The research, led by David Jenkins and colleagues, tackles the question through beta diversity, the measure of how dissimilar two communities are in their species composition. The logic is elegant: if the clearest possible separation between adjacent communities occurs at a particular spatial resolution, then that resolution represents the empirical size of a community. Maximal beta diversity, in other words, marks the scale at which nature draws its sharpest boundaries between assemblages of species.

To test this, the team assembled point data for ants, birds, diatoms, and trees, four taxa chosen for their radically different life histories, dispersal abilities, and data origins. Ant records spanned two centuries of literature synthesis, totaling nearly 25,000 samples and 699 species. Bird data came from the eBird community science platform, with over 810,000 cleaned reports from January and July between 2010 and 2015, standardized as counts per person-hour. Diatoms were sampled from the top five centimeters of lake sediment across 1,070 lakes in a single year, yielding 1,957 species. Tree data, covering stems wider than five centimeters at breast height, came from the US Forest Service’s Forest Inventory Analysis across four years spaced five years apart, totaling nearly 40,000 samples and 403 species.

The analytical framework organized all georeferenced observations into hexagonal polygons, with cell size defining the spatial grain. At each grain, ranging from one square kilometer to one million square kilometers, the researchers calculated mean pairwise beta diversity between each central hexagon and its immediate neighbors. This neighborhood-based approach, borrowed conceptually from remote sensing research on optimized spatial resolution, controls for sample size across grains because hexagonal grids are constrained to fewer than six neighbors.

A critical methodological decision involved how beta diversity was calculated. The team used a relatively new deviation from a null model based on spatial heterogeneity, called beta NBD for its underlying negative binomial distribution. This measure, developed by Youhua Chen and Fangliang He, represents clustered species patterns more accurately than the older deviation based on spatial homogeneity. The newer measure made only modest adjustments to observed beta diversity and showed no vulnerability to sample size effects, whereas the older measure substantially altered observed values and increased with greater sampling effort.

The results were strikingly consistent. For all four taxa, beta diversity peaked at intermediate, regional spatial grains. Trees showed peak values at roughly 300 square kilometers, remarkably stable across four evaluated years spanning two decades. Winter birds peaked at approximately 500 square kilometers, while summer birds and ants both peaked near 2,000 square kilometers. Diatoms, the microscopic algae inhabiting lake bottoms, showed the largest peak at about 11,000 square kilometers. Hump-shaped quadratic curves fit the data far better than linear models, with Akaike Information Criterion weights exceeding 0.95 in all cases.

These rankings defied the team’s initial expectations. They had predicted that diatoms, confined to discrete lake habitats, would show the smallest community scales, followed by ants, trees, and birds. Instead, diatoms exhibited the largest peak, and trees the smallest. The researchers suggest that diatom community size roughly matched the average density of sampled lakes across the contiguous US, meaning the apparent regional scale may actually reflect the average dispersion of discrete diatom habitats rather than long-range dispersal. For terrestrial taxa inhabiting intergrading habitats, the regional peaks may reflect genuinely regional processes.

The repeatability of the patterns adds considerable weight to the findings. Bird beta diversity scaling was consistent across six consecutive years, though sensitive to seasonality, with winter communities concentrating at smaller spatial scales than summer ones. Tree patterns showed very little within- or among-annual variation at their peak grain. Given that birds and trees differ so enormously in life history and mobility, this commonality suggests that community assembly processes provide a strong and general basis for the observed regional scaling.

The results broadly support the regional community concept advanced by Robert Ricklefs, who argued in 2008 that regional scales should be preferred to local ones to capture the full suite of selective conditions driving diversity. The relatively low beta diversity at fine spatial grains in this study supports Ricklefs’ argument that local communities are one end of spatiotemporal continua rather than empirically distinct entities. The authors suggest that metacommunity ecology may be wise to treat local communities as sample points rather than bounded units, steering the field toward a species-centric approach.

Beyond its conceptual implications, the work bears fundamental consequences for conservation biogeography in the Anthropocene. If ecological communities are regional in scale, then local conservation efforts can best ensure success when coordinated regionally, through corridors and networks among conserved sites. The findings may also help researchers reconsider the appropriate spatial grains to use when studying diversity responses to land use and climate change, suggesting that rasterized study units matching peak beta diversity would obtain maximal resolution. The authors note that similar peaked spatial scaling may exist for other biogeographical patterns, potentially revealing maximal signal amidst noise and better representing natural patterns than maps designed for visual appeal.

