The wide distribution and diverse varieties of chickens make them important models for studying genetic adaptation. The aim of this study was to identify genes that alter heat adaptation in commercial chicken breeds by comparing genetic differences between tropical and cold-resistant chickens. We analyzed whole-genome resequencing data of 186 chickens across various regions in Asia, including the following breeds: Bian chickens (B), Dagu chickens (DG), Beijing-You chickens (BY), and Gallus gallus jabouillei from China; Gallus gallus murghi from India; Vietnam native chickens (VN); Thailand native chickens (TN) and Gallus gallus spadiceus from Thailand; and Indonesia native chickens (IN), Gallus gallus gallus, and Gallus gallus bankiva from Indonesia. In total, 5,454,765 SNPs were identified for further analyses. Population genetic structure analysis revealed that each local chicken breed had undergone independent evolution. Additionally, when K = 5, B, BY, and DG chickens shared a common ancestor and exhibited high levels of inbreeding, suggesting that northern cold-resistant chickens are likely the result of artificial selection. In contrast, the runs of homozygosity (ROH) and the ROH-based genomic inbreeding coefficient (FROH) results for IN, TN, and VN chickens showed low levels of inbreeding. Low population differentiation index values indicated low differentiation levels, suggesting low genetic diversity in tropical chickens, implying increased vulnerability to environmental changes, decreased adaptability, and disease resistance. Whole-genome selection sweep analysis revealed 69 candidate genes, including LGR4, G6PC, and NBR1, between tropical and cold-resistant chickens. The genes were further subjected to GO and KEGG enrichment analyses, revealing that most of the genes were primarily enriched in biological synthesis processes, metabolic processes, central nervous system development, ion transmembrane transport, and the Wnt signaling pathway. Our study identified heat adaptation genes and their functions in chickens that primarily affect chickens in high-temperature environments through metabolic pathways. These heat-resistance genes provide a theoretical basis for improving the heat-adaptation capacity of commercial chicken breeds.

The genetic variety and habitats of Camptophora species, generally known as black yeast, have not been clarified. In this study, we re-evaluated Camptophora based on morphological observations and phylogenetic analyses. Because prior investigations on Camptophora only included a few strains/specimens, 24 Camptophora-related strains were newly obtained from 13 leaf samples of various plant species to redefine the genetic and species concepts of Camptophora. Their molecular phylogenetic relationships were examined using small subunit nuclear ribosomal DNA (nSSU, 18S rDNA), the internal transcribed spacer (ITS) rDNA operon, the large subunit nuclear ribosomal DNA (LSU, 28S rDNA), β-tubulin, the second largest subunit of RNA polymerase II (rpb2), and mitochondrial small subunit DNA (mtSSU). Single- and multi-locus analyses using nSSU-ITS-LSU-rpb2-mtSSU revealed a robust phylogenetic relationship among Camptophora species within Chaetothyriaceae. Camptophora species could be distinguished from other chaetothyriaceous genera by their snake-shaped conidia with microcyclic conidiation and loosely interwoven mycelial masses. Based on the results of phylogenetic analyses, two undescribed lineages were recognized, and Ca. schimae was excluded from the genus. ITS sequence comparison with environmental DNA sequences revealed that the distribution of the genus is restricted to the Asia-Pacific region. Camptophora has been isolated or detected from abrupt sources, and this was attributed to its microcycle. The mechanisms driving genetic diversity within species are discussed with respect to their phyllosphere habitats.

Mastering the self-organization of nanoparticle morphologies is pivotal in soft matter physics and film growth. Silicon dioxide (SiO2) nanoparticles are an archetypical model of nanomotor in soft matter. Here, the emphasis is on the self-organizing behavior of SiO2 nanoparticles under extreme conditions. It is unveiled that manipulating the states of the metal substrate profoundly dictates the motion characteristics of SiO2 nanoparticles. This manipulation triggers the emergence of intricate morphologies and distinctive patterns. Employing a reaction-diffusion model, the fundamental roles played by Brownian motion and Marangoni-driven motion in shaping fractal structures and radial Turing patterns are demonstrated, respectively. Notably, these radial Turing patterns showcase hyperuniform order, challenging conventional notions of film morphology. These discoveries pave the way for crafting non-equilibrium morphological materials, poised with the potential for self-healing, adaptability, and innovative applications.

