12 research outputs found

    Different waves and directions of Neolithic migrations in the Armenian Highland

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    Background: The peopling of Europe and the nature of the Neolithic agricultural migration as a primary issue in the modern human colonization of the globe is still widely debated. At present, much uncertainty is associated with the reconstruction of the routes of migration for the first farmers from the Near East. In this context, hospitable climatic conditions and the key geographic position of the Armenian Highland suggest that it may have served as a conduit for several waves of expansion of the first agriculturalists from the Near East to Europe and the North Caucasus. Results: Here, we assess Y-chromosomal distribution in six geographically distinct populations of Armenians that roughly represent the extent of historical Armenia. Using the general haplogroup structure and the specific lineages representing putative genetic markers of the Neolithic Revolution, haplogroups R1b1a2, J2, and G, we identify distinct patterns of genetic affinity between the populations of the Armenian Highland and the neighboring ones north and west from this area. Conclusions: Based on the results obtained, we suggest a new insight on the different routes and waves of Neolithic expansion of the first farmers through the Armenian Highland. We detected at least two principle migratory directions: (1) westward alongside the coastline of the Mediterranean Sea and (2) northward to the North Caucasus. Electronic supplementary material The online version of this article (doi:10.1186/s13323-014-0015-6) contains supplementary material, which is available to authorized users

    Machine learned-based visualization of the diversity of grapevine genomes worldwide and in Armenia using SOMmelier

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    In the proposed study three major issues have been addressed: Firstly, the diversity of grapevine accessions worldwide and particularly in Armenia, a small country located in the largely volcanic Armenian Highlands, is incredibly rich in cultivated and especially wild grapes; secondly, the information hidden in their (whole) genomes, e.g., about the domestication history of grapevine over the last 11,000 years and phenotypic traits such as cultivar utilization and a putative resistance against powdery mildew, and, thirdly machine learning methods to extract and to visualize this information in an easy to percept way. We shortly describe the Self Origanizing Maps (SOM) portrayal method called “SOMmelier” (as the vine-genome “waiter”) and illustrate its power by applying it to whole genome data of hundreds of grapevine accessions. We also give a short outlook on possible future directions of machine learning in grapevine transcriptomics and ampelogaphy

    On the Easy Use of Scientific Computing Services for Large Scale Linear Algebra and Parallel Decision Making with the P-Grade Portal

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    International audienceScientific research is becoming increasingly dependent on the large-scale analysis of data using distributed computing infrastructures (Grid, cloud, GPU, etc.). Scientific computing (Petitet et al. 1999) aims at constructing mathematical models and numerical solution techniques for solving problems arising in science and engineering. In this paper, we describe the services of an integrated portal based on the P-Grade (Parallel Grid Run-time and Application Development Environment) portal (http://www.p-grade.hu) that enables the solution of large-scale linear systems of equations using direct solvers, makes easier the use of parallel block iterative algorithm and provides an interface for parallel decision making algorithms. The ultimate goal is to develop a single sign on integrated multi-service environment providing an easy access to different kind of mathematical calculations and algorithms to be performed on hybrid distributed computing infrastructures combining the benefits of large clusters, Grid or cloud, when needed

    Origin and spread of human mitochondrial DNA haplogroup U7

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    Human mitochondrial DNA haplogroup U is among the initial maternal founders in Southwest Asia and Europe and one that best indicates matrilineal genetic continuity between late Pleistocene hunter-gatherer groups and present-day populations of Europe. While most haplogroup U subclades are older than 30 thousand years, the comparatively recent coalescence time of the extant variation of haplogroup U7 (~16–19 thousand years ago) suggests that its current distribution is the consequence of more recent dispersal events, despite its wide geographical range across Europe, the Near East and South Asia. Here we report 267 new U7 mitogenomes that – analysed alongside 100 published ones – enable us to discern at least two distinct temporal phases of dispersal, both of which most likely emanated from the Near East. The earlier one began prior to the Holocene (~11.5 thousand years ago) towards South Asia, while the later dispersal took place more recently towards Mediterranean Europe during the Neolithic (~8 thousand years ago). These findings imply that the carriers of haplogroup U7 spread to South Asia and Europe before the suggested Bronze Age expansion of Indo-European languages from the Pontic-Caspian Steppe region

    Machine learned-based visualization of the diversity of grapevine genomes worldwide and in Armenia using SOMmelier

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    In the proposed study three major issues have been addressed: Firstly, the diversity of grapevine accessions worldwide and particularly in Armenia, a small country located in the largely volcanic Armenian Highlands, is incredibly rich in cultivated and especially wild grapes; secondly, the information hidden in their (whole) genomes, e.g., about the domestication history of grapevine over the last 11,000 years and phenotypic traits such as cultivar utilization and a putative resistance against powdery mildew, and, thirdly machine learning methods to extract and to visualize this information in an easy to percept way. We shortly describe the Self Origanizing Maps (SOM) portrayal method called “SOMmelier” (as the vine-genome “waiter”) and illustrate its power by applying it to whole genome data of hundreds of grapevine accessions. We also give a short outlook on possible future directions of machine learning in grapevine transcriptomics and ampelogaphy

    Prevalence of uncoupling protein one genetic polymorphisms and their relationship with cardiovascular and metabolic health.

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    Contribution of UCP1 single nucleotide polymorphisms (SNPs) to susceptibility for cardiometabolic pathologies (CMP) and their involvement in specific risk factors for these conditions varies across populations. We tested whether UCP1 SNPs A-3826G, A-1766G, Ala64Thr and A-112C are associated with common CMP and their risk factors across Armenia, Greece, Poland, Russia and United Kingdom. This case-control study included genotyping of these SNPs, from 2,283 Caucasians. Results were extended via systematic review and meta-analysis. In Armenia, GA genotype and A allele of Ala64Thr displayed ~2-fold higher risk for CMP compared to GG genotype and G allele, respectively (p0.05). Concluding, the studied SNPs could be associated with the most common CMP and their risk factors in some populations
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