Seasonally fluctuating selection can maintain polymorphism at many loci via segregation lift

Most natural populations are affected by seasonal changes in temperature, rainfall, or resource availability. Seasonally fluctuating selection could potentially make a large contribution to maintaining genetic polymorphism in populations. However, previous theory suggests that the conditions for multilocus polymorphism are restrictive. Here, we explore a more general class of models with multilocus seasonally fluctuating selection in diploids. In these models, the multilocus genotype is mapped to fitness in two steps. The first mapping is additive across loci and accounts for the relative contributions of heterozygous and homozygous loci-that is, dominance. The second step uses a nonlinear fitness function to account for the strength of selection and epistasis. Using mathematical analysis and individual-based simulations, we show that stable polymorphism at many loci is possible if currently favored alleles are sufficiently dominant. This general mechanism, which we call "segregation lift," requires seasonal changes in dominance, a phenomenon that may arise naturally in situations with antagonistic pleiotropy and seasonal changes in the relative importance of traits for fitness. Segregation lift works best under diminishing-returns epistasis, is not affected by problems of genetic load, and is robust to differences in parameters across loci and seasons. Under segregation lift, loci can exhibit conspicuous seasonal allele-frequency fluctuations, but often fluctuations may be small and hard to detect. An important direction for future work is to formally test for segregation lift in empirical data and to quantify its contribution to maintaining genetic variation in natural populations.

Fluctuating Environments and Phytoplankton Community Structure: A Stochastic Model

Spatial heterogeneity in organism and resource distributions can generate temporal heterogeneity in resource access for simple organisms like phytoplankton. The role of temporal heterogeneity as a structuring force for simple communities is investigated via models of phytoplankton with contrasting life histories competing for a single fluctuating resource. A stochastic model in which environmental and demographic stochasticity are treated separately is compared with a model with deterministic resource variation to assess the importance of stochasticity. When compared with the deterministic model, the stochastic model allows for coexistence over a wider range of parameter values (or life-history types). The model suggests that demographic stochasticity alone is far more important in increasing the possibility of coexistence than environmental stochasticity alone. However, the combined effects of both types of stochasticity produce the largest likelihood of coexistence. Finally, the influence of relative nutrient levels and nutrient pulse frequency on these results is addressed. We relate our findings to variable environment theory with evidence for both relative nonlinearity and the storage effect acting in this model. We show for the first time that temporal dynamics generated by demographic stochasticity may operate like the storage effect at particular spatial scales.

Understanding patterns of HIV multi-drug resistance through models of temporal and spatial drug heterogeneity

Triple-drug therapies have transformed HIV from a fatal condition to a chronic one. These therapies should prevent HIV drug resistance evolution, because one or more drugs suppress any partially resistant viruses. In practice, such therapies drastically reduced, but did not eliminate, resistance evolution. In this article, we reanalyze published data from an evolutionary perspective and demonstrate several intriguing patterns about HIV resistance evolution - resistance evolves (1) even after years on successful therapy, (2) sequentially, often via one mutation at a time and (3) in a partially predictable order. We describe how these observations might emerge under two models of HIV drugs varying in space or time. Despite decades of work in this area, much opportunity remains to create models with realistic parameters for three drugs, and to match model outcomes to resistance rates and genetic patterns from individuals on triple-drug therapy. Further, lessons from HIV may inform other systems.

