations of synthetic tetraploids derived from Chinese cabbage (Brassica rapa L. ssp. pekinensis) and cabbage (Brassica oleracea L. var. capitata). One- or two-copy DelDups, with a mean size of 5.70 Mb (400 kb - 65.85 Mb), occurred from the first generation of selfing and thereafter. The duplication of a fragment in one subgenome consistently coincided with the deletion of its syntenic fragment in the other subgenome, and vice versa, indicating that these DelDups were generated by homoeologous exchanges (HEs). Interestingly, the larger the genomic syntenic region, the higher the frequency of DelDups, further suggesting that the pairing of large homoeologous fragments is crucial for HEs. Moreover, we found that the active transcription of continuously distributed genes in local regions is positively associated with the occurrence of HE breakpoints. In addition, the expression of genes within DelDups exhibited a dosage effect, and plants with extra parental genomic fragments generally displayed phenotypes biased towards the corresponding parent. Genome-wide methylation fluctuated remarkably, which did not clearly affect gene expression on a large scale. Our findings provide insights into the early evolution of polyploid genomes, offering valuable knowledge for polyploidization-based breeding.

Genetic analysis of 106 sporadic cases with hearing loss in the UAE population.

BACKGROUND: Hereditary hearing loss is a rare hereditary condition that has a significant presence in consanguineous populations. Despite its prevalence, hearing loss is marked by substantial genetic diversity, which poses challenges for diagnosis and screening, particularly in cases with no clear family history or when the impact of the genetic variant requires functional analysis, such as in the case of missense mutations and UTR variants. The advent of next-generation sequencing (NGS) has transformed the identification of genes and variants linked to various conditions, including hearing loss. However, there remains a high proportion of undiagnosed patients, attributable to various factors, including limitations in sequencing coverage and gaps in our knowledge of the entire genome, among other factors. In this study, our objective was to comprehensively identify the spectrum of genes and variants associated with hearing loss in a cohort of 106 affected individuals from the UAE. RESULTS: In this study, we investigated 106 sporadic cases of hearing impairment and performed genetic analyses to identify causative mutations. Screening of the GJB2 gene in these cases revealed its involvement in 24 affected individuals, with specific mutations identified. For individuals without GJB2 mutations, whole exome sequencing (WES) was conducted. WES revealed 33 genetic variants, including 6 homozygous and 27 heterozygous DNA changes, two of which were previously implicated in hearing loss, while 25 variants were novel. We also observed multiple potential pathogenic heterozygous variants across different genes in some cases. Notably, a significant proportion of cases remained without potential pathogenic variants. CONCLUSIONS: Our findings confirm the complex genetic landscape of hearing loss and the limitations of WES in achieving a 100% diagnostic rate, especially in conditions characterized by genetic heterogeneity. These results contribute to our understanding of the genetic basis of hearing loss and emphasize the need for further research and comprehensive genetic analyses to elucidate the underlying causes of this condition.

Functional ex vivo DNA fibre assay to measure replication dynamics in breast cancer tissue.

Replication stress (RS) is a key trait of cancer cells, and a potential actionable target in cancer treatment. Accurate methods to measure RS in tumour samples are currently lacking. DNA fibre analysis has been used as a common technique to measure RS in cell lines. Here, we investigated DNA fibre analysis on fresh breast cancer specimens and correlated DNA replication kinetics to known RS markers and genomic alterations. Fresh, treatment-naïve primary breast cancer samples (n = 74) were subjected to ex vivo DNA fibre analysis to measure DNA replication kinetics. Tumour cell proliferation was confirmed by EdU incorporation and cytokeratin AE1/AE3 (CK) staining. The RS markers phospho-S33-RPA and γH2AX and the RS-inducing proto-oncogenes Cyclin E1 and c-Myc were analysed by immunohistochemistry. Copy number variations (CNVs) were assessed from genome-wide single nucleotide polymorphism (SNP) arrays. We found that the majority of proliferating (EdU-positive) cells in each sample were CK-positive and therefore considered to be tumour cells. DNA fibre lengths varied largely in most tumour samples. The median DNA fibre length showed a significant inverse correlation with pRPA expression (r = -0.29, p = 0.033) but was not correlated with Cyclin E1 or c-Myc expression and global CNVs in this study. Nuclear Cyclin E1 expression showed a positive correlation with pRPA levels (r = 0.481, p < 0.0001), while cytoplasmic Cyclin E1 expression exhibited an inverse association with pRPA expression (r = -0.353, p = 0.002) and a positive association with global CNVs (r = 0.318, p = 0.016). In conclusion, DNA fibre analysis performed with fresh primary breast cancer samples is feasible. Fibre lengths were associated with pRPA expression. Cyclin E1 expression was associated with pRPA and the percentage of CNVs. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Mesonephric-like adenocarcinoma harbours characteristic copy number variations and a distinct DNA methylation signature closely related to mesonephric adenocarcinoma of the cervix.

