In an ongoing swarm of earthquakes that began hitting Japan in 2020, the shifting weight of surface water may have spurred the shaking

This year could bring up to 25 named tropical storms in the Atlantic Ocean due to a shift to La Niña conditions, says the US National Oceanic and Atmospheric Administration

Smoke from wildfires burning in Canada and Mexico is already worsening air quality in the US, but some signs suggest clearer skies than last year

Taylor Roades's images of a river in north-west Alaska that has turned orange because of global warming have won the New Scientist Editors Award at the Earth Photo competition

A documentary film about three young survivors of super-typhoon Odette, a tropical cyclone that hit the Philippines in 2021, wins the New Scientist Editors Award at Earth Photo 2024

Millions of tonnes of water vapour have been lingering in the atmosphere since the Hunga Tonga-Hunga Ha’apai volcano erupted in 2022– possibly contributing to global warming

Exhausted by today's political and environmental instability, Annalee Newitz investigated what a future Earth might look like. Get ready for green mining, soft cities and robo-taxis

Sea-floor nodules raise oxygen levels in the deep ocean, suggesting they may have a valuable role in ecosystems and adding to concerns about the impact of deep-sea mining

Amazing images of an open-air library, underground lab and design museum show the reincarnation of dead mines, captured in a new book, 102 Things to Do With a Hole in the Ground

The dynamics of how plants and animals change Earth is central to this last book in a trilogy by Other Minds author and "scuba-diving philosopher" Peter Godfrey-Smith

See some of the top entries to this year's Mangrove Photography Awards, showing the beauty and fragility of these unique ecosystems

The books, TV, games and more that New Scientist staff have enjoyed this week

A scientific drilling ship has burrowed further into Earth’s mantle than ever before, obtaining new clues about the processes that feed oceanic volcanoes and the possible origins of life

Pascal Maitre's photos from the Democratic Republic of Congo detail the problems arising as demand for cobalt grows

After over a year of record-high global sea temperatures, the equatorial Atlantic is cooling off more quickly than ever recorded, which could impact weather around the world

James Lovelock's hypothesis that our planet is a living entity is well known. Ferris Jabr's new book Becoming Earth takes it a step further

Quartz crystals produce electricity when they are deformed by mechanical stress, which may explain how enormous chunks of gold can form in inert rock

This claustrophobia-inducing image is taken from photographer Martin Broen's new book Light in the Underworld, a collection of shots from the Yucatán’s cenotes, or sinkholes

Seismologists were mystified by a strange signal that persisted for nine days in 2023 – now its source has been identified as a standing wave caused by a landslide in Greenland

A ring of asteroid debris could have orbited Earth for tens of millions of years, and perhaps even have altered the planet's climate

A sprawling research program aims to improve hurricane forecasts by collecting data at the chaotic interface of ocean and atmosphere

Geographer Alastair Bonnett on his pick of the most diverse maps, from a collection of 100,000 galaxies to a 12th-century Chinese depiction of rivers on a grid

Rapid erosion caused by a geological act of “piracy” tens of thousands of years ago may have raised Earth’s crust and elevated Mount Everest by as much as 50 metres

El Niño and La Niña cycles driven by ocean temperatures in the Pacific can influence weather in the North Atlantic 12 months later – a finding that could improve long-range forecasts

A story passed down in folklore led scientists to evidence of an 8-metre tsunami that hit an island in Hawaii hundreds of years ago

In the western US, the average maximum growth rate of fires has more than doubled over the past two decades

Forget Armageddon-sized rocks, just one of 25,000 smaller asteroids could destroy a city on Earth. How to Kill an Asteroid by Robin George Andrew shows how science plans to save the planet

Endurance sank beneath the ice during Ernest Shackleton’s legendary Antarctic expedition. More than a hundred years later, researchers document their own saga of how they found the vessel

An analysis of crystals in lava from the 2022 eruption of Mauna Loa has revealed an unknown magma reservoir within the volcano, which could extend forecasts of eruptions from minutes to months

