Sequence Evolution Research Articles

Insights into Genetic and Antigenic Characteristics of Influenza A(H1N1)pdm09 Viruses Circulating in Sicily During the Surveillance Season 2023-2024: The Potential Effect on the Seasonal Vaccine Effectiveness.

After disruption in the influenza circulation due to the emergence of SARS-CoV-2, the intensity of seasonal outbreaks has returned to the pre-pandemic levels. This study aimed to evaluate the evolution and variability of whole-genome sequences of A(H1N1)pdm09, the predominant influenza virus in Sicily (Italy) during the season 2023-2024. The potential vaccine efficacy was calculated using the pepitope model based on amino acid changes in the dominant epitope of hemagglutinin. The HA gene sequences showed several amino acid substitutions, some of which were within the major antigenic sites. The phylogenetic analysis showed that Sicilian strains grouped into two main genetic clades (6B.1A.5a.2a.1 and 6B.1A.5a.2a) and several subclades. Notably, about 40% of sequences partially drifted from the WHO-recommended vaccine strain A/Victoria/4897/2022 for the Northern Hemisphere. These sequences mostly belonged to the subclades C.1.8 and C.1.9 and harboured the amino acid mutations responsible for the modest predicted vaccine efficacy (E = 38.12% of 53%, pepitope = 0) against these viruses. Amino acid substitutions in other gene segments were also found. Since influenza viruses are constantly evolving, genomic surveillance is crucial in monitoring their molecular evolution and the occurrence of genetic and antigenic changes, and, thus, their potential impact on vaccine efficacy.

Evolutionary Sequences and Structural Information-driven Reconstruction of New Insulin-like Growth Factor-I Peptide Variants.

Insulin-like growth factor-I (IGF-I) is crucial in controlling cell growth, proliferation, and apoptosis. Its strong link to the development of cancers such as breast, prostate, lung, thyroid, and colorectal has positioned the IGF-1 signalling pathway as a promising target for novel cancer therapies. When activated, the IGF-1 receptor (IGF-1R) binds to IGF-I, playing a central role in promoting tumour cell growth and survival. In this study, we combined evolutionary sequences with structural and functional data of IGF-1 to reconstruct ancestral sequences and design novel IGF-1 peptide variants. The insulin-like growth factor system exhibits a vast sequence diversity, yet it shares a similar structural topology with conserved three pairs of disulfide linkages. Our study reveals that IGF-1 is associated with the IGF system of cell surface receptors through protein-protein interactions. Reconstructed IGF-1 variants show similar structure fold to reported viral IGF-1 competitive antagonists. This new insight guides the design of novel natural IGF-1 mimic peptides. It enhances our understanding of IGF-1's functionality and opens new avenues for the development of therapeutic peptides and small molecules as anticancer agents.

Constitutive sodium permeability in a C. elegans two-pore domain potassium channel

Two-pore domain potassium (K2P) channels play a central role in modulating cellular excitability and neuronal function. The unique structure of the selectivity filter in K2P and other potassium channels determines their ability to allow the selective passage of potassium ions across cell membranes. The nematode C. elegans has one of the largest K2P families, with 47 subunit-coding genes. This remarkable expansion has been accompanied by the evolution of atypical selectivity filter sequences that diverge from the canonical TxGYG motif. Whether and how this sequence variation may impact the function of K2P channels has not been investigated so far. Here, we show that the UNC-58 K2P channel is constitutively permeable to sodium ions and that a cysteine residue in its selectivity filter is responsible for this atypical behavior. Indeed, by performing in vivo electrophysiological recordings and Ca2+ imaging experiments, we demonstrate that UNC-58 has a depolarizing effect in muscles and sensory neurons. Consistently, unc-58 gain-of-function mutants are hypercontracted, unlike the relaxed phenotype observed in hyperactive mutants of many neuromuscular K2P channels. Finally, by combining molecular dynamics simulations with functional studies in Xenopus laevis oocytes, we show that the atypical cysteine residue plays a key role in the unconventional sodium permeability of UNC-58. As predicting the consequences of selectivity filter sequence variations in silico remains a major challenge, our study illustrates how functional experiments are essential to determine the contribution of such unusual potassium channels to the electrical profile of excitable cells.

