Serra, L. | bioRxiv Science

bioRxiv2019

Hybrid assembly of the genome of the entomopathogenic nematode Steinernema carpocapsae identifies the X-chromosome

Entomopathogenic nematodes from the genus Steinernema are lethal insect parasites that quickly kill their insect hosts with the help of their symbiotic bacteria. Steinernema carpocapsae is one of the most studied entomopathogens due to its broad lethality to diverse insect species and its effective commercial use as a biological control agent for insect pests, as well as a genetic model for studying parasitism, pathogenesis, and symbiosis. In this study, we used long-reads from the Pacific Biosciences platform and BioNano Genomics Irys system to assemble the best genome of S. carpocapsae ALL strain to date, comprising 84.5 Mb in 16 scaffolds, with an N50 of 7.36Mb. The largest scaffold, with 20.9Mb, was identified as chromosome X based on sex-specific genome sequencing. The high level of contiguity allowed us to characterize gene density, repeat content, and GC content. RNA-seq data from 17 developmental stages, spanning from embryo to adult, were used to predict 30,957 gene models. Using this new genome, we performed a macrosyntenic analysis to Caenorhabditis elegans and Pristionchus pacificus and found S. carpocapsaes chromosome X to be primarily orthologous to C. elegans and P. pacificus chromosome II and IV. We also investigated the expansion of protein families and gene expression differences between male and female stage nematodes. This new genome and more accurate set of annotations provide a foundation for new comparative genomic and gene expression studies within the Steinernema clade and across the Nematoda phylum.\n\nArticle SummaryThe insect killing worms Steinernema carpocapsae is a model organism for parasitism and symbiosis. The authors have used long reads and optical mapping to generate substantially contiguous assembly and a new set of gene annotations. They have identified the X chromosome as well as expansions in specific family proteases found in the venom of this worm. A macrosyntenic analysis with C. elegans shows a broad conservation of ancestral chromosomes with the exception of chromosome X. This new assembly will be useful to the Steinernema community and the broader nematode genomics community.

genomics↗

bioRxiv2019

A data-driven method to locate nest sites and estimate reproductive outcome from avian telemetry data

Recursive movement patterns have been used to detect behavioral structure within individual movement trajectories in the context of foraging ecology, home-ranging behavior, and predator avoidance. Some animals exhibit movement recursions to locations that are tied to reproductive functions, including nests and dens; while existing literature recognizes that, no method is currently available to explicitly target different types of revisited locations. Moreover, the temporal persistence of recursive movements to a breeding location can carry information regarding the fate of breeding attempts, but it has never been used as a metric to quantify recursive movement patterns. Here, we introduce a method to locate breeding attempts and estimate their fate from GPS-tracking data of central place foragers. We tested the performance of our method in three bird species differing in breeding ecology (wood stork (Mycteria americana), lesser kestrel (Falco naumanni), Mediterranean gull (Ichthyaetus melanocephalus)) and implemented it in the R package nestR. We identified breeding sites based on the analysis of recursive movements within individual tracks. Using trajectories with known breeding attempts, we estimated a set of species-specific criteria for the identification of nest sites, which we further validated using non-reproductive individuals as controls. We then estimated individual nest survival as a binary measure of reproductive fate (success, corresponding to fledging of at least one chick, or failure) from nest-site revisitation histories during breeding attempts, using a Bayesian hierarchical modeling approach that accounted for temporally variable revisitation patterns, probability of visit detection, and missing data. Across the three species, positive predictive value of the nest-site detection algorithm varied between 87-100% and sensitivity between 88-92%, and we correctly estimated the fate of 86-100% breeding attempts. By providing a method to formally distinguish among revisited locations that serve different ecological functions and introducing a probabilistic framework to quantify temporal persistence of movement recursions, we demonstrated how the analysis of recursive movement patterns can be applied to estimate reproduction in central place foragers. Beyond avian species, the principles of our method can be applied to other central place foraging breeders such as denning mammals. Our method estimates a component of individual fitness from movement data and will help bridge the gap between movement behavior, environmental factors, and their fitness consequences.

ecology↗