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Synopsis Interdisciplinary collaborations are essential for addressing complex global challenges, yet forming and sustaining such teams is often hindered by institutional barriers, differences in discipline-specific languages, and cultural divides. Existing tools and platforms frequently fail to foster the deep, ongoing engagement necessary for successful interdisciplinary work. This paper proposes a novel web-based platform designed to stimulate and support interdisciplinary collaborations by integrating social media elements, such as user-friendly communication tools, algorithms for identifying and connecting individuals with complementary and unique skills, and smart suggestions for potential collaborators. The platform would facilitate building and maintaining the engagement of target users, and provide guardrails to engender community trust, with a goal to also tackle issues related to power dynamics, cultural differences, institutional structures, and varying levels of prestige or funding. By addressing these challenges, the proposed platform would enable and accelerate productive interdisciplinary research and collaborative ideation, and ultimately stimulate more innovative and effective solutions to complex scientific and societal problems. 

Synopsis A major goal of research in evolution and genetics is linking genotype to phenotype. This work could be direct, such as determining the genetic basis of a phenotype by leveraging genetic variation or divergence in a developmental, physiological, or behavioral trait. The work could also involve studying the evolutionary phenomena (e.g., reproductive isolation, adaptation, sexual dimorphism, behavior) that reveal an indirect link between genotype and a trait of interest. When the phenotype diverges across evolutionarily distinct lineages, this genotype-to-phenotype problem can be addressed using phylogenetic genotype-to-phenotype (PhyloG2P) mapping, which uses genetic signatures and convergent phenotypes on a phylogeny to infer the genetic bases of traits. The PhyloG2P approach has proven powerful in revealing key genetic changes associated with diverse traits, including the mammalian transition to marine environments and transitions between major mechanisms of photosynthesis. However, there are several intermediate traits layered in between genotype and the phenotype of interest, including but not limited to transcriptional profiles, chromatin states, protein abundances, structures, modifications, metabolites, and physiological parameters. Each intermediate trait is interesting and informative in its own right, but synthesis across data types has great promise for providing a deep, integrated, and predictive understanding of how genotypes drive phenotypic differences and convergence. We argue that an expanded PhyloG2P framework (the PhyloG2P matrix) that explicitly considers intermediate traits, and imputes those that are prohibitive to obtain, will allow a better mechanistic understanding of any trait of interest. This approach provides a proxy for functional validation and mechanistic understanding in organisms where laboratory manipulation is impractical. 

Abstract Conflict between genes inherited from the mother (matrigenes) and the father (patrigenes) is predicted to arise during social interactions among offspring if these genes are not evenly distributed among offspring genotypes. This intragenomic conflict drives parent-specific transcription patterns in offspring resulting from parent-specific epigenetic modifications. Previous tests of the kinship theory of intragenomic conflict in honey bees (Apis mellifera) provided evidence in support of theoretical predictions for variation in worker reproduction, which is associated with extreme variation in morphology and behavior. However, more subtle behaviors – such as aggression – have not been extensively studied. Additionally, the canonical epigenetic mark (DNA methylation) associated with parent-specific transcription in plant and mammalian model species does not appear to play the same role as in honey bees, and thus the molecular mechanisms underlying intragenomic conflict in this species is an open area of investigation. Here, we examined the role of intragenomic conflict in shaping aggression in honey bee workers through a reciprocal cross design and Oxford Nanopore direct RNA sequencing. We attempted to probe the underlying regulatory basis of this conflict through analyses of parent-specific RNA m6A and alternative splicing patterns. We report evidence that intragenomic conflict occurs in the context of honey bee aggression, with increased paternal and maternal allele-biased transcription in aggressive compared to non-aggressive bees, and higher paternal allele-biased transcription overall. However, we found no evidence to suggest that RNA m6A or alternative splicing mediate intragenomic conflict in this species.