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Abstract As generative AI becomes ubiquitous, writers must decide if, when, and how to incorporate generative AI into their writing process. Educators must sort through their role in preparing students to make these decisions in a quickly evolving technological landscape. We created an AI-enabled writing tool that provides scaffolded use of a large language model as part of a research study on integrating generative AI into an upper division STEM writing-intensive course. Drawing on decades of research on integrating digital tools into instruction and writing research, we discuss the framework that drove our initial design considerations and instructional resources. We then share our findings from a year of design-based implementation research during the 2023–2024 academic year. Our original instruction framework identified the need for students to understand, access, prompt, corroborate, and incorporate the generative AI use effectively. In this paper, we explain the need for students to think first, before using AI, move through good enough prompting to agentic iterative prompting, and reflect on their use at the end. We also provide emerging best practices for instructors, beginning with identifying learning objectives, determining the appropriate AI role, revising the content, reflecting on the revised curriculum, and reintroducing learning as needed. We end with an indication of our future directions. 

Abstract Recombination is central to genetics and to evolution of sexually reproducing organisms. However, obtaining accurate estimates of recombination rates, and of how they vary along chromosomes, continues to be challenging. To advance our ability to estimate recombination rates, we present Hi-reComb, a new method and software for estimation of recombination maps from bulk gamete chromosome conformation capture sequencing (Hi-C). Simulations show that Hi-reComb produces robust, accurate recombination landscapes. With empirical data from sperm of five fish species we show the advantages of this approach, including joint assessment of recombination maps and large structural variants, map comparisons using bootstrap, and workflows with trio phasing vs. Hi-C phasing. With off-the-shelf library construction and a straightforward rapid workflow, our approach will facilitate routine recombination landscape estimation for a broad range of studies and model organisms in genetics and evolutionary biology. Hi-reComb is open-source and freely available at https://github.com/millanek/Hi-reComb. 

Abstract The rate at which mutations arise is a fundamental parameter of biology. Despite progress in measuring germline mutation rates across diverse taxa, such estimates are missing for much of Earth's biodiversity. Here, we present the first estimate of a germline mutation rate from the phylum Mollusca. We sequenced three pedigreed families of the white abalone Haliotis sorenseni, a long-lived, large-bodied, and critically endangered mollusk, and estimated a de novo mutation rate of 8.60 × 10−9 single nucleotide mutations per site per generation. This mutation rate is similar to rates measured in vertebrates with comparable generation times and longevity to abalone, and higher than mutation rates measured in faster-reproducing invertebrates. The spectrum of de novo mutations is also similar to that seen in vertebrate species, although an excess of rare C > A polymorphisms in wild individuals suggests that a modifier allele or environmental exposure may have once increased C > A mutation rates. We use our rate to infer baseline effective population sizes (Ne) across multiple Pacific abalone and find that abalone persisted over most of their evolutionary history as large and stable populations, in contrast to extreme fluctuations over recent history and small census sizes in the present day. We then use our mutation rate to infer the timing and pattern of evolution of the abalone genus Haliotis, which was previously unknown due to few fossil calibrations. Our findings are an important step toward understanding mutation rate evolution and they establish a key parameter for conservation and evolutionary genomics research in mollusks. 

Although most ancient DNA studies have focused on the last 50,000 years, paleogenomic approaches can now reach into the early Pleistocene, an epoch of repeated environmental changes that shaped present-day biodiversity. Emerging deep-time genomic transects, including from DNA preserved in sediments, will enable inference of adaptive evolution, discovery of unrecognized species, and exploration of how glaciations, volcanism, and paleomagnetic reversals shaped demography and community composition. In this Review, we explore the state-of-the-art in paleogenomics and discuss key challenges, including technical limitations, evolutionary divergence and associated biases, and the need for more precise dating of remains and sediments. We conclude that with improvements in laboratory and computational methods, the emerging field of deep-time paleogenomics will expand the range of questions addressable using ancient DNA. 

