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At least 19 recordsLinked to original sources

PubMed2025

Sex differences in the developing human cortex intersect with genetic risk of neurodevelopmental disorders.

Autism is highly heritable and diagnosed more frequently in males than females. To identify neurodevelopmental processes that might present sex-biased vulnerability, we generated transcriptomic and epigenomic profiles of cell types present in the prenatally developing human cerebral cortex of 27 males and 21 females. By intersecting sex-biased molecular signatures and genes with de novo mutations in male and female autistic probands, we reveal two points of vulnerability contributing to the sex-biased penetrance in neurodevelopmental disorders (NDDs). First, we show that NDD risk genes are biased towards higher expression in females, identifying the NDD gene MEF2C as a critical transcription factor for female-biased expression. Second, we identify a significant contribution of X chromosome genes to NDD pathobiology. We construct a gene regulatory map of X-linked risk genes to enable functional studies of genetic variants that likely disrupt gene expression in the developing brains of autistic males. Together, these results point towards an outsized contribution of the X-chromosome to both the origin of sex differences in the developing human cortex and NDD vulnerability. We propose a model where female-biased vulnerability is driven by coding variation within genes while male-biased vulnerability is driven by noncoding variation in regulatory elements that affect gene expression.

Sex differences↗

PubMed2026

Multilevel Exploration of Shared Genetic Architecture Between Primary Biliary Cholangitis and Four Autoimmune Diseases.

INTRODUCTION: Primary Biliary Cholangitis (PBC) frequently coexists with various autoimmune diseases, such as Multiple Sclerosis (MS), Psoriasis (PS), Rheumatoid Arthritis (RA), and Sjögren's Syndrome (SS). Understanding the genetic associations between these diseases is crucial for providing deeper insights into their shared pathogenic mechanisms and comorbidity patterns. METHODS: This study utilized genome-wide association study summary data of PBC and four autoimmune diseases (MS, PS, RA, and SS). A multi-stage analytical pipeline was employed to systematically investigate the genetic associations between the diseases. The analytical approach consisted of three stages: first, linkage disequilibrium score regression and high-definition likelihood methods were applied to estimate overall genetic correlations between the diseases; second, local genetic correlation analysis was conducted to pinpoint genetic signals in specific chromosomal regions; third, conditional/conjunctional false discovery rate (cond/conjFDR) algorithms were used to quantitatively assess genetic overlap and identify shared susceptibility loci. RESULTS: Genome-wide analysis revealed significant genetic associations between PBC and the four autoimmune diseases (MS, PS, RA, and SS). Regional analysis showed local genetic correlations across various chromosomal segments. cond/conjFDR analysis confirmed genetic intersections among the diseases and identified several critical genetic polymorphic loci that influence disease susceptibility. DISCUSSION: This study comprehensively delineates the shared genetic architecture underlying PBC and four autoimmune diseases through integrative analyses of multiple genome-wide approaches. The results highlight strong genetic correlations, particularly between PBC and MS, PS, RA, and SS, and identify key shared susceptibility genes, including CLEC16A, CD58, CD86, STAT4, IRF5, TYK2, and TNFAIP3, which collectively mediate immune dysregulation through autophagy, cytokine signaling, and NF-κB pathways. These findings not only extend current understanding of the molecular mechanisms driving autoimmune comorbidity but also provide potential genetic targets for future functional validation and therapeutic exploration. CONCLUSION: This study provides comprehensive genomic evidence for the genetic connections between PBC and the four autoimmune diseases (MS, PS, RA, and SS), offering valuable insights into the shared pathological mechanisms underlying their comorbidities.

Humans↗

PubMed2026

Transient YAP activation uncovers the neurogenic potential of proliferative mammalian Müller glia.

