Upward Sun River 1, an individual from a unique burial of the Denali tradition in Alaska (11500 calBP), is considered a type representative of Ancient Beringians who split from other First Americans 22000-18000 calBP in Beringia. Using a new admixture graph model-comparison approach resistant to overfitting, we show that Ancient Beringians do not form the deepest American lineage, but instead harbor ancestry from a lineage more closely related to northern North Americans than to southern North Americans. Ancient Beringians also harbor substantial admixture from a lineage that did not contribute to other Native Americans: Amur River Basin populations represented by a newly reported site in northeastern China. Relying on these results, we propose a new model for the genomic formation of First American ancestors in Asia.

The development of landscapes of the central part of the Middle-Volga region in the last 2500 years was a discontinuous process of the explosive growth of population and land utilization alternating with stages of depopulation and desolation. The periods of depopulation and transitions of cultures occurred at similar times to climate changes. Some cultures were associated with distinct climatic episodes, such as the association of the Dark Ages Cold Period with Hun, post Hun, Heraldic, and Khasarian times, and the Medival Warm Period with the time of Volga Bulgaria. A combination of archaeological and paleoecological analyses allowed us to reconstruct a sequence of landscape and land use changes in relation to the historical development of the region. The first millennium CE was a time of major changes in population, agricultural technologies, social structure, and settlement patterns in the forest-steppe zone. The MiddleVolga region underwent a transition from a non-populated, mainlyforested landscape of first centuries CE to a highly deforested agricultural landscape of the Volga Bulgarian state by the 11th century CE. Within several centuries, the landscape was transformed by shifting cultivation, wood and ore extraction, and the formation and expansion of pastures and road networks. The process of deforestation in the region was facilitated by the relatively warm climates of the Medieval Warm Period.

Although a broad range of methods exists for reconstructing population history from genome-wide single nucleotide polymorphism data, just a few methods gained popularity in archaeogenetics: principal component analysis (PCA); ADMIXTURE, an algorithm that models individuals as mixtures of multiple ancestral sources represented by actual or inferred populations; formal tests for admixture such as f3-statistics and D-statistics; and qpAdm, a tool for fitting two-component and more complex admixture models to groups or individuals. Despite their popularity in archaeogenetics, which is explained by modest computational requirements and ability to analyse data of various types and qualities, protocols relying on qpAdm that screen numerous alternative models of varying complexity and find "fitting" models (often considering both estimated admixture proportions and p-values as a composite criterion of model fit) remain untested on complex simulated population histories in the form of admixture graphs of random topology. We analysed genotype data extracted from such simulations and tested various types of high-throughput qpAdm protocols ("rotating" and "non-rotating", with or without temporal stratification of target groups and proxy ancestry sources, with or without a "model competition" step). We caution that these qpAdm protocols may be inappropriate for exploratory analyses in poorly studied regions/periods since their false discovery rates varied between 12% and 68% depending on the details of the protocol and on the amount and quality of simulated data (i.e., >12% of fitting two-way admixture models imply gene flows that were not simulated), although our study has a number of limitations. We demonstrate that for reducing false discovery rates of qpAdm protocols to nearly 0% it is advisable to use large SNP sets with low missing data rates, the rotating qpAdm protocol with a strictly enforced rule that target groups do not pre-date their proxy sources, and an unsupervised ADMIXTURE analysis as a way to verify feasible qpAdm models.

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Главный редактор член-корреспондент АН РТ, доктор исторических наук А.Г. Ситдиков Заместители главного редактора: член-корреспондент АН РТ, доктор исторических наук Ф.Ш. Хузин доктор исторических наук Ю.А. Зеленеев Ответственный секретарь-кандидат ветеринарных наук Г.Ш. Асылгараева Редакционный совет: Б.А. Байтанаев-академик НАН РК, доктор исторических наук (Алматы, Казахстан) (председатель), Р.С. Хакимов-вице-президент АН РТ (Казань, Россия), Х.А. Амирханов-член-корреспондент РАН, доктор исторических наук, профессор (Москва, Россия), И. Бальдауф-доктор наук, профессор (Берлин, Германия), С.Г. Бочаров-кандидат исторических наук (Казань, Россия), П. Георгиев-доктор наук, доцент (Шумен, Болгария), Е.П. Казаков-доктор исторических наук (Казань, Россия), Н.Н. Крадин-членкорреспондент РАН, доктор исторических наук, профессор (Владивосток, Россия), А. Тюрк-PhD (Будапешт, Венгрия), И. Фодор-доктор исторических наук, профессор (Будапешт, Венгрия), В.Л. Янин-академик РАН, доктор исторических наук профессор (Москва, Россия), В.С. Синика-кандидат исторических наук (Тирасполь, Молдова), Б.В. Базаров-академик РАН доктор исторических наук, профессор (Улан-Удэ, Бурятия), Д.С. Коробов-доктор исторических наук, профессор РАН (Москва, Россия), П. Дегри-профессор (Лёвен, Бельгия), Вэй Джан-Ph.D, профессор (Пекин, Китай). Редакционная коллегия: А.А. Выборнов-доктор исторических наук, профессор (Самара, Россия) М.Ш. Галимова-кандидат исторических наук (Казань, Россия) Р.Д. Голдина-доктор исторических наук, профессор (Ижевск, Россия) И.Л. Измайлов-доктор исторических наук (Казань, Россия) С.В. Кузьминых-кандидат исторических наук (Москва, Россия) А.Е. Леонтьев-доктор исторических наук (Москва, Россия) Т.Б. Никитина-доктор исторических наук (Йошкар-Ола, Россия) Ответственный за выпуск: М.Ш. Галимова-кандидат исторических наук