The shallow hydrothermal vents (HVs) of Kueishan Island are considered as a template for studying the extremes of sulfide-polluted and acidified water. The present study examined the biological and spatiotemporal aspects of mesozooplankton mortality in waters around this extreme HV environment. Zooplankton sample collection was carried out in three monsoonal periods and the results revealed that there was a significant decrease in the mortality of total mesozooplankton with increasing distance from the HVs. The overall mortality of mesozooplankton showed a significant negative correlation with sea surface temperature and pH. Particularly, mortality of copepods showed a significant negative correlation with pH, whereas it was significantly positive correlated with sea surface temperature in the southwest monsoon prevailing period. Overall, the results may imply a situation that zooplankton will encounter in the more acidified environment of a future ocean.

The great majority of microorganisms are as-yet-uncultivated, mostly found in extreme environments. High-throughput sequencing provides data-rich genomes from single-cell and metagenomic techniques, which has enabled researchers to obtain a glimpse of the unexpected genetic diversity of \"microbial dark matter.\" However, cultivating microorganisms from extreme environments remains essential for dissecting and utilizing the functions of extremophiles. Here, we provide a straightforward protocol for efficiently isolating prokaryotic microorganisms from different extreme habitats (thermal, xeric, saline, alkaline, acidic, and cryogenic environments), which was established through previous successful work and our long-term experience in extremophile resource mining. We propose common processes for extremophile isolation at first and then summarize multiple cultivation strategies for recovering prokaryotic microorganisms from extreme environments and meanwhile provide specific isolation tips that are always overlooked but important. Furthermore, we propose the use of multi-omics-guided microbial cultivation approaches for culturing these as-yet-uncultivated microorganisms and two examples are provided to introduce how these approaches work. In summary, the protocol allows researchers to significantly improve the isolation efficiency of pure cultures and novel taxa, which therefore paves the way for the protection and utilization of microbial resources from extreme environments.

UNASSIGNED: The accurate estimation of postmortem interval (PMI), the time between death and discovery of the body, is crucial in forensic science investigations as it impacts legal outcomes. PMI estimation in extremely cold environments becomes susceptible to errors and misinterpretations, especially with prolonged PMIs. This study addresses the lack of data on decomposition in extreme cold by providing the first overview of decomposition in such settings. Moreover, it proposes the first postmortem microbiome prediction model for PMI estimation in cold environments, applicable even when the visual decomposition is halted.
UNASSIGNED: The experiment was conducted on animal models in the second-coldest region in the United States, Grand Forks, North Dakota, and covered 23 weeks, including the winter months with temperatures as low as -39°C. Random Forest analysis models were developed to estimate the PMI based either uniquely on 16s rRNA gene microbial data derived from nasal swabs or based on both microbial data and measurable environmental parameters such as snow depth and outdoor temperatures, on a total of 393 samples.
UNASSIGNED: Among the six developed models, the best performing one was the complex model based on both internal and external swabs. It achieved a Mean Absolute Error (MAE) of 1.36 weeks and an R2 value of 0.91. On the other hand, the worst performing model was the minimal one that relied solely on external swabs. It had an MAE of 2.89 weeks and an R2 of 0.73. Furthermore, among the six developed models, the commonly identified predictors across at least five out of six models included the following genera: Psychrobacter (ASV1925 and ASV1929), Carnobacterium (ASV2872) and Pseudomonas (ASV1863).
UNASSIGNED: The outcome of this research provides the first microbial model able to predict PMI with an accuracy of 9.52 days over a six-month period of extreme winter conditions.

