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Abstract Diversity in plant specialized metabolites plays critical roles in plant–environment interactions. In longer evolutionary scales, e.g. between families or orders, this diversity arises from whole-genome and tandem duplication events. Less is known about the evolutionary patterns that shape chemical diversity at shorter scales, e.g. within a family. Utilizing the aliphatic glucosinolate pathway, we explored how the genes encoding the terminal structural modification enzyme GSL-OH evolved across the Brassicaceae and the genomic processes that control presence–absence variation of its products (R)-2-hydroxy-but-3-enyl and (S)-2-hydroxy-but-3-enyl glucosinolate. We implemented a phylo-functional approach to functionally validate GSL-OH orthologs across the Brassicaceae and used that information to map the genomic origin and trajectory of the locus. This uncovered a complex mechanism involving at least 3 ancestral loci with extensive gene loss across all species, creating unequal retention across the phylogenetic relationships. Convergent evolution in enantiomeric specificity was observed, where several independent species had tandem duplicates that diverged toward producing the R or S enantiomers. To explore potential biological differences between the enantiomers, we performed Trichoplusia ni larval choice assays and tested resistance against Botrytis cinerea in a detached leaf assay. We found that plants with the S-enantiomer were more susceptible to B. cinerea infection than to T. ni larval herbivory, while plants with the R-enantiomer seemed more susceptible to T. ni larval herbivory when compared to B. cinerea. Ultimately, we observed recurrent GSL-OH loss, uncovered a complex origin story for the gene, and measured the bioactivity of the enzyme's metabolic products. 

Public genomic datasets like the 1000 Genomes project (1KGP), Human Genome Diversity Project (HGDP), and the Adolescent Brain Cognitive Development (ABCD) study are valuable public resources that facilitate scientific advancements in biology and enhance the scientific and economic impact of federally funded research projects. Regrettably, these datasets have often been developed and studied in ways that propagate outdated racialized and typological thinking, leading to fallacious reasoning among some readers that social and health disparities among the so-called races are due in part to innate biological differences between them. We highlight how this framing has set the stage for the racist exploitation of these datasets in two ways: First, we discuss the use of public biomedical datasets in studies that claim support for innate genetic differences in intelligence and other social outcomes between the groups identified as races. We further highlight recent instances of this which involve unauthorized access, use, and dissemination of public datasets. Second, we discuss thememification,use of simple figures meant for quick dissemination among lay audiences, of population genetic data to argue for a biological basis for purported human racial groups. We close with recommendations for scientists, to preempt the exploitation and misuse of their data, and for funding agencies, to better enforce violations of data use agreements. 

Summary Eukaryotic genomes harbor many forms of variation, including nucleotide diversity and structural polymorphisms, which experience natural selection and contribute to genome evolution and biodiversity. However, harnessing this variation for agriculture hinges on our ability to detect, quantify, catalog, and utilize genetic diversity.Here, we explore seven complete genomes of the emerging biofuel crop pennycress (Thlaspi arvense) drawn from across the species’s current genetic diversity to catalogue variation in genome structure and content.Across this new pangenome resource, we find contrasting evolutionary modes in different genomic regions. Gene-poor, repeat-rich pericentromeric regions experience frequent rearrangements, including repeated centromere repositioning. In contrast, conserved gene-dense chromosome arms maintain large-scale synteny across accessions, even in fast-evolving immune genes where microsynteny breaks down across species but the macrosynteny of gene cluster positioning is maintained.Our findings highlight that multiple elements of the genome experience dynamic evolution that conserves functional content on the chromosome scale but allows rearrangement and presence-absence variation on a local scale. This diversity is invisible to classical reference-based approaches and highlights the strength and utility of pangenomic resources. These results provide a valuable case study of rapid genomic structural evolution within a species and powerful resources for crop development in an emerging biofuel crop. 