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Retrotransposable elements (RTEs) are common mobile genetic elements comprising ~42% of the human genome. RTEs play critical roles in gene regulation and function, but how they are specifically involved in complex diseases is largely unknown. Here, we investigate the cellular heterogeneity of RTEs using 12 single-cell transcriptome profiles covering three neurodegenerative diseases, Alzheimer's disease (AD), Parkinson's disease, and multiple sclerosis. We identify cell type marker RTEs in neurons, astrocytes, oligodendrocytes, and oligodendrocyte precursor cells that are related to these diseases. The differential expression analysis reveals the landscape of dysregulated RTE expression, especially L1s, in excitatory neurons of multiple neurodegenerative diseases. Machine learning algorithms for predicting cell disease stage using a combination of RTE and gene expression features suggests dynamic regulation of RTEs in AD. Furthermore, we construct a single-cell atlas of retrotransposable elements in neurodegenerative disease (scARE) using these data sets and features. scARE has six feature analysis modules to explore RTE dynamics in a user-defined condition. To our knowledge, scARE represents the first systematic investigation of RTE dynamics at the single-cell level within the context of neurodegenerative diseases.

PWAS (proteome-wide association study) is an innovative genetic association approach that complements widely used methods like GWAS (genome-wide association study). The PWAS approach involves consecutive phases. Initially, machine learning modeling and probabilistic considerations quantify the impact of genetic variants on protein-coding genes’ biochemical functions. Secondly, for each individual, aggregating the variants per gene determines a gene-damaging score. Finally, standard statistical tests are activated in the case-control setting to yield statistically significant genes per phenotype. The PWAS Hub offers a user-friendly interface for an in-depth exploration of gene–disease associations from the UK Biobank (UKB). Results from PWAS cover 99 common diseases and conditions, each with over 10,000 diagnosed individuals per phenotype. Users can explore genes associated with these diseases, with separate analyses conducted for males and females. For each phenotype, the analyses account for sex-based genetic effects, inheritance modes (dominant and recessive), and the pleiotropic nature of associated genes. The PWAS Hub showcases its usefulness for asthma by navigating through proteomic-genetic analyses. Inspecting PWAS asthma-listed genes (a total of 27) provide insights into the underlying cellular and molecular mechanisms. Comparison of PWAS-statistically significant genes for common diseases to the Open Targets benchmark shows partial but significant overlap in gene associations for most phenotypes. Graphical tools facilitate comparing genetic effects between PWAS and coding GWAS results, aiding in understanding the sex-specific genetic impact on common diseases. This adaptable platform is attractive to clinicians, researchers, and individuals interested in delving into gene–disease associations and sex-specific genetic effects.

Sequence variation observed in populations of pathogens can be used for important public health and evolutionary genomic analyses, especially outbreak analysis and transmission reconstruction. Identifying this variation is typically achieved by aligning sequence reads to a reference genome, but this approach is susceptible to reference biases and requires careful filtering of called genotypes. There is a need for tools that can process this growing volume of bacterial genome data, providing rapid results, but that remain simple so they can be used without highly trained bioinformaticians, expensive data analysis, and long-term storage and processing of large files. Here we describe split k-mer analysis (SKA2), a method that supports both reference-free and reference-based mapping to quickly and accurately genotype populations of bacteria using sequencing reads or genome assemblies. SKA2 is highly accurate for closely related samples, and in outbreak simulations, we show superior variant recall compared with reference-based methods, with no false positives. SKA2 can also accurately map variants to a reference and be used with recombination detection methods to rapidly reconstruct vertical evolutionary history. SKA2 is many times faster than comparable methods and can be used to add new genomes to an existing call set, allowing sequential use without the need to reanalyze entire collections. With an inherent absence of reference bias, high accuracy, and a robust implementation, SKA2 has the potential to become the tool of choice for genotyping bacteria. SKA2 is implemented in Rust and is freely available as open-source software.

