Cyanobacterial growth and cyanophycin production with urea and ammonium as nitrogen source

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Combining metagenomics, metatranscriptomics and viromics to explore novel microbial interactions: towards a systems-level understanding of human microbiome

AbstractThe advances in experimental methods and the development of high performance bioinformatic tools have substantially improved our understanding of microbial communities associated with human niches. Many studies have documented that changes in microbial abundance and composition of the human microbiome is associated with human health and diseased state. The majority of research on human microbiome is typically focused in the analysis of one level of biological information, i.e., metagenomics or metatranscriptomics. In this review, we describe some of the different experimental and bioinformatic strategies applied to analyze the 16S rRNA gene profiling and shotgun sequencing data of the human microbiome. We also discuss how some of the recent insights in the combination of metagenomics, metatranscriptomics and viromics can provide more detailed description on the interactions between microorganisms and viruses in oral and gut microbiomes. Recent studies on viromics have begun to gain importance due to the potential involvement of viruses in microbial dysbiosis. In addition, metatranscriptomic combined with metagenomic analysis have shown that a substantial fraction of microbial transcripts can be differentially regulated relative to their microbial genomic abundances. Thus, understanding the molecular interactions in the microbiome using the combination of metagenomics, metatranscriptomics and viromics is one of the main challenges towards a system level understanding of human microbiome

Dietary fat and carbohydrate modulate the effect of the ATP-binding cassette A1 (ABCA1) R230C variant on metabolic risk parameters in premenopausal women from the Genetics of Atherosclerotic Disease (GEA) Study

Table S1. Demographic characteristics of the population. Table S2. Comparison of biochemical parameters stratified by gender and menopausal status. Table 3. Correlation between metabolic parameters and dietary macronutrients according to ABCA1/R230C genotypes in premenopausal women. Table S4. Comparison of biochemical parameters stratified by ABCA1/R230C genotypes in the study population and premenopausal women. Table 5. Comparison of biochemical parameters stratified by ABCA1/R230C genotypes and carbohydrate percentage tertiles in premenopausal women. Table 6. Comparison of biochemical parameters stratified by ABCA1/R230C genotypes and fat percentage tertiles in premenopausal women. (DOCX 162 kb

Variation in dental morphology and inference of continental ancestry in admixed Latin Americans

Objectives: To investigate the variation in dental nonmetric traits and to evaluate the utility of this variation for inferring genetic ancestry proportions in a sample of admixed Latin Americans.; Materials and Methods: We characterized a sample from Colombia (N = 477) for 34 dental traits and obtained estimates of individual Native American, European, and African ancestry using genome‐wide SNP data. We tested for correlation between dental traits, genetic ancestry, age, and sex. We carried out a biodistance analysis between the Colombian sample and reference continental population samples using the mean measure of divergence statistic calculated from dental trait frequencies. We evaluated the inference of genetic ancestry from dental traits using a regression approach (with 10‐fold cross‐validation) as well as by testing the correlation between estimates of ancestry obtained from genetic and dental data.; Results: Latin Americans show intermediate dental trait frequencies when compared to Native Americans, Europeans, and Africans. Significant correlations were observed for several dental traits, genetic ancestry, age, and sex. The biodistance analysis displayed a closer relationship of Colombians to Europeans than to Native Americans and Africans. Mean ancestry estimates obtained from the dental data are similar to the genetic estimates (Native American: 32% vs. 28%, European: 59% vs. 63%, and African: 9% vs. 9%, respectively). However, dental features provided low predictive power for genetic ancestry of individuals in both approaches tested (R2 < 5% for all genetic ancestries across methods).; Discussion: The frequency of dental traits in Latin Americans reflects their admixed Native American, European and African ancestry and can provide reasonable average estimates of genetic ancestry. However, the accuracy of individual genetic ancestry estimates is relatively low, probably influenced by the continental differentiation of dental traits, their genetic architecture, and the distribution of genetic ancestry in the individuals examined.Facultad de Ciencias Naturales y Muse

