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1. The geno-geo-climate nexus: contributions of geographic and ecological factors in shaping the genomic divergence of two closely related threatened rainforest species of Fontainea Heckel (Euphorbiaceae)

   https://doi.org/10.1007/s10980-024-01828-w  

   Brunton, Aaron J. ; Farleigh, Keaka ; Ogbourne, Steven M. ; Rossetto, Maurizio ; Schoeman, David S. ; Conroy, Gabriel C. ( January 2024 , Landscape Ecology)

   Processes that shape genomic and ecological divergence can reveal important evolutionary dynamics to inform the conservation of threatened species.Fontaineais a genus of rainforest shrubs and small trees including critically endangered and threatened species restricted to narrow, but complex geographic and ecological regions. Several species ofFontaineaare subject to spatially explicit conditions and experience limited intra-specific gene flow, likely generating genetic differentiation and local adaptation.

   Here, we explored the genetic and ecological mechanisms underlying patterns of diversification in two, closely related threatenedFontaineaspecies. Our aim was to compare spatial patterns of genetic variation between the vulnerableFontainea australis(Southern Fontainea) and critically endangeredF. oraria(Coastal Fontainea), endemic to the heterogeneous subtropical region of central, eastern Australia, where large-scale clearing has severely reduced rainforest habitat to a fraction (< 1%) of its pre-European settlement extent.

   We used a set of 10,000 reduced-representation markers to infer genetic relationships and the drivers of spatial genetic variation across the two species. In addition, we employed a combination of univariate and multivariate genome-environment association analysis using a set of topo-climatic variables to explore potential patterns of local adaptation as a factor impacting genomic divergence.

   Our study revealed that Coastal Fontainea have a close genetic relationship with Southern Fontainea. We showed that isolation by distance has played a key role in their genetic variation, indicating that vicariance can explain the spatial genetic distribution of the two species. Genotype-environment analyses showed a strong association with temperature and topographic features, suggesting adaptation to localised thermal environments. We used a multivariate redundancy analysis to identify a range of putatively adapted loci associated with local environmental conditions.

   Divergent selection at the local-habitat scale as a result of dispersal limitations and environmental heterogeneity (including physical barriers) are likely contributors to adaptive divergence between the twoFontaineaspecies. Our findings have presented evidence to indicate that Southern and Coastal Fontainea were comprised of distinct genetic groups and ecotypes, that together may form a single species continuum, with further phenotype research suggested to confirm the current species boundaries. Proactive conservation actions, including assisted migration to enhance the resilience of populations lacking stress-tolerant single nucleotide polymorphisms (SNPs) may be required to secure the long-term future of both taxa. This is especially vital for the critically endangered Coastal Fontainea given projections of habitat decline for the species under future climate scenarios.

    

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2. Relating enhancer genetic variation across mammals to complex phenotypes using machine learning

   https://doi.org/10.1126/science.abm7993  

   Kaplow, Irene M. ; Lawler, Alyssa J. ; Schäffer, Daniel E. ; Srinivasan, Chaitanya ; Sestili, Heather H. ; Wirthlin, Morgan E. ; Phan, BaDoi N. ; Prasad, Kavya ; Brown, Ashley R. ; Zhang, Xiaomeng ; et al ( April 2023 , Science)