Complex Models of Sequence Evolution Improve Fit, but not Gene Tree Discordance, for Tetrapod Mitogenomes.

Variation in gene tree estimates is widely observed in empirical phylogenomic data and is often assumed to be the result of biological processes. However, a recent study using tetrapod mitochondrial genomes to control for biological sources of variation due to their haploid, uniparentally inherited, and non-recombining nature found that levels of discordance among mitochondrial gene trees were comparable to those found in studies that assume only biological sources of variation. Additionally, they found that several of the models of sequence evolution chosen to infer gene trees were doing an inadequate job fitting the sequence data. These results indicated that significant amounts of gene tree discordance in empirical data may be due to poor fit of sequence evolution models, and that more complex and biologically realistic models may be needed. To test how the fit of sequence evolution models relates to gene tree discordance, we analyzed the same mitochondrial datasets as the previous study using two additional, more complex models of sequence evolution that each includes a different biologically realistic aspect of the evolutionary process: a covarion model to incorporate site-specific rate variation across lineages (heterotachy), and a partitioned model to incorporate variable evolutionary patterns by codon position. Our results show that both additional models fit the data better than the models used in the previous study, with the covarion being consistently and strongly preferred as tree size increases. However, even these more preferred models still inferred highly discordant mitochondrial gene trees, thus deepening the mystery around what we label the "Mito-Phylo Paradox" and leading us to ask whether the observed variation could, in fact, be biological in nature after all.

Syntenic lncRNA locus exhibits DNA regulatory functions with sequence evolution

Syntenic long non-coding RNAs (lncRNAs) often show limited sequence conservation across species, prompting concern in the field. This study delves into functional signatures of syntenic lncRNAs between humans and zebrafish. Syntenic lncRNAs are highly expressed in zebrafish, with ∼90 % located near protein-coding genes, either in sense or antisense orientation. During early zebrafish development and in human embryonic stem cells (H1-hESC), syntenic lncRNA loci are enriched with cis-regulatory repressor signatures, influencing the expression of development-associated genes. In later zebrafish developmental stages and specific human cell lines, these syntenic lncRNA loci function as enhancers or transcription start sites (TSS) for protein-coding genes. Analysis of transposable elements (TEs) in syntenic lncRNA sequences revealed intriguing patterns: human lncRNAs are enriched in simple repeat elements, while their zebrafish counterparts show enrichment in LTR elements. This sequence evolution likely arises from post-rearrangement mutations that enhance DNA elements or cis-regulatory functions. It may also contribute to vertebrate innovation by creating novel transcription factor binding sites within the locus. This study highlights the conserved functionality of syntenic lncRNA loci through DNA elements, emphasizing their conserved roles across species despite sequence divergence.

Drivers of interlineage variability in mitogenomic evolutionary rates in Platyhelminthes.

Studies of forces driving interlineage variability in the evolutionary rates (both sequence and architecture) of mitochondrial genomes often produce contradictory results. Flatworms (Platyhelminthes) exhibit the fastest-evolving mitogenomic sequences among all bilaterian phyla. To test the effects of multiple factors previously associated with different aspects of mitogenomic evolution, we used mitogenomes of 223 flatworm species, phylogenetic multilevel regression models, and causal inference. Thermic host environment (endothermic vs. ectothermic) had nonsignificant impacts on both sequence evolution and mitogenomic size. Mitogenomic gene order rearrangements (GORR) were mostly positively correlated with mitogenomic size (R2 ≈ 20-30%). Longevity was not (negatively) correlated with sequence evolution in flatworms. The predominantly free-living "turbellaria" exhibited much shorter branches and faster-evolving mitogenomic architecture than parasitic Neodermata. As a result, "parasitism" had a strong explanatory power on the branch length variability (>90%), and there was a negative correlation between GORR and branch length. However, the stem branch of Neodermata comprised 63.6% of the total average branch length. This evolutionary period was also marked by a high rate of gene order rearrangements in the ancestral Neodermata. We discuss how this period of rapid evolution deep in the evolutionary history may have decoupled sequence evolution rates from longevity and GORR, and overestimated the explanatory power of "parasitism". This study shows that impacts of variables often vary across lineages, and stresses the importance accounting for the episodic nature of evolutionary patterns in studies of mitogenomic evolution.

