The major histocompatibility complex (MHC) is a highly polymorphic gene family that is crucial in immunity, and its diversity can be effectively used as a fitness marker for populations. Despite this, MHC remains poorly characterised in non-model species (e.g., cetaceans: whales, dolphins and porpoises) as high gene copy number variation, especially in the fast-evolving class I region, makes analyses of genomic sequences difficult. To date, only small sections of class I and IIa genes have been used to assess functional diversity in cetacean populations. Here, we undertook a systematic characterisation of the MHC class I and IIa regions in available cetacean genomes. We extracted full-length gene sequences to design pan-cetacean primers that amplified the complete exon2 from MHC class I and IIa genes in one combined sequencing panel. We validated this panel in 19 cetacean species and described 354 alleles for both classes. Furthermore, we identified likely assembly artefacts for many MHC class I assemblies based on the presence of class I genes in the amplicon data compared to missing genes from genomes. Finally, we investigated MHC diversity using the panel in 25 humpback and 30 southern right whales, including four paternity trios for humpback whales. This revealed copy-number variable class I haplotypes in humpback whales, which is likely a common phenomenon across cetaceans. These MHC alleles will form the basis for a cetacean branch of the Immuno-Polymorphism Database (IPD-MHC), a curated resource intended to aid in the systematic compilation of MHC alleles across several species, to support conservation initiatives. The dataset contains 85 fastq files. Each file contains reads of amplicons from five MHC loci (DQA, DQB, DRA, DRB, and class I genes) combined across separate sequencing runs from a single cetacean. Details on individual cetacean sample abbreviations can be found in the manuscript. Reads are paired and merged with the Illumina adapter removed. It also contains one fastq file with all class I alleles found and one fastq file with non-functional DRB alleles found. Alleles are labeled with four letter species abbreviation followed by locus designation (DRB or N for class I) and are numbered in the order they were discovered. Further details are provided at: Heimeier, D., Garland, E. C., Eichenberger, F., Garrigue, C., Vella, A., Baker, C. S., & Carroll, E. L. (2024). A pan-cetacean MHC amplicon sequencing panel developed and evaluated in combination with genome assemblies. Molecular Ecology Resources, 00, e13955. https://doi.org/10.1111/1755-0998.13955 GET DATA: https://doi.org/10.5061/dryad.wh70rxwvb

Microsatellites are widely used in population genetics, but their evolutionary dynamics remain poorly understood. It is unclear whether microsatellite loci drift in length over time. This is important because the mutation processes that underlie these important genetic markers are central to the evolutionary models that employ microsatellites. We identify more than 27 million microsatellites using a novel and unique dataset of modern and ancient Adélie penguin genomes along with data from 63 published chordate genomes. We investigate microsatellite evolutionary dynamics over two time scales: one based on Adélie penguin samples dating to approximately 46.5 kya, the other dating to the diversification of chordates more than 500 Mya. We show that the process of microsatellite allele length evolution is at dynamic equilibrium; while there is length polymorphism among individuals, the length distribution for a given locus remains stable. Many microsatellites persist over very long time scales, particularly in exons and regulatory sequences. These often retain length variability, suggesting that they may play a role in maintaining phenotypic variation within populations. Further details are provided at: Bennet J McComish, Michael A Charleston, Matthew Parks, Carlo Baroni, Maria Cristina Salvatore, Ruiqiang Li, Guojie Zhang, Craig D Millar, Barbara R Holland, David M Lambert, Ancient and Modern Genomes Reveal Microsatellites Maintain a Dynamic Equilibrium Through Deep Time, Genome Biology and Evolution, Volume 16, Issue 3, March 2024, evae017, https://doi.org/10.1093/gbe/evae017 GET DATA: https://doi.org/10.5061/dryad.7gt3rg2

Data includes estimates of abundance of seaweed taxa on the seafloor across the Northern Victoria Land coast, Ross Sea, Antarctica. This includes: - Metadata of video transects - Seaweed density across transects - Modelled outputs of light attenuation across sites. Descriptions: - "Antarctic_Seaweed_Metadata_TAN2101_TAN2302_Dryad.xlsx" - Metadata of video transects, date and time, locations, gear, depth, distance covered. - "Antarctic_Seaweeds_TAN2101_TAN2302.csv" - Density of seaweed functional groups across video transects - "Light_transects_TAN2021_TAN2302.csv" - Outputs of light modelling for seafloor regions of the Ross Sea - "Antarctic_Seaweed_RScript_Tait_etal_2024.txt" - R sripts used to plot, analyse and model the above datasets Further details are provided at: Tait, L.W., Chin, C., Nelson, W. et al. Deep-living and diverse Antarctic seaweeds as potentially important contributors to global carbon fixation. Commun Earth Environ 5, 205 (2024). https://doi.org/10.1038/s43247-024-01362-2 GET DATA: https://doi.org/10.5061/dryad.w6m905qwz

The data is generated through modelling simulations using the University of Victoria Earth system climate model. The modelling dataset presented here corresponds to the study entitled "Transient response of Southern Ocean ecosystems during Heinrich stadials". This dataset contains data files of the complete transient simulations (FW,FE and FWFE) and 40ka-control simulation mentioned in Table 1 and Table 2 of the manuscript. We first performed a control simulation 40ka-control integrating a total of 10000 years. We use only the last 200 years of this control simulation for our analysis. The data is generated through modelling simulations using the University of Victoria Earth system climate model. All the final data is in nc format, which can be easily read by Python/ferret or any other common data analysing software. RELATED PUBLICATION: Saini,H., Meissner,K.J., Menviel,L., & Kvale,K.(2024). Transient response of Southern Ocean ecosystems during Heinrich stadials. Paleoceanography and Paleoclimatology, 39, e2023PA004754. https://doi.org/10.1029/2023PA004754 GET DATA: https://doi.org/10.5061/dryad.k3j9kd5dt