The Hippo pathway effector YAP promotes spontaneous proliferation of Müller glia (MG), suggesting that bypassing Hippo signaling and activating YAP could enhance retinal regeneration. However, whether proliferative adult MGs retain meaningful neurogenic competence remains unclear. Here, using viral delivery of a Hippo-resistant YAP variant to wild-type adult MGs, we achieved transient YAP activation in adult MGs, inducing proliferation followed by cell-cycle withdrawal and differentiation. Intersectional genetic lineage tracing and EdU labeling, combined with transcriptomic analyses, revealed that YAP-activated MGs predominantly regenerate MGs, whereas only a subset gives rise to bipolar cell-like neurons. These results indicate that proliferative MGs acquire a state resembling that of late-stage retinal progenitors, with limited neurogenic lineage potential. We conclude that YAP-activated cell-cycle reentry inefficiently reprograms adult MGs toward photoreceptor or ganglion cell fates. These findings define the limited competence of proliferative adult MGs to contribute to neurogenic fates and provide a rigorous framework for assessing in vivo glial reprogramming strategies.

AAV↗

PubMed2024

Obesity: exploring its connection to brain function through genetic and genomic perspectives.

Obesity represents an escalating global health burden with profound medical and economic impacts. The conventional perspective on obesity revolves around its classification as a "pure" metabolic disorder, marked by an imbalance between calorie consumption and energy expenditure. Present knowledge, however, recognizes the intricate interaction of rare or frequent genetic factors that favor the development of obesity, together with the emergence of neurodevelopmental and mental abnormalities, phenotypes that are modulated by environmental factors such as lifestyle. Thirty years of human genetic research has unveiled >20 genes, causing severe early-onset monogenic obesity and ~1000 loci associated with common polygenic obesity, most of those expressed in the brain, depicting obesity as a neurological and mental condition. Therefore, obesity's association with brain function should be better recognized. In this context, this review seeks to broaden the current perspective by elucidating the genetic determinants that contribute to both obesity and neurodevelopmental and mental dysfunctions. We conduct a detailed examination of recent genetic findings, correlating them with clinical and behavioral phenotypes associated with obesity. This includes how polygenic obesity, influenced by a myriad of genetic variants, impacts brain regions associated with addiction and reward, differentiating it from monogenic forms. The continuum between non-syndromic and syndromic monogenic obesity, with evidence from neurodevelopmental and cognitive assessments, is also addressed. Current therapeutic approaches that target these genetic mechanisms, yielding improved clinical outcomes and cognitive advantages, are discussed. To sum up, this review corroborates the genetic underpinnings of obesity, affirming its classification as a neurological disorder that may have broader implications for neurodevelopmental and mental conditions. It highlights the promising intersection of genetics, genomics, and neurobiology as a foundation for developing tailored medical approaches to treat obesity and its related neurological aspects.

Humans↗

PubMed2026

Genetic diversity and molecular mechanisms in hypertrophic cardiomyopathy: toward personalized therapy.

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac muscle disorder, yet contemporary genomic and mechanistic research still lacks a cohesive model explaining how diverse genetic architectures give rise to heterogeneous phenotypes. This review synthesizes advances across sarcomeric and nonsarcomeric mutations, including intermediate-effect variants, polygenic modifiers, and ancestry-dependent sources of variant misclassification to elucidate how these factors govern disease penetrance and clinical expression. It critically evaluates how genetic diversity intersects with key molecular pathways, including sarcomeric hypercontractility, calcium dysregulation, mitochondrial energy deficiency, and transforming growth factor-β (TGF-β) and protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling, to drive hypertrophic and fibrotic remodeling. Emerging mechanism-based therapies, such as myosin inhibition, allele-specific silencing, clustered regularly interspaced short palindromic repeats (CRISPR)-based correction, and metabolic modulation, are examined with respect to their capacity to modify upstream molecular drivers rather than downstream hemodynamic consequences. Persistent challenges, including variants of uncertain significance classification, ancestry-biased databases, inequitable access to genetic testing, and unresolved safety concerns for gene-based therapies, are critically assessed as major barriers to precision-medicine integration. By linking genetic architecture, molecular pathogenesis, and targeted interventions, this review advances a contemporary, mechanistically grounded framework that informs both individualized management and future research directions. Future research should prioritize pathway-specific therapeutics, functional and mechanistic validation of emerging variants, deeper physiologic phenotyping to refine disease modeling, and accelerate translation throughout the continuum of HCM pathophysiology.