As the Arctic continues to warm, woody shrubs are expected to expand northward. This process, known as ‘shrubification,’ has important implications for regional biodiversity, food web structure, and high-latitude temperature amplification. While the future rate of shrubification remains poorly constrained, past records of plant immigration to newly deglaciated landscapes in the Arctic may serve as useful analogs. We provide one new postglacial Holocene sedimentary ancient DNA (sedaDNA) record of vascular plants from Iceland and place a second Iceland postglacialsedaDNA record on an improved geochronology; both show Salicaceae present shortly after deglaciation, whereas Betulaceae first appears more than 1000 y later. We find a similar pattern of delayed Betulaceae colonization in eight previously published postglacialsedaDNA records from across the glaciated circum North Atlantic. In nearly all cases, we find that Salicaceae colonizes earlier than Betulaceae and that Betulaceae colonization is increasingly delayed for locations farther from glacial-age woody plant refugia. These trends in Salicaceae and Betulaceae colonization are consistent with the plant families’ environmental tolerances, species diversity, reproductive strategies, seed sizes, and soil preferences. As these reconstructions capture the efficiency of postglacial vascular plant migration during a past period of high-latitude warming, a similarly slow response of some woody shrubs to current warming in glaciated regions, and possibly non-glaciated tundra, may delay Arctic shrubification and future changes in the structure of tundra ecosystems and temperature amplification. 

As the Arctic continues to warm, woody shrubs are expected to expand northward. This process, known as ‘shrubification,’ has important implications for regional biodiversity, food web structure, and high-latitude temperature amplification. While the future rate of shrubification remains poorly constrained, past records of plant immigration to newly deglaciated landscapes in the Arctic may serve as useful analogs. We provide one new postglacial Holocene sedimentary ancient DNA (sedaDNA) record of vascular plants from Iceland and place a second Iceland postglacialsedaDNA record on an improved geochronology; both show Salicaceae present shortly after deglaciation, whereas Betulaceae first appears more than 1000 y later. We find a similar pattern of delayed Betulaceae colonization in eight previously published postglacialsedaDNA records from across the glaciated circum North Atlantic. In nearly all cases, we find that Salicaceae colonizes earlier than Betulaceae and that Betulaceae colonization is increasingly delayed for locations farther from glacial-age woody plant refugia. These trends in Salicaceae and Betulaceae colonization are consistent with the plant families’ environmental tolerances, species diversity, reproductive strategies, seed sizes, and soil preferences. As these reconstructions capture the efficiency of postglacial vascular plant migration during a past period of high-latitude warming, a similarly slow response of some woody shrubs to current warming in glaciated regions, and possibly non-glaciated tundra, may delay Arctic shrubification and future changes in the structure of tundra ecosystems and temperature amplification. 

Natural history collections are invaluable repositories of biological information that provide an unrivaled record of Earth's biodiversity. Museum genomics—genomics research using traditional museum and cryogenic collections and the infrastructure supporting these investigations—has particularly enhanced research in ecology and evolutionary biology, the study of extinct organisms, and the impact of anthropogenic activity on biodiversity. However, leveraging genomics in biological collections has exposed challenges, such as digitizing, integrating, and sharing collections data; updating practices to ensure broadly optimal data extraction from existing and new collections; and modernizing collections practices, infrastructure, and policies to ensure fair, sustainable, and genomically manifold uses of museum collections by increasingly diverse stakeholders. Museum genomics collections are poised to address these challenges and, with increasingly sensitive genomics approaches, will catalyze a future era of reproducibility, innovation, and insight made possible through integrating museum and genome sciences. 

Many humans carry genes from Neanderthals, a legacy of past admixture. Existing methods detect this archaic hominin ancestry within human genomes using patterns of linkage disequilibrium or direct comparison to Neanderthal genomes. Each of these methods is limited in sensitivity and scalability. We describe a new ancestral recombination graph inference algorithm that scales to large genome-wide datasets and demonstrate its accuracy on real and simulated data. We then generate a genome-wide ancestral recombination graph including human and archaic hominin genomes. From this, we generate a map within human genomes of archaic ancestry and of genomic regions not shared with archaic hominins either by admixture or incomplete lineage sorting. We find that only 1.5 to 7% of the modern human genome is uniquely human. We also find evidence of multiple bursts of adaptive changes specific to modern humans within the past 600,000 years involving genes related to brain development and function.