Pan‐Arctic Peatlands Have Expanded During Recent Warming - J. Handley; R. E. Fewster; T. G. Sim; S. Hodson; B. Parker; K. Crichton; D. Charman; K. Anderson; M. Garneau; M. Väliranta; D. W. Beilman; G. T. Swindles; et al. (Global Change Biology, 2026)
The fate of carbon stored in Arctic peatlands remains uncertain because of the complex nature of the effects of climate change on permafrost and peatland carbon cycling. Expansion and/or shrinkage of Arctic peatlands under climate change also remain unknown due to lack of ground data and difficulties detecting changes in the extent of these ecosystems, meaning that land surface model predictions currently inadequately quantify Arctic terrestrial carbon storage changes. Pan‐Arctic shifts in peatland extent would profoundly change the fate of carbon in the terrestrial Arctic. Here, we tackle this knowledge gap by answering three main questions: (a) has lateral expansion occurred in Arctic peatlands as a response to recent warming? (b) if so, how fast has this occurred? (c) how does the response vary regionally? To answer these, we collected a dataset (12 peatland sites, 91 peat cores) combining peat cores collected across two latitudinal (north–south) transects: one in the European Arctic and one in the Canadian Arctic. In each region, we selected three peatland sites, with cores collected from transects spanning the peat‐edge to the peat‐centre. Our large‐scale dataset shows that peatlands have expanded, often rapidly, with some rates exceeding ~1 m per year since 1950 AD. This rapid expansion has occurred during a period of widespread Arctic warming and is still ongoing: two thirds (8/12) of our peatland sites evidence new peat formation after ~1990 AD based on age‐depth models constrained by 14 C and 210 Pb dating. Given that our sites comprise a broad range of Arctic conditions, we expect peatland expansion to be a pan‐Arctic phenomenon. Within specific regions, there are constraints on peat expansion including topographical limits, but we present the basis for future work to estimate pan‐Arctic peatland expansion, plus the associated carbon cycle implications under future climate change.

Genomic analysis of Vanessa tameamea, the threatened Hawaiian endemic butterfly, reveals population genetic structure relevant to conservation efforts - Haley E. Arnold; Julian R. Dupuis; Daniel Rubinoff; William P. Haines; Michael San Jose; Renee L. Corpuz; Angela N. Kauwe; Tyler J. Simmonds; Scott M. Geib; Sheina B. Sim (Conservation Genetics, 2025)
Patterns of divergence and speciation on islands have long been of interest in the broader study of evolution. Hawaiʻi’s endemic Kamehameha butterfly ( Vanessa tameamea ) is experiencing population decline, but because of its high vagility and assumed genetic homogeneity as a species, its population structure has not been investigated. To evaluate V. tameamea genetic variation across the Hawaiian Islands, we assembled a reference quality genome assembly for the species using HiFi and HiC reads and performed range-wide population genetic analyses using ddRAD sequencing data. A discriminant analysis of principal components (DAPC) revealed that, contrary to prior assumptions, V. tameamea populations appear to be diverging based on geography, in a pattern similar to other native Hawaiian terrestrial arthropods. Specifically, through demographic history analyses, we find that the distinct population on Kauaʻi is likely to be ancestral, the central islands of Maui, Molokaʻi, and Oʻahu comprise another population, and Hawaiʻi Island forms a third population, with likely more gene exchange with the central islands. Finally, we investigate the SNPs driving differences between groups and find that many are associated with genes that may be relevant to local adaptation to environmental chemicals such as host plant defenses or chemicals introduced by human activity, notably to do with metabolism and detoxification. While much field work remains to investigate any cryptic or phenotypic patterns as well as quantify effective migration, we hope that this work will inform refinement of conservation plans for one of Hawaiʻi’s two native butterflies.