Humans↗

PubMed2026

ProMeta: a meta-learning framework for robust disease diagnosis and prediction from plasma proteomics.

MOTIVATION: The plasma proteome offers a dynamic window of human health, capturing the real-time intersections between genetics and physiology. However, the application of deep learning to proteomics is currently hindered by a reliance on large-scale labeled datasets, rendering standard models ineffective for rare or novel diseases where patient samples are inherently scarce. RESULTS: Here, we present ProMeta, a meta-learning framework designed to enable robust disease modeling under extreme data restrictions. By integrating knowledge-guided pathway encoding with bi-level meta-optimization, ProMeta projects unstructured proteomic profiles into biologically interpretable functional tokens. This architecture allows the model to learn a global initialization containing transferable biological priors from biobank-scale data, facilitating rapid adaptation to novel tasks. Through comprehensive benchmark experiments, ProMeta consistently outperformed transfer learning and traditional machine learning baselines in both disease diagnosis and prediction tasks. In the most challenging 4-shot scenarios (utilizing only 2 cases and 2 controls), the model achieved robust generalization with an average AUROC of ∼0.69, representing a 24.6% relative improvement over the best-performing baseline methods. Mechanistic investigation revealed that ProMeta disentangles cases from controls in the latent space prior to task-specific adaptation, confirming the acquisition of universal biological rules rather than rote memorization. Furthermore, gradient-based interpretation identified disease-specific protein biomarkers and functional pathways consistent with known pathophysiology. Collectively, ProMeta overcomes the data-scarcity bottleneck in precision medicine, providing a scalable, interpretable framework for characterizing the full spectrum of human diseases, particularly for rare conditions lacking extensive clinical cohorts. AVAILABILITY AND IMPLEMENTATION: The source code of ProMeta is available at GitHub (https://github.com/lihan97/ProMeta).

Proteomics↗

PubMed2026

Generation and validation of a Myh11Dre-Spp1Cre intersectional mouse model for lineage tracing of disease-associated smooth muscle cell states.

BACKGROUND: Phenotypic modulation of vascular smooth muscle cells (VSMCs) is a hallmark of vascular remodeling and cardiovascular disease. Recent lineage-tracing and single-cell transcriptomic studies have identified secreted phosphoprotein 1 (SPP1) as a prominent marker associated with disease-associated VSMC states, particularly those linked to fibrotic remodeling and vascular calcification. However, the cellular origins and fate of SPP1-associated VSMC populations remain incompletely understood. METHODS AND RESULTS: We generated a novel Spp1-rSTOPr-Cre (Spp1Cre) knock-in mouse line in which Cre recombinase is expressed from the endogenous Spp1 locus following Dre-mediated excision of a rox-flanked transcriptional STOP cassette. Correct targeting of the knock-in allele was validated by internal, 5' junction, 3' junction, and long-range PCR analyses, as well as Sanger sequencing. To establish an intersectional lineage-tracing strategy, Spp1Cre mice were crossed with Myh11DreERT2 and Rosa26-RSR-LSL-tdTomato-LSL-eGFP reporter mice, enabling permanent labeling of VSMC-derived populations following activation of the endogenous Spp1 locus. Under physiological conditions, eGFP-positive cells were detected at low frequency within the vascular wall and were predominantly negative for the contractile markers ACTA2 and MYH11. As a proof-of-principle application, eGFP-positive cells markedly expanded within atherosclerotic lesions induced by AAV-PCSK9D377Y and high-fat diet feeding. These lineage-traced cells remained largely ACTA2- and MYH11-negative, consistent with a modulated phenotype. Notably, only a minority of eGFP-positive cells expressed SPP1 or fibronectin at the time of analysis, demonstrating the utility of permanent lineage tracing for tracking cells with a history of endogenous Spp1 activation during vascular remodeling. CONCLUSION: We report the generation and validation of a novel Myh11Dre-Spp1Cre intersectional mouse model for lineage tracing of VSMC-derived populations that have activated the endogenous Spp1 locus. This genetic resource provides a valuable platform for investigating the origin, fate, and phenotypic evolution of Spp1-associated VSMC populations during vascular remodeling and cardiovascular disease.