Subject of Research: Peak beta diversity occurs at regional spatial grains

Article Title: Peak beta diversity occurs at regional spatial grains

Article References: Ohyama, L., Bogota-Gregory, J. D., & Jenkins, D. G. (2024). Peak beta diversity occurs at regional spatial grains. Frontiers of Biogeography, 17, Article e132675. https://doi.org/10.21425/fob.17.132675

Image Credits: AI Generated

DOI: 10.21425/fob.17.132675

Keywords: Peak, beta, diversity, occurs, regional, spatial, grains, scientific research

The research drew on the Household Influenza Vaccine Evaluation study, known as the HIVE cohort, a longitudinal surveillance program that has followed roughly 300 households annually for acute respiratory illness. This infrastructure, originally built to study influenza transmission, proved to be a valuable resource for tracking SARS-CoV-2 immunity because participants undergo active surveillance for respiratory symptoms and provide serum samples that can be archived and analyzed retrospectively. For the present analysis, the team selected serum samples drawn between July 1 and December 31, 2021, a period that captures the interval just before Omicron displaced Delta as the dominant circulating strain.

From this collection, the researchers analyzed 156 serum samples from 117 participants. Adults accounted for 65.8 percent of the samples, and a majority of donors, 77.8 percent, had received vaccination during the analysis period. This composition reflects the reality of mid-2021 in the United States, when vaccine rollout had reached most adults but authorization for younger age groups was still limited or recent, leaving children with immunity derived almost exclusively from natural infection.

Methodologically, the study stands out for its systematic comparison of three complementary assay platforms. The first is a multiplex electrochemiluminescence assay, abbreviated ECL, which quantifies variant-specific immunoglobulin G antibodies binding to spike proteins from the original strain and from the Delta, Beta, and Omicron variants. The second is a pseudoviral neutralization assay, or PN, which uses engineered viruses carrying variant spike proteins to measure the functional ability of antibodies to block viral entry. The third is an ACE2 inhibition assay, which tests how effectively antibodies compete with the human ACE2 receptor for binding to the viral spike, a proxy for neutralizing capacity that can be run at higher throughput than live-virus neutralization.

The correlations among these platforms were strikingly high. Within the ECL IgG assays, Spearman rank correlation coefficients ranged from 0.95 to 1.00, indicating near-perfect agreement in how antibody concentrations measured against different variant antigens tracked together across samples. Within the ACE2 inhibition assays, correlations ranged from 0.70 to 0.99. Between platforms, ECL measurements correlated with pseudoviral neutralization at 0.81 to 0.83, and ACE2 inhibition correlated with neutralization at 0.88 to 0.95. These findings suggest that binding antibody titers, which are faster and cheaper to measure than functional neutralization tests, provide a reliable readout of the functional quality of the antibody response across antigenically distinct variants.

Receiver operating characteristic analysis, which evaluates how well a test discriminates between two states, was used to determine whether the assays could reliably identify vaccination status. The ECL IgG assays performed strongly, with areas under the curve between 0.84 and 0.88, sensitivity between 0.88 and 0.91, and specificity between 0.87 and 0.88. In practical terms, this means the binding assays could distinguish vaccinated from unvaccinated individuals with high accuracy. The ACE2 inhibition assays showed more variable performance, with areas under the curve ranging from 0.53 to 0.96, sensitivity from 0.17 to 0.93, and specificity from 0.91 to 1.00. Notably, some antigens related to the BA.2 sublineage of Omicron showed lower discrimination, a finding the authors attribute to the limited exposure of this cohort to Omicron antigens at the time of sampling, since most participants had never encountered Omicron through infection or vaccination with an Omicron-matched vaccine.

Beyond assay validation, the study used generalized additive mixed models to estimate how population immunity varied with age against each SARS-CoV-2 variant. The results showed that SARS-CoV-2 IgG concentrations generally increased with age and appeared to plateau in early adulthood. This age gradient reflects the combined influence of infection history and vaccination uptake, both of which were captured by the active surveillance infrastructure of the HIVE cohort. Younger children, who had fewer opportunities for infection and limited vaccine access during the study period, showed the lowest antibody concentrations, marking them as a susceptible group for continued surveillance.

The authors caution that estimates in the youngest age groups were imprecise because of small sample sizes, a limitation inherent in a cohort designed around households rather than stratified age sampling. Nevertheless, the concordance between the age-specific antibody patterns and the behavior and infection histories collected through active surveillance lends confidence to the overall picture. The study demonstrates that a high-throughput, low-volume assay strategy can describe strain-specific IgG measurement in a longitudinally followed community cohort, providing a template for ongoing serosurveillance as the virus continues to evolve.

