Asia harbors substantial cultural and linguistic diversity, but the geographic structure of genetic variation across the continent remains enigmatic. Here we report a large-scale survey of autosomal variation from a broad geographic sample of Asian human populations. Our results show that genetic ancestry is strongly correlated with linguistic affiliations as well as geography. Most populations show relatedness within ethnic/linguistic groups, despite prevalent gene flow among populations. More than 90% of East Asian (EA) haplotypes could be found in either Southeast Asian (SEA) or Central-South Asian (CSA) populations and show clinal structure with haplotype diversity decreasing from south to north. Furthermore, 50% of EA haplotypes were found in SEA only and 5% were found in CSA only, indicating that SEA was a major geographic source of EA populations.

Analyses of frequency profiles of markers on disease or drug-response related genes in diverse populations are important for the dissection of common diseases. We report the results of analyses of data on 405 SNPs from 75 such genes and a 5.2 Mb chromosome, 22 genomic region in 1871 individuals from diverse 55 endogamous Indian populations. These include 32 large (>10 million individuals) and 23 isolated populations, representing a large fraction of the people of India. We observe high levels of genetic divergence between groups of populations that cluster largely on the basis of ethnicity and language. Indian populations not only overlap with the diversity of HapMap populations, but also contain population groups that are genetically distinct. These data and results are useful for addressing stratification and study design issues in complex traits especially for heterogeneous populations.

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Purpose The field of supply chain management (SCM) evolves dramatically due to factors of globalization, innovation, sustainability, and technology. These changes raise challenges not only to higher education institutions, but also to students, employing organizations, and third parties like SCM-related professional bodies. To understand the challenge, the purpose of this paper is to examine the gap between demand and supply of SCM-related knowledge areas, answer-related design questions, and make recommendations to close the gaps. Design/methodology/approach To compare the demand and supply of SCM-related knowledge areas, demand data is collected from a professional career website and supply data is gathered from operations management (OM) and SCM course syllabi from AACSB-accredited business schools in the USA. Cluster analysis identifies how supply and demand are matched on the data collected. Findings First, gaps exist between SCM talent requirements from industry and the knowledge/skill training by US business schools. This paper identifies matching, under-supplying, and over-supplying knowledge areas. Under-supply in emerging areas such as SCM information technology and certain logistics management topics are found. Some traditional OM topics are over-supplied due to out-of-date industry applications and should be revised to reflect the field’s transition from an OM to SCM view. Last, this paper makes recommendations to different stakeholders in this matching supply with demand process. Originality/value This study contributes to the literature in two ways. First, it provides an up-to-date understanding on demand and supply of SCM talent in USA. Second, it provides insights and recommendations not only to educators on curriculum design, but also to potential candidates interested in SCM careers, to companies’ job recruiters, and to professional organizations (such as APICS and Council of Supply Chain Management Professionals) to reduce the gaps between demand and supply.

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