Background: Evolution of cooperation is a major, extensively studied problem in evolutionary biology. Cooperation is beneficial for a population as a whole but costly for the bearers of social traits such that cheaters enjoy a selective advantage over cooperators. Here, we focus on coevolution of cooperators and cheaters in a multi-level selection framework, by modeling competition among groups composed of cooperators and cheaters. Cheaters enjoy a reproductive advantage over cooperators at the individual level, independent of the presence of cooperators in the group. Cooperators carry a social trait that provides a fitness advantage to the respective groups.
Results: In the case of absolute fitness advantage, where the survival probability of a group is independent of the composition of other groups, the survival of cooperators does not correlate with the presence of cheaters. By contrast, in the case of relative fitness advantage, where the survival probability of a group depends on the composition of all groups, the survival of cooperators positively correlates with the presence of cheaters. Increasing the strength of the social trait alone fails to ensure survival of cooperators, and the increase of the reproduction advantage of the cheaters is necessary to avoid population extinction. This unexpected effect comes from multilevel selection whereby cheaters at the individual level become altruists at the group level, enabling overall growth of the population that is essential for the persistence of cooperators. We validate these theoretical results with an agent-based model of a bacterial biofilm where emergence of the cooperative trait is facilitated by the presence of cheaters, leading to evolution of new spatial organization.
Conclusions: Our results suggest that, counterintuitively, cheaters often promote, not destabilize, evolution of cooperation.
Background: Circular RNAs (circRNAs) have been recognized as key contributors to tumorigenesis in various cancer types. However, the biological functions and mechanisms of hypoxia-induced exosomal circRNAs in pancreatic cancer (PC) are largely unknown.
Methods: A comparison of hypoxic versus normoxic PC cells was conducted using RNA sequencing to identify differentially expressed circRNAs. Quantitative reverse transcription PCR (RT-qPCR) and in situ hybridization (ISH) was used to assess the expression levels of circ_0006840 in PC patients. In vitro and in vivo experiments were conducted to validate the biological functions of circ_0006840 in PC. Gene expression regulation was observed by RNA pull-down, ChIP, RIP, dual-luciferase assays. Gain- and loss-of-function studies were performed to observe the impacts of circRNA and its partners on the invasion, and metastasis of PC cells.
Results: We identified differentially expressed circRNAs in exosomes derived from normoxic and hypoxic PC cells through RNA sequencing. We show that high level of circ_0006840 was found in PC tissues and serum exosomes, which was associated with poor patient survival. Both in vitro and in vivo, circ_0006840 enhanced PC cell proliferation and migration. At the transcriptional level, HIF1A mediated circ_0006840 activation. WNT inhibitory factor 1 (WIF1), a key component of the WNT signaling pathway, was identified as the primary target of circ_0006840, suppressed at the post-transcriptional level. These findings suggest that circ_0006840, activated by HIF1A, regulated WIF1 transcripts promoting their decay. Exosomal circ_0006840 thus emerges as a potential therapeutic target for PC.
Conclusions: It has been shown that circ_0006840 was transcriptionally activated by HIF1A and specifically regulated WIF1 transcripts, which is considered a potential target for PC therapy.
Background: The molecular mechanisms that underlie adaptive divergence in complex traits can be assessed in traits like animal venoms where variation in gene sequence and expression levels can be directly linked to functional divergence in phenotypes. We used novel metrics for measuring functional divergence based on amino acid variation to assess the impact of coding sequence evolution, gene duplication and loss, and expression variation on the divergence in venom between sister species in two lineages of pitvipers.
Results: In both lineages, coding sequence and expression variation made significant contributions to overall functional divergence whereas genic variation was less important. Locus-specific analyses of two multigene families that encode important venom proteins (serine proteases and metalloproteases) showed that (1) There were differences between lineages in the distributions of locus effect size on functional divergence between Sistrurus (many loci with similar effects) and Bothrops (loci with either small or large effects); (2) A small number of loci were under strong positive selection, but only in serine proteases was the intensity of selection positively correlated with contributions to functional divergence in venom. (3) Patterns of overall serine protease and metalloprotease expression differed between lineages, but there was no association between expression levels of individual genes and contributions to divergence.
Conclusions: Our results show that the genetic underpinnings of early adaptive divergence in snake venoms are multifaceted and vary across lineages. Broadly, sequence and expression divergence both have substantial effects on functional divergence and each of these mechanisms has greater impacts than genic variation.
Changes in endocrine and kidney functions have been associated with spaceflight. Here, we discuss the most relevant evidence about the impact of spaceflight on the cardiometabolic system, the cardiorenal function and the reproductive/gonadal axis. Notably, these changes appear to be interrelated with other organ/system functions, suggesting the need of a systemic approach leading to a more comprehensive understanding of physiological and health-related impacts of the space environment. Therefore, this review will also focus on the need to move space endocrinological research to multi-omics approaches and the implementation of "machine learning" and "data mining" strategies.
Background: Therapeutic peptides have become an important direction in drug discovery because of their high targeting and low side effects, and are used to treat many diseases. Peptides are short-chain molecules formed by connecting amino acids through peptide bonds and play key roles in the body. The stability and production costs of peptides are challenges that need to be overcome for their pharmaceutical applications. Researchers have improved the accuracy of therapeutic peptide sequence function predictions by constructing and integrating peptide features from different sources. However, accurately predicting multi-functional therapeutic peptides is challenging due to the limitations of handcrafted feature properties, which are unable to capture the full complexity of biological systems.