The COVID-19 pandemic has highlighted the critical role of genomic surveillance for guiding policy and control. Timeliness is key, but sequence alignment and phylogeny slow most surveillance techniques. Millions of SARS-CoV-2 genomes have been assembled. Phylogenetic methods are ill equipped to handle this sheer scale. We introduce a pangenomic measure that examines the information diversity of a k-mer library drawn from a country's complete set of clinical, pooled, or wastewater sequence. Quantifying diversity is central to ecology. Hill numbers, or the effective number of species in a sample, provide a simple metric for comparing species diversity across environments. The more diverse the sample, the higher the Hill number. We adopt this ecological approach and consider each k-mer an individual and each genome a transect in the pangenome of the species. Structured in this way, Hill numbers summarize the temporal trajectory of pandemic variants, collapsing each day's assemblies into genome equivalents. For pooled or wastewater sequence, we instead compare days using survey sequence divorced from individual infections. Across data from the UK, USA, and South Africa, we trace the ascendance of new variants of concern as they emerge in local populations well before these variants are named and added to phylogenetic databases. Using data from San Diego wastewater, we monitor these same population changes from raw, unassembled sequence. This history of emerging variants senses all available data as it is sequenced, intimating variant sweeps to dominance or declines to extinction at the leading edge of the COVID-19 pandemic.

High-throughput sequencing (HTS) technologies have been instrumental in investigating biological questions at the bulk and single-cell levels. Comparative analysis of two HTS data sets often relies on testing the statistical significance for the difference of two negative binomial distributions (DOTNB). Although negative binomial distributions are well studied, the theoretical results for DOTNB remain largely unexplored. Here, we derive basic analytical results for DOTNB and examine its asymptotic properties. As a state-of-the-art application of DOTNB, we introduce DEGage, a computational method for detecting differentially expressed genes (DEGs) in scRNA-seq data. DEGage calculates the mean of the sample-wise differences of gene expression levels as the test statistic and determines significant differential expression by computing the P-value with DOTNB. Extensive validation using simulated and real scRNA-seq data sets demonstrates that DEGage outperforms five popular DEG analysis tools: DEGseq2, DEsingle, edgeR, Monocle3, and scDD. DEGage is robust against high dropout levels and exhibits superior sensitivity when applied to balanced and imbalanced data sets, even with small sample sizes. We utilize DEGage to analyze prostate cancer scRNA-seq data sets and identify marker genes for 17 cell types. Furthermore, we apply DEGage to scRNA-seq data sets of mouse neurons with and without fear memory and reveal eight potential memory-related genes overlooked in previous analyses. The theoretical results and supporting software for DOTNB can be widely applied to comparative analyses of dispersed count data in HTS and broad research questions.

Mapping transcriptomic variations using either short- or long-read RNA sequencing is a staple of genomic research. Long reads are able to capture entire isoforms and overcome repetitive regions, whereas short reads still provide improved coverage and error rates. Yet, open questions remain, such as how to quantitatively compare the technologies, can we combine them, and what is the benefit of such a combined view? We tackle these questions by first creating a pipeline to assess matched long- and short-read data using a variety of transcriptome statistics. We find that across data sets, algorithms, and technologies, matched short-read data detects ~30% more splice junctions, such that ~10%–30% of the splice junctions included at ≥20% by short reads are missed by long reads. In contrast, long reads detect many more intron-retention events and can detect full isoforms, pointing to the benefit of combining the technologies. We introduce MAJIQ-L, an extension of the MAJIQ software, to enable a unified view of transcriptome variations from both technologies and demonstrate its benefits. Our software can be used to assess any future long-read technology or algorithm and can be combined with short-read data for improved transcriptome analysis.

Most studies of genome organization have focused on intrachromosomal (cis) contacts because they harbor key features such as DNA loops and topologically associating domains. Interchromosomal (trans) contacts have received much less attention, and tools for interrogating potential biologically relevant trans structures are lacking. Here, we develop a computational framework that uses Hi-C data to identify sets of loci that jointly interact in trans. This method, trans-C, initiates probabilistic random walks with restarts from a set of seed loci to traverse an input Hi-C contact network, thereby identifying sets of trans-contacting loci. We validate trans-C in three increasingly complex models of established trans contacts: the Plasmodium falciparum var genes, the mouse olfactory receptor "Greek islands," and the human RBM20 cardiac splicing factory. We then apply trans-C to systematically test the hypothesis that genes coregulated by the same trans-acting element (i.e., a transcription or splicing factor) colocalize in three dimensions to form "RNA factories" that maximize the efficiency and accuracy of RNA biogenesis. We find that many loci with multiple binding sites of the same DNA-binding proteins interact with one another in trans, especially those bound by factors with intrinsically disordered domains. Similarly, clustered binding of a subset of RNA-binding proteins correlates with trans interaction of the encoding loci. We observe that these trans-interacting loci are close to nuclear speckles. These findings support the existence of trans-interacting chromatin domains (TIDs) driven by RNA biogenesis. Trans-C provides an efficient computational framework for studying these and other types of trans interactions, empowering studies of a poorly understood aspect of genome architecture.