Reconstructing Native American population history

The peopling of the Americas has been the subject of extensive genetic, archaeological and linguistic research; however, central questions remain unresolved. One contentious issue is whether the settlement occurred by means of a single migration or multiple streams of migration from Siberia. The pattern of dispersals within the Americas is also poorly understood. To address these questions at a higher resolution than was previously possible, we assembled data from 52 Native American and 17 Siberian groups genotyped at 364,470 single nucleotide polymorphisms. Here we show that Native Americans descend from at least three streams of Asian gene flow. Most descend entirely from a single ancestral population that we call First American. However, speakers of Eskimog-Aleut languages from the Arctic inherit almost half their ancestry from a second stream of Asian gene flow, and the Na-Dene-speaking Chipewyan from Canada inherit roughly one-tenth of their ancestry from a third stream. We show that the initial peopling followed a southward expansion facilitated by the coast, with sequential population splits and little gene flow after divergence, especially in South America. A major exception is in Chibchan speakers on both sides of the Panama isthmus, who have ancestry from both North and South America. © 2012 Macmillan Publishers Limited. All rights reserved.Fil: Reich, David. Harvard Medical School; Estados Unidos. Massachusetts Institute of Technology; Estados UnidosFil: Patterson, Nick. Massachusetts Institute of Technology; Estados UnidosFil: Campbell, Desmond. Colegio Universitario de Londres; Reino Unido. The University Of Hong Kong; Hong KongFil: Tandon, Arti. Harvard Medical School; Estados Unidos. Massachusetts Institute of Technology; Estados UnidosFil: Mazieres, Stéphane. Colegio Universitario de Londres; Reino UnidoFil: Ray, Nicolas. Universidad de Ginebra; SuizaFil: Parra, Maria V.. Colegio Universitario de Londres; Reino Unido. Universidad de Antioquia; ColombiaFil: Rojas, Winston. Colegio Universitario de Londres; Reino Unido. Universidad de Antioquia; ColombiaFil: Duque, Constanza. Universidad de Antioquia; Colombia. Colegio Universitario de Londres; Reino UnidoFil: Mesa, Natalia. Universidad de Antioquia; Colombia. Colegio Universitario de Londres; Reino UnidoFil: García, Luis F.. Universidad de Antioquia; ColombiaFil: Triana, Omar. Universidad de Antioquia; ColombiaFil: Blair, Silvia. Universidad de Antioquia; ColombiaFil: Maestre, Amanda. Universidad de Antioquia; ColombiaFil: Dib, Juan C.. Fundación Salud Para El Tró Pico; ColombiaFil: Bravi, Claudio Marcelo. Colegio Universitario de Londres; Reino Unido. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Multidisciplinario de Biología Celular. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Multidisciplinario de Biología Celular. Universidad Nacional de La Plata. Instituto Multidisciplinario de Biología Celular; ArgentinaFil: Bailliet, Graciela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Multidisciplinario de Biología Celular. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Multidisciplinario de Biología Celular. Universidad Nacional de La Plata. Instituto Multidisciplinario de Biología Celular; ArgentinaFil: Corach, Daniel. Universidad de Buenos Aires; ArgentinaFil: Hünemeier, Tábita. Colegio Universitario de Londres; Reino Unido. Universidade Federal do Rio Grande do Sul; BrasilFil: Bortolini, Maria Cátira. Universidade Federal do Rio Grande do Sul; BrasilFil: Salzano, Francisco M.. Universidade Federal do Rio Grande do Sul; BrasilFil: Petzl Erler, María Luiza. Universidade Federal do Paraná; BrasilFil: Acuña Alonzo, Victor. National Institute Of Anthropology And History; MéxicoFil: Aguilar Salinas, Carlos. Instituto Nacional de la Nutrición Salvador Zubiran; MéxicoFil: Canizales-Quinteros, Samuel. Universidad Nacional Autónoma de México; MéxicoFil: Tusié Luna, Teresa. Universidad Nacional Autónoma de México; MéxicoFil: Riba, Laura. Universidad Nacional Autónoma de México; MéxicoFil: Rodríguez Cruz, Maricela. Umae Hospital de Pediatría Centro Medico Nacional Siglo Xxi; MéxicoFil: Lopez Alarcón, Mardia. Umae Hospital de Pediatría Centro Medico Nacional Siglo Xxi; MéxicoFil: Coral Vazquez, Ramón. Instituto Politécnico Nacional; Méxic

Genome-wide association studies and CRISPR/Cas9-mediated gene editing identify regulatory variants influencing eyebrow thickness in humans