The increased availability of quality genomic data has greatly improved the scope and resolution of our understanding of the recent evolutionary history of wild species adapted to extreme environments and their susceptibility to anthropogenic impacts. The guanaco (Lama guanicoe), the largest wild ungulate in South America, is a good example. The guanaco is well adapted to a wide range of habitats, including the Sechura Desert, the high Andes Mountains to the north, and the extreme temperatures and conditions of Navarino Island to the south. Guanacos also have a long history of overexploitation by humans. To assess the evolutionary impact of these challenging habitats on the genomic diversity, we analyzed 38 genomes (∼10 to 16×) throughout their extensive latitudinal distribution from the Sechura and Atacama Desert to southward into Tierra del Fuego Island. These included analyses of patterns of unique differentiation in the north and geographic region further south with admixture among L. g. cacsilensis and L. g. guanicoe. Our findings provide new insights on the divergence of the subspecies ∼800,000 yr BP and document two divergent demographic trajectories and to the initial expansion of guanaco into the more southern portions of the Atacama Desert. Patagonian guanacos have experienced contemporary reductions in effective population sizes, likely the consequence of anthropogenic impacts. The lowest levels of genetic diversity corresponded to their northern and western limits of distribution and some varying degrees of genetic differentiation. Adaptive genomic diversity was strongly linked with environmental variables and was linked with colonization toward the south followed by adaptation.

UNASSIGNED: Group living skills (GLS), that is, being tidy and considerate of others, are an important skillset for teams who live and work together. However, this construct does not have a validated measure to enable an understanding of how group living skills influence team dynamics over time. We developed and validated a short measure of group living skills for teams living in extreme work environments.
UNASSIGNED: We collected data from 83 individuals in 24 teams living and working in space and spaceflight analog environments on missions of 45-240 days.
UNASSIGNED: We provide evidence of reliability and validity for the GLS Survey over time and identify a two-factor structure. We also demonstrate its use as a measure of team-level dynamics and its utility as a sociometric measure to identify a person\'s degree of group living skills.
UNASSIGNED: We outline recommendations for using this new measure in future research and applied settings to understand this unique aspect of teams living and working together.

Lithium-based batteries (LBBs) have been highly researched and recognized as a mature electrochemical energy storage (EES) system in recent years. However, their stability and effectiveness are primarily confined to room temperature conditions. At temperatures significantly below 0 °C or above 60 °C, LBBs experience substantial performance degradation. Under such challenging extreme contexts, sodium-ion batteries (SIBs) emerge as a promising complementary technology, distinguished by their fast dynamics at low-temperature regions and superior safety under elevated temperatures. Notably, developing SIBs suitable for wide-temperature usage still presents significant challenges, particularly for specific applications such as electric vehicles, renewable energy storage, and deep-space/polar explorations, which requires a thorough understanding of how SIBs perform under different temperature conditions. By reviewing the development of wide-temperature SIBs, the influence of temperature on the parameters related to battery performance, such as reaction constant, charge transfer resistance, etc., is systematically and comprehensively analyzed. The review emphasizes challenges encountered by SIBs in both low and high temperatures while exploring recent advancements in SIB materials, specifically focusing on strategies to enhance battery performance across diverse temperature ranges. Overall, insights gained from these studies will drive the development of SIBs that can handle the challenges posed by diverse and harsh climates.

Characterisation of genomic variation among corals can help uncover variants underlying trait differences and contribute towards genotype prioritisation in coastal restoration projects. For example, there is growing interest in identifying resilient genotypes for transplantation, and to better understand the genetic processes that allow some individuals to survive in specific conditions better than others. The coral species Pocillopora acuta is known to survive in a wide range of habitats, from reefs artificial coastal defences, suggesting its potential use as a starter species for ecological engineering efforts involving coral transplantation onto intertidal seawalls. However, the intertidal section of coastal armour is a challenging environment for corals, with conditions during periods of emersion being particularly stressful. Here, we scanned the entire genome of P. acuta corals to identify the regions harbouring single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) that separate intertidal colonies (n = 18) from those found in subtidal areas (n = 21). Findings revealed 74,391 high quality SNPs distributed across 386 regions of the P. acuta genome. While the majority of the detected SNPs were in non-coding regions, 12% were identified in exons (i.e. coding regions). Functional SNPs that were significantly associated with intertidal colonies were found in overrepresented genomic regions linked to cellular homeostasis, metabolism, and signalling processes, which may represent local environmental adaptation in the intertidal. Interestingly, regions that exhibited CNVs were also associated with metabolic and signalling processes, suggesting P. acuta corals living in the intertidal have a high capacity to perform biological functions critical for survival in extreme environments.