RESUMO
Tens of millions of images from biological collections have become available online over the last two decades. In parallel, there has been a dramatic increase in the capabilities of image analysis technologies, especially those involving machine learning and computer vision. While image analysis has become mainstream in consumer applications, it is still used only on an artisanal basis in the biological collections community, largely because the image corpora are dispersed. Yet, there is massive untapped potential for novel applications and research if images of collection objects could be made accessible in a single corpus. In this paper, we make the case for infrastructure that could support image analysis of collection objects. We show that such infrastructure is entirely feasible and well worth investing in.
RESUMO
The giant sable antelope is one of the most endangered African bovids. Populations of this iconic animal, the national symbol of Angola, were recently rediscovered, after many decades of presumed extinction. Even so, their numbers are scarce and hence conservation plans are essential. However, fundamental information such as its taxonomic position, time of divergence and degree of genetic variation are still lacking. Here, we used a museum preserved horn as a source of DNA to describe, for the first time, the complete mitochondrial genome of the giant sable antelope, and provide insights into its evolutionary history. Reads generated by shotgun sequencing were mapped against the mitochondrial genome of common sable antelope and the nuclear genomes of cow and sheep. Phylogenetic reconstruction and divergence time estimate give support to the monophyly of the giant sable and a maximum divergence time of 170 thousand years to the closest subspecies. About 7% of the nuclear genome was mapped against the reference. The genetic resources reported here are now available for future work in the field of conservation genetics and phylogeny, in this and related species.