Animals↗

PubMed2026

Identification of Candidate Genes Associated with Growth Traits in Procambarus clarkii Using Whole-Genome Resequencing.

Growth is a critical economic trait in all aquaculture industries. To address issues such as germplasm degradation, a comprehensive understanding of the growth and development mechanisms, along with genetic improvement strategies, for Procambarus clarkii (P. clarkii) is urgently required. In this study, we performed whole-genome resequencing on 89 individuals from five cultured stocks to investigate growth traits (body length) and identified a total of 46,919,297 high-quality single nucleotide polymorphisms (SNPs). Based on these SNPs, we conducted principal component analysis (PCA), phylogenetic analysis, and population genetic structure analysis. Furthermore, we performed selective sweep analysis (using FST, Pi, and XP-CLR) and a genome-wide association study (GWAS) to identify genetic variants associated with growth traits. The results revealed significant genetic differentiation among the five cultured stocks, with the Ma'anshan cultured stock exhibiting the fastest linkage disequilibrium (LD) decay. Additionally, long-term aquaculture in different geographical regions resulted in distinct genetic differences among cultured stocks. Through selective sweep analysis, the intersection of FST, Pi, and XP-CLR across the five populations yielded several growth-related candidate genes: Nephrin, Somatostatin, zinc finger protein 154, and yeti. Subsequent the GWAS identified two candidate genes associated with growth traits: Cullin-associated and neddylation-dissociated protein 1 (CAND1) and Baculoviral IAP repeat-containing protein 8 (BIRC8). These genes are presumed to play pivotal roles in the growth and development of P. clarkii. Overall, our findings provide new insights into the genetic mechanisms underlying growth and development in P. clarkii, and these identified genes serve as promising candidates for further functional studies and genetic improvement of this species.

Polymorphism, Single Nucleotide↗

PubMed2026

Beyond Earth: Recent Advancements in Microgravity Biomedical and Genetic Research in Saudi Arabia.

Microgravity research has emerged as a rapidly evolving field at the intersection of space medicine, genomics, biotechnology, and precision medicine. Exposure to the space environment induces complex physiological and molecular adaptations that affect multiple biological systems, including immune regulation, metabolism, musculoskeletal function, and gene expression. Recent advances in genomics, multi-omics technologies, artificial intelligence, and bioengineering have substantially improved our understanding of biological adaptation to spaceflight and expanded opportunities for translational biomedical research. This review summarizes recent advances in genetic and biomedical research under microgravity conditions, with particular emphasis on molecular mechanisms, omics technologies, genome editing, microbiome research, regenerative medicine, and personalized healthcare approaches. Major experimental platforms, landmark spaceflight studies, and translational applications in infectious diseases, cancer biology, aging, tissue engineering, and pharmaceutical development are discussed. The review also highlights Saudi Arabia's emerging contributions to genomic medicine and space biosciences through initiatives such as the Saudi Human Genome Program, the Saudi Pangenome Project, the Saudi Space Agency, and the BioGravity Initiative. Recent Saudi participation in human spaceflight and microgravity-associated biomedical research is discussed within the context of Vision 2030 and national investments in biotechnology and precision medicine. Collectively, advances in microgravity research are expected to contribute to the advancement of precision medicine and facilitate the development of innovative diagnostic and therapeutic strategies with significant implications for both human space exploration and terrestrial healthcare.

Humans↗

PubMed2026

Integrative multi-omics analyses suggest a candidate microbial metabolite-associated host gene network in ulcerative colitis.

