How novel traits originate in evolution is still one of the most perplexing questions in Evolutionary Biology. Building on a previous account of evolutionary innovation, I here propose that evolutionary novelties are those individualized characters that are not homologous to any characters in the ancestor. To clarify this definition, I here provide a detailed analysis of the concepts of "character individuality" and "homology" first, before addressing their role for our understanding of evolutionary innovation. I will argue (1) that functional as well as structural considerations are important for character individualization; and (2) that compositional (structural) and positional homology need to be clearly distinguished to properly describe the evolutionary transformations of hierarchically structured characters. My account will therefore integrate functional and structural perspectives and put forward a new multi-level view of character identity and transformation.
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http://dx.doi.org/10.1002/jmor.21522 | DOI Listing |
Sci Rep
January 2025
College of Architecture and Civil Engineering, Xinyang Normal University, Xinyang, 464000, China.
The construction industry is generally characterized by high emissions, making its transition to low-carbon practices essential for achieving a low-carbon economy. However, due to information asymmetry, there remains a gap in research regarding the strategic interactions and reward/punishment mechanisms between governments and firms throughout this transition. This paper addresses this gap by investigating probabilistic and static reward and punishment evolutionary games.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
February 2025
Aix-Marseille Université-CNRS UMR 7283, Institut de Microbiologie de la Méditerranée and Turing Center for Living Systems, Marseille 13009, France.
Despite growing awareness of their importance in soil ecology, the genetic and physiological traits of bacterial predators are still relatively poorly understood. In the course of a predator evolution experiment, we identified a class of genotypes leading to enhanced predation against diverse species. RNA-seq analysis demonstrated that this phenotype is linked to the constitutive activation of a predation-specific program.
View Article and Find Full Text PDFHum Genet
January 2025
TCS Research, Tata Consultancy Services, Hyderabad, India.
Variants of uncertain significance (VUS) represent variants that lack sufficient evidence to be confidently associated with a disease, thus posing a challenge in the interpretation of genetic testing results. Here we report an improved method for predicting the VUS of Arylsulfatase A (ARSA) gene as part of the Critical Assessment of Genome Interpretation challenge (CAGI6). Our method uses a transfer learning approach that leverages a pre-trained protein language model to predict the impact of mutations on the activity of the ARSA enzyme, whose deficiency is known to cause a rare genetic disorder, metachromatic leukodystrophy.
View Article and Find Full Text PDFEnviron Microbiol
January 2025
Trivedi School of BioSciences and Koita Centre for Digital Health, Ashoka University, Sonipat, India.
Evolutionary novelty has been one of the central themes in the field of evolutionary biology for many years. Structural and functional innovations such as scales in the reptiles, fins in the fishes and mammary glands in the mammals have been the focus of the studies. Insights obtained from these studies have shaped the criterion for the identification of novelty as well as provide the framework for studying novelty.
View Article and Find Full Text PDFAlzheimers Dement
January 2025
Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.
Introduction: Traditional multivariate methods for neuroimaging studies overlook the interdependent relationship between brain features. This study addresses this gap by analyzing relative brain volumetric patterns to capture how Alzheimer's disease (AD) and genetics influence brain structure along the disease continuum.
Methods: This study analyzed data from participants across the AD continuum from the Alzheimer's and Families (ALFA) and Alzheimer's Disease Neuroimaging Initiative (ADNI) studies.
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