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The retrotransposition of L1 is controlled by functionally diverse genes at the transcriptional or post-transcriptional levels, and its silencing can lead to the downregulation of host gene expression. Silence on LINE-1 LINE-1 (L1) retrotransposons comprise around 17% of the human genome and are the only active, autonomous transposable element in humans. Here, Joanna Wysocka and colleagues perform a systematic CRISPR–Cas9 screen in human cell lines for factors that control L1 retrotransposition. They provide a resource of functionally diverse factors and pathways that control L1 activity at transcriptional or post-transcriptional levels. They also show that transcriptional silencing of L1 retrotransposons by MORC2 and HUSH complex subunits can occur within introns of transcriptionally active genes and can dampen expression of these genes, indicating how silencing of retrotransposons can influence host gene expression programs. Transposable elements, also known as transposons, are now recognized not only as parasitic DNA, the spread of which in the genome must be controlled by the host, but also as major players in genome evolution and regulation 1 , 2 , 3 , 4 , 5 , 6 . Long interspersed element-1 (LINE-1, also known as L1), the only currently autonomous mobile transposon in humans, occupies 17% of the genome and generates inter- and intra-individual genetic variation, in some cases resulting in disease 1 , 2 , 3 , 4 , 5 , 6 , 7 . However, how L1 activity is controlled and the function of L1s in host gene regulation are not completely understood. Here we use CRISPR–Cas9 screening strategies in two distinct human cell lines to provide a genome-wide survey of genes involved in the control of L1 retrotransposition. We identify functionally diverse genes that either promote or restrict L1 retrotransposition. These genes, which are often associated with human diseases, control the L1 life cycle at the transcriptional or the post-transcriptional level in a manner that can depend on the endogenous L1 nucleotide sequence, underscoring the complexity of L1 regulation. We further investigate the restriction of L1 by the protein MORC2 and by the human silencing hub (HUSH) complex subunits MPP8 and TASOR 8 . HUSH and MORC2 can selectively bind evolutionarily young, full-length L1s located within transcriptionally permissive euchromatic environments, and promote deposition of histone H3 Lys9 trimethylation (H3K9me3) for transcriptional silencing. Notably, these silencing events often occur within introns of transcriptionally active genes, and lead to the downregulation of host gene expression in a HUSH-, MORC2-, and L1-dependent manner. Together, these results provide a rich resource for studies of L1 retrotransposition, elucidate a novel L1 restriction pathway and illustrate how epigenetic silencing of transposable elements rewires host gene expression programs.

Recent international efforts at communicating climate change have begun using the notion of a climate indicator—a climate-related metric that can be used to track changes in the Earth system over time. Based upon a recently developed global-scale classification of daily air masses, this research examines the trends and variability in the frequencies of these air masses and then utilizes them to develop two nontraditional climate indicators: a warm/cool index (WCI) and a global extremes index (GEI). Results show that both indices trend significantly upward over the 40-yr period of record, indicating an increase in warm-based air masses (WCI) and extreme air masses (GEI). The two indices also exhibit a moderate (GEI) to strong (WCI) association with the global mean temperature record, multiple near-surface climate variables, and other existing climate indicators over that same time, showing promise as global indicators. Shorter-term variability in these indices also show a linear relationship between the WCI and changes in the Atlantic multidecadal oscillation and a nonlinear relationship between GEI and El Niño–Southern Oscillation. While many published climate indicators are based upon a single variable, and/or are regional in scope, the two indices presented herein are unique in that they are representative of the trends in the multivariate (and extreme, in the case of the GEI) weather conditions that are experienced near Earth’s surface, while also being global in scope.

Recruiting a hyperactive cytidine deaminase via the guide RNA to dCas9 allows for the introduction of diverse point mutations at the CRISPR target locus to create complex libraries of variants for protein engineering or dissection of protein function. Engineering and study of protein function by directed evolution has been limited by the technical requirement to use global mutagenesis or introduce DNA libraries. Here, we develop CRISPR-X, a strategy to repurpose the somatic hypermutation machinery for protein engineering in situ . Using catalytically inactive dCas9 to recruit variants of cytidine deaminase (AID) with MS2-modified sgRNAs, we can specifically mutagenize endogenous targets with limited off-target damage. This generates diverse libraries of localized point mutations and can target multiple genomic locations simultaneously. We mutagenize GFP and select for spectrum-shifted variants, including EGFP. Additionally, we mutate the target of the cancer therapeutic bortezomib, PSMB5, and identify known and novel mutations that confer bortezomib resistance. Finally, using a hyperactive AID variant, we mutagenize loci both upstream and downstream of transcriptional start sites. These experiments illustrate a powerful approach to create complex libraries of genetic variants in native context, which is broadly applicable to investigate and improve protein function.