Ulcerative colitis (UC) is associated with gut microbial dysbiosis, but the host molecular alterations potentially linked to microbially derived metabolites remain incompletely understood. We integrated Mendelian randomization (MR), microbial metabolite annotation, computational target prediction, colonic transcriptomics, network analysis, and machine learning. MiBioGen microbiome GWAS data were used as exposures and FinnGen Release 12 ULCERENTER as the outcome. Metabolites linked to MR-prioritized taxa were retrieved from GutMGene, and human targets were predicted using SwissTargetPrediction and SEA. UC-related genes were defined by integrating differential expression analysis and WGCNA and then intersected with predicted metabolite targets. MR prioritized one family and eight genera showing nominal genetically supported associations with UC, but none remained significant after Benjamini-Hochberg FDR correction. Three prioritized genera were linked to 15 microbe-metabolite records, corresponding to 13 unique metabolites; nine were retained for target prediction, yielding 277 unique predicted human targets. Transcriptomic analysis identified 1,530 DEGs and a 312-gene MEgrey60 module, with 273 overlapping genes, producing 1,569 unique UC-related genes. Their intersection with the 277 predicted targets yielded 47 candidate genes. Enrichment analyses highlighted mainly metabolic and lipid-related processes. Random Forest showed the highest mean AUC across the two independent external benchmarking cohorts, and SHAP prioritized EPHX1, HSD17B2, IGFBP5, and MMP10. IBDome analysis showed inflammation-associated expression differences in these genes. This study provides a genomics-informed, hypothesis-generating framework that prioritizes candidate microbe-metabolite-host relationships in UC for future experimental validation.

Humans↗

PubMed2025

MYC Regulates a DNA Repair Gene Expression Program in Small Cell Carcinoma of the Ovary, Hypercalcemic Type.

BACKGROUND/OBJECTIVES: SCCOHT is an aggressive and often fatal cancer that belongs to the ~20% of cancers defined by mutations to subunits of the SWI/SNF chromatin remodeling complex. In SCCOHT, mutations to the SMARCA4 gene, which encodes the SWI/SNF ATPase BRG1, are sufficient to impair SWI/SNF function. This single genetic lesion leads to a cascade of events that promote tumorigenesis, some of which may involve the intersection of SWI/SNF with oncogenic pathways such as those regulated by the MYC oncogene. In SCCOHT tumors and other cancers marked by SWI/SNF subunit mutation, MYC target genes are recurrently activated, pointing to a relationship between SWI/SNF and MYC that has yet to be fully explored. METHODS: In this study, we investigate the contribution of MYC to SCCOHT biology by performing a combination of chromatin binding and transcriptome assays in genetically engineered SCCOHT cell lines, with subsequent validation using patient tumor expression data. RESULTS: We find that MYC binds to thousands of active promoters in the BIN-67 SCCOHT cell line and that the depletion of MYC results in a broad range of gene expression changes with a notable effect on the expression of genes related to DNA repair. We uncover an MYC-regulated DNA repair gene expression program in BIN-67 cells that is antagonized by BRG1 reintroduction. Finally, we identify a DNA repair gene signature that is upregulated in SCCOHT tumors and in tumors defined by loss of the SWI/SNF subunit SNF5. CONCLUSIONS: Collectively, these data implicate MYC as a robust regulator of DNA repair gene expression in SCCOHT and lay a foundation for future studies focused on interrogating the relationship between BRG1 and MYC.

ATR↗

PubMed2026

A safety-centric perspective on innovation and risk in the use of artificial intelligence in genomics.

Adopting a safety-centric approach, this article explores how generative artificial intelligence (AI), and more specifically, foundation models for biological sequences, can exacerbate data quality issues, technical biases, and dual-use potential, particularly in critical applications such as clinical genetics, precision medicine, and pathogen engineering. This work centres on how misuse risks emerge throughout the innovation pipeline and how these intersect with the growing accessibility of generative genomic models. Particular attention is given to dual-use governance and infrastructure hardening in sequence analysis workflows. The work aims to provide scientists, regulators, and policymakers with a toolkit to discuss beneficial innovation in genomic AI while maintaining robust safeguards against harm and misuse.

Genomics↗

PubMed2026

Progress towards a biotypic biomarker profile for amyotrophic lateral sclerosis-frontotemporal spectrum disorders.