The implications extend to vaccine strain selection, one of the most consequential decisions in pandemic response. Continued serosurveys that quantify variant-specific population immunity are critical for identifying which segments of the population lack protection against emerging variants and for informing the composition of updated vaccines. By validating that binding antibody assays correlate strongly with functional neutralization across variants, this study lowers the barrier to conducting such surveys at scale. As new variants emerge, the ability to rapidly measure strain-specific immunity in community cohorts, using small serum volumes and multiplex platforms, will remain a cornerstone of evidence-based pandemic preparedness.

Subject of Research: Evaluation of pre-Omicron population immunity for SARS-CoV-2 in the Household Influenza Vaccine Evaluation (HIVE) cohort

Article Title: Evaluation of pre-Omicron population immunity for SARS-CoV-2 in the Household Influenza Vaccine Evaluation (HIVE) cohort

Article References: Yang, Y., Juntila-Raymond, C., Callear, A., Smith, M., Atkinson, R. K., Zhao, Y., Shah, R., Santos, J. J. S., Hensley, S. E., Monto, A. S., & Martin, E. T. (2026). Evaluation of pre-Omicron population immunity for SARS-CoV-2 in the Household Influenza Vaccine Evaluation (HIVE) cohort. PLOS One, 21(10), e0360506. https://doi.org/10.1371/journal.pone.0360506

Image Credits: AI Generated

DOI: 10.1371/journal.pone.0360506

Keywords: SARS-CoV-2, population immunity, serosurvey, HIVE cohort, variant-specific IgG, electrochemiluminescence assay, pseudoviral neutralization, ACE2 inhibition, vaccine strain selection, Omicron, Evaluation, pre-Omicron

An international research team led by investigators at Huazhong Agricultural University assembled the first cross-genus integrated analysis of coronavirus transcriptomes and RNA-RNA interactomes, spanning all four coronavirus genera: alpha, beta, gamma, and delta. The team performed new RNA sequencing and RIC-seq experiments on the porcine epidemic diarrhea virus, an alpha-coronavirus, and porcine deltacoronavirus, a delta-coronavirus, filling a critical gap left by earlier studies that focused almost exclusively on beta-coronaviruses such as SARS-CoV-2 and MERS-CoV. By combining their new data with publicly available datasets, the researchers constructed a resource of 234 transcriptomes and 12 RNA-RNA interactome maps, hosted in a publicly accessible database called the Coronavirus Omics Data Explorer.

The first major finding to emerge from this integrated analysis was a conserved U-shaped distribution of RNA-RNA interaction frequencies across all four coronavirus genera. Interactions follow a power-law decay at short genomic distances, reach a minimum between 5 and 20 kilobases, and then rise again at distances exceeding 20 kilobases. This hierarchical folding pattern, preferentially enriching both short-range and long-range contacts, suggests that coronaviruses employ a shared genome organization strategy that may help coordinate transcription and replication during infection, regardless of which genus the virus belongs to.

The researchers then systematically classified canonical, TRS-dependent, and non-canonical, TRS-independent, transcription junctions across 103 high-quality RNA sequencing samples covering 14 different coronaviruses. Unsupervised clustering revealed three distinct groups of samples: a canonical-dominant group accounting for 63.1 percent of samples, a mixed group at 19.4 percent, and a non-canonical-dominant group at 17.5 percent. Notably, the balance between canonical and non-canonical transcription shifted with infection time, serial passage, viral genetic background, and specific experimental perturbations. Non-canonical junctions accumulated with serial passage in five of six independent passage datasets, and treatments such as luteolin altered the junction ratio, whereas others, including the nucleoside analog NHC, had minimal impact.

Turning to the structural basis of these events, the team used aggregate peak analysis of RNA-RNA interaction data to examine the genomic regions flanking canonical junction sites. Across PEDV, SARS-CoV-2, PDCoV, and MERS-CoV, interaction hotspots preferentially occurred between the flanking regions of the leader transcription regulatory sequence and body transcription regulatory sequences oriented in the same genomic direction, producing pronounced diagonal enrichment in the heatmaps. This same-directionality pattern, validated independently by COMRADES, SPLASH, and simplified-SPLASH in SARS-CoV-2, suggests that parallel spatial proximity between these regulatory elements facilitates the template-switching step carried out by the viral polymerase during canonical sgRNA synthesis.

Non-canonical junctions told a different structural story. Short-range non-canonical junctions, those spanning less than roughly 1.7 kilobases, showed anti-diagonal enrichment in the interaction heatmaps, indicating convergent, or antiparallel, orientations between the participating genomic regions. These convergent interactions are consistent with reverse-complementary base pairing that stabilizes RNA stem-loop structures. In SARS-CoV-2-infected cells, the researchers identified 5,014 non-canonical junctions between three TRS-like sequence pairs co-localized within a single stem-loop spanning nucleotides 29,262 to 29,870, demonstrating that such structures can physically bring distant sequence motifs into contact to drive discontinuous transcription without any involvement of the canonical leader sequence.