The Paleogene Forebulge Carbonate Banks, Zagros Foreland Basin, Northern Iraq: their Paleogeography, Basin Evolution, and Economic Implications

The Paleogene sequence of Zagros foreland basin NE Iraq during the Late Paleocene- Middle Eocene is punctuated by linear and disconnected chains of carbonate bank-ramp associations. These carbonate units had developed over the NW-SE trending Paleogene basin forebuldge. Discussion of origin, facies type, and stratigraphic architecture of these banks and associated facies was fully covered by the first part of this research project. In this part the chronostratigraphic synthases of the sequence, the paleogeography, and basin evolution is examined as an integral part of the investigation of the evolution of the Paleogene Zagros foreland basin. Research methods include regional stratigraphic correlation, and biostratigraphic data compilation to infer the chronostratigraphic sequence of the events. The paleogeographic facies mapping and basin history are reviewed accordingly. Research data are collected from 15 master surface sections. In addition to the re-examination and re-interpretation of 40 previously studied surface and subsurface well logs, which are compiled for basin-wide study and regional paleogeographic mapping. The analysis of the compiled biostratigraphic data shows that the inferred age of the associated stratigraphic units is as follows: Sinjar Formation. (E. Thanetian – L. Ypresian), Khurmala Formation (Ypresian - E. Lutetian), Kolosh Formation (Daian -Thanetian), and Aaliji Formation (Danian - Ypresian). Based on this chronostratigraphic synthesis, the basin forebulge history during the Paleogene period is divided into 5 stages: the Pre-bank, Early Bank Development, Bank-ramp Development, Back-bank Lagoon, and Lagoonal dolomitization stage. The paleogeography and paleofacies maps of each stage is discussed in terms of the basin forebulge evolution. An alternative hydrocarbon play of the forebulge-controlled Paleogene sequence is discussed, with a case study from the Sufaiyah oil field of northwest Iraq.

Evolutionary Innovations in Conserved Regulatory Elements Associate With Developmental Genes in Mammals.

Transcriptional enhancers orchestrate cell type- and time point-specific gene expression programs. Genetic variation within enhancer sequences is an important contributor to phenotypic variation including evolutionary adaptations and human disease. Certain genes and pathways may be more prone to regulatory evolution than others, with different patterns across diverse organisms, but whether such patterns exist has not been investigated at a sufficient scale. To address this question, we identified signatures of accelerated sequence evolution in conserved enhancer elements throughout the mammalian phylogeny at an unprecedented scale. While different genes and pathways were enriched for regulatory evolution in different parts of the tree, we found a striking overall pattern of pleiotropic genes involved in gene regulatory and developmental processes being enriched for accelerated enhancer evolution. These genes were connected to more enhancers than other genes, which was the basis for having an increased amount of sequence acceleration over all their enhancers combined. We provide evidence that sequence acceleration is associated with turnover of regulatory function. Detailed study of one acceleration event in an enhancer of HES1 revealed that sequence evolution led to a new activity domain in the developing limb that emerged concurrently with the evolution of digit reduction in hoofed mammals. Our results provide evidence that enhancer evolution has been a frequent contributor to regulatory innovation at conserved developmental signaling genes in mammals.