Determining the optimal timing of disease-modifying therapies for neurodegenerative disorders will necessitate identification of when the underlying pathobiological process becomes active, well in advance of the point at which clinical manifestions appear. Phenoconversion, the emergence of clinically manifest syndomes, may be preceded by years to decades of silent pathobiological activity that can only be mapped by an array of biomarkers. ALS and FTD, traditionally identified as distinct clinical syndromes, are increasingly recognized to exist along a spectrum of clinical syndromes with shared genetic risk and shared underlying pathology. This clinicopathological spectrum is underpinned by cytoplasmic aggregation of TAR DNA-binding protein 43 (TDP-43) as the common neuropathological hallmark. In contrast, the majority of neuropathologically-defined frontotemporal lobar degeneration (FTLD) is associated with alterations in either TDP-43 metabolism (FTLD-TDP) or of the microtubule associated protein tau (FTLD-tau), with a smaller percentage associated with either autosomal dominant genetic mutations or impairments in the ubiquitin proteasome system. As the field of neurodegenerative disorders increasingly shifts towards the frameworks of a pathobiological definition of disease, there is a growing imperative to develop biomarkers that reflect the varied pathobiologies that underly these disorders, and to determine the sensitivity of such biomarkers to detect the presence of these pathobiologies before phenoconversion. To that end, an international workshop was convened in London, Canada in 2025 to review the evidence for existing or evolving biomarkers suitable for (1) the detection of either ALS or FTD pathobiology prior to phenoconversion and/or (2) predict phenoconversion in at risk individuals. Such biomarkers might be conceptualized as "biotypic biomarkers", capturing their ability to describe an underlying pathophysiology whilst being agnostic to the emergent clinical manifestations. Whereas no single biotypic marker is yet able to predict the emergence of ALS, FTD or their intersection, a multimodal approach to developing a biotypic biomarker profile holds promise for the detection of relevant pathobiological processes. The strength of such an approach would be augmented by also addressing issues of resiliency/susceptibility both in terms of genetic risk susceptibility profiles and developing sensitive biomarkers of genomic and cellular aging. By including such nontraditional markers of disease, a more robust picture of not only the degenerative process but also of those factors that might potentially mitigate or drive a heightened probability of disease can be derived.

cryptic exons↗

PubMed2025

Sex as a modifier of genetic risk for type 1 diabetes.

Sex differences influence the pathogenesis of type 1 diabetes (T1D), yet most genetic studies have treated sex as a control covariate rather than a dynamic effect modifier. Sex influences immune cell behaviour, including CD4+ and CD8+ T cell activation, regulatory T cell stability, B cell autoantibody production, dendritic cell priming and monocyte/macrophage inflammation. Underlying mechanisms include hormone-responsive enhancers, X-escape gene dosage and sex-biassed chromatin states, intersecting with T1D-associated variants to produce sex-specific immune phenotypes. These insights help explain regional variation in sex ratios of T1D incidence, such as male predominance in high-risk populations and female excess in low-risk populations. Biological sex shapes T1D risk across multiple layers, including polygenic load; environmental exposures such as vitamin D deficiency and enteroviral infection; and sex-specific hormonal, chromosomal and epigenetic influences. An integrative G × E × S (genetic × environmental × sex-specific) liability-threshold framework is thus supported. Clinical and translational implications include developing sex-specific polygenic risk scores, biomarker panels and interventional strategies targeting pathways such as hormone signalling, vitamin D metabolism and the microbiome. Future multi-omic, longitudinal studies are warranted to test genotype-sex interactions, integrate sex as a core effect modifier and enable precision prevention and treatment of T1D in both males and females.

Humans↗

PubMed2024

Molecular mechanisms of the specialization of human synapses in the neocortex.

Synapses of the neocortex specialized during human evolution to develop over extended timescales, process vast amounts of information and increase connectivity, which is thought to underlie our advanced social and cognitive abilities. These features reflect species-specific regulations of neuron and synapse cell biology. However, despite growing understanding of the human genome and the brain transcriptome at the single-cell level, linking human-specific genetic changes to the specialization of human synapses has remained experimentally challenging. In this review, we describe recent progress in characterizing divergent morphofunctional and developmental properties of human synapses, and we discuss new insights into the underlying molecular mechanisms. We also highlight intersections between evolutionary innovations and disorder-related dysfunctions at the synapse.

Humans↗

PubMed2026

Adaptive evolution of polyploid crops.