Results: In this study, we introduce a novel method TPpred-CMvL for the prediction of multi-functional therapeutic peptide (MTP) based on a contrastive multi-view learning model. This framework directly integrates semantic information pretraining TAPE from protein large language model and evolutionary information. Subsequently, TPpred-CMvL leverages contrastive multi-view learning to comprehensively capture representations of peptide sequences, thereby enhancing the prediction accuracy of MTPs. We utilized adaptive synthetic sampling and focal loss to address the classification imbalance arising from the long-tailed distribution. The experimental results demonstrate that the proposed method outperforms existing related approaches and exhibits the most advanced performance.
Conclusion: We developed a contrast multi-view learning model TPpred-CMvL utilizing sequential semantic information TAPE and evolutionary information PSSM. Compared with existing related methods, this method achieved state-of-the-art performance. Finally, a web server has been established and is accessible at http://bliulab.net/TPpred-CMvL .
Background: Cooperation among conspecific seeds, which influences germination timing and quantity, can enhance the interspecific competitive ability and environmental adaptability of invasive plants. However, the specific underlying mechanisms require further investigation. This study investigates whether a chemical mechanism of mutual perception exists among seeds of the invasive plant Ambrosia trifida L. and its potential impact on seed germination.
Results: We found that increased seed density and higher concentrations of seed extracts significantly promoted germination rates and reduced germination time in Ambrosia trifida L. seeds. Aggregated seeds germinated earlier and more synchronously than isolated seeds, indicating the presence of seed-to-seed communication mediated by chemical signals. Widely targeted metabolomic analysis identified 527 chemical compounds in the seed extracts, with 150 involved in key metabolic pathways. Notably, secondary metabolites in the shikimates and phenylpropanoids class were enriched, particularly angelicin. Quantitative analysis confirmed that angelicin significantly enhanced germination synchronicity when applied at various concentrations.
Conclusions: Our research findings indicate that Ambrosia trifida seeds communicate through secondary metabolites, with angelicin playing a key role in promoting synchronized germination. This chemical communication among conspecific seeds facilitates the rapid and uniform establishment of populations. Understanding this mechanism provides new insights into plant ecology and offers potential strategies for managing invasive species.
Background: The development of planarians is unique among Spiralians. Instead of the stereotypical spiral cleavage, planarians exhibit a dispersed cleavage. There is no apparent gastrulation, and the morphogenesis of the yolk-feeding embryo remains a mystery. In this study, we examine the subcellular localization of βcatenin-1 and the transcriptomic profile during the early embryonic development of Schmidtea polychroa to shed light on these early events.
Results: The first localization of βcatenin-1 in the nucleus occurs in yolk cells surrounding the embryonic syncytium. By 24 h post-deposition, βcatenin-1 starts to be nuclear in blastomeres, coinciding with the activation of signaling and cell motility genes. During morphogenesis of the yolk-feeding embryo, βcatenin-1 is first localized in the nucleus at one pole (gut and pharynx progenitors) and in epidermal progenitors, and afterward in the embryonic pharynx. At this stage, genes involved in a first morphogenetic event are turned on. Following the yolk ingestion by the embryo, a dramatic transcriptomic shift occurs that coincides with the activation of genes related to cell proliferation. Finally, between 5 and 7 days post-deposition, βcatenin-1 is massively located in the nucleus, and genes involved in the morphogenesis and patterning of the adult tissues get activated.
Conclusions: Our findings provide new insights into the early developmental events of Schmidtea polychroa, including cleavage, the involvement of βcatenin-1 in forming the embryonic tissues, and the morphogenesis of two distinct body plans. These findings are significant to understanding the evolution of the peculiar mode of planarian development.
Background: With the growing availability of reference-grade genome assemblies across diverse taxa, there is an increasing need for efficient and scalable tools for multi-species comparative genomics, including synteny detection. Here, we introduce ntSynt, a scalable utility for computing large-scale multi-genome synteny using an alignment-free, minimizer graph-based approach.
Results: Through benchmarking on vertebrate genomes (~ 3 Gbp) and 11 bee genomes, we demonstrate that ntSynt produces accurate synteny maps with high genome coverage (79-100%) while using modest computational resources (~ 2 h, 34 GB memory).
Conclusions: ntSynt's efficiency and scalability enable large-scale comparative analyses across the tree of life, providing a robust foundation for downstream comparative and functional genomic studies.
Background: Deep-diving cetaceans tolerate acute hypoxia better than their terrestrial ancestors and shallow-diving counterparts. However, our poor understanding of how genetic factors, cellular functions, and physiological characteristics combine to drive hypoxia adaptation in deep-diving cetaceans remains a critical gap.
Results: Here, we studied the genetic basis for this ability by creating a de novo genome assembly for the pygmy sperm whale (Kogia breviceps) and comparatively analyzing genomes from 12 cetacean species, including 2 other deep-diving cetaceans. We also sequenced and compared single-nucleus RNA data from the muscle and heart of the pygmy sperm whale and its terrestrial relative Bos taurus. We found that genetic and cellular changes in the HIF-1 pathway, electron transport chain, glucose and fatty acid catabolism, and heart rate may contribute to hypoxia tolerance in deep-diving cetaceans. Key adaptations include rapid evolution of glycolysis-related genes (PYGM and ENO3), differential expression of HIF-1 pathway genes like ARNT, and accelerated conserved noncoding elements in genes such as ATP5F1E (ATP synthase) and DMD (dystrophin). We found an increase in myocytes and type II cardiomyocytes in the pygmy sperm whale's muscle and heart tissues, which may support energy metabolism and homeostasis during deep dives.
Conclusions: These findings suggest deep-diving cetaceans have unique genetic and cellular adaptations to cope with hypoxia, offering insights into how mammals handle low oxygen levels at the cellular level.
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