Icehouse mixed carbonate and siliciclastic sequence evolution based on 3D seismic analysis: Insights from the Eastern Shelf of the Permian Basin, Texas

Reciprocal model was introduced for mixed carbonate and siliciclastic sequences within the Virgilian (Upper Pennsylvanian – Gzhelian) and Wolfcampian (Lower Cisuralian) on the Eastern Shelf of the Permian Basin in Texas. This model emphasizes carbonate dominance during transgressive and highstand on the slope, and siliciclastic dominance in the basin during lowstand. Contradictory observations from other mixed basins, such as compositionally mixed lithology in slope cores, accumulation of siliciclastics behind carbonate highs on the outer shelf, off-shelf transport of siliciclastics during highstands, and carbonate deposition on the slope during falling stage, require a re-evaluation of the reciprocal model. This research examines mixed sequences in the Cisco Group and maps lithology distribution by integrating geological and geophysical data, using advanced seismic interpretation techniques, wireline-log crossplot analyses, model-based post-stack inversion, probabilistic neural networks, and supervised Bayesian classification. Observations from the investigation are presented at two scales. In ∼400kyr sequences, relative sea level fall starts with carbonate deposition on the slope while siliciclastics persist near the inner shelf. As the falling stage progresses, siliciclastics reach the shelf edge, forming offlapping fans at the toe of the slope, likely truncating part of the siliciclastic topsets. Subsequently, mixed facies were deposited during the early stages of rising relative sea level, followed by carbonate deposition on the slope and shelf throughout transgression. The mixed facies found inland of transgressive carbonates indicate that prodelta siliciclastics mixed with carbonate mud. Occasionally, transgressive carbonates create shelf-edge build ups, hindering the transport of highstand siliciclastics to the slope. In the composite sequence spanning ∼1200kyr, siliciclastic input decreases significantly with the onset of sea-level fall. The fall truncates topsets with limited siliciclastics, preserving carbonate and mixed facies-dominated foresets with offlapping fans at the toe of the slope. This study advances our understanding of mixed sequences, challenges existing models and lays the groundwork for future investigations in similar geological settings.

Molecular clouds as hubs in spiral galaxies: gas inflow and evolutionary sequence

ABSTRACT We decomposed the molecular gas in the spiral galaxy NGC 628 (M74) into multiscale hub-filament structures using the CO (2$-$1) line by the dendrogram algorithm. All leaf structures as potential hubs were classified into three categories, i.e. leaf-HFs-A, leaf-HFs-B and leaf-HFs-C. Leaf-HFs-A exhibit the best hub-filament morphology, which also have the highest density contrast, the largest mass and the lowest virial ratio. We employed the filfinder algorithm to identify and characterize filaments within 185 leaf-HFs-A structures, and fitted the velocity gradients around the intensity peaks. Measurements of velocity gradients provide evidence for gas inflow within these structures, which can serve as a kinematic evidence that these structures are hub-filament structures. The numbers of the associated 21 μm and H α structures and the peak intensities of 7.7 μm, 21 μm, and H α emissions decrease from leaf-HFs-A to leaf-HFs-C. The spatial separations between the intensity peaks of CO and 21 μm structures of leaf-HFs-A are larger than those of leaf-HFs-C. These evidence indicate that leaf-HFs-A are more evolved than leaf-HFs-C. There may be an evolutionary sequence from leaf-HFs-C to leaf-HFs-A. Currently, leaf-HFs-C lack a distinct gravitational collapse process that would result in a significant density contrast. The density contrast can effectively measure the extent of the gravitational collapse and the depth of the gravitational potential of the structure which, in turn, shapes the hub-filament morphology. Combined with the kinematic analysis presented in previous studies, a picture emerges that molecular gas in spiral galaxies is organized into network structures through the gravitational coupling of multiscale hub-filament structures. Molecular clouds, acting as knots within these networks, serve as hubs, which are local gravitational centres and the main sites of star formation.

Identifying Impacts of Contact Tracing on Epidemiological Inference from Phylogenetic Data.

