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Sequencing high molecular weight (HMW) DNA with long-read and linked-read technologies has promoted a major increase in more complete genome sequences for nonmodel organisms. Sequencing approaches that rely on HMW DNA have been limited to larger organisms or pools of multiple individuals, but recent advances have allowed for sequencing from individuals of small-bodied organisms. Here, we use HMW DNA sequencing with PacBio long reads and TELL-Seq linked reads to assemble and annotate the genome from a single individual feather louse (Brueelia nebulosa) from a European Starling (Sturnus vulgaris). We assembled a genome with a relatively high scaffold N50 (637 kb) and with BUSCO scores (96.1%) comparable to louse genomes assembled from pooled individuals. We annotated a number of genes (10,938) similar to the human louse (Pediculus humanus) genome. Additionally, calling phased variants revealed that the Brueelia genome is more heterozygous (∼1%) then expected for a highly obligate and dispersal-limited parasite. We also assembled and annotated the mitochondrial genome and primary endosymbiont (Sodalis) genome from the individual louse, which showed evidence for heteroplasmy in the mitogenome and a reduced genome size in the endosymbiont compared to its free-living relative. Our study is a valuable demonstration of the capability to obtain high-quality genomes from individual small, nonmodel organisms. Applying this approach to other organisms could greatly increase our understanding of the diversity and evolution of individual genomes.

Divergence time estimation from multilocus genetic data has become common in population genetics and phylogenetics. We present a new Bayesian inference method that treats the divergence time as a random variable. The divergence time is calculated from an assembly of splitting events on individual lineages in a genealogy. The time for such a splitting event is drawn from a hazard function of the truncated normal distribution. This allows easy integration into the standard coalescence framework used in programs such as Migrate. We explore the accuracy of the new inference method with simulated population splittings over a wide range of divergence time values and with a reanalysis of a dataset of 5 populations consisting of 3 present-day populations (Africans, Europeans, Asian) and 2 archaic samples (Altai and Ust’Isthim). Evaluations of simple divergence models without subsequent geneflow show high accuracy, whereas the accuracy of the results of isolation with migration models depends on the magnitude of the immigration rate. High immigration rates lead to a time of the most recent common ancestor of the sample that, looking backward in time, predates the divergence time. Even with many independent loci, accurate estimation of the divergence time with high immigration rates becomes problematic. Our comparison to other software tools reveals that our lineage-switching method, implemented in Migrate, is comparable to IMa2p. The software Migrate can run large numbers of sequence loci (>1,000) on computer clusters in parallel.