An RNA gene expressed during cortical development evolved rapidly in humans

Pollard, Katherine S.; Salama, Sofie R.; Lambert, Nelle; Lambot, Marie-Alexandra; Coppens, Sandra; Pedersen, Jakob Skou; Katzman, Sol; King, Brian F.; Onodera, Courtney; Siepel, Adam; Kern, Andrew D.; Dehay, Colette; Igel, Haller; Ares, Manuel; Vanderhaeghen, Pierre; Haussler, David

doi:10.1038/nature05113

Cited by 880 publications

(791 citation statements)

References 43 publications

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“…Also indicated are the four CARs studied in the combinatorial analyses, evolutionarily ultraconserved (uc) sequence blocks 21 and a sequence region showing human accelerated evolution (HAR). 22 CAR, core associated region; LD, linkage disequilibrium; NPAS3, neuronal PAS domain 3; SNP, single-nucleotide polymorphism. For each region, the most significant individual haplotypes are shown for the combined case group as well as the bipolar disorder and schizophrenia groups separately.…”

Section: Resultsmentioning

confidence: 99%

Interacting haplotypes at the NPAS3 locus alter risk of schizophrenia and bipolar disorder

et al. 2008

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The neuronal PAS domain 3 (NPAS3) gene encodes a neuronal transcription factor that is implicated in psychiatric disorders by the identification of a human chromosomal translocation associated with schizophrenia and a mouse knockout model with behavioural and hippocampal neurogenesis defects. To determine its contribution to the risk of psychiatric illness in the general population, we genotyped 70 single-nucleotide polymorphisms across the NPAS3 gene in 368 individuals with bipolar disorder, 386 individuals with schizophrenia and 455 controls. Modestly significant single-marker and global and individual haplotypes were identified in four discrete regions of the gene. The presence of both risk and protective haplotypes at each of these four regions indicated locus and allelic heterogeneity within NPAS3 and suggested a model whereby interactions between variants across the gene might contribute to susceptibility to illness. This was supported by predicting the most likely haplotype for each individual at each associated region and then calculating an NPAS3-mediated 'net genetic load' value. This value differed significantly from controls for both bipolar disorder (P = 0.0000010) and schizophrenia (P = 0.0000012). Logistic regression analysis also confirmed the combinatorial action of the four associated regions on disease risk. In addition, sensitivity/specificity plots showed that the extremes of the genetic loading distribution possess the greatest predictive power-a feature suggesting multiplicative allele interaction. These data add to recent evidence that the combinatorial analysis of a number of relatively small effect size haplotypes may have significant power to predict an individual's risk of a complex genetic disorder such as psychiatric illness.

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Section: Resultsmentioning

confidence: 99%

Interacting haplotypes at the NPAS3 locus alter risk of schizophrenia and bipolar disorder

et al. 2008

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“…These are regions of the genome that are, in general, highly conserved (e.g., among mammals or vertebrates), suggesting that they are functionally important, but have nonetheless changed considerably during human evolution. One such region involves a particular RNA sequence, HAR1F, that is expressed specifically in a subclass of human cortical neurons (Pollard et al, 2006) and may play a role in specifying the six-layered structure of the neocortex. This gene illustrates another surprise of the genomic era: the importance of Bnoncoding^RNA in biology and development.…”

Section: The Long Time Scale: Comparative Genomicsmentioning

confidence: 99%

Empirical approaches to the study of language evolution

2017

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The study of language evolution, and human cognitive evolution more generally, has often been ridiculed as unscientific, but in fact it differs little from many other disciplines that investigate past events, such as geology or cosmology. Well-crafted models of language evolution make numerous testable hypotheses, and if the principles of strong inference (simultaneous testing of multiple plausible hypotheses) are adopted, there is an increasing amount of relevant data allowing empirical evaluation of such models. The articles in this special issue provide a concise overview of current models of language evolution, emphasizing the testable predictions that they make, along with overviews of the many sources of data available to test them (emphasizing comparative, neural, and genetic data). The key challenge facing the study of language evolution is not a lack of data, but rather a weak commitment to hypothesistesting approaches and strong inference, exacerbated by the broad and highly interdisciplinary nature of the relevant data. This introduction offers an overview of the field, and a summary of what needed to evolve to provide our species with language-ready brains. It then briefly discusses different contemporary models of language evolution, followed by an overview of different sources of data to test these models. I conclude with my own multistage model of how different components of language could have evolved.

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“…For example, the highly accelerated region 1A/B lncRNAs (HAR1A/B) are transcribed from a Human Accelerated Region, which refers to regions of the genome subject to positive selection since our divergence from the great apes. HAR1A is expressed in Cajal-Retzius cells of the developing human neocortex during gestational weeks 7-19 in a pattern similar to that of reelin, a key protein that is responsible for orchestrating forebrain development [23]. In contrast, other lncRNAs are evolutionarily conserved.…”

Section: Brain Developmentmentioning

confidence: 99%

Long Non-coding RNAs: Novel Targets for Nervous System Disease Diagnosis and Therapy

2013

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The human genome encodes tens of thousands of long non-coding RNAs (lncRNAs), a novel and important class of genes. Our knowledge of lncRNAs has grown exponentially since their discovery within the last decade. lncRNAs are expressed in a highly cell-and tissue-specific manner, and are particularly abundant within the nervous system. lncRNAs are subject to post-transcriptional processing and inter-and intra-cellular transport. lncRNAs act via a spectrum of molecular mechanisms leveraging their ability to engage in both sequence-specific and conformational interactions with diverse partners (DNA, RNA, and proteins). Because of their size, lncRNAs act in a modular fashion, bringing different macromolecules together within the three-dimensional context of the cell. lncRNAs thus coordinate the execution of transcriptional, post-transcriptional, and epigenetic processes and critical biological programs (growth and development, establishment of cell identity, and deployment of stress responses). Emerging data reveal that lncRNAs play vital roles in mediating the developmental complexity, cellular diversity, and activitydependent plasticity that are hallmarks of brain. Corresponding studies implicate these factors in brain aging and the pathophysiology of brain disorders, through evolving paradigms including the following: (i) genetic variation in lncRNA genes causes disease and influences susceptibility; (ii) epigenetic deregulation of lncRNAs genes is associated with disease; (iii) genomic context links lncRNA genes to disease genes and pathways; and (iv) lncRNAs are otherwise interconnected with known pathogenic mechanisms. Hence, Electronic supplementary material The online version of this article

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An RNA gene expressed during cortical development evolved rapidly in humans

Cited by 880 publications

References 43 publications

Interacting haplotypes at the NPAS3 locus alter risk of schizophrenia and bipolar disorder

Interacting haplotypes at the NPAS3 locus alter risk of schizophrenia and bipolar disorder

Empirical approaches to the study of language evolution

Long Non-coding RNAs: Novel Targets for Nervous System Disease Diagnosis and Therapy

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