Avril M. Harder’s research while affiliated with HudsonAlpha Institute for Biotechnology and other places

Ancient whole-genome duplications (WGDs) are believed to facilitate novelty and adaptation by providing the raw fuel for new genes. However, it is unclear how recent WGDs may contribute to evolvability within recent polyploids. Hybridization accompanying some WGDs may combine divergent gene content among diploid species. Some theory and evidence suggest that polyploids have a greater accumulation and tolerance of gene presence-absence and genomic structural variation, but it is unclear to what extent either is true. To test how recent polyploidy may influence pangenomic variation, we sequenced, assembled, and annotated twelve complete, chromosome-scale genomes of Camelina sativa, an allohexaploid biofuel crop with three distinct subgenomes. Using pangenomic comparative analyses, we characterized gene presence-absence and genomic structural variation both within and between the subgenomes. We found over 75% of ortholog gene clusters are core in Camelina sativa and <10% of sequence space was affected by genomic structural rearrangements. In contrast, 19% of gene clusters were unique to one subgenome, and the majority of these were Camelina-specific (no ortholog in Arabidopsis). We identified an inversion that may contribute to vernalization requirements in winter-type Camelina, and an enrichment of Camelina-specific genes with enzymatic processes related to seed oil quality and Camelina’s unique glucosinolate profile. Genes related to these traits exhibited little presence-absence variation. Our results reveal minimal pangenomic variation in this species, and instead show how hybridization accompanied by WGD may benefit polyploids by merging diverged gene content of different species.

Wild populations are increasingly threatened by human-mediated climate change and land use changes. As populations decline, the probability of inbreeding increases, along with the potential for negative effects on individual fitness. Detecting and characterizing runs of homozygosity (ROHs) is a popular strategy for assessing the extent of individual inbreeding present in a population and can also shed light on the genetic mechanisms contributing to inbreeding depression. Here, we analyze simulated and empirical datasets to demonstrate the downstream effects of program selection and long-term demographic history on ROH inference, leading to context-dependent biases in the results. Through a sensitivity analysis we evaluate how various parameter values impact ROH-calling results, highlighting its utility as a tool for parameter exploration. Our results indicate that ROH inferences are sensitive to factors such as sequencing depth and ROH length distribution, with bias direction and magnitude varying with demographic history and the programs used. Estimation biases are particularly pronounced at lower sequencing depths, potentially leading to either underestimation or overestimation of inbreeding. These results are particularly important for the management of endangered species, as underestimating inbreeding signals in the genome can substantially undermine conservation initiatives. We also found that small true ROHs can be incorrectly lumped together and called as longer ROHs, leading to erroneous inference of recent inbreeding. To address these challenges, we suggest using a combination of ROH detection tools and ROH length-specific inferences, along with sensitivity analysis, to generate robust and context-appropriate population inferences regarding inbreeding history. We outline these recommendations for ROH estimation at multiple levels of sequencing effort, which are typical of conservation genomics studies.

Thiamine deficiency complex (TDC) has been identified in an ever-expanding list of species and populations. In many documented occurrences of TDC in fishes, juvenile mortality can be high—up to 90% at the population level. Such sweeping demographic losses and concomitant decreases in genetic diversity due to TDC can be prevented by treating pre-spawn females or fertilized eggs with supplemental thiamine. However, some fisheries managers are hesitant to widely apply thiamine treatments due to the potential for unforeseen evolutionary consequences. With these concerns in mind, we first review the existing data regarding genetic adaptation to low-thiamine conditions and provide perspectives on evolution-informed treatment strategies with specific population examples. We also provide practical treatment information, consider the potential logistical constraints of thiamine supplementation, and explore the consequences of deciding against supplementation. Until new evidence bolsters or refutes the genetic adaptation hypothesis, we suggest that TDC mitigation strategies should be designed to support maximum population genetic diversity through thiamine supplementation.

