AI Article Synopsis
- The study investigates how certain genetic traits reemerge in nature, specifically looking at stickleback fish transitioning from marine to freshwater habitats.
- Researchers identified numerous genomic regions that consistently evolve during this colonization, demonstrating that these changes can occur rapidly due to existing genetic variations and connections between beneficial traits.
- The findings not only show predictable patterns in sticklebacks but also suggest similar evolutionary mechanisms may apply to other species, like Darwin's finches, highlighting common features across different organisms.
Article Abstract
Similar forms often evolve repeatedly in nature, raising long-standing questions about the underlying mechanisms. Here, we use repeated evolution in stickleback to identify a large set of genomic loci that change recurrently during colonization of freshwater habitats by marine fish. The same loci used repeatedly in extant populations also show rapid allele frequency changes when new freshwater populations are experimentally established from marine ancestors. Marked genotypic and phenotypic changes arise within 5 years, facilitated by standing genetic variation and linkage between adaptive regions. Both the speed and location of changes can be predicted using empirical observations of recurrence in natural populations or fundamental genomic features like allelic age, recombination rates, density of divergent loci, and overlap with mapped traits. A composite model trained on these stickleback features can also predict the location of key evolutionary loci in Darwin's finches, suggesting that similar features are important for evolution across diverse taxa.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213234 | PMC |
| http://dx.doi.org/10.1126/sciadv.abg5285 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
AI Interventions to Alleviate Healthcare Shortages and Enhance Work Conditions in Critical Care: Qualitative Analysis.
J Med Internet Res
January 2025
ETH Zurich, Zurich, Switzerland.
Background: The escalating global scarcity of skilled health care professionals is a critical concern, further exacerbated by rising stress levels and clinician burnout rates. Artificial intelligence (AI) has surfaced as a potential resource to alleviate these challenges. Nevertheless, it is not taken for granted that AI will inevitably augment human performance, as ill-designed systems may inadvertently impose new burdens on health care workers, and implementation may be challenging.
View Article and Find Full Text PDFRegression tools for chemical release modeling: An additive manufacturing case study.
J Occup Environ Hyg
January 2025
Center for Environmental Solutions and Emergency Response, United States Environmental Protection Agency, Cincinnati, Ohio.
Chemical release data are essential for performing chemical risk assessments to understand the potential exposures arising from industrial processes. Often, these data are unknown or unavailable and must be estimated. A case study of volatile organic compound releases during extrusion-based additive manufacturing is used here to explore the viability of various regression methods for predicting chemical releases to inform chemical assessments.
View Article and Find Full Text PDFA multi-level feature fusion artificial neural network for classification of acoustic emission signals.
Ann N Y Acad Sci
January 2025
Hainan Institute, Zhejiang University, Sanya, China.
In this paper, we introduce FUSION-ANN, a novel artificial neural network (ANN) designed for acoustic emission (AE) signal classification. FUSION-ANN comprises four distinct ANN branches, each housing an independent multilayer perceptron. We extract denoised features of speech recognition such as linear predictive coding, Mel-frequency cepstral coefficient, and gammatone cepstral coefficient to represent AE signals.
View Article and Find Full Text PDFRetrospective exploratory evaluation of individual pigs' behaviour involved in tail biting during rearing and fattening.
PLoS One
January 2025
Friedrich-Loeffler-Institut, Institute of Animal Welfare and Animal Husbandry, Celle, Germany.
Tail biting is one of the biggest welfare problems in pigs. However, depending on the individuals involved (e.g.
View Article and Find Full Text PDFOpen Soil Spectral Library (OSSL): Building reproducible soil calibration models through open development and community engagement.
PLoS One
January 2025
Woodwell Climate Research Center, Falmouth, MA, United States of America.
Soil spectroscopy is a widely used method for estimating soil properties that are important to environmental and agricultural monitoring. However, a bottleneck to its more widespread adoption is the need for establishing large reference datasets for training machine learning (ML) models, which are called soil spectral libraries (SSLs). Similarly, the prediction capacity of new samples is also subject to the number and diversity of soil types and conditions represented in the SSLs.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!