This study improves the understanding of circulation patterns associated with regional temperature trends by characterizing boreal summer temperature variability patterns in North America using rotated S-mode principal component analysis. We analyzed gridded observational 2-m temperature datasets and the ERA5 reanalysis temperature dataset to examine the climate patterns associated with long-term trends and inter-annual variability of temperature variability patterns in North America. Our analysis revealed significant trends among some classified temperature variability patterns from 1979 to 2022 summers, with inter-annual amplitudes (i.e., a departure from the mean state) signaling toward the warm regime. The anticyclonic circulation anomaly over the temperature coherent regions associated with Greenland/northeastern Canada, and Alaska, respectively, is linked to an increase in warm air advection and above-average temperatures, while cyclonic circulation over the northeast Pacific coast enhanced warm air advection and temperature increases in the coherent region comprising the northwestern portion of North America. The increase in global mean land and ocean temperatures is strongly associated with the long-term increase in the amplitude of atmospheric circulations associated with warm regimes in parts of North America. At the interannual time scale, temperature increase over Greenland/northeastern Canada is strongly associated with the negative phase of the Arctic Oscillation. These findings highlight the modulating effects of global temperature increase and warming of the western tropical Pacific Ocean on the increasing amplitude of circulations associated with warm regimes in North America. Our results further indicate that the enhancement of anticyclonic circulations over the Arctic contributes to nearly 68% of the observed reduction in sea ice extent.

Global warming necessitates continual insights into changing atmospheric temperatures to enhance climate change monitoring and prediction. The thickness of an atmospheric layer serves as an effective proxy for the average temperature of that layer, playing a pivotal role in weather forecasting, understanding atmospheric dynamics, and detecting shifts in extreme weather conditions. This study investigates the global trends in thickness of the layer between 1000 hPa and 500 hPa, from 1940 to the present and evaluates the impact of tropical and extra-tropical climate modes on these trends. Our findings reveal a consistent, statistically significant positive trend in atmospheric layer thickness. However, the magnitude of this trend varies both regionally and seasonally. The most substantial absolute changes are observed in the high latitudes during their respective winter seasons; however, when considering global changes relative to each location’s unique historical variability, the most pronounced increase occurs in the tropics, specifically over central Africa, with a standard deviation increase of up to 0.03 σ yr −1 . Based on the relative changes, the thickness over the Southern Hemisphere’s high-latitude landmasses is increasing at a faster pace during its winter compared to the Northern Hemisphere during its winter. Furthermore, our analysis of the impact of dominant tropical and extra-tropical climate modes revealed a strong correlation ( R ∼ 0.9) between sea surface temperature changes in the Pacific warm pool region and the global average thickness. This relationship accounts for about 76% to 78% variance of the inter-annual variability in thickness. Consequently, we identify the increase in sea surface temperature in the Indo-Pacific warm pool as a significant controller of the rate and magnitude of atmospheric layer thickness changes globally. This underscores the crucial role of oceanic-atmospheric interactions in driving global climate variations and extremes.

This study investigates the relationship between circulation patterns and austral summer temperature anomalies in southern Africa. The results show that the formation of continental lows tends to increase the thickness of the lower atmosphere. Further, the distinct variabilities of high and low pressure under the circulation types, influence air mass advection from the adjacent oceans, as well as atmospheric stability over land. Stronger anticyclonic circulation at the western branch of the Mascarene high-pressure system enhances the low-level cold air advection by southeast winds, decreases the thickness, and lowers the temperature over a majority of the land in southern Africa. Conversely, a weaker Mascarene High, coupled with enhanced cyclonic activity in the southwest Indian Ocean increases low-level warm air advection and increases temperature anomalies over vast regions in southern Africa. The ridging of a closed South Atlantic anticyclone at the southern coast of southern Africa results in colder temperatures near the tip of southern Africa due to enhanced low-level cold air advection by southeast winds. However, when the ridge is weak and westerly winds dominate the southern coast of southern Africa, these areas experience temperature increases. The northward track of the Southern Hemisphere mid-latitude cyclone, which can be linked to the negative Southern Annular Mode, reduces the temperature in the southwestern part of southern Africa. Also, during the analysis period, El Niño was associated with temperature increases over the central parts of southern Africa; while the positive Indian Ocean dipole was linked to a temperature increase over the northeastern, northwestern, and southwestern parts of southern Africa.

