Abstract: Less than half of individuals with a suspected Mendelian condition receive a precise molecular diagnosis after comprehensive clinical genetic testing. Improvements in data quality and costs have heightened interest in using long-read sequencing (LRS) to streamline clinical genomic testing, but the absence of control datasets for variant filtering and prioritization has made tertiary analysis of LRS data challenging. To address this, the 1000 Genomes Project ONT Sequencing Consortium aims to generate LRS data from at least 800 of the 1000 Genomes Project samples. Our goal is to use LRS to identify a broader spectrum of variation so we may improve our understanding of normal patterns of human variation. Here, we present data from analysis of the first 100 samples, representing all 5 superpopulations and 19 subpopulations. These samples, sequenced to an average depth of coverage of 37x and sequence read N50 of 54 kbp, have high concordance with previous studies for identifying single nucleotide and indel variants outside of homopolymer regions. Using multiple structural variant (SV) callers, we identify an average of 24,543 high-confidence SVs per genome, including shared and private SVs likely to disrupt gene function as well as pathogenic expansions within disease-associated repeats that were not detected using short reads. Evaluation of methylation signatures revealed expected patterns at known imprinted loci, samples with skewed X-inactivation patterns, and novel differentially methylated regions. All raw sequencing data, processed data, and summary statistics are publicly available, providing a valuable resource for the clinical genetics community to discover pathogenic SVs.


Abstract: Passive dispersal via wind or ocean currents can drive asymmetric gene flow, which influences patterns of genetic variation and the capacity of populations to evolve in response to environmental change. The mangrove rivulus fish (Kryptolebias marmoratus), hereafter “rivulus,” is an intertidal fish species restricted to the highly fragmented New World mangrove forests of Central America, the Caribbean, the Bahamas, and Florida. Mangrove patches are biological islands with dramatic differences in both abiotic and biotic conditions compared to adjacent habitat. Over 1,000 individual rivulus across 17 populations throughout its range were genotyped at 32 highly polymorphic microsatellites. Range-wide population genetic structure was evaluated with five complementary approaches that found eight distinct population clusters. However, an analysis of molecular variance indicated significant population genetic structure among regions, populations within regions, sampling locations within populations, and individuals within sampling locations, indicating that rivulus has both broad- and fine-scale genetic differentiation. Integrating range-wide genetic data with biophysical modeling based on 10 years of ocean current data showed that ocean currents and the distance between populations over water drive gene flow patterns on broad scales. Directional migration estimates suggested some significant asymmetries in gene flow that also were mediated by ocean currents and distance. Specifically, populations in the center of the range (Florida Keys) were identified as sinks that received migrants (and alleles) from other populations but failed to export individuals. These populations thus harbor genetic variation, perhaps even from extirpated populations across the range, but ocean currents and complex arrangements of landmasses might prevent the distribution of that genetic variation elsewhere. Hence, the inherent asymmetry of ocean currents shown to impact both genetic differentiation and directional migration rates may be responsible for the complex distribution of genetic variation across the range and observed patterns of metapopulation structure.

Abstract: Understanding the evolutionary consequences of anthropogenic change is imperative for estimating long-term species resilience. While contemporary genomic data can provide us with important insights into recent demographic histories, investigating past change using present genomic data alone has limitations. In comparison, temporal genomics studies, defined herein as those that incorporate time series genomic data, utilize museum collections and repeated field sampling to directly examine evolutionary change. As temporal genomics is applied to more systems, species and questions, best practices can be helpful guides to make the most efficient use of limited resources. Here, we conduct a systematic literature review to synthesize the effects of temporal genomics methodology on our ability to detect evolutionary changes. We focus on studies investigating recent change within the past 200 years, highlighting evolutionary processes that have occurred during the past two centuries of accelerated anthropogenic pressure. We first identify the most frequently studied taxa, systems, questions and drivers, before highlighting overlooked areas where further temporal genomic studies may be particularly enlightening. Then, we provide guidelines for future study and sample designs while identifying key considerations that may influence statistical and analytical power. Our aim is to provide recommendations to a broad array of researchers interested in using temporal genomics in their work.

