Lai, Y. Y. Y. | bioRxiv Science

bioRxiv2019

A high-resolution, chromosome-assigned Komodo dragon genome reveals adaptations in the cardiovascular, muscular, and chemosensory systems of monitor lizards

Monitor lizards are unique among ectothermic reptiles in that they have a high aerobic capacity and distinctive cardiovascular physiology which resembles that of endothermic mammals. We have sequenced the genome of the Komodo dragon (Varanus komodoensis), the largest extant monitor lizard, and present a high resolution de novo chromosome-assigned genome assembly for V. komodoensis, generated with a hybrid approach of long-range sequencing and single molecule physical mapping. Comparing the genome of V. komodoensis with those of related species showed evidence of positive selection in pathways related to muscle energy metabolism, cardiovascular homeostasis, and thrombosis. We also found species-specific expansions of a chemoreceptor gene family related to pheromone and kairomone sensing in V. komodoensis and several other lizard lineages. Together, these evolutionary signatures of adaptation reveal genetic underpinnings of the unique Komodo sensory, cardiovascular, and muscular systems, and suggest that selective pressure altered thrombosis genes to help Komodo dragons evade the anticoagulant effects of their own saliva. As the only sequenced monitor lizard genome, the Komodo dragon genome is an important resource for understanding the biology of this lineage and of reptiles worldwide.

genomics↗

bioRxiv2017

OMSV enables accurate and comprehensive identification of large structural variations from nanochannel-based single-molecule optical maps

Human genomes contain structural variations (SVs) that are associated with various phenotypic variations and diseases. SV detection by sequencing is incomplete due to limited read length. Nanochannel-based optical mapping (OM) allows direct observation of SVs up to hundreds of kilo-bases in size on individual DNA molecules, making it a promising alternative technology for identifying large SVs. SV detection from optical maps is non-trivial due to complex types of error present in OM data, and no existing methods can simultaneously handle all these complex errors and the wide spectrum of SV types. Here we present a novel method, OMSV, for accurate and comprehensive identification of SVs from optical maps. OMSV detects both homozygous and heterozygous SVs, SVs of various types and sizes, and SVs with and without creating/destroying restriction sites. In an extensive series of tests based on real and simulated data, OMSV achieved both high sensitivity and specificity, with clear performance gains over the latest existing method. Applying OMSV to a human cell line, we identified hundreds of SVs >2kbp, with 65% of them missed by sequencing-based callers. Independent experimental validations confirmed the high accuracy of these SVs. We also demonstrate how OMSV can incorporate sequencing data to determine precise SV break points and novel sequences in the SVs not contained in the reference. We provide OMSV as open-source software to facilitate systematic studies of large SVs.

bioinformatics↗