ABSTRACT
The harsh climate of Arabia has posed challenges in generating ancient DNA from the region, hindering the direct examination of ancient genomes for understanding the demographic processes that shaped Arabian populations. In this study, we report whole-genome sequence data obtained from four Tylos-period individuals from Bahrain. Their genetic ancestry can be modeled as a mixture of sources from ancient Anatolia, Levant, and Iran/Caucasus, with variation between individuals suggesting population heterogeneity in Bahrain before the onset of Islam. We identify the G6PD Mediterranean mutation associated with malaria resistance in three out of four ancient Bahraini samples and estimate that it rose in frequency in Eastern Arabia from 5 to 6 kya onward, around the time agriculture appeared in the region. Our study characterizes the genetic composition of ancient Arabians, shedding light on the population history of Bahrain and demonstrating the feasibility of studies of ancient DNA in the region.
Subject(s)
Arabs , DNA, Ancient , Genetics, Population , Genome, Human , Humans , Arabs/genetics , BahrainABSTRACT
microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms' role in ecology and human health.
Subject(s)
Metabolomics , Tandem Mass Spectrometry , Humans , Metabolomics/methods , Databases, FactualABSTRACT
MicrobeMASST, a taxonomically-informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbial-derived metabolites and relative producers, without a priori knowledge, will vastly enhance the understanding of microorganisms' role in ecology and human health.