The continuing transmission of coronavirus disease 2019 (COVID-19) remains a world-wide 21st-century public health emergency of concern. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused greater than 600 million cases of COVID-19 and over 6 million deaths globally. COVID-19 continues to be a highly transmissible disease despite efforts by public health officials and healthcare providers to manage and control the disease. Variants identified in selected worldwide epicenters add to the complexity of vaccine efficacy, overage, and antibody titer maintenance and bioactivity. The identification of the SARS-CoV-2 variants is described with respect to evading protective efficacy of COVID-19 vaccines and breakthrough infections. Vaccines and other therapeutics have prevented millions of SARS-CoV-2 infections and thousands of deaths in the United States. We explore aspects of the immune response in a condensed discussion to understand B and T cell lymphocyte regulatory mechanisms and antibody effectiveness and senescence. Finally, COVID-19 therapies including Paxlovid, Remdisivir, Molnupiravir and convalescent plasma in non-hospitalized patients are presented with limitations for identification, collection, and distribution to infected patients.

While the impact of absolute extreme temperatures on human health has been amply studied, far less attention has been given to relative temperature extremes, that is, events that are highly unusual for the time of year but not necessarily extreme relative to a location’s overall climate. In this research, we use a recently defined extreme temperature event metric to define absolute extreme heat events (EHE) and extreme cold events (ECE) using absolute thresholds, and relative extreme heat events (REHE) and relative extreme cold events (RECE) using relative thresholds. All-cause mortality outcomes using a distributed lag nonlinear model are evaluated for the largest 51 metropolitan areas in the US for the period 1975–2010. Both the immediate impacts and the cumulative 20-day impacts are assessed for each of the extreme temperature event types. The 51 metropolitan areas were then grouped into 8 regions for meta-analysis. For heat events, the greatest mortality increases occur with a 0-day lag, with the subsequent days showing below-expected mortality (harvesting) that decreases the overall cumulative impact. For EHE, increases in mortality are still statistically significant when examined over 20 days. For REHE, it appears as though the day-0 increase in mortality is short-term displacement. For cold events, both relative and absolute, there is little mortality increase on day 0, but the impacts increase on subsequent days. Cumulative impacts are statistically significant at more than half of the stations for both ECE and RECE. The response to absolute ECE is strongest, but is also significant when using RECE across several southern locations, suggesting that there may be a lack of acclimatization, increasing mortality in relative cold events both early and late in winter.

Temperature-related mortality is the leading cause of weather-related deaths in the United States. Herein, we explore the effect of air masses (AMs) – a relatively novel and holistic measure of environmental conditions – on human mortality across 61 cities in the United States. Geographic and seasonal differences in the effects of each AM on deseasonalized and detrended anomalous lagged mortality are examined using simple descriptive statistics, one-way analyses of variance, relative risks of excess mortality, and regression-based artificial neural network (ANN) models. Results show that AMs are significantly related to anomalous mortality in most US cities, and in most seasons. Of note, two of the three cool AMs (Cool and Dry-Cool) each show a strong, but delayed mortality response in all seasons, with peak mortality 2 to 4 days after they occur, with the Dry-Cool AM having nearly a 15% increased risk of excess mortality. Humid-Warm (HW) air masses are associated with increases in deaths in all seasons 0 to 1 days after they occur. In most seasons, these near-term mortality increases are offset by reduced mortality for 1–2 weeks afterwards; however, in summer, no such reduction is noted. The Warm and Dry-Warm AMs show slightly longer periods of increased mortality, albeit slightly less intensely as compared with HW, but with a similar lag structure by season. Meanwhile, the most seasonally consistent results are with transitional weather, whereby passing cold fronts are associated with a significant decrease in mortality 1 day after they occur, while warm fronts are associated with significant increases in mortality at that same lag time. Finally, ANN modeling reveals that AM-mortality relationships gleaned from a combined meta-analysis can actually lead to more skillful modeling of these relationships than models trained on some individual cities, especially in the cities where such relationships might be masked due to low average daily mortality.

Self-organizing maps (SOMs) are a relative newcomer to synoptic climatology; the method itself has only been utilized in the field for around a decade. In this article, we review the major developments and climatological applications of SOMs in the literature. The SOM can be used in synoptic climatological analysis in a manner similar to most other clustering methods. However, as the results from a SOM are generally represented by a two-dimensional array of cluster types that ‘self-organize’, the synoptic categories in the array effectively represent a continuum of synoptic categorizations, compared with discrete realizations produced through most traditional methods. Thus, a larger number of patterns can be more readily understood, and patterns, as well as transitional nodes between patterns, can be discerned. Perhaps the most intriguing development with SOMs has been the new avenues of visualization; the resultant spatial patterns of any variable can be more readily understood when displayed in a SOM. This improved visualization has led to SOMs becoming an increasingly popular tool in various research with climatological applications from other disciplines as well.