Changes in DNA Damage Response Markers with Treatment in Advanced Ovarian Cancer

Ovarian cancer (OC) is sensitive to upfront chemotherapy, which is likely attributable to defects in DNA damage repair (DDR). Unfortunately, patients relapse and the evolution of DDR competency are poorly described. We examined the expression of proposed effectors in homologous recombination (HR: RAD51, ATM, FANCD2), error-prone non-homologous end-joining (NHEJ: 53BP1), and base excision repair pathways (BER: PAR and PARP1) in a cohort of sequential OC samples obtained at diagnosis, after neoadjuvant chemotherapy (NACT), and/or at relapse from a total of 147 patients. Immunohistochemical (IHC) expression was quantified using the H-score (0-300), where H ≤ 10 defined negativity. Before NACT, a significant number of cases lacked the expression of some effectors: 60%, 60%, and 24% were PAR-, FANCD2-, or RAD51-negative, with a reassuringly similar proportion of negative biomarkers after NACT. In multivariate analysis, there was a poorer progression-free survival (PFS) and overall survival (OS) for cases with competent HR at diagnosis (PRE-NACT 53BP1-/RAD51+, hazard ratio (HR) 3.13, p = 0.009 and HR 2.78, p = 0.024) and after NACT (POST-NACT FANCD2+/RAD51+ HR 1.89, p = 0.05 and HR 2.38, p = 0.02; POST-NACT PARP-1+/RAD51+ HR 1.79, p = 0.038 and HR 2.04, p = 0.034), reflecting proficient DNA repair. Overall, HR-competent tumors appeared to have a dismal prognosis in comparison with tumors utilizing NHEJ, as assessed either at baseline or post-NACT. Accurate knowledge of the HR status during treatment is clinically important for the efficient timing of platinum-based and targeted therapies with poly(ADP-ribose) polymerase inhibitors (PARPi).

Natural quantitative genetic variance in plant growth differs in response to ecologically relevant temperature heterogeneity

Adaptation to large‐scale spatial heterogeneity in the environment accounts for a major proportion of genetic diversity within species. Theory predicts the erosion of adaptive genetic variation on a within‐population level, but considerable genetic diversity is often found locally. Genetic diversity could be expected to be maintained within populations in temporally or spatially variable conditions if genotypic rank orders vary across contrasting microenvironmental settings. Taking advantage of fine‐resolution environmental data, we tested the hypothesis that temperature heterogeneity among years could be one factor maintaining quantitative genetic diversity within a natural and genetically diverse plant population. We sampled maternal families of Boechera stricta, an Arabidopsis thaliana relative, at one location in the central Rocky Mountains and grew them in three treatments that, based on records from an adjacent weather station, simulated hourly temperature changes at the native site during three summers with differing mean temperatures. Treatment had a significant effect on all traits, with 2–3‐fold increase in above‐ and belowground biomass and the highest allocation to roots observed in the treatment simulating the warmest summer on record at the site. Treatment affected bivariate associations between traits, with the weakest correlation between above‐ and belowground biomass in the warmest treatment. The magnitude of quantitative genetic variation for all traits differed across treatments: Genetic variance of biomass was 0 in the warmest treatment, while highly significant diversity was found in average conditions, resulting in broad‐sense heritability of 0.31. Significant genotype × environment interactions across all treatments were found only in root‐to‐shoot ratio. Therefore, temperature variation among summers appears unlikely to account for the observed levels of local genetic variation in size in this perennial species, but may influence family rank order in growth allocation. Our results indicate that natural environmental fluctuations can have a large impact on the magnitude of within‐population quantitative genetic variance.

Multiregional Sequencing of IDH-WT Glioblastoma Reveals High Genetic Heterogeneity and a Dynamic Evolutionary History

Simple Summary

Glioblastoma is the most common and aggressive primary brain malignancy in adults. In addition to extensive inter-patient heterogeneity, glioblastoma shows intra-tumor extensive cellular and molecular heterogeneity, both spatially and temporally. This heterogeneity is one of the main reasons for the poor prognosis and overall survival. Moreover, it raises the important question of whether the molecular characterization of a single biopsy sample, as performed in standard diagnostics, actually represents the entire lesion. In this study, we sequenced the whole exome of nine spatially different cancer regions of three primary glioblastomas. We characterized their mutational profiles and copy number alterations, with implications for our understanding of tumor biology in relation to clonal architecture and evolutionary dynamics, as well as therapeutically relevant alterations.

