Browsing by Author "Chande, Aroon T."
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Item Genomic characterization and computational phenotyping of nitrogen-fixing bacteria isolated from Colombian sugarcane fields(2021-12) Medina Cordoba, Luz K; Chande, Aroon T.; Rishishwar, Lavanya; Mayer, Leonard W; Valderrama Aguirre, Lina C; Valderrama Aguirre, Augusto; Gaby, John Christian; Kostka, Joel E.; Jordan, I. KingPrevious studies have shown the sugarcane microbiome harbors diverse plant growth promoting microorganisms, including nitrogen-fixing bacteria (diazotrophs), which can serve as biofertilizers. The genomes of 22 diazotrophs from Colombian sugarcane fields were sequenced to investigate potential biofertilizers. A genome-enabled computational phenotyping approach was developed to prioritize sugarcane associated diazotrophs according to their potential as biofertilizers. This method selects isolates that have potential for nitrogen fixation and other plant growth promoting (PGP) phenotypes while showing low risk for virulence and antibiotic resistance. Intact nitrogenase (nif) genes and operons were found in 18 of the isolates. Isolates also encode phosphate solubilization and siderophore production operons, and other PGP genes. The majority of sugarcane isolates showed uniformly low predicted virulence and antibiotic resistance compared to clinical isolates. Six strains with the highest overall genotype scores were experimentally evaluated for nitrogen fixation, phosphate solubilization, and the production of siderophores, gibberellic acid, and indole acetic acid. Results from the biochemical assays were consistent and validated computational phenotype predictions. A genotypic and phenotypic threshold was observed that separated strains by their potential for PGP versus predicted pathogenicity. Our results indicate that computational phenotyping is a promising tool for the assessment of bacteria detected in agricultural ecosystemsItem The Impact of Ethnicity and Genetic Ancestry on Disease Prevalence and Risk in Colombia(2021) Chande, Aroon T.; Nagar, Shashwat Deepali; Rishishwar, Lavanya; Mariño Ramírez, Leonardo; Medina Rivas, Miguel A.; Valderrama Aguirre, Augusto E.; Jordan, I. King; Gallo, Juan EstebanCurrently, the vast majority of genomic research cohorts are made up of participants with European ancestry. Genomic medicine will only reach its full potential when genomic studies become more broadly representative of global populations. We are working to support the establishment of genomic medicine in developing countries in Latin America via studies of ethnically and ancestrally diverse Colombian populations. The goal of this study was to analyze the effect of ethnicity and genetic ancestry on observed disease prevalence and predicted disease risk in Colombia. Population distributions of Colombia’s three major ethnic groups – Mestizo, Afro-Colombian, and Indigenous – were compared to disease prevalence and socioeconomic indicators. Indigenous and Mestizo ethnicity show the highest correlations with disease prevalence, whereas the effect of Afro-Colombian ethnicity is substantially lower. Mestizo ethnicity is mostly negatively correlated with six high-impact health conditions and positively correlated with seven of eight common cancers; Indigenous ethnicity shows the opposite effect. Malaria prevalence in particular is strongly correlated with ethnicity. Disease prevalence co-varies across geographic regions, consistent with the regional distribution of ethnic groups. Ethnicity is also correlated with regional variation in human development, partially explaining the observed differences in disease prevalence. Patterns of genetic ancestry and admixture for a cohort of 624 individuals from Medellín were compared to disease risk inferred via polygenic risk scores (PRS). African genetic ancestry is most strongly correlated with predicted disease risk, whereas European and Native American ancestry show weaker effects. African ancestry is mostly positively correlated with disease risk, and European ancestry is mostly negatively correlated. The relationships between ethnicity and disease prevalence do not show an overall correspondence with the relationships between ancestry and disease risk. We discuss possible reasons for the divergent health effects of ethnicity and ancestry as well as the implication of our results for the development of precision medicine in Colombia.Item The phenotypic consequences of genetic divergence between admixed latin american populations: Antioquia and Chocó, Colombia(2021) Chande, Aroon T.; Rishishwar, Lavanya; Ban, Dongjo; Nagar, Shashwat D.; Conley, Andrew B.; Rowell, Jessica; Valderrama Aguirre, Augusto E.; Medina Rivas, Miguel A.; Jordan, I. KingGenome-wide association studies have uncovered thousands of genetic variants that are associated with a wide variety of human traits. b Knowledge of howtrait-associated variants are distributed within and between populations can provide insight into the genetic basis of a group-specific phenotypic differences, particularly for health-related traits. We analyzed the genetic divergence levels for 1) individual i trait-associated variants and 2) collections of variants that function together to encode polygenic traits, between two neighboring 1 populations in Colombia that have distinct demographic profiles: Antioquia (Mestizo)and Choco (Afro-Colombian). Genetic ancestry 9 analysis showed 62% European, 32% Native American, and 6% African ancestry for Antioquia compared with 76% African, 10% 5 European, and 14% Native American ancestry for Choco, consistent with demography and previous results. Ancestry differences can g confound cross-population comparison of polygenic risk scores (PRS); however, we did not find any systematic bias in PRS distributions 7 for the two populations studied here, and population-specific differences in PRS were, for the most part, small and symmetrically 1 distributed around zero. Both genetic differentiation at individual trait-associated single nucleotide polymorphisms and population- b specific PRS differences between Antioquia and Choco largely reflected anthropometric phenotypic differences that can be readily g observed between the populations along with reported disease prevalence differences. Cases where population-specific differences in $ genetic risk did not align with observed trait (disease) prevalence point to the importance of environmental contributions to phenotypic g variance, for both infectious and complex, common disease. The results reported here are distributed via a web-based platform for 3 searching trait-associated variants and PRS divergence levels at http://map.chocogen.com (last accessed August 12, 2020)