Mycobacterium tuberculosis strains of the Beijing lineage are globally distributed and are associated with the massive spread of multidrug-resistant (MDR) tuberculosis in Eurasia. Here we reconstructed the biogeographical structure and evolutionary history of this lineage by genetic analysis of 4,987 isolates from 99 countries and whole-genome sequencing of 110 representative isolates. We show that this lineage initially originated in the Far East, from where it radiated worldwide in several waves. We detected successive increases in population size for this pathogen over the last 200 years, practically coinciding with the Industrial Revolution, the First World War and HIV epidemics. Two MDR clones of this lineage started to spread throughout central Asia and Russia concomitantly with the collapse of the public health system in the former Soviet Union. Mutations identified in genes putatively under positive selection and associated with virulence might have favored the expansion of the most successful branches of the lineage.

To characterize natural selection, various analytical methods for detecting candidate genomic regions have been developed. We propose to perform genome-wide scans of natural selection using principal component analysis (PCA). We show that the common FST index of genetic differentiation between populations can be viewed as the proportion of variance explained by the principal components. Considering the correlations between genetic variants and each principal component provides a conceptual framework to detect genetic variants involved in local adaptation without any prior definition of populations. To validate the PCA-based approach, we consider the 1000 Genomes data (phase 1) considering 850 individuals coming from Africa, Asia, and Europe. The number of genetic variants is of the order of 36 millions obtained with a low-coverage sequencing depth (3×). The correlations between genetic variation and each principal component provide well-known targets for positive selection (EDAR, SLC24A5, SLC45A2, DARC), and also new candidate genes (APPBPP2, TP1A1, RTTN, KCNMA, MYO5C) and noncoding RNAs. In addition to identifying genes involved in biological adaptation, we identify two biological pathways involved in polygenic adaptation that are related to the innate immune system (beta defensins) and to lipid metabolism (fatty acid omega oxidation). An additional analysis of European data shows that a genome scan based on PCA retrieves classical examples of local adaptation even when there are no well-defined populations. PCA-based statistics, implemented in the PCAdapt R package and the PCAdapt fast open-source software, retrieve well-known signals of human adaptation, which is encouraging for future whole-genome sequencing project, especially when defining populations is difficult.