Hair plays an important role in primates and is clearly subject to adaptive selection. While humans have lost most facial hair, eyebrows are a notable exception. Eyebrow thickness is heritable and widely believed to be subject to sexual selection. Nevertheless, few genomic studies have explored its genetic basis. Here, we performed a genome-wide scan for eyebrow thickness in 2961 Han Chinese. We identified two new loci of genome-wide significance, at 3q26.33 near SOX2 (rs1345417: P = 6.51×10−10) and at 5q13.2 near FOXD1 (rs12651896: P = 1.73×10−8). We further replicated our findings in the Uyghurs, a population from China characterized by East Asian-European admixture (N = 721), the CANDELA cohort from five Latin American countries (N = 2301), and the Rotterdam Study cohort of Dutch Europeans (N = 4411). A meta-analysis combining the full GWAS results from the three cohorts of full or partial Asian descent (Han Chinese, Uyghur and Latin Americans, N = 5983) highlighted a third signal of genome-wide significance at 2q12.3 (rs1866188: P = 5.81×10−11) near EDAR. We performed fine-mapping and prioritized four variants for further experimental verification. CRISPR/Cas9-mediated gene editing provided evidence that rs1345417 and rs12651896 affect the transcriptional activity of the nearby SOX2 and FOXD1 genes, which are both involved in hair development. Finally, suitable statistical analyses revealed that none of the associated variants showed clear signals of selection in any of the populations tested. Contrary to popular speculation, we found no evidence that eyebrow thickness is subject to strong selective pressure

A genome-wide association scan implicates DCHS2, RUNX2, GLI3, PAX1 and EDAR in human facial variation

We report a genome-wide association scan for facial features in B6,000 Latin Americans. We evaluated 14 traits on an ordinal scale and found significant association (P valueso5 10 8) at single-nucleotide polymorphisms (SNPs) in four genomic regions for three nose-related traits: columella inclination (4q31), nose bridge breadth (6p21) and nose wing breadth (7p13 and 20p11). In a subsample of B3,000 individuals we obtained quantitative traits related to 9 of the ordinal phenotypes and, also, a measure of nasion position. Quantitative analyses confirmed the ordinal-based associations, identified SNPs in 2q12 associated to chin protrusion, and replicated the reported association of nasion position with SNPs in PAX3. Strongest association in 2q12, 4q31, 6p21 and 7p13 was observed for SNPs in the EDAR, DCHS2, RUNX2 and GLI3 genes, respectively. Associated SNPs in 20p11 extend to PAX1. Consistent with the effect of EDAR on chin protrusion, we documented alterations of mandible length in mice with modified Edar funtion

Native American ancestry significantly contributes to neuromyelitis optica susceptibility in the admixed Mexican population

