South Asia possesses a significant amount of genetic diversity due to considerable intergroup differences in culture and language. There have been numerous reports on the genetic structure of Asian Indians, although these have mostly relied on genotyping microarrays or targeted sequencing of the mitochondria and Y chromosomes. Asian Indians in Singapore are primarily descendants of immigrants from Dravidian-language–speaking states in south India, and 38 individuals from the general population underwent deep whole-genome sequencing with a target coverage of 30X as part of the Singapore Sequencing Indian Project (SSIP). The genetic structure and diversity of these samples were compared against samples from the Singapore Sequencing Malay Project and populations in Phase 1 of the 1,000 Genomes Project (1 KGP). SSIP samples exhibited greater intra-population genetic diversity and possessed higher heterozygous-to-homozygous genotype ratio than other Asian populations. When compared against a panel of well-defined Asian Indians, the genetic makeup of the SSIP samples was closely related to South Indians. However, even though the SSIP samples clustered distinctly from the Europeans in the global population structure analysis with autosomal SNPs, eight samples were assigned to mitochondrial haplogroups that were predominantly present in Europeans and possessed higher European admixture than the remaining samples. An analysis of the relative relatedness between SSIP with two archaic hominins (Denisovan, Neanderthal) identified higher ancient admixture in East Asian populations than in SSIP. The data resource for these samples is publicly available and is expected to serve as a valuable complement to the South Asian samples in Phase 3 of 1 KGP.

The role of Pre- and Protohistoric anthropogenic land cover changes needs to be quantified i) to establish a baseline for comparison with current human impact on the environment and ii) to separate it from naturally occurring changes in our environment. Results are presented from the simple, adaptation-driven, spatially explicit Global Land Use and technological Evolution Simulator (GLUES) for pre-Bronze age demographic, technological and economic change. Using scaling parameters from the History Database of the Global Environment as well as GLUES-simulated population density and subsistence style, the land requirement for growing crops is estimated. The intrusion of cropland into potentially forested areas is translated into carbon loss due to deforestation with the dynamic global vegetation model VECODE. The land demand in important Prehistoric growth areas - converted from mostly forested areas - led to large-scale regional (country size) deforestation of up to 11% of the potential forest. In total, 29 Gt carbon were lost from global forests between 10 000 BC and 2000 BC and were replaced by crops; this value is consistent with other estimates of Prehistoric deforestation. The generation of realistic (agri-)cultural development trajectories at a regional resolution is a major strength of GLUES. Most of the pre-Bronze age deforestation is simulated in a broad farming belt from Central Europe via India to China. Regional carbon loss is, e.g., 5 Gt in Europe and the Mediterranean, 6 Gt on the Indian subcontinent, 18 Gt in East and Southeast Asia, or 2.3 Gt in subsaharan Africa. Global subsistence style and technological progress for the period 9500 BC to 2000 BC were hindcasted with the Global Land Use and technological Evolution Simulator (GLUES) for 685 land regions of the world. The intensification of subsistence is visible in the transition from hunting-gathering to agropastoral life style in many world regions. This transition is based on an increase of domesticated plant and animal resources and technological progress, and can sustain much higher population densities than the foraging life style.The advent of agriculture creates an areal demand for growing crops; where the crop area is occupied by forest in potential vegetation estimated with a dynamical global vegetation model (VECODE), the aboveground and belowground carbon pools are reallocated; the net release of carbon to the atmosphere is calculated.Initial values for each prognostic variable are identical at simulation start (9500 BC), but the background vegetation varies. Vegetation productivity in terms of net primary production (NPP) was derived from Climber-2 climate anomalies on the IIASA database for mean monthly precipitation and temperature and subsequent application of the Miami model.Data are presented as 50-year averages with time indicating the central year of each 50-year period (i.e. -2425 denotes the period 2450 BC - 2401 BC), and geographically on a half degree grid with latitude and longitude values denoting the central value within each grid cell.Model data are from sub-project GLUES (Global Land Use and Technological Evolution Simulations on New Paleoclimate data: Quantified impact of Holocene climate change on land use, regional agrarianisation and anthropogenic deforestation with feedback, see: hdl:10013/epic.35233.d001).

This dataset provides values for RETIREMENT AGE WOMEN reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This dataset provides values for CORONAVIRUS DEATHS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.