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Biological Reviews of the Cambridge... Dec 2021Dominance is a basic property of inheritance systems describing the link between a diploid genotype at a single locus and the resulting phenotype. Models for the... (Review)
Review
Dominance is a basic property of inheritance systems describing the link between a diploid genotype at a single locus and the resulting phenotype. Models for the evolution of dominance have long been framed as an opposition between the irreconcilable views of Fisher in 1928 supporting the role of largely elusive dominance modifiers and Wright in 1929, who viewed dominance as an emerging property of the structure of enzymatic pathways. Recent theoretical and empirical advances however suggest that these opposing views can be reconciled, notably using models investigating the regulation of gene expression and developmental processes. In this more comprehensive framework, phenotypic dominance emerges from departures from linearity between any levels of integration in the genotype-to-phenotype map. Here, we review how these different models illuminate the emergence and evolution of dominance. We then detail recent empirical studies shedding new light on the diversity of molecular and physiological mechanisms underlying dominance and its evolution. By reconciling population genetics and functional biology, we hope our review will facilitate cross-talk among research fields in the integrative study of dominance evolution.
Topics: Genes, Dominant; Genetics, Population; Genotype; Models, Genetic; Phenotype
PubMed: 34382317
DOI: 10.1111/brv.12786 -
BMC Bioinformatics May 2022Molecular gene signatures are useful tools to characterize the physiological state of cell populations, but most have developed under a narrow range of conditions and... (Meta-Analysis)
Meta-Analysis
Molecular gene signatures are useful tools to characterize the physiological state of cell populations, but most have developed under a narrow range of conditions and cell types and are often restricted to a set of gene identities. Focusing on the transcriptional response to hypoxia, we aimed to generate widely applicable classifiers sourced from the results of a meta-analysis of 69 differential expression datasets which included 425 individual RNA-seq experiments from 33 different human cell types exposed to different degrees of hypoxia (0.1-5%[Formula: see text]) for 2-48 h. The resulting decision trees include both gene identities and quantitative boundaries, allowing for easy classification of individual samples without control or normoxic reference. Each tree is composed of 3-5 genes mostly drawn from a small set of just 8 genes (EGLN1, MIR210HG, NDRG1, ANKRD37, TCAF2, PFKFB3, BHLHE40, and MAFF). In spite of their simplicity, these classifiers achieve over 95% accuracy in cross validation and over 80% accuracy when applied to additional challenging datasets. Our results indicate that the classifiers are able to identify hypoxic tumor samples from bulk RNAseq and hypoxic regions within tumor from spatially resolved transcriptomics datasets. Moreover, application of the classifiers to histological sections from normal tissues suggest the presence of a hypoxic gene expression pattern in the kidney cortex not observed in other normoxic organs. Finally, tree classifiers described herein outperform traditional hypoxic gene signatures when compared against a wide range of datasets. This work describes a set of hypoxic gene signatures, structured as simple decision tress, that identify hypoxic samples and regions with high accuracy and can be applied to a broad variety of gene expression datasets and formats.
Topics: Genes, Regulator; Humans; Hypoxia; Neoplasms; Transcriptome
PubMed: 35641902
DOI: 10.1186/s12859-022-04741-8 -
Nature Communications Mar 2024Myelinated axons form long-range connections that enable rapid communication between distant brain regions, but how genetics governs the strength and organization of...
Myelinated axons form long-range connections that enable rapid communication between distant brain regions, but how genetics governs the strength and organization of these connections remains unclear. We perform genome-wide association studies of 206 structural connectivity measures derived from diffusion magnetic resonance imaging tractography of 26,333 UK Biobank participants, each representing the density of myelinated connections within or between a pair of cortical networks, subcortical structures or cortical hemispheres. We identify 30 independent genome-wide significant variants after Bonferroni correction for the number of measures studied (126 variants at nominal genome-wide significance) implicating genes involved in myelination (SEMA3A), neurite elongation and guidance (NUAK1, STRN, DPYSL2, EPHA3, SEMA3A, HGF, SHTN1), neural cell proliferation and differentiation (GMNC, CELF4, HGF), neuronal migration (CCDC88C), cytoskeletal organization (CTTNBP2, MAPT, DAAM1, MYO16, PLEC), and brain metal transport (SLC39A8). These variants have four broad patterns of spatial association with structural connectivity: some have disproportionately strong associations with corticothalamic connectivity, interhemispheric connectivity, or both, while others are more spatially diffuse. Structural connectivity measures are highly polygenic, with a median of 9.1 percent of common variants estimated to have non-zero effects on each measure, and exhibited signatures of negative selection. Structural connectivity measures have significant genetic correlations with a variety of neuropsychiatric and cognitive traits, indicating that connectivity-altering variants tend to influence brain health and cognitive function. Heritability is enriched in regions with increased chromatin accessibility in adult oligodendrocytes (as well as microglia, inhibitory neurons and astrocytes) and multiple fetal cell types, suggesting that genetic control of structural connectivity is partially mediated by effects on myelination and early brain development. Our results indicate pervasive, pleiotropic, and spatially structured genetic control of white-matter structural connectivity via diverse neurodevelopmental pathways, and support the relevance of this genetic control to healthy brain function.
