Abstract:The Siddis are a unique Indian tribe of African, South Asian, and European ancestry. While previous investigations have traced their ancestral origins to the Bantu populations from subSaharan Africa, the geographic localization of their ancestry has remained elusive. Here, we performed biogeographical analysis to delineate the ancestral origin of the Siddis employing an admixture based algorithm, Geographical Population Structure (GPS). We evaluated the Siddi genomes in reference to five African populations fr… Show more
“…1 was exclusively observed among the Siddis. Given that the Siddis are a unique Indian population of African ancestry [ 11 , 44 , 45 ] their genomic proximity to Yorubans is not unexpected. Fig.…”
Section: Resultsmentioning
confidence: 99%
“…Presently several biogeographical approaches using high-resolution next-generation sequencing data are available that are based on identity by distance, nevertheless the accurate geo-localization of populations has remained a challenge. GPS has been used successfully for determination of the biogeographical affinity of several worldwide populations [ 2 , 6 , 7 , 9 – 11 ]. This approach correlates the admixture proportions of the query populations with that of the reference groups known to have resided in a specific geographic location for a substantial period of time and infers the geographic coordinates (latitude and longitude) of the former based on the geographic information pertaining to the latter.…”
Section: Discussionmentioning
confidence: 99%
“…It relies on extrapolating the genomic similarity between the query and reference populations to infer the likely biogeographical affinity of the former using the geographic locations (latitude and longitude) corresponding to the latter as a reference. GPS has been effectively employed for reconstructing the population history of several populations worldwide [ 2 , 6 , 7 , 9 – 11 ]. However, so far its utility and robustness in accurately localizing highly admixed populations whose genetic structure has been modified by significant demographic, biological and social factors has remained largely unexplored.…”
BackgroundThe utilization of biological data to infer the geographic origins of human populations has been a long standing quest for biologists and anthropologists. Several biogeographical analysis tools have been developed to infer the geographical origins of human populations utilizing genetic data. However due to the inherent complexity of genetic information these approaches are prone to misinterpretations. The Geographic Population Structure (GPS) algorithm is an admixture based tool for biogeographical analyses and has been employed for the geo-localization of various populations worldwide. Here we sought to dissect its sensitivity and accuracy for localizing highly admixed groups. Given the complex history of population dispersal and gene flow in the Indian subcontinent, we have employed the GPS tool to localize five South Asian populations, Punjabi, Gujarati, Tamil, Telugu and Bengali from the 1000 Genomes project, some of whom were recent migrants to USA and UK, using populations from the Indian subcontinent available in Human Genome Diversity Panel (HGDP) and those previously described as reference.ResultsOur findings demonstrate reasonably high accuracy with regards to GPS assignment even for recent migrant populations sampled elsewhere, namely the Tamil, Telugu and Gujarati individuals, where 96%, 87% and 79% of the individuals, respectively, were positioned within 600 km of their native locations. While the absence of appropriate reference populations resulted in moderate-to-low levels of precision in positioning of Punjabi and Bengali genomes.ConclusionsOur findings reflect that the GPS approach is useful but likely overtly dependent on the relative proportions of admixture in the reference populations for determination of the biogeographical origins of test individuals. We conclude that further modifications are desired to make this approach more suitable for highly admixed individuals.Electronic supplementary materialThe online version of this article (doi: 10.1186/s12863-017-0579-2) contains supplementary material, which is available to authorized users.
“…1 was exclusively observed among the Siddis. Given that the Siddis are a unique Indian population of African ancestry [ 11 , 44 , 45 ] their genomic proximity to Yorubans is not unexpected. Fig.…”
Section: Resultsmentioning
confidence: 99%
“…Presently several biogeographical approaches using high-resolution next-generation sequencing data are available that are based on identity by distance, nevertheless the accurate geo-localization of populations has remained a challenge. GPS has been used successfully for determination of the biogeographical affinity of several worldwide populations [ 2 , 6 , 7 , 9 – 11 ]. This approach correlates the admixture proportions of the query populations with that of the reference groups known to have resided in a specific geographic location for a substantial period of time and infers the geographic coordinates (latitude and longitude) of the former based on the geographic information pertaining to the latter.…”
Section: Discussionmentioning
confidence: 99%
“…It relies on extrapolating the genomic similarity between the query and reference populations to infer the likely biogeographical affinity of the former using the geographic locations (latitude and longitude) corresponding to the latter as a reference. GPS has been effectively employed for reconstructing the population history of several populations worldwide [ 2 , 6 , 7 , 9 – 11 ]. However, so far its utility and robustness in accurately localizing highly admixed populations whose genetic structure has been modified by significant demographic, biological and social factors has remained largely unexplored.…”
BackgroundThe utilization of biological data to infer the geographic origins of human populations has been a long standing quest for biologists and anthropologists. Several biogeographical analysis tools have been developed to infer the geographical origins of human populations utilizing genetic data. However due to the inherent complexity of genetic information these approaches are prone to misinterpretations. The Geographic Population Structure (GPS) algorithm is an admixture based tool for biogeographical analyses and has been employed for the geo-localization of various populations worldwide. Here we sought to dissect its sensitivity and accuracy for localizing highly admixed groups. Given the complex history of population dispersal and gene flow in the Indian subcontinent, we have employed the GPS tool to localize five South Asian populations, Punjabi, Gujarati, Tamil, Telugu and Bengali from the 1000 Genomes project, some of whom were recent migrants to USA and UK, using populations from the Indian subcontinent available in Human Genome Diversity Panel (HGDP) and those previously described as reference.ResultsOur findings demonstrate reasonably high accuracy with regards to GPS assignment even for recent migrant populations sampled elsewhere, namely the Tamil, Telugu and Gujarati individuals, where 96%, 87% and 79% of the individuals, respectively, were positioned within 600 km of their native locations. While the absence of appropriate reference populations resulted in moderate-to-low levels of precision in positioning of Punjabi and Bengali genomes.ConclusionsOur findings reflect that the GPS approach is useful but likely overtly dependent on the relative proportions of admixture in the reference populations for determination of the biogeographical origins of test individuals. We conclude that further modifications are desired to make this approach more suitable for highly admixed individuals.Electronic supplementary materialThe online version of this article (doi: 10.1186/s12863-017-0579-2) contains supplementary material, which is available to authorized users.
“…In Karnataka they reside in North Karnataka region and adapted to local social and religious lifestyle. We under took this study to see the common non dermatophytes causing the superficial fungal infection in Siddi tribal community (4,5) .…”
Dermatophytes are the common etiological agent to cause superficial mycosis, however non-dermatophytes like yeast and non dermatophyte mould (NDM) are emerging as potential agent to cause superficial mycosis. In this study, we evaluated epidemiological, clinical and mycological characters of non-dermatophytes causing superficial infection in the Siddi tribal community. A total of 1004 samples were collected from 937 Siddi community patients with superficial infection. In that 158 samples shown culture positive, Candida species (32, 20.25%) was the predominant agent to cause superficial infection other than dermatophytes followed by Aspergillus species (12, 7.59%), Fusarium species (10, 6.32%) and cladosporium species (2, 1.26%). Further, Cladosporium species isolated from tineacapitis infection was subjected to PCR, sequencing of ITS region and identified as Cladosporium halotolerans. Therefore, this study also revealed non dermatophytic fungi are emerging as important cause of superficial infection.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
