Hessen, D. O. | Search bioRxiv

bioRxiv2026

A chromosome-level genome assembly of a "living fossil", the tadpole shrimp Lepidurus arcticus (Pallas, 1793)

We present the first chromosome-level reference genome for Lepidurus arcticus (Pallas, 1793), a freshwater crustacean with circumpolar distribution. L. arcticus belongs to the small order of freshwater Notostracan crustaceans that are representatives of the ancient group Branchiopoda. This group has a remarkable morphological stability and is frequently labelled "living fossils". Its ancient origin, streamlined genome (estimated to 0.11 Gb) and reproductive flexibility makes this a very interesting candidate for genomic studies. The haplotype-resolved assemblies are composed of two pseudo-haplotypes spanning 81.2 megabases (Mb) and 81.8 Mb, respectively, and each scaffolded into 6 chromosomes. Both haplotypes (hap) show high completeness and identical BUSCO scores of 98.3 for hap1 and hap2. The scaffold N50 length is 13.4 Mb for hap1 and 13.9 Mb for hap2, and k-mer completeness estimated from PacBio HiFi reads was 95.79% and 96.18%, respectively. The haplotypes display very low estimated genome-wide heterozygosity of 0.133%. The assembly contains 10901 (hap1) and 10910 (hap2) protein-coding genes. Repetitive elements comprised approximately 24-25% of each haplotype, with long terminal repeat retrotransposons representing the most abundant transposable element class at approximately 8-9%. Comparison with the near chromosome-level genome of Lepidurus packardi revealed substantial intrachromosomal rearrangements, despite similar chromosome numbers and chromosome sizes. Differences in transposable element content between L. arcticus and L. packardi were primarily driven by retrotransposons, particularly LTR and LINE elements. This reference genome provides a valuable resource for future population genomic studies and for investigating evolutionary stasis at the genome level.

genomics↗

bioRxiv2021

Neural networks and extreme gradient boosting predict multiple thresholds and trajectories of microbial biodiversity responses due to browning

Ecological association studies often assume monotonicity such as between biodiversity and environmental properties although there is growing evidence that non-monotonic relations dominate in nature. Here we apply machine learning algorithms to reveal the non-monotonic association between microbial diversity and an anthropogenic induced large scale change, the browning of freshwaters, along a longitudinal gradient covering 70 boreal lakes in Scandinavia. Measures of bacterial richness and evenness (alpha diversity) showed non-monotonic trends in relation to environmental gradients, peaking at intermediate levels of browning. Depending on the statistical methods, variables indicative for browning could explain 5% of the variance in bacterial community composition (beta diversity) when applying standard methods assuming monotonic relations and up to 45 % with machine learning methods (i.e. extreme gradient boosting and feed-forward neural networks) taking non-monotonicity into account. This non-monotonicity observed at the community level was explained by the complex interchangeable nature of individual taxa responses as shown by a high degree of non-monotonic responses of individual bacterial sequence variants to browning. Furthermore, the non-monotonic models provide the position of thresholds and predict alternative bacterial diversity trajectories in boreal freshwater as a result of ongoing climate and land use changes, which in turn will affect entire ecosystem metabolism and likely greenhouse gas production.

microbiology↗