Robust sampling methods are foundational to inferences using phylogenies. Yet the impact of using contact tracing, a type of non-uniform sampling used in public health applications such as infectious disease outbreak investigations, has not been investigated in the molecular epidemiology field. To understand how contact tracing influences a recovered phylogeny, we developed a new simulation tool called SEEPS (Sequence Evolution and Epidemiological Process Simulator) that allows for the simulation of contact tracing and the resulting transmission tree, pathogen phylogeny, and corresponding virus genetic sequences. Importantly, SEEPS takes within-host evolution into account when generating pathogen phylogenies and sequences from transmission histories. Using SEEPS, we demonstrate that contact tracing can significantly impact the structure of the resulting tree, as described by popular tree statistics. Contact tracing generates phylogenies that are less balanced than the underlying transmission process, less representative of the larger epidemiological process, and affects the internal/external branch length ratios that characterize specific epidemiological scenarios. We also examined real data from a 2007-2008 Swedish HIV-1 outbreak and the broader 1998-2010 European HIV-1 epidemic to highlight the differences in contact tracing and expected phylogenies. Aided by SEEPS, we show that the data collection of the Swedish outbreak was strongly influenced by contact tracing even after downsampling, while the broader European Union epidemic showed little evidence of universal contact tracing, agreeing with the known epidemiological information about sampling and spread. Overall, our results highlight the importance of including possible non-uniform sampling schemes when examining phylogenetic trees. For that, SEEPS serves as a useful tool to evaluate such impacts, thereby facilitating better phylogenetic inferences of the characteristics of a disease outbreak. SEEPS is available at github.com/MolEvolEpid/SEEPS.

A putative scenario of how de novo protein-coding genes originate in the Saccharomyces cerevisiae lineage

BackgroundNovel protein-coding genes were considered to be born by re-organization of pre-existing genes, such as gene duplication and gene fusion. However, recent progress of genome research revealed that more protein-coding genes than expected were born de novo, that is, gene origination by accumulating mutations in non-genic DNA sequences. Nonetheless, the in-depth process (scenario) for de novo origination is not well understood.ResultsWe have conceived bioinformatic analysis for sketching a scenario for de novo origination of protein-coding genes. For each de novo protein-coding gene, we firstly identified an edge of a given phylogenetic tree where the gene was born based on parsimony. Then, from a multiple sequence alignment of the de novo gene and its orthologous regions, we constructed ancestral DNA sequences of the gene corresponding to both end nodes of the edge. We finally revealed statistical features observed in evolution between the two ancestral sequences. In the analysis of the Saccharomyces cerevisiae lineage, we have successfully sketched a putative scenario for de novo origination of protein-coding genes. (1) In the beginning was GC-rich genome regions. (2) Neutral mutations were accumulated in the regions. (3) ORFs were extended/combined, and then (4) translation signature (Kozak consensus sequence) was recruited. Interestingly, as the scenario progresses from (2) to (4), the specificity of mutations increases.ConclusionTo the best of our knowledge, this is the first report outlining a scenario of de novo origination of protein-coding genes. Our bioinformatic analysis can capture events that occur during a short evolutionary time by directly observing the evolution of the ancestral sequences from non-genic to genic. This property is suitable for the analysis of fast evolving de novo genes.

Revisiting the massive star-forming complex RCW 122: New millimeter and submillimeter study