Ancient whole-genome duplications (WGDs) are believed to facilitate novelty and adaptation by providing the raw fuel for new genes. However, it is unclear how recent WGDs may contribute to evolvability within recent polyploids. Hybridization accompanying some WGDs may combine divergent gene content among diploid species. Some theory and evidence suggest that polyploids have a greater accumulation and tolerance of gene presence-absence and genomic structural variation, but it is unclear to what extent either is true. To test how recent polyploidy may influence pangenomic variation, we sequenced, assembled, and annotated twelve complete, chromosome-scale genomes of Camelina sativa , an allohexaploid biofuel crop with three distinct subgenomes. Using pangenomic comparative analyses, we characterized gene presence-absence and genomic structural variation both within and between the subgenomes. We found over 75% of ortholog gene clusters are core in Camelina sativa and <10% of sequence space was affected by genomic structural rearrangements. In contrast, 19% of gene clusters were unique to one subgenome, and the majority of these were Camelina-specific (no ortholog in Arabidopsis). We identified an inversion that may contribute to vernalization requirements in winter-type Camelina, and an enrichment of Camelina-specific genes with enzymatic processes related to seed oil quality and Camelina’s unique glucosinolate profile. Genes related to these traits exhibited little presence-absence variation. Our results reveal minimal pangenomic variation in this species, and instead show how hybridization accompanied by WGD may benefit polyploids by merging diverged gene content of different species.

Thiamine deficiency complex (TDC) in fishes has been identified in an ever-expanding list of species and populations. In many documented occurrences of TDC in fishes, rates of juvenile mortality have reached 90% at the population level, with many females producing no surviving offspring. Such sweeping demographic losses and concomitant decreases in genetic diversity due to TDC can be prevented by treating pre-spawn females or fertilized eggs with supplemental thiamine. However, some fisheries managers are hesitant to widely apply thiamine treatments due to the potential for unforeseen evolutionary consequences. Specifically, these hesitations are due in part to apprehension that thiamine supplementation may impede genetic adaptation to low-thiamine conditions or may give hatchery fish an advantage over wild-origin fish. With these concerns in mind, we first review the existing data regarding genetic adaptation to low-thiamine conditions and provide perspectives on evolution-informed treatment strategies with specific population examples. We also provide practical treatment information, consider the potential logistical constraints of thiamine supplementation, and explore the consequences of deciding against supplementation. Until new evidence bolsters or refutes the genetic adaptation hypothesis, we suggest that TDC mitigation strategies should be designed to support maximum population genetic diversity through thiamine supplementation. Furthermore, we offer guidelines on when the adaptation strategy may be applicable to certain populations.

The increasing availability of satellite imagery has supported a rapid expansion in forward‐looking studies seeking to track and predict how climate change will influence wild population dynamics. However, these data can also be used in retrospect to provide additional context for historical data in the absence of contemporaneous environmental measurements. We used 167 Landsat‐5 Thematic Mapper (TM) images spanning 13 years to identify environmental drivers of fitness and population size in a well‐characterized population of banner‐tailed kangaroo rats ( Dipodomys spectabilis ) in the southwestern United States. We found evidence of two decoupled processes that may be driving population dynamics in opposing directions over distinct time frames. Specifically, increasing mean surface temperature corresponded to increased individual fitness, where fitness is defined as the number of offspring produced by a single individual. This result contrasts with our findings for population size, where increasing surface temperature led to decreased numbers of active mounds. These relationships between surface temperature and (i) individual fitness and (ii) population size would not have been identified in the absence of remotely sensed data, indicating that such information can be used to test existing hypotheses and generate new ecological predictions regarding fitness at multiple spatial scales and degrees of sampling effort. To our knowledge, this study is the first to directly link remotely sensed environmental data to individual fitness in a nearly exhaustively sampled population, opening a new avenue for incorporating remote sensing data into eco‐evolutionary studies.

Wild populations are increasingly threatened by human-mediated climate change and land use changes. As populations decline, the probability of inbreeding increases, along with the potential for negative effects on individual fitness. Detecting and characterizing runs of homozygosity (ROHs) is a popular strategy for assessing the extent of individual inbreeding present in a population and can also shed light on the genetic mechanisms contributing to inbreeding depression. However, selecting an appropriate program and parameter values for such analyses is often difficult for species of conservation concern, for which little is often known about population demographic histories or few high-quality genomic resources are available. Herein, we analyze simulated and empirical data sets to demonstrate the downstream effects of program selection on ROH inference. We also apply a sensitivity analysis to evaluate the effects of various parameter values on ROH-calling results and demonstrate its utility for parameter value selection. We show that ROH inferences can be biased when sequencing depth and the distribution of ROH length is not interpreted in light of program-specific tendencies. This is particularly important for the management of endangered species, as some program and parameter combinations consistently underestimate inbreeding signals in the genome, substantially undermining conservation initiatives. Based on our conclusions, we suggest using a combination of ROH detection tools and ROH length-specific inferences to generate robust population inferences regarding inbreeding history. We outline these recommendations for ROH estimation at multiple levels of sequencing effort typical of conservation genomics studies.