Validation of a laboratory craving assessment and evaluation of 4 different interventions on cravings among adults with overweight or obesity - Ellen K. Pasquale; David R. Strong; Dawn M. Eichen; Carol B. Peterson; D. Eastern Kang-Sim; Kerri N. Boutelle (Appetite, 2024)

Recurrent selection shapes the genomic landscape of differentiation between a pair of host‐specialized haplodiploids that diverged with gene flow - Ashleigh N. Glover; Vitor C. Sousa; Ryan D. Ridenbaugh; Sheina B. Sim; Scott M. Geib; Catherine R. Linnen (Molecular Ecology, 2024)
Understanding the genetics of adaptation and speciation is critical for a complete picture of how biodiversity is generated and maintained. Heterogeneous genomic differentiation between diverging taxa is commonly documented, with genomic regions of high differentiation interpreted as resulting from differential gene flow, linked selection and reduced recombination rates. Disentangling the roles of each of these non‐exclusive processes in shaping genome‐wide patterns of divergence is challenging but will enhance our knowledge of the repeatability of genomic landscapes across taxa. Here, we combine whole‐genome resequencing and genome feature data to investigate the processes shaping the genomic landscape of differentiation for a sister‐species pair of haplodiploid pine sawflies, Neodiprion lecontei and Neodiprion pinetum . We find genome‐wide correlations between genome features and summary statistics are consistent with pervasive linked selection, with patterns of diversity and divergence more consistently predicted by exon density and recombination rate than the neutral mutation rate (approximated by dS). We also find that both global and local patterns of F ST , d XY and π provide strong support for recurrent selection as the primary selective process shaping variation across pine sawfly genomes, with some contribution from balancing selection and lineage‐specific linked selection. Because inheritance patterns for haplodiploid genomes are analogous to those of sex chromosomes, we hypothesize that haplodiploids may be especially prone to recurrent selection, even if gene flow occurred throughout divergence. Overall, our study helps fill an important taxonomic gap in the genomic landscape literature and contributes to our understanding of the processes that shape genome‐wide patterns of genetic variation.

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

Global Island Monitoring Scheme (GIMS): a proposal for the long-term coordinated survey and monitoring of native island forest biota - Paulo A. V. Borges; Pedro Cardoso; Holger Kreft; Robert J. Whittaker; Simone Fattorini; Brent C. Emerson; Artur Gil; Rosemary G. Gillespie; Thomas J. Matthews; Ana M. C. Santos; Manuel J. Steinbauer; Christophe Thébaud; et al. (Biodiversity and Conservation, 2018)

Population genomics and comparisons of selective signatures in two invasions of melon fly, Bactrocera cucurbitae (Diptera: Tephritidae) - Julian R. Dupuis; Sheina B. Sim; Michael San Jose; Luc Leblanc; M. Aftab Hoassain; Daniel Rubinoff; Scott M. Geib (Biological Invasions, 2018)

Tree-pulling experiment: an analysis into the mechanical stability of rain trees - Lai Fern Ow; F. R. Harnas; I. G. B. Indrawan; A. Sahadewa; E. K. Sim; H. Rahardjo; E. C. Leong; Y. K. Fong; P. Y. Tan (Trees, 2010)

Exposure to Inorganic Arsenic in Soil Increases Urinary Inorganic Arsenic Concentrations of Residents Living in Old Mining Areas - Andrea L. Hinwood; Malcolm R. Sim; Damien Jolley; Nick de Klerk; Elisa B. Bastone; Jim Gerostamoulos; Olaf H. Drummer (Environmental Geochemistry and Health, 2004)

Construction of a BAC library and generation of BAC end sequence-tagged connectors for genome sequencing of the African malaria mosquito Anopheles gambiae - Y. S. Hong; J. R. Hogan; X. Wang; A. Sarkar; C. Sim; B. J. Loftus; C. Ren; E. R. Huff; J. L. Carlile; K. Black; H.-B. Zhang; M. J. Gardner; et al. (Molecular Genetics and Genomics, 2003)

Angiostatin and Endostatin: Endogenous Inhibitors of Tumor Growth - B. Kim Lee Sim; Nicholas J. MacDonald; Edward R. Gubish (Cancer and Metastasis Reviews, 2000)

Mapping the bovine factor H gene to Chromosome 16 by SSCP analysis - J. L. Williams; D. H. Lester; V. M. Teres; W. Barendse; R. B. Sim; C. J. Soames (Mammalian Genome, 1997)