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Feeding exclusively on blood, vampire bats represent the only obligate sanguivorous lineage among mammals. To uncover genomic changes associated with adaptations to this unique dietary specialization, we generated a new haplotype-resolved reference-quality genome of the common vampire bat (Desmodus rotundus) and screened 26 bat species for genes that were specifically lost in the vampire bat lineage. We discovered previously-unknown gene losses that relate to metabolic and physiological changes, such as reduced insulin secretion (FFAR1, SLC30A8), limited glycogen stores (PPP1R3E), and a distinct gastric physiology (CTSE). Other gene losses likely reflect the biased nutrient composition (ERN2, CTRL) and distinct pathogen diversity of blood (RNASE7). Interestingly, the loss of REP15 likely helped vampire bats to adapt to high dietary iron levels by enhancing iron excretion and the loss of the 24S-hydroxycholesterol metabolizing enzyme CYP39A1 could contribute to their exceptional cognitive abilities. Finally, losses of key cone phototransduction genes (PDE6H, PDE6C) suggest that these strictly-nocturnal bats completely lack cone-based vision. These findings enhance our understanding of vampire bat biology and the genomic underpinnings of adaptations to sanguivory.
Precise estimates of genome sizes are important parameters for both theoretical and practical biodiversity genomics. We present here a fast, easy-to-implement and precise method to estimate genome size from the number of bases sequenced and the mean sequence coverage. To estimate the latter, we take advantage of the fact that a precise estimation of the Poisson distribution parameter lambda is possible from truncated data, restricted to the part of the coverage distribution representing the true underlying distribution. With simulations we could show that reasonable genome size estimates can be gained even from low-coverage (10X), highly discontinuous genome drafts. Comparison of estimates from a wide range of taxa and sequencing strategies with flow-cytometry estimates of the same individuals showed a very good fit and suggested that both methods yield comparable, interchangeable results.