   INTRODUCTION Diverse phenotypes, including large brains relative to body size, group living, and vocal learning ability, have evolved multiple times throughout mammalian history. These shared phenotypes may have arisen repeatedly by means of common mechanisms discernible through genome comparisons. RATIONALE Protein-coding sequence differences have failed to fully explain the evolution of multiple mammalian phenotypes. This suggests that these phenotypes have evolved at least in part through changes in gene expression, meaning that their differences across species may be caused by differences in genome sequence at enhancer regions that control gene expression in specific tissues and cell types. Yet the enhancers involved in phenotype evolution are largely unknown. Sequence conservation–based approaches for identifying such enhancers are limited because enhancer activity can be conserved even when the individual nucleotides within the sequence are poorly conserved. This is due to an overwhelming number of cases where nucleotides turn over at a high rate, but a similar combination of transcription factor binding sites and other sequence features can be maintained across millions of years of evolution, allowing the function of the enhancer to be conserved in a particular cell type or tissue. Experimentally measuring the function of orthologous enhancers across dozens of species is currently infeasible, but new machine learning methods make it possible to make reliable sequence-based predictions of enhancer function across species in specific tissues and cell types. RESULTS To overcome the limits of studying individual nucleotides, we developed the Tissue-Aware Conservation Inference Toolkit (TACIT). Rather than measuring the extent to which individual nucleotides are conserved across a region, TACIT uses machine learning to test whether the function of a given part of the genome is likely to be conserved. More specifically, convolutional neural networks learn the tissue- or cell type–specific regulatory code connecting genome sequence to enhancer activity using candidate enhancers identified from only a few species. This approach allows us to accurately associate differences between species in tissue or cell type–specific enhancer activity with genome sequence differences at enhancer orthologs. We then connect these predictions of enhancer function to phenotypes across hundreds of mammals in a way that accounts for species’ phylogenetic relatedness. We applied TACIT to identify candidate enhancers from motor cortex and parvalbumin neuron open chromatin data that are associated with brain size relative to body size, solitary living, and vocal learning across 222 mammals. Our results include the identification of multiple candidate enhancers associated with brain size relative to body size, several of which are located in linear or three-dimensional proximity to genes whose protein-coding mutations have been implicated in microcephaly or macrocephaly in humans. We also identified candidate enhancers associated with the evolution of solitary living near a gene implicated in separation anxiety and other enhancers associated with the evolution of vocal learning ability. We obtained distinct results for bulk motor cortex and parvalbumin neurons, demonstrating the value in applying TACIT to both bulk tissue and specific minority cell type populations. To facilitate future analyses of our results and applications of TACIT, we released predicted enhancer activity of >400,000 candidate enhancers in each of 222 mammals and their associations with the phenotypes we investigated. CONCLUSION TACIT leverages predicted enhancer activity conservation rather than nucleotide-level conservation to connect genetic sequence differences between species to phenotypes across large numbers of mammals. TACIT can be applied to any phenotype with enhancer activity data available from at least a few species in a relevant tissue or cell type and a whole-genome alignment available across dozens of species with substantial phenotypic variation. Although we developed TACIT for transcriptional enhancers, it could also be applied to genomic regions involved in other components of gene regulation, such as promoters and splicing enhancers and silencers. As the number of sequenced genomes grows, machine learning approaches such as TACIT have the potential to help make sense of how conservation of, or changes in, subtle genome patterns can help explain phenotype evolution. Tissue-Aware Conservation Inference Toolkit (TACIT) associates genetic differences between species with phenotypes. TACIT works by generating open chromatin data from a few species in a tissue related to a phenotype, using the sequences underlying open and closed chromatin regions to train a machine learning model for predicting tissue-specific open chromatin and associating open chromatin predictions across dozens of mammals with the phenotype. [Species silhouettes are from PhyloPic] 

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3. The genetics of extreme microgeographic adaptation: an integrated approach identifies a major gene underlying leaf trichome divergence in Yellowstone Mimulus guttatus

   https://doi.org/10.1111/mec.13753  

   Hendrick, Margaret F. ; Finseth, Findley R. ; Mathiasson, Minna E. ; Palmer, Kristen A. ; Broder, Emma M. ; Breigenzer, Peter ; Fishman, Lila ( August 2016 , Molecular Ecology)