Asgard archaea are of great interest as the progenitors of Eukaryotes, but little is known about the mobile genetic elements (MGEs) that may shape their ongoing evolution. Here, we describe MGEs that replicate in Atabeyarchaeia, a wetland Asgard archaea lineage represented by two complete genomes. We used soil depth–resolved population metagenomic data sets to track 18 MGEs for which genome structures were defined and precise chromosome integration sites could be identified for confident host linkage. Additionally, we identified a complete 20.67 kbp circular plasmid and two family-level groups of viruses linked to Atabeyarchaeia, via CRISPR spacer targeting. Closely related 40 kbp viruses possess a hypervariable genomic region encoding combinations of specific genes for small cysteine-rich proteins structurally similar to restriction-homing endonucleases. One 10.9 kbp integrative conjugative element (ICE) integrates genomically into the Atabeyarchaeum deiterrae-1 chromosome and has a 2.5 kbp circularizable element integrated within it. The 10.9 kbp ICE encodes an expressed Type IIG restriction-modification system with a sequence specificity matching an active methylation motif identified by Pacific Biosciences (PacBio) high-accuracy long-read (HiFi) metagenomic sequencing. Restriction-modification of Atabeyarchaeia differs from that of another coexisting Asgard archaea, Freyarchaeia, which has few identified MGEs but possesses diverse defense mechanisms, including DISARM and Hachiman, not found in Atabeyarchaeia. Overall, defense systems and methylation mechanisms of Asgard archaea likely modulate their interactions with MGEs, and integration/excision and copy number variation of MGEs in turn enable host genetic versatility.

Somatic mutations arise and accumulate during tissue culture and vegetative propagation, potentially affecting various traits in horticultural crops, but their characteristics are still unclear. Here, somatic mutations in regenerated woodland strawberry derived from tissue culture of shoot tips under different conditions and 12 cultivated strawberry individuals are analyzed by whole genome sequencing. The mutation frequency of single nucleotide variants is significantly increased with increased hormone levels or prolonged culture time in the range of 3.3 x 10^–8–3.0 x 10^–6 mutations per site. CG methylation shows a stable reduction (0.71%–8.03%) in regenerated plants, and hypoCG-DMRs are more heritable after sexual reproduction. A high-quality haplotype-resolved genome is assembled for the strawberry cultivar "Beni hoppe." The 12 "Beni hoppe" individuals randomly selected from different locations show 4731–6005 mutations relative to the reference genome, and the mutation frequency varies among the subgenomes. Our study has systematically characterized the genetic and epigenetic variants in regenerated woodland strawberry plants and different individuals of the same strawberry cultivar, providing an accurate assessment of somatic mutations at the genomic scale and nucleotide resolution in plants.

The poly(A) signal, together with auxiliary elements, directs cleavage of a pre-mRNA and thus determines the 3' end of the mature transcript. In many species, including humans, the poly(A) signal is an AAUAAA hexamer, but we recently found that the deeply branching eukaryote Giardia lamblia uses a distinct hexamer (AGURAA) and lacks any known auxiliary elements. Our discovery prompted us to explore the evolutionary dynamics of poly(A) signals and auxiliary elements in the eukaryotic kingdom. We use direct RNA sequencing to determine poly(A) signals for four protists within the Metamonada clade (which also contains G. lamblia) and two outgroup protists. These experiments reveal that the AAUAAA hexamer serves as the poly(A) signal in at least four different eukaryotic clades, indicating that it is likely the ancestral signal, whereas the unusual Giardia version is derived. We find that the use and relative strengths of auxiliary elements are also plastic; in fact, within Metamonada, species like G. lamblia make use of a previously unrecognized auxiliary element where nucleotides flanking the poly(A) signal itself specify genuine cleavage sites. Thus, despite the fundamental nature of pre-mRNA cleavage for the expression of all protein-coding genes, the motifs controlling this process are dynamic on evolutionary timescales, providing motivation for future biochemical and structural studies as well as new therapeutic angles to target eukaryotic pathogens.