Neuromyelitis Optica (NMO) is an autoimmune disease with a higher prevalence in non-European populations. Because the Mexican population resulted from the admixture between mainly Native American and European populations, we used genome-wide microarray, HLA high-resolution typing and AQP4 gene sequencing data to analyze genetic ancestry and to seek genetic variants conferring NMO susceptibility in admixed Mexican patients. A total of 164 Mexican NMO patients and 1,208 controls were included. On average, NMO patients had a higher proportion of Native American ancestry than controls (68.1% vs 58.6%; p = 5 × 10–6). GWAS identified a HLA region associated with NMO, led by rs9272219 (OR = 2.48, P = 8 × 10–10). Class II HLA alleles HLA-DQB1*03:01, -DRB1*08:02, -DRB1*16:02, -DRB1*14:06 and -DQB1*04:02 showed the most significant associations with NMO risk. Local ancestry estimates suggest that all the NMO-associated alleles within the HLA region are of Native American origin. No novel or missense variants in the AQP4 gene were found in Mexican patients with NMO or multiple sclerosis. To our knowledge, this is the first study supporting the notion that Native American ancestry significantly contributes to NMO susceptibility in an admixed population, and is consistent with differences in NMO epidemiology in Mexico and Latin America.Fil: Romero Hidalgo, Sandra. Instituto Nacional de Medicina Genómica; MéxicoFil: Flores Rivera, José. Instituto Nacional de Neurología y Neurocirugía; MéxicoFil: Rivas Alonso, Verónica. Instituto Nacional de Neurología y Neurocirugía; MéxicoFil: Barquera, Rodrigo. Max Planck Institute For The Science Of Human History; Alemania. Instituto Nacional de Antropología e Historia; MéxicoFil: Villarreal Molina, María Teresa. Instituto Nacional de Medicina Genómica; MéxicoFil: Antuna Puente, Bárbara. Instituto Nacional de Medicina Genómica; MéxicoFil: Macias Kauffer, Luis Rodrigo. Universidad Nacional Autónoma de México; MéxicoFil: Villalobos Comparán, Marisela. Instituto Nacional de Medicina Genómica; MéxicoFil: Ortiz Maldonado, Jair. Instituto Nacional de Neurología y Neurocirugía; MéxicoFil: Yu, Neng. American Red Cross; Estados UnidosFil: Lebedeva, Tatiana V.. American Red Cross; Estados UnidosFil: Alosco, Sharon M.. American Red Cross; Estados UnidosFil: García Rodríguez, Juan Daniel. Instituto Nacional de Medicina Genómica; MéxicoFil: González Torres, Carolina. Instituto Nacional de Medicina Genómica; MéxicoFil: Rosas Madrigal, Sandra. Instituto Nacional de Medicina Genómica; MéxicoFil: Ordoñez, Graciela. Neuroimmunología, Instituto Nacional de Neurología y Neurocirugía; MéxicoFil: Guerrero Camacho, Jorge Luis. Instituto Nacional de Neurología y Neurocirugía; MéxicoFil: Treviño Frenk, Irene. American British Cowdray Medical Center; México. Instituto Nacional de la Nutrición Salvador Zubiran; MéxicoFil: Escamilla Tilch, Monica. Instituto Nacional de la Nutrición Salvador Zubiran; MéxicoFil: García Lechuga, Maricela. Instituto Nacional de la Nutrición Salvador Zubiran; MéxicoFil: Tovar Méndez, Víctor Hugo. Instituto Nacional de la Nutrición Salvador Zubiran; MéxicoFil: Pacheco Ubaldo, Hanna. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; MéxicoFil: Acuña Alonzo, Victor. Instituto Nacional de Antropología E Historia. Escuela Nacional de Antropología E Historia; MéxicoFil: Bortolini, María Cátira. Universidade Federal do Rio Grande do Sul; BrasilFil: Gallo, Carla. Universidad Peruana Cayetano Heredia; PerúFil: Bedoya Berrío, Gabriel. Universidad de Antioquia; ColombiaFil: Rothhammer, Francisco. Universidad de Tarapacá; ChileFil: Gonzalez-Jose, Rolando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Instituto Patagónico de Ciencias Sociales y Humanas; ArgentinaFil: Ruiz Linares, Andrés. Colegio Universitario de Londres; Reino UnidoFil: Canizales Quinteros, Samuel. Universidad Nacional Autónoma de México; MéxicoFil: Yunis, Edmond. Dana Farber Cancer Institute; Estados UnidosFil: Granados, Julio. Instituto Nacional de la Nutrición Salvador Zubiran; MéxicoFil: Corona, Teresa. Instituto Nacional de Neurología y Neurocirugía; Méxic

Fully automatic landmarking of 2D photographs identifies novel genetic loci influencing facial features

We report a genome-wide association study for facial features in > 6,000 Latin Americans. We placed 106 landmarks on 2D frontal photographs using the cloud service platform Face++. After Procrustes superposition, genome-wide association testing was performed for 301 inter-landmark distances. We detected nominally significant association (P-value < 5×10− 8) for 42 genome regions. Of these, 9 regions have been previously reported in GWAS of facial features. In follow-up analyses, we replicated 26 of the 33 novel regions (in East Asians or Europeans). The replicated regions include 1q32.3, 3q21.1, 8p11.21, 10p11.1, and 22q12.1, all comprising strong candidate genes involved in craniofacial development. Furthermore, the 1q32.3 region shows evidence of introgression from archaic humans. These results provide novel biological insights into facial variation and establish that automatic landmarking of standard 2D photographs is a simple and informative approach for the genetic analysis of facial variation, suitable for the rapid analysis of large population samples.- Introduction - Results And Discussion -- Study sample and phenotyping -- Trait/covariate correlation and heritability -- Overview of GWAS results and integration with the literature -- Follow-up of genomic regions newly associated with facial features: Replication in two human cohorts -- Follow-up of genomic regions newly associated with facial features: effects in the mouse -- Genome annotations at associated loci - Conclusion - Methods -- Study subjects -- Genotype data -- Phenotyping -- Statistical genetic analysis -- Interaction of EDAR with other genes -- Expression analysis for significant SNPs -- Detection of archaic introgression near ATF3 and association with facial features -- Annotation of SNPs in FUMA -- Shape GWAS in outbred mic