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1.
Mol Biol Evol ; 34(12): 3154-3168, 2017 Dec 01.
Artículo en Inglés | MEDLINE | ID: mdl-29029226

RESUMEN

Human high-altitude (HA) adaptation or mal-adaptation is explored to understand the physiology, pathophysiology, and molecular mechanisms that underlie long-term exposure to hypoxia. Here, we report the results of an analysis of the largest whole-genome-sequencing of Chronic Mountain Sickness (CMS) and nonCMS individuals, identified candidate genes and functionally validated these candidates in a genetic model system (Drosophila). We used PreCIOSS algorithm that uses Haplotype Allele Frequency score to separate haplotypes carrying the favored allele from the noncarriers and accordingly, prioritize genes associated with the CMS or nonCMS phenotype. Haplotypes in eleven candidate regions, with SNPs mostly in nonexonic regions, were significantly different between CMS and nonCMS subjects. Closer examination of individual genes in these regions revealed the involvement of previously identified candidates (e.g., SENP1) and also unreported ones SGK3, COPS5, PRDM1, and IFT122 in CMS. Remarkably, in addition to genes like SENP1, SGK3, and COPS5 which are HIF-dependent, our study reveals for the first time HIF-independent gene PRDM1, indicating an involvement of wider, nonHIF pathways in HA adaptation. Finally, we observed that down-regulating orthologs of these genes in Drosophila significantly enhanced their hypoxia tolerance. Taken together, the PreCIOSS algorithm, applied on a large number of genomes, identifies the involvement of both new and previously reported genes in selection sweeps, highlighting the involvement of multiple hypoxia response systems. Since the overwhelming majority of SNPs are in nonexonic (and possibly regulatory) regions, we speculate that adaptation to HA necessitates greater genetic flexibility allowing for transcript variability in response to graded levels of hypoxia.


Asunto(s)
Aclimatación/genética , Mal de Altura/genética , Adaptación Fisiológica/genética , Adulto , Alelos , Altitud , Mal de Altura/metabolismo , Mal de Altura/fisiopatología , Animales , Enfermedad Crónica , Drosophila/genética , Evolución Molecular , Frecuencia de los Genes/genética , Haplotipos/genética , Humanos , Hipoxia/genética , Hipoxia/fisiopatología , Masculino , Perú , Polimorfismo de Nucleótido Simple/genética , Factor 1 de Unión al Dominio 1 de Regulación Positiva/genética , Factor 1 de Unión al Dominio 1 de Regulación Positiva/metabolismo , Secuenciación Completa del Genoma/métodos
2.
Am J Hum Genet ; 93(3): 452-62, 2013 Sep 05.
Artículo en Inglés | MEDLINE | ID: mdl-23954164

RESUMEN

The hypoxic conditions at high altitudes present a challenge for survival, causing pressure for adaptation. Interestingly, many high-altitude denizens (particularly in the Andes) are maladapted, with a condition known as chronic mountain sickness (CMS) or Monge disease. To decode the genetic basis of this disease, we sequenced and compared the whole genomes of 20 Andean subjects (10 with CMS and 10 without). We discovered 11 regions genome-wide with significant differences in haplotype frequencies consistent with selective sweeps. In these regions, two genes (an erythropoiesis regulator, SENP1, and an oncogene, ANP32D) had a higher transcriptional response to hypoxia in individuals with CMS relative to those without. We further found that downregulating the orthologs of these genes in flies dramatically enhanced survival rates under hypoxia, demonstrating that suppression of SENP1 and ANP32D plays an essential role in hypoxia tolerance. Our study provides an unbiased framework to identify and validate the genetic basis of adaptation to high altitudes and identifies potentially targetable mechanisms for CMS treatment.


Asunto(s)
Mal de Altura/genética , Genoma Humano/genética , Análisis de Secuencia de ADN , Adulto , Animales , Enfermedad Crónica , Regulación hacia Abajo/genética , Drosophila melanogaster/genética , Femenino , Estudios de Asociación Genética , Genética de Población , Genómica , Humanos , Hipoxia/genética , Masculino , Perú , Reproducibilidad de los Resultados , Análisis de Supervivencia
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