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Summary: The domestic Asian water buffalo (Bubalus bubalis) is found on all five continents, with a global population of some 202 million. The livelihoods of more people depend on this species than on any other domestic animal. The two distinct types (river and swamp) descended from different wild Asian water buffalo (Bubalus arnee) populations that diverged some 900 kyr BP and then evolved in separate geographical regions. After domestication in the western region of the Indian subcontinent (ca. 6300 years BP), the river buffalo spread west as far as Egypt, the Balkans and Italy. Conversely, after domestication in the China/Indochina border region ca. 3000–7000 years BP, swamp buffaloes dispersed through south‐east Asia and China as far as the Yangtze River valley. Molecular and morphological evidence indicates that swamp buffalo populations have strong geographic genetic differentiation and a lack of gene flow, but strong phenotypic uniformity. In contrast, river buffalo populations show a weaker phylogeographic structure, but higher phenotypic diversity (i.e. many breeds). The recent availability of a high‐quality reference genome and of a medium‐density marker panel for genotyping has triggered a number of genome‐wide investigations on diversity, evolutionary history, production traits and functional elements. The growing molecular knowledge combined with breeding programmes should pave the way to improvements in production, environmental adaptation and disease resistance in water buffalo populations worldwide. [ABSTRACT FROM AUTHOR]

The verification of the breed origin of animal products is relevant for food safety and authenticity. We assessed the suitability of AFLP molecular markers in the assignment of cattle individuals to their breed of origin. Three hundred and ninety-six animals belonging to 16 cattle breeds genotyped with 141 AFLP markers were used as reference data set. Assignment was performed with likelihood (aflpop) and Bayesian (structure) methods. The Bayesian approach was superior to the likelihood algorithm with respect to (i) the correct assignment of simulated individuals to their breed of origin (93% vs. 81% respectively), (ii) the correct assignment of 44 sampled Romagnola animals (91% vs. 45% respectively) and (iii) the correct classification of animals belonging to a breed that was not included within the reference dataset. Thus, AFLP profiling in combination with the Bayesian approach seems a useful tool for breed assignment. [ABSTRACT FROM AUTHOR]