   Microgeographic adaptation provides a particularly interesting context for understanding the genetic basis of phenotypic divergence and may also present unique empirical challenges. In particular, plant adaptation to extreme soil mosaics may generate barriers to gene flow or shifts in mating system that confound simple genomic scans for adaptive loci. Here, we combine three approaches – quantitative trait locus (QTL) mapping of candidate intervals in controlled crosses, population resequencing (PoolSeq) and analyses of wild recombinant individuals – to investigate one trait associated withMimulus guttatus(yellow monkeyflower) adaptation to geothermal soils in Yellowstone National Park. We mapped a majorQTLcausing dense leaf trichomes in thermally adapted plants to a <50‐kb region of linkage Group 14 (Tr14) previously implicated in trichome divergence between independentM. guttatuspopulations. A PoolSeq scan of Tr14 region revealed a cluster of six genes, coincident with the inferredQTLpeak, with high allele frequency differences sufficient to explain observed phenotypic differentiation. One of these, the R2R3MYBtranscription factor Migut.N02661, is a plausible functional candidate and was also strongly associated (r² = 0.27) with trichome phenotype in analyses of wild‐collected admixed individuals. Although functional analyses will be necessary to definitively link molecular variants in Tr14 with trichome divergence, our analyses are a major step in that direction. They point to a simple, and parallel, genetic basis for one axis ofMimulus guttatusadaptation to an extreme habitat, suggest a broadly conserved genetic basis for trichome variation across flowering plants and pave the way for further investigations of this challenging case of microgeographic incipient speciation.

    

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4. Combining Experimental Evolution and Genomics to Understand How Seed Beetles Adapt to a Marginal Host Plant

   https://doi.org/10.3390/genes11040400  

   Rêgo, Alexandre ; Chaturvedi, Samridhi ; Springer, Amy ; Lish, Alexandra M. ; Barton, Caroline L. ; Kapheim, Karen M. ; Messina, Frank J. ; Gompert, Zachariah ( April 2020 , Genes)

   Genes that affect adaptive traits have been identified, but our knowledge of the genetic basis of adaptation in a more general sense (across multiple traits) remains limited. We combined population-genomic analyses of evolve-and-resequence experiments, genome-wide association mapping of performance traits, and analyses of gene expression to fill this knowledge gap and shed light on the genomics of adaptation to a marginal host (lentil) by the seed beetle Callosobruchus maculatus. Using population-genomic approaches, we detected modest parallelism in allele frequency change across replicate lines during adaptation to lentil. Mapping populations derived from each lentil-adapted line revealed a polygenic basis for two host-specific performance traits (weight and development time), which had low to modest heritabilities. We found less evidence of parallelism in genotype-phenotype associations across these lines than in allele frequency changes during the experiments. Differential gene expression caused by differences in recent evolutionary history exceeded that caused by immediate rearing host. Together, the three genomic datasets suggest that genes affecting traits other than weight and development time are likely to be the main causes of parallel evolution and that detoxification genes (especially cytochrome P450s and beta-glucosidase) could be especially important for colonization of lentil by C. maculatus. 

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5. Genetic and functional variation across regional and local scales is associated with climate in a foundational prairie grass

   https://doi.org/10.1111/nph.16547  

   Hoffman, Ava M. ; Bushey, Julie A. ; Ocheltree, Troy W. ; Smith, Melinda D. ( April 2020 , New Phytologist)

   Global change forecasts in ecosystems require knowledge of within‐species diversity, particularly of dominant species within communities. We assessed site‐level diversity and capacity for adaptation inBouteloua gracilis, the dominant species in the Central US shortgrass steppe biome.

   We quantified genetic diversity from 17 sites across regional scales, north to south from New Mexico to South Dakota, and local scales in northern Colorado. We also quantified phenotype and plasticity within and among sites and determined the extent to which phenotypic diversity inB. graciliswas correlated with climate.

   Genome sequencing indicated pronounced population structure at the regional scale, and local differences indicated that gene flow and/or dispersal may also be limited. Within a common environment, we found evidence of genetic divergence in biomass‐related phenotypes, plasticity, and phenotypic variance, indicating functional divergence and different adaptive potential. Phenotypes were differentiated according to climate, chiefly median Palmer Hydrological Drought Index and other aridity metrics.

   Our results indicate conclusive differences in genetic variation, phenotype, and plasticity in this species and suggest a mechanism explaining variation in shortgrass steppe community responses to global change. This analysis ofB. gracilisintraspecific diversity across spatial scales will improve conservation and management of the shortgrass steppe ecosystem in the future.

    

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