Topics: Adult; Humans; Connectome; Genome-Wide Association Study; Semaphorin-3A; Genes, Regulator; Brain; Protein Kinases; Repressor Proteins; Microfilament Proteins; Intracellular Signaling Peptides and Proteins
PubMed: 38438384
DOI: 10.1038/s41467-024-46023-2 -
Current Opinion in Structural Biology Dec 2022The spliceosome is a multi-megadalton RNA-protein complex responsible for the removal of non-coding introns from pre-mRNAs. Due to its complexity and dynamic nature, it... (Review)
Review
The spliceosome is a multi-megadalton RNA-protein complex responsible for the removal of non-coding introns from pre-mRNAs. Due to its complexity and dynamic nature, it has proven to be a very challenging target for structural studies. Developments in single particle cryo-EM have overcome these previous limitations and paved the way towards a structural characterisation of the splicing machinery. Despite tremendous progress, many aspects of spliceosome structure and function remain elusive. In particular, the events leading to the definition of exon-intron boundaries, alternative and non-canonical splicing events, and cross-talk with other cellular machineries. Efforts are being made to address these knowledge gaps and further our mechanistic understanding of the spliceosome. Here, we summarise recent progress in the structural and functional analysis of the spliceosome.
Topics: Spliceosomes; RNA Splicing; RNA Precursors; Introns; Exons
PubMed: 36116369
DOI: 10.1016/j.sbi.2022.102461 -
Genes Jan 2023The regulatory elements in proximal and distal regions of genes are involved in the regulation of gene expression. Risk alleles in intronic and intergenic regions may...
The regulatory elements in proximal and distal regions of genes are involved in the regulation of gene expression. Risk alleles in intronic and intergenic regions may alter gene expression by modifying the binding affinity and stability of diverse DNA-binding proteins implicated in gene expression regulation. By focusing on the local ancestral structure of coding and regulatory regions using the paired whole-genome sequence and tissue-wide transcriptome datasets from the Genotype-Tissue Expression project, we investigated the impact of genetic variants, in aggregate, on tissue-specific gene expression regulation. Local ancestral origins of the coding region, immediate and distant upstream regions, and distal regulatory region were determined using RFMix with the reference panel from the 1000 Genomes Project. For each tissue, inter-individual variation of gene expression levels explained by concordant or discordant local ancestry between coding and regulatory regions was estimated. Compared to European, African descent showed more frequent change in local ancestral structure, with shorter haplotype blocks. The expression level of the Adenosine Deaminase Like ( gene was significantly associated with admixed ancestral structure in the regulatory region across multiple tissue types. Further validations are required to understand the impact of the local ancestral structure of regulatory regions on gene expression regulation in humans and other species.
Topics: Humans; Alleles; Black People; Gene Expression Regulation; Haplotypes; White People
PubMed: 36672888
DOI: 10.3390/genes14010147 -
Nature Communications Jul 2023Variation in the antibody response has been linked to differential outcomes in disease, and suboptimal vaccine and therapeutic responsiveness, the determinants of which...
Variation in the antibody response has been linked to differential outcomes in disease, and suboptimal vaccine and therapeutic responsiveness, the determinants of which have not been fully elucidated. Countering models that presume antibodies are generated largely by stochastic processes, we demonstrate that polymorphisms within the immunoglobulin heavy chain locus (IGH) impact the naive and antigen-experienced antibody repertoire, indicating that genetics predisposes individuals to mount qualitatively and quantitatively different antibody responses. We pair recently developed long-read genomic sequencing methods with antibody repertoire profiling to comprehensively resolve IGH genetic variation, including novel structural variants, single nucleotide variants, and genes and alleles. We show that IGH germline variants determine the presence and frequency of antibody genes in the expressed repertoire, including those enriched in functional elements linked to V(D)J recombination, and overlapping disease-associated variants. These results illuminate the power of leveraging IGH genetics to better understand the regulation, function, and dynamics of the antibody response in disease.
Topics: Humans; Genes, Immunoglobulin Heavy Chain; Genes, Immunoglobulin; Alleles; Germ-Line Mutation; Immunoglobulin Heavy Chains
PubMed: 37479682
DOI: 10.1038/s41467-023-40070-x -
Nature Dec 2023The group II intron ribonucleoprotein is an archetypal splicing system with numerous mechanistic parallels to the spliceosome, including excision of lariat introns....