Crop evolution represents a fundamental biological process through which plants respond to selection in different environments. This encompasses mechanisms operating at multiple scales of biological organization, including genetic and epigenetic regulation and higher-order interactions among molecular complexes. This Review synthesizes how polyploidy shapes crop evolution by generating duplicated genes, driving genome reorganization, altering dosage relationships and promoting regulatory divergence, which together influence crop metabolism, physiology, development and environmental responses. We focus mainly on the mechanisms underlying adaptation in polyploid crops, including the consequences of gene and genome duplication, genome reorganization and subfunctionalization. We also examine how hybridization, phenotypic plasticity and crop-microbiome interactions intersect with polyploidy to expand or constrain adaptive potential. Together, these processes affect crop survival, fitness and breeding value under changing environments. We suggest that future research connect polyploid genome architecture with experimentally validated signatures of selection and field performance to make better use of polyploidy-derived variation in crop improvement.

Polyploidy↗

PubMed2026

Cooperative care influences genome-wide levels of DNA methylation in nestling chestnut-crowned babblers.

Carers in cooperatively breeding vertebrates increase food acquisition for offspring; however, they also impact the developmental social environment. One means of linking early-life environments, such as nutrition and social structure, with later-life phenotypes is DNA methylation. Here, using whole-genome methylation sequencing, we measured how additional carers influence DNA methylation in nestlings of the cooperatively breeding chestnut-crowned babbler (Pomatostomus ruficeps). A comparison of nestlings raised by their parents (two carers) and those raised by parents plus additional helpers ('three plus' carers; mean = 4.3 ± 1.4 s.d.) revealed that additional care is associated with genome-wide differences in DNA methylation. Overall, 570 cytosine-phosphate-guanine sites from the regulatory regions of 487 genes were differentially methylated, with 85% being more methylated in nestlings reared by groups. Specifially, sites associated with genes that are integral for metabolism, growth, the regulation and promotion of sociality, the ability to cope with stressors, and cell communication were differentially methylated between the groups. Furthermore, gene ontology-term analysis revealed that differentially methylated sites were over-represented in multiple pathways, including those important for protein binding, metabolism and cell-to-cell and environment-to-cell communication. Our results suggest that the effects of being reared by groups as opposed to pairs in cooperative breeders can extend beyond those typically attributed to nutritional benefits and that these effects are molecularly mediated. This article is part of the theme issue 'Ecological epigenetics at the intersection of behaviour and life history variation in non-model animals'.

Animals↗

PubMed2024

Genome-wide copy number variation association study in anorexia nervosa.

This study represents the first large-scale investigation of rare (<1% population frequency) copy number variants (CNVs) in anorexia nervosa (AN). Large, rare CNVs are reported to be causally associated with anthropometric traits, neurodevelopmental disorders, and schizophrenia, yet their role in the genetic basis of AN is unclear. Using genome-wide association study (GWAS) array data from the Anorexia Nervosa Genetics Initiative (ANGI), which included 7414 AN case and 5044 controls, we investigated the association of 67 well-established syndromic CNVs and 178 pleiotropic disease-risk dosage-sensitive CNVs with AN. To identify novel CNV regions (CNVRs) that increase the risk of AN, we conducted genome-wide association studies with a focus on rare CNV-breakpoints (CNV-GWAS). We found no net enrichment of rare CNVs, either deletions or duplications, in AN, and none of the well-established syndromic or pleiotropic CNVs had a significant association with AN status. However, the CNV-GWAS found 21 nominally associated CNVRs that contribute to AN risk, covering protein-coding genes implicated in synaptic function, metabolic/mitochondrial factors, and lipid characteristics, like the CD36 (7q21.11) gene, which transports long-chain fatty acids into cells. CNVRs intersecting genes previously related to neurodevelopmental traits include deletions of NRXN1 intron 5 (2p16.3), IMMP2L (7q31.1), and PTPRD (9p23). Overall, given that our study is well powered to detect the CNV burden level reported for schizophrenia, we can conclude that rare CNVs have a limited role in the etiology of AN, as reported for bipolar disorder. Our nominal associations for the 21 discovered CNVRs are consistent with AN being a metabo-psychiatric trait, as demonstrated by the common genetic architecture of AN, and we provide association results to allow for replication in future research.

Humans↗