Abstract: Sequencing data—genomics, transcriptomics, epigenomics, proteomics, and metabolomics—have revolutionized biological research, enabling a more detailed study of processes, ranging from subcellular to evolutionary, that drive biological organization. These processes, collectively, are responsible for generating patterns of phenotypic variation and can operate over dramatically different timescales (milliseconds to billions of years). While researchers often study phenotypic variation at specific levels of biological organization to isolate processes operating at that particular scale, the varying types of sequence data, or ‘omics, can also provide complementary inferences to link molecular and phenotypic variation to produce an integrated view of evolutionary biology, ranging from molecular pathways to speciation. We briefly describe how ‘omics has been used across biological levels and then demonstrate the utility of integrating different types of sequencing data across multiple biological levels within the same study to better understand biological phenomena. However, single-time-point studies cannot evaluate the temporal dynamics of these biological processes. Therefore, we put forward temporal ‘omics as a framework that can better enable researchers to study the temporal dynamics of target processes. Temporal ‘omics is not infallible, as the temporal sampling regime directly impacts inferential ability. Thus, we also discuss the role the temporal sampling regime plays in deriving inferences about the environmental conditions driving biological processes and provide examples that demonstrate the impact of the sampling regime on biological inference. Finally, we forecast the future of temporal ‘omics by highlighting current methodological advancements that will enable temporal ‘omics to be extended across species and timescales. We extend this discussion to using temporal multi-omics to integrate across the biological hierarchy to evaluate and link the temporal dynamics of processes that generate phenotypic variation.

Excerpt from Introduction: Natural history collections, advancing methodologies, and lower sequencing costs have propelled the field of temporal genomics. The field is diverse, with both applied (Wasko et al. 2004; Vega et al. 2017; Kotzé et al. 2019) and fundamental (Bergland et al. 2014; Machugh et al. 2017) research focused on short (Kawecki et al. 2012; Lenski et al. 2015; Durland et al. 2021) and long (Brunel et al. 2020; Der Sarkissian et al. 2020) timescales. On longer timescales, ancient DNA (aDNA) research focuses on processes that act over thousands (Machugh et al. 2017; Yang et al. 2020) to millions (van der Valk et al. 2021) of years. Loog et al. (2020) used contemporary and ancient samples of the grey wolf, Canis lupus, spanning 50,000 years to trace modern wolf ancestry back to an expansion from Beringia (the land bridge spanning Asia and North America). On a shorter timescale, Perry et al. (2022), this issue, quantify gene expression in brown bears, Ursus arctos, in different tissue types to investigate differences in gene isoform expression among seasons of the hibernation cycle. By sampling repeatedly within a year, the authors uncovered specific changes in gene expression that relate to hibernation phenotypes, providing insights into the molecular mechanisms that regulate complex animal behaviors. Furthermore, temporal methodologies can use samples across development to better understand changes in gene expression throughout an organism's life. In this issue, Oomen et al. (2022) used experimental tanks of Atlantic cod (Gadus morhua) larvae at different temperatures and sampled them throughout development to examine the temporal dynamics of gene expression under thermal stress. Through this special issue, we aim to highlight the diversity of temporal genomic research while promoting the extension of time-series methodologies to other “omics” approaches (e.g., metabolomics, proteomics, epigenomics). This introduction provides a brief overview of the application of temporal genomics to study microevolution, and its implementation within conservation. We also contextualize the studies within this special issue to inspire future research with time-series molecular data.