In this paper, we present a new multifrequency study of the giant star-forming complex RCW 122. We used molecular data obtained with the ASTE 10 m and the APEX 12 m telescopes, along with infrared observations spanning from 3.6 µm to 870 µm, obtained from available databases. We also incorporated a range of public datasets, including the radio continuum at 3 GHz, narrowband Ha images, and deep JHK photometry. Our analysis focuses mostly on cataloged ATLASGAL sources, showcasing a spectrum of evolutionary stages from infrared dark cloud (IRDC)/high-mass protostellar object (HMPO) to ultra-compact HII region (UCHII), as inferred from preliminary inspections of the public dataset. Based on ASTE HCO+(4−3) and CO(3−2) data, we identified five molecular clumps, designated A, B, C, D, and E, as molecular counterparts of the ATLASGAL sources. These clumps have radial velocities ranging from ~−15 km s−1 to −10 km s−1, confirming their association with RCW 122. In addition, we report the detection of 20 transitions from 11 distinct molecules in the APEX spectra in the frequency ranges from 258.38 GHz to 262.38 GHz, 228.538 GHz to 232.538 GHz, and 218.3 GHz to 222.3 GHz, unveiling a diverse chemical complexity among the clumps. Utilizing CO(2−1) and C18O(2−1) data taken from the observations with the APEX telescope, we estimated the total LTE molecular mass, ranging from 200 M⊙ (clump A) to 4400 M⊙ (clump B). Our mid- to far-infrared (MIR-FIR) flux density analysis yielded minimum dust temperatures of 23.7 K (clump A) to maximum temperatures of 33.9 K (clump B), indicating varying degrees of internal heating among the clumps. The bolometric luminosities span 1.7×103 L⊙ (clump A) to 2.4×105 L⊙ (clump B), while the total (dust+gas) mass ranges from 350 M⊙ (clump A) to 3800 M⊙ (clump B). Our analysis of the molecular line richness, L/M ratios, and CH3CCH and dust temperatures reveals an evolutionary sequence of A/E→C→D/B, consistent with preliminary inferences of the ATLASGAL sources. In this context, clumps A and E exhibit early stages of collapse, with clump A likely in an early HMPO phase, which is supported by identifying a candidate molecular outflow. Clump E appears to be in an intermediate stage between IRDC and HMPO. Clumps D and B show evidence of being in the UCHII phase, with clump B likely more advanced. Clump C likely represents an intermediate stage between HMPO and HMC. Our findings suggest clump B is undergoing ionization and heating by multiple stellar and protostellar members of the stellar cluster DBS 119. Meanwhile, other cluster members may be responsible for ionizing other regions of RCW 122 that have evolved into fully developed HII regions, beyond the molecular dissociation stage.

Machine learning can be as good as maximum likelihood when reconstructing phylogenetic trees and determining the best evolutionary model on four taxon alignments

Phylogenetic tree reconstruction with molecular data is important in many fields of life science research. The gold standard in this discipline is the phylogenetic tree reconstruction based on the Maximum Likelihood method. In this study, we present neural networks to predict the best model of sequence evolution and the correct topology for four sequence alignments of nucleotide or amino acid sequence data. We trained neural networks with different architectures using simulated alignments for a wide range of evolutionary models, model parameters and branch lengths. By comparing the accuracy of model and topology prediction of the trained neural networks with Maximum Likelihood and Neighbour Joining methods, we show that for quartet trees, the neural network classifier outperforms the Neighbour Joining method and is in most cases as good as the Maximum Likelihood method to infer the best model of sequence evolution and the best tree topology. These results are consistent for nucleotide and amino acid sequence data. We also show that our method is superior for model selection than previously published methods based on convolutionary networks. Furthermore, we found that neural network classifiers are much faster than the IQ-TREE implementation of the Maximum Likelihood method. Our results show that neural networks could become a true competitor for the Maximum Likelihood method in phylogenetic reconstructions.

Particle acceleration, escape, and non-thermal emission from core-collapse supernovae inside non-identical wind-blown bubbles