The group II intron ribonucleoprotein is an archetypal splicing system with numerous mechanistic parallels to the spliceosome, including excision of lariat introns. Despite the importance of branching in RNA metabolism, structural understanding of this process has remained elusive. Here we present a comprehensive analysis of three single-particle cryogenic electron microscopy structures captured along the splicing pathway. They reveal the network of molecular interactions that specifies the branchpoint adenosine and positions key functional groups to catalyse lariat formation and coordinate exon ligation. The structures also reveal conformational rearrangements of the branch helix and the mechanism of splice site exchange that facilitate the transition from branching to ligation. These findings shed light on the evolution of splicing and highlight the conservation of structural components, catalytic mechanism and dynamical strategies retained through time in premessenger RNA splicing machines.
Topics: Adenosine; Biocatalysis; Cryoelectron Microscopy; Exons; Introns; Nucleic Acid Conformation; RNA Precursors; RNA Splice Sites; RNA Splicing
PubMed: 37993708
DOI: 10.1038/s41586-023-06746-6 -
Journal of Hematology & Oncology May 2022Chromatin has distinct three-dimensional (3D) architectures important in key biological processes, such as cell cycle, replication, differentiation, and transcription... (Review)
Review
Chromatin has distinct three-dimensional (3D) architectures important in key biological processes, such as cell cycle, replication, differentiation, and transcription regulation. In turn, aberrant 3D structures play a vital role in developing abnormalities and diseases such as cancer. This review discusses key 3D chromatin structures (topologically associating domain, lamina-associated domain, and enhancer-promoter interactions) and corresponding structural protein elements mediating 3D chromatin interactions [CCCTC-binding factor, polycomb group protein, cohesin, and Brother of the Regulator of Imprinted Sites (BORIS) protein] with a highlight of their associations with cancer. We also summarise the recent development of technologies and bioinformatics approaches to study the 3D chromatin interactions in gene expression regulation, including crosslinking and proximity ligation methods in the bulk cell population (ChIA-PET and HiChIP) or single-molecule resolution (ChIA-drop), and methods other than proximity ligation, such as GAM, SPRITE, and super-resolution microscopy techniques.
Topics: Chromatin; DNA-Binding Proteins; Gene Expression Regulation; Humans; Neoplasms; Promoter Regions, Genetic
PubMed: 35509102
DOI: 10.1186/s13045-022-01271-x -
Trends in Biochemical Sciences Oct 2023Core promoters are sites where transcriptional regulatory inputs of a gene are integrated to direct the assembly of the preinitiation complex (PIC) and RNA polymerase II... (Review)
Review
Core promoters are sites where transcriptional regulatory inputs of a gene are integrated to direct the assembly of the preinitiation complex (PIC) and RNA polymerase II (Pol II) transcription output. Until now, core promoter functions have been investigated by distinct methods, including Pol II transcription initiation site mappings and structural characterization of PICs on distinct promoters. Here, we bring together these previously unconnected observations and hypothesize how, on metazoan TATA promoters, the precisely structured building up of transcription factor (TF) IID-based PICs results in sharp transcription start site (TSS) selection; or, in contrast, how the less strictly controlled positioning of the TATA-less promoter DNA relative to TFIID-core PIC components results in alternative broad TSS selections by Pol II.
Topics: Animals; Transcription Factor TFIID; Transcription, Genetic; TATA Box; Promoter Regions, Genetic; RNA Polymerase II
PubMed: 37574371
DOI: 10.1016/j.tibs.2023.07.009 -
Trends in Pharmacological Sciences Dec 2019Understanding why driver mutations that promote cancer are sometimes rare is important for precision medicine since it would help in their identification. Driver... (Review)
Review
Understanding why driver mutations that promote cancer are sometimes rare is important for precision medicine since it would help in their identification. Driver mutations are largely discovered through their frequencies. Thus, rare mutations often escape detection. Unlike high-frequency drivers, low-frequency drivers can be tissue specific; rare drivers have extremely low frequencies. Here, we discuss rare drivers and strategies to discover them. We suggest that allosteric driver mutations shift the protein ensemble from the inactive to the active state. Rare allosteric drivers are statistically rare since, to switch the protein functional state, they cooperate with additional mutations, and these are not considered in the patient cancer-specific protein sequence analysis. A complete landscape of mutations that drive cancer will reveal tumor-specific therapeutic vulnerabilities.
Topics: Genes, Tumor Suppressor; Humans; Models, Molecular; Mutation; Neoplasms; Oncogenes; Precision Medicine; Proteins
PubMed: 31699406
DOI: 10.1016/j.tips.2019.10.003