Perhaps the most striking connection emerged when the team mapped genomic deletion hotspots. Across multiple genome alignments, they identified 105 deletions exceeding 20 nucleotides in SARS-CoV-2, 31 in PEDV, 17 in MERS-CoV, and 8 in PDCoV. The interaction patterns at deletion boundaries mirrored those at short-range non-canonical junctions, with significant anti-diagonal enrichment. Moreover, 29.5 percent of SARS-CoV-2 deletions, 45.2 percent of PEDV deletions, and 62.5 percent of PDCoV deletions overlapped with predicted stem-loop regions. In SARS-CoV-2, a 2,250-nucleotide window in the 3-prime proximal genome, encompassing the 3’SL1, 3’SL2, and 3’SL3 stem-loops, contained 16 deletions concentrated in the ORF7a, ORF7b, and ORF8 accessory genes, a density far exceeding the genome-wide expectation. These findings suggest that stem-loop-mediated short-range non-canonical junctions may serve as initiating events for genomic deletions that shape viral evolution.

The conserved 3’SL1/2/3 region also revealed a mechanism for expressing ORF10, a SARS-CoV-2 gene that lacks its own canonical body TRS. The 5-prime portions of these stem-loops sit downstream of the TRS-B elements of upstream genes such as N, ORF7a, and ORF7b, while their 3-prime portions lie upstream of ORF10, an arrangement that allows TRS-B transfer from upstream genes to ORF10. Nanopore sequencing confirmed the existence of double-junction sgRNAs containing ORF10, upstream TRS-B sequences, and the leader, with an average of 11.37 percent of non-canonical ORF10 sgRNAs arising through this route. The remaining ORF10 transcripts were formed by a single long-range junction between the N gene and ORF1a, generating what the researchers designated sgRNA-N-ORF1a.

Remarkably, this N-ORF1a junction proved to be a recurring feature across coronavirus genera. Full-length sgRNA-N-ORF1a molecules were confirmed by nanopore sequencing in PEDV, MERS-CoV, MHV, and HCoV-229E, and reproducible RNA-RNA interactions between the two participating genomic regions were detected across different viruses. The transcription level of sgRNA-N-ORF1a tracked changes in interaction strength over the infection time course, declining in parallel with a 12.76 percent reduction in N-ORF1a genomic interaction between 24 and 48 hours post-infection. These sgRNAs carry the 3-prime untranslated region at their termini, and within these regions the team identified potential open reading frames, designated ORF-UTR3, in MERS-CoV, PEDV, and PDCoV, predicted using non-canonical GUG or UUG initiation codons.

Functional experiments lent biological weight to these predictions. When the researchers engineered a PDCoV ORF-UTR3 variant with its non-canonical GUG start codon converted to AUG and overexpressed it in LLC-PK1 cells, the construct significantly reduced the transcription of IFN-alpha1, IFN-beta, ISG15, and OAS1 upon PDCoV infection, mirroring the immune-suppressive function previously reported for SARS-CoV-2 ORF10. Viral N sgRNA abundance also increased in ORF-UTR3-overexpressing cells, indicating enhanced replication. Taken together, the study proposes that architecturally programmed discontinuous RNA synthesis links non-canonical sgRNAs to genomic plasticity and immune modulation, offering a framework for understanding coronavirus adaptation and potentially informing the design of more stable attenuated vaccines, since deletion-prone stem-loop regions appear to be central to both viral evolvability and passage-based attenuation strategies.

Subject of Research: Architecturally programmed discontinuous transcription and subgenomic RNA synthesis patterns across coronavirus genera

Article Title: Cross-genus analysis reveals architecturally programmed sgRNA synthesis patterns in coronaviruses

Article References: Wen, Z., Chen, L., Luo, D., Sun, J., Guo, L., Deng, Y., Huang, Z., Wang, Y., Pan, K., Wang, F., Xiao, S., Li, L., & Wei, D. (2026). Cross-genus analysis reveals architecturally programmed sgRNA synthesis patterns in coronaviruses. Molecular Systems Biology. https://doi.org/10.1038/s44320-026-00239-0

Image Credits: AI Generated

DOI: 10.1038/s44320-026-00239-0

Keywords: coronavirus, subgenomic RNA, discontinuous transcription, RNA-RNA interactome, RNA architecture, stem-loop, genomic deletion, ORF10, immune modulation, SARS-CoV-2, PEDV, PDCoV