Context. In the core-collapse scenario, supernova remnants (SNRs) evolve inside complex wind-blown bubbles structured by massive progenitors during their lifetime. Therefore, particle acceleration and the emissions from these SNRs can carry the fingerprints of the evolutionary sequences of the progenitor stars. Aims. We investigate the impact of the ambient environment of core-collapse SNRs on particle spectra and emissions for two progenitors with different evolutionary tracks while accounting for the spatial transport of cosmic rays (CRs) and the magnetic turbulence that scatters CRs. Methods. We used the RATPaC code to model the particle acceleration at the SNRs with progenitors having zero-age main sequence (ZAMS) masses of 20 M⊙ and 60 M⊙. We constructed the pre-supernova circumstellar medium (CSM) by solving the hydrodynamic equations for the lifetime of the progenitor stars. Then, the transport equation for cosmic rays, the magnetic turbulence in test-particle approximation, and the induction equation for the evolution of a large-scale magnetic field were solved simultaneously with the hydro-dynamic equations for the expansion of SNRs inside the pre-supernova CSM in 1-D spherical symmetry. Results. The profiles of gas density and temperature of the wind bubbles along with the magnetic field and the scattering turbulence regulate the spectra of accelerated particles for both of the SNRs. For the 60 M⊙ progenitor, the spectral index reaches 2.4, even below 10 GeV, during the propagation of the SNR shock inside the hot shocked wind. In contrast, we did not observe a persistent soft spectra at earlier evolutionary stages of the SNR with the 20 M⊙ progenitor, for which the spectral index becomes 2.2 only for a brief period during the interaction of SNR shock with the dense shell of red supergiant (RSG) wind material. At later stages of evolution, the spectra become soft above ~10 GeV for both SNRs, as weak driving of turbulence permits the escape of high-energy particles from the remnants. The emission morphology of the SNRs strongly depends on the type of progenitors. For instance, the radio morphology of the SNR with the 20 M⊙ progenitor is centre-filled at early stages, whereas that of the more massive progenitor is shell-like.

ACA CO(J = 2–1) mapping of the nearest spiral galaxy M 33. II. Exploring the evolution of giant molecular clouds

Abstract The evolution of giant molecular clouds (GMCs), the main sites of high-mass star formation, is an essential process to unravel the galaxy evolution. Using a GMC catalogue of M 33 from the ALMA-ACA (Atacama Large Millimeter/submillimeter Array–Atacama Compact Array) survey, we classified 848 GMCs into three types based on the association with H ii regions and their H$\alpha$ luminosities $L\, (\rm{H}\alpha )$: Type I is associated with no H ii regions; Type II with H ii regions of $L\, (\rm{H}\alpha )$ $\lt 10^{37.5}$ erg s$^{-1}$; and Type III with H ii regions of $L\, (\rm{H}\alpha )$ $\geqq$ $10^{37.5}$ erg s$^{-1}$. These criteria yield 224 Type I GMCs, 473 Type II GMCs, and 151 Type III GMCs. GMCs show changes in their physical properties according to the types; mass, radius, velocity dispersion, and $^{13}$CO detection rate of GMCs systematically increase from Type I to Type III, and additionally, Type III GMCs are closest to virial equilibrium. Type III GMCs show the highest spatial correlation with clusters younger than $10\:$Myr, Type II GMCs moderate correlation, and Type I GMCs are almost uncorrelated. We interpret that these types indicate an evolutionary sequence from Type I to Type II, and then to Type III with timescales of 4 Myr, 13 Myr, and 5 Myr, respectively, indicating a GMC lifetime of 22 Myr by assuming that a Type II GMC has the same timescale as the Large Magellanic Cloud. The evolved GMCs are concentrated on the spiral arms, while the younger GMCs are apart from the arm, both to the leading and trailing sides. This indicates that GMCs collide with each other via the spiral potential, leading to the compression of GMCs and the triggering of high-mass star formation, which may support the dynamic spiral model. Overall, we suggest that the GMC evolution concept helps illuminate the galaxy evolution, including the spiral arm formation.

Microscopic marvels: Decoding the role of micropeptides in innate immunity.

The innate immune response is under selection pressures from changing environments and pathogens. While sequence evolution can be studied by comparing rates of amino acid mutations within and between species, how a gene's birth and death contribute to the evolution of immunity is less known. Short open reading frames, once regarded as untranslated or transcriptional noise, can often produce micropeptides of <100 amino acids with a wide array of biological functions. Some micropeptide sequences are well conserved, whereas others have no evolutionary conservation, potentially representing new functional compounds that arise from species-specific adaptations. To date, few reports have described the discovery of novel micropeptides of the innate immune system. The diversity of immune-related micropeptides is a blind spot for gene and functional annotation. Immune-related micropeptides represent a potential reservoir of untapped compounds for understanding and treating disease. This review consolidates what is currently known about the evolution and function of innate immune-related micropeptides to facilitate their investigation.