Abstract Camelina (Camelina sativa), an allohexaploid species, is an emerging aviation biofuel crop that has been the focus of resurgent interest in recent decades. To guide future breeding and crop improvement efforts, the community requires a deeper comprehension of subgenome dominance, often noted in allopolyploid species, “alongside an understanding of the genetic diversity” and population structure of material present within breeding programs. We conducted population genetic analyses of a C. sativa diversity panel, leveraging a new genome, to estimate nucleotide diversity and population structure, and analyzed for patterns of subgenome expression dominance among different organs. Our analyses confirm that C. sativa has relatively low genetic diversity and show that the SG3 subgenome has substantially lower genetic diversity compared to the other two subgenomes. Despite the low genetic diversity, our analyses identified 13 distinct subpopulations including two distinct wild populations and others putatively representing founders in existing breeding populations. When analyzing for subgenome composition of long non-coding RNAs, which are known to play important roles in (a)biotic stress tolerance, we found that the SG3 subgenome contained significantly more lincRNAs compared to other subgenomes. Similarly, transcriptome analyses revealed that expression dominance of SG3 is not as strong as previously reported and may not be universal across all organ types. From a global analysis, SG3 “was only significant higher expressed” in flower, flower bud, and fruit organs, which is an important discovery given that the crop yield is associated with these organs. Collectively, these results will be valuable for guiding future breeding efforts in camelina. 

Abstract 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. 

The gene balance hypothesis proposes that selection acts on the dosage (i.e. copy number) of genes within dosage-sensitive portions of networks, pathways, and protein complexes to maintain balanced stoichiometry of interacting proteins, because perturbations to stoichiometric balance can result in reduced fitness. This selection has been called dosage balance selection. Dosage balance selection is also hypothesized to constrain expression responses to dosage changes, making dosage-sensitive genes (those encoding members of interacting proteins) experience more similar expression changes. In allopolyploids, where whole-genome duplication involves hybridization of diverged lineages, organisms often experience homoeologous exchanges that recombine, duplicate, and delete homoeologous regions of the genome and alter the expression of homoeologous gene pairs. Although the gene balance hypothesis makes predictions about the expression response to homoeologous exchanges, they have not been empirically tested. We used genomic and transcriptomic data from 6 resynthesized, isogenic Brassica napus lines over 10 generations to identify homoeologous exchanges, analyzed expression responses, and tested for patterns of genomic imbalance. Groups of dosage-sensitive genes had less variable expression responses to homoeologous exchanges than dosage-insensitive genes, a sign that their relative dosage is constrained. This difference was absent for homoeologous pairs whose expression was biased toward the B. napus A subgenome. Finally, the expression response to homoeologous exchanges was more variable than the response to whole-genome duplication, suggesting homoeologous exchanges create genomic imbalance. These findings expand our knowledge of the impact of dosage balance selection on genome evolution and potentially connect patterns in polyploid genomes over time, from homoeolog expression bias to duplicate gene retention. 

Plant growth, development, and nutritional quality depends upon amino acid homeostasis, especially in seeds. However, our understanding of the underlying genetics influencing amino acid content and composition remains limited, with only a few candidate genes and quantitative trait loci identified to date. Improved knowledge of the genetics and biological processes that determine amino acid levels will enable researchers to use this information for plant breeding and biological discovery. Toward this goal, we used genomic prediction to identify biological processes that are associated with, and therefore potentially influence, free amino acid (FAA) composition in seeds of the model plant Arabidopsis thaliana . Markers were split into categories based on metabolic pathway annotations and fit using a genomic partitioning model to evaluate the influence of each pathway on heritability explained, model fit, and predictive ability. Selected pathways included processes known to influence FAA composition, albeit to an unknown degree, and spanned four categories: amino acid, core, specialized, and protein metabolism. Using this approach, we identified associations for pathways containing known variants for FAA traits, in addition to finding new trait-pathway associations. Markers related to amino acid metabolism, which are directly involved in FAA regulation, improved predictive ability for branched chain amino acids and histidine. The use of genomic partitioning also revealed patterns across biochemical families, in which serine-derived FAAs were associated with protein related annotations and aromatic FAAs were associated with specialized metabolic pathways. Taken together, these findings provide evidence that genomic partitioning is a viable strategy to uncover the relative contributions of biological processes to FAA traits in seeds, offering a promising framework to guide hypothesis testing and narrow the search space for candidate genes.