Abstract: New World mangrove trees are foundation species, and their range is predicted to expand northward with climate change. Foundation species are commonly prioritized for conservation, with the goal of preserving the entire community that depends on them. However, no studies have explicitly investigated whether mangrove-dependent species' ranges will track the northward expansion of New World mangrove forests. We use the mangrove rivulus fish, Kryptolebias marmoratus, to investigate shifts in habitat suitability in response to various climate change scenarios (Representative Concentration Pathways 2.6, 4.5, 6.0, and 8.5). Niche models for coastal species focus on traditional climatic variables (e.g., precipitation, temperature) even though coastal habitats also are directly influenced by marine variables (e.g., sea surface salinity). We employ a novel data integration method that combines marine and climatic variables, and that accounts for model selection uncertainty using model averaging to provide robust estimates of habitat suitability. Contrary to expectation, suitability of rivulus habitat is predicted to increase in the south and decrease or remain unchanged in the north across all climate change scenarios. Thus, rivulus might experience range contraction, not expansion. Habitat became more suitable with increased salinity of the saltiest month and precipitation of the driest quarter. In laboratory settings, rivulus have higher survival, reproductive success, and growth rates in low salinities. This discrepancy suggests that some combination of the responses of rivulus and its competitors to environmental change will restrict rivulus to habitats that laboratory experiments consider suboptimal. Our models suggest that focusing conservation decisions on foundation species could overestimate habitat availability and resilience of affiliated communities while simultaneously underestimating species declines and extinction risks.

Abstract: Steroid hormones accumulate in recirculation aquaculture systems (RAS) and may influence the reproductive physiology of farmed fish. Ozone reduces hormone concentrations in freshwater RAS used to rear Atlantic salmon, but its effect on reproductive development is unknown. Accordingly, an 8-month trial was carried out to evaluate the growth, health, and maturation of post-smolt Atlantic salmon (296 ± 4 g initial weight) reared in six replicated freshwater RAS (9.5 m3 total volume) operated with or without ozone (N = 3/treatment). Residual ozone was controlled with an oxidation reduction potential (ORP) of 300–320 mV, and mean water temperature was maintained at 14.7 °C. Atlantic salmon growth was generally faster in ozonated RAS. Salmon from RAS with and without ozone weighed 2156 ± 101 and 1810 ± 15 g, respectively, by the end of the study. Caudal, anal, and pelvic fin damage was greater (P < 0.05) for salmon in ozonated RAS early in the trial but improved thereafter. No statistical differences in gill, skin, and skeletal muscle histopathology were observed between treatments at the end of the study. Waterborne estradiol, testosterone, and 11-ketotestosterone levels were periodically lower (P < 0.05) in ozonated RAS, but maturing salmon were more prevalent in these systems. At the end of the trial, percent maturation of salmon populations reared in RAS with and without ozone was 63 ± 7 and 48 ± 1%, respectively; however, maturity appeared to be related to fish size. Improved water quality was observed in ozonated RAS including reduced dissolved copper, iron, and zinc levels, total heterotrophic bacteria counts, and true color, and increased ultraviolet transmittance, which may have supported improved Atlantic salmon growth. Overall, ozone did not inhibit the onset or prevalence of Atlantic salmon maturation, but significant improvements in water quality and salmon growth performance resulted from its use.

Special Issues

Media Coverage

Excerpt: The rivulus fish is native to mangrove forests in Florida, the Caribbean, and Central America. Most individuals in this species are hermaphrodites, allowing them to reproduce on their own. Because of this quality, and their tolerance to a wide range of environmental conditions, rivulus is an important species in researching genetics, ecology, and evolution. One question that studying rivulus helps answer is how species adjust in harshly changing environmental conditions. Mangrove forests in which this fish lives are located in saltwater or brackish water in coastal intertidal zones. The forests experience changing tide levels as well as have general susceptibility to changing environmental conditions such as salinity, temperature, and precipitation.

General Publications

Excerpt: “Network! Network! Network!” I can hear the phrase ringing in my ears, and it transports me back to when I was a fresh PhD student in my advisor’s office. As early career scientists, we have been told that networking is important, and I took that to heart. I jumped at every chance to meet new people, even when I was already stretched too thin, but why? There are nontangible reasons like developing interpersonal skills and making good impressions to hopefully aid in future career transitions. However, there is also a more immediate reason, collaborations. We all know that science is collaborative, and strong collaborations can make or break your research. However, no one ever tells you how to transition your network into meaningful collaborations. While not all relationships are easily expanded into collaborative projects, I have some tips and suggestions, that I learned the hard way, to grow your relationships into collaborations that, hopefully, you maintain throughout your career.