A potential role for RNA aminoacylation prior to its role in peptide synthesis

Coded ribosomal peptide synthesis could not have evolved unless its sequence and amino acid-specific aminoacylated tRNA substrates already existed. We therefore wondered whether aminoacylated RNAs might have served some primordial function prior to their role in protein synthesis. Here, we show that specific RNA sequences can be nonenzymatically aminoacylated and ligated to produce amino acid-bridged stem-loop RNAs. We used deep sequencing to identify RNAs that undergo highly efficient glycine aminoacylation followed by loop-closing ligation. The crystal structure of one such glycine-bridged RNA hairpin reveals a compact internally stabilized structure with the same eponymous T-loop architecture that is found in many noncoding RNAs, including the modern tRNA. We demonstrate that the T-loop-assisted amino acid bridging of RNA oligonucleotides enables the rapid template-free assembly of a chimeric version of an aminoacyl-RNA synthetase ribozyme. We suggest that the primordial assembly of amino acid-bridged chimeric ribozymes provides a direct and facile route for the covalent incorporation of amino acids into RNA. A greater functionality of covalently incorporated amino acids could contribute to enhanced ribozyme catalysis, providing a driving force for the evolution of sequence and amino acid-specific aminoacyl-RNA synthetase ribozymes in the RNA World. The synthesis of specifically aminoacylated RNAs, an unlikely prospect for nonenzymatic reactions but a likely one for ribozymes, could have set the stage for the subsequent evolution of coded protein synthesis.

Reduced-order reconstruction of discrete grey forecasting model and its application

Discrete grey forecasting models based on an accumulative operator have been widely used in many practical fields. With the development of grey forecasting models, it is a problem to be solved to further analyze internal mechanisms and unify the structures. This paper aims to reconstruct the model from a perspective of sequence characteristics and simplify the modeling steps under the condition of ensuring the accuracy of the model. First, this paper analyzes dynamic sequence evolution hidden and mines relationship between the structure and original sequence features contained in discrete grey forecasting model. Then, the reconstruction is carried out to prove the equivalence and quantitative relation between reduced-order model and original model. Under order recursive estimation, new parameters are addressed. Finally, theoretical correctness is verified by large-scale numerical simulation. Moreover, the reduced-order model is applied for prediction on the peak of battery incremental capacity and capacity degradation. Results show the effectiveness and superior prediction performance of the reduced-order model, where MAPEs of grey forecasting models have controlled under 4%.

Co-seismic and post-seismic slip associated with the 2021 Mw5.9 Arkalochori, Central Crete (Greece) earthquake constrained by geodetic data and aftershocks

The co-seismic and post-seismic deformation field associated with the Mw5.9 Arkalochori main shock that occurred in central Crete (Greece) on 27 September 2021 is analyzed using Copernicus Sentinel-1A & 1B images, GNSS measurements and seismological data. The fault geometry is constrained through the joint inversion of multiple datasets and the slip distribution for the co-seismic and post-seismic period is obtained using a homogeneous half-space elastic model and the Steepest Descent Method. The results indicate a blind normal fault striking 215° with a 55° dip to the northwest and the co-seismic slip model suggests a nearly circular main slip patch (8 × 6 km2) with a maximum slip of 0.98 m. Post-seismic displacements started rapidly after the main shock followed by a gradual decay as highlighted by the calculated InSAR time series. The temporal evolution of post-seismic slip is described by a simple logarithmic function, decaying faster at the southwest part of the fault. The cumulative afterslip model suggests that the maximum post-seismic slip of 0.23 m occurred within a similar depth range compared to the co-seismic one, yet with a shift towards the southwest. Post-seismic slip inside the main shock rupture area is sustained, highlighting the slow recovery of locking in the co-seismic slip region. Afterslip (seismic or aseismic) played a dominant role in the early post-seismic period acting complementarily to the main rupture. Indications suggest that the spatiotemporal evolution of the productive aftershock sequence may be driven afterslip, alongside other potential factors.