Mesonephric-like adenocarcinoma (MLA) of the female genital tract is an uncommon histotype that can arise in both the endometrium and the ovary. The exact cell of origin and histogenesis currently remain unknown. Here, we investigated whole genome DNA methylation patterns and copy number variations (CNVs) in a series of MLAs in the context of a large cohort of various gynaecological carcinoma types. CNV analysis of 19 MLAs uncovered gains of chromosomes 1q (18/19, 95%), 10 (15/19, 79%), 12 (14/19, 74%), and 2 (10/19, 53%), as well as loss of chromosome 1p (7/19, 37%). Gains of chromosomes 1q, 10, and 12 were also identified in the majority of mesonephric adenocarcinomas of the uterine cervix (MAs) as well as subsets of endometrioid carcinomas (ECs) and low-grade serous carcinomas of the ovary (LGSCs) but only in a minority of serous carcinomas of the uterine corpus (USCs), clear cell carcinomas (CCCs), and tubo-ovarian high-grade serous carcinomas (HGSCs). While losses of chromosome 1p together with gains of chromosome 1q were also identified in both MA and LGSC, gains of chromosome 2 were almost exclusively identified in MLA and MA. Unsupervised hierarchical clustering and t-SNE analysis of DNA methylation data (Illumina EPIC array) identified a co-clustering for MLAs and MAs, which was distinct from clusters of ECs, USCs, CCCs, LGSCs, and HGSCs. Group-wise comparisons confirmed a close epigenetic relationship between MLA and MA. These findings, in conjunction with the established histological and immunophenotypical overlap, suggest bona fide mesonephric differentiation, and support a more precise terminology of mesonephric-type adenocarcinoma instead of MLA in these tumours. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Association of 3'UTR variations of EGFR and KRAS oncogenes with clinical parameters in lung cancer tumours.

BACGROUND INFORMATION: Lung cancer is one of the leading types of cancer deaths worldwide, with approximately 2 million people diagnosed with lung cancer each year. In this study, we aimed to determine the exonic and 3'UTR sequences of EGFR, PIK3CA and KRAS genes in 39 sporadic lung cancer tumors and to reveal the changes in the miRNA binding profile of tumors with somatic variation in the 3'UTR region and to examine the relationship of these changes with clinical parameters. RESULTS: A statistically significant correlation was found between the presence of miRNA that could not bind to the 3'UTR region due to variation in at least one of the EGFR or KRAS genes and the presence of metastasis in the tumor. At the same time, Kaplan-Meier analysis between those with and without alterations in the miRNA profile due to somatic variation in the 3'UTR region showed that survival was lower in those with miRNA alterations and this was statistically significant. CONCLUSIONS: In our study, it was shown that variations in the 3'UTR regions of EGFR and KRAS oncogenes may cause increased expression of these oncogenes by preventing the binding of miRNAs, and it was suggested that this may be related to metastasis, survival and drug resistance mechanism. SIGNIFICANCE: In this study, we show that hsa-miR-124-3p, hsa-miR-506-3p, hsa-miR-1290 and hsa-miR-6514-3p are particularly prominent in lung carcinoma in relation to these biological pathways and the roles that variations in the 3'UTR regions of oncogenes may play in the carcinogenesis process.

Structural Basis for the Versatile and Methylation-Dependent Binding of CTCF to DNA.

The multidomain CCCTC-binding factor (CTCF), containing a tandem array of 11 zinc fingers (ZFs), modulates the three-dimensional organization of chromatin. We crystallized the human CTCF DNA-binding domain in complex with a known CTCF-binding site. While ZF2 does not make sequence-specific contacts, each finger of ZF3-7 contacts three bases of the 15-bp consensus sequence. Each conserved nucleotide makes base-specific hydrogen bonds with a particular residue. Most of the variable base pairs within the core sequence also engage in interactions with the protein. These interactions compensate for deviations from the consensus sequence, allowing CTCF to adapt to sequence variations. CTCF is sensitive to cytosine methylation at position 2, but insensitive at position 12 of the 15-bp core sequence. These differences can be rationalized structurally. Although included in crystallizations, ZF10 and ZF11 are not visible, while ZF8 and ZF9 span the backbone of the DNA duplex, conferring no sequence specificity but adding to overall binding stability.

Evolutionary divergence of duplicated genomes in newly described allotetraploid cottons.

Allotetraploid cotton (Gossypium) species represents a model system for the study of plant polyploidy, molecular evolution, and domestication. Here, chromosome-scale genome sequences were obtained and assembled for two recently described wild species of tetraploid cotton, Gossypium ekmanianum [(AD)6, Ge] and Gossypium stephensii [(AD)7, Gs], and one early form of domesticated Gossypium hirsutum, race punctatum [(AD)1, Ghp]. Based on phylogenomic analysis, we provide a dated whole-genome level perspective for the evolution of the tetraploid Gossypium clade and resolved the evolutionary relationships of Gs, Ge, and domesticated G. hirsutum. We describe genomic structural variation that arose during Gossypium evolution and describe its correlates-including phenotypic differentiation, genetic isolation, and genetic convergence-that contributed to cotton biodiversity and cotton domestication. Presence/absence variation is prominent in causing cotton genomic structural variations. A presence/absence variation-derived gene encoding a phosphopeptide-binding protein is implicated in increasing fiber length during cotton domestication. The relatively unimproved Ghp offers the potential for gene discovery related to adaptation to environmental challenges. Expanded gene families enoyl-CoA δ isomerase 3 and RAP2-7 may have contributed to abiotic stress tolerance, possibly by targeting plant hormone-associated biochemical pathways. Our results generate a genomic context for a better understanding of cotton evolution and for agriculture.

Satellite magnetic data reveal interannual waves in Earth's core.

SignificanceThe physics responsible for most of the interannual geomagnetic field changes, continually recorded by satellites for 20 years, is a long-standing open issue. By analyzing magnetic data, we detect Magneto-Coriolis waves in the Earth's outer core that account for a significant part of this signal. We further propose theoretical advances in the physical characterization of these waves, enabling a deeper understanding of the dynamics behind the geomagnetic signal. It should allow one to better sketch the heterogeneous magnetic field deep within the core, shedding further light on the mechanisms that sustain the geodynamo. Our interpretation does not require the presence of a stratified layer at the top of the core, with potent consequences regarding the Earth's thermal history.