Abstract

Glioblastoma is one of the most common and lethal primary neoplasms of the brain. Patient survival has not improved significantly over the past three decades and the patient median survival is just over one year. Tumor heterogeneity is thought to be a major determinant of therapeutic failure and a major reason for poor overall survival. This work aims to comprehensively define intra- and inter-tumor heterogeneity by mapping the genomic and mutational landscape of multiple areas of three primary IDH wild-type (IDH-WT) glioblastomas. Using whole exome sequencing, we explored how copy number variation, chromosomal and single loci amplifications/deletions, and mutational burden are spatially distributed across nine different tumor regions. The results show that all tumors exhibit a different signature despite the same diagnosis. Above all, a high inter-tumor heterogeneity emerges. The evolutionary dynamics of all identified mutations within each region underline the questionable value of a single biopsy and thus the therapeutic approach for the patient. Multiregional collection and subsequent sequencing are essential to try to address the clinical challenge of precision medicine. Especially in glioblastoma, this approach could provide powerful support to pathologists and oncologists in evaluating the diagnosis and defining the best treatment option.

Liquid biopsy for the assessment of adrenal cancer heterogeneity: where do we stand?

Almost 10 years have passed since the first attempts of liquid biopsy aimed at the characterisation of tumor cells present in the bloodstream from a regular sample of peripheral blood were performed. Liquid biopsy has been used to characterise tumor heterogeneity in various types of solid tumors including adrenocortical carcinoma. The development of molecular biology, genetics, and methodological advances such as digital PCR and next-generation sequencing allowed us to use besides circulating tumor cells a variety of circulating cell-free nucleic acids, DNAs, RNAs and microRNAs secreted by tumors into blood and other body fluids as specific molecular markers. These markers are used for diagnosis, to check tumor development, selecting efficient therapies, therapy monitoring and even possess prognostic power. In adrenocortical carcinoma, there are some studies reporting analysis of circulating tumor cells, circulating cell free DNA and microRNAs for assessing tumor heterogeneity. Among microRNAs, hsa-miR-483-5p seems to be the most important player. Combined with other microRNAs like hsa-miR-195, their expression correlates with recurrence-free survival. Most studies support the applicability of liquid biopsy for assessing temporal tumor heterogeneity (i.e. tumor progression) in adrenocortical cancer. In this mini-review, the available findings of liquid biopsy for assessing tumor heterogeneity in adrenocortical cancer are presented.

Last-come, best served? Mosquito biting order and Plasmodium transmission

A pervasive characteristic of parasite infections is their tendency to be overdispersed. Understanding the mechanisms underlying this overdispersed distribution is of key importance as it may impact the transmission dynamics of the pathogen. Although multiple factors ranging from environmental stochasticity to inter-individual heterogeneity may explain parasite overdispersion, parasite infection is also overdispersed in an inbred host population maintained under laboratory conditions, suggesting that other mechanisms are at play. Here, we show that the aggregated distribution of malaria parasites within mosquito vectors is partially explained by a temporal heterogeneity in parasite infectivity triggered by the bites of mosquitoes. Parasite transmission tripled between the mosquito's first and last blood feed in a period of only 3 h. Surprisingly, the increase in transmission is not associated with an increase in parasite investment in production of the transmissible stage. Overall, we highlight that Plasmodium is capable of responding to the bites of mosquitoes to increase its own transmission at a much faster pace than initially thought and that this is partly responsible for overdispersed distribution of infection. We discuss the underlying mechanisms as well as the broader implications of this plastic response for the epidemiology of malaria.

Timing of Histological Distal Villous Fetal Vascular Malperfusion in the Placenta: Clinical Significance and Placental Features

OBJECTIVE

This retrospective analysis compares the diagnostic value of placental large vessel (global, partial) and distal villous (complete, segmental) fetal vascular malperfusion (FVM), remote/established, recent and on-going.

METHODS

24 independent abnormal clinical and 46 placental phenotypes were retrospectively statistically analyzed among 1002 consecutive cases, mostly with congenital anomalies in which CD34 immunostaining was performed. Group A: 398 cases without distal FVM and none or up to two large vessels FVM lesions. Group B: 221 cases with distal villous FVM without clustered endothelial fragmentation by CD34 immunostain. Group C: 145 cases with clustered endothelial fragmentation by CD34 immunostain but no clustered sclerotic or mineralized distal villi. Group D: 163 cases with coexistence of distal villous lesions of Group B and Group C. Group E: 75 cases with three or four lesions of large vessel FVM, but no distal villous FVM lesions.

RESULTS

Established and/or remote FVM had clinical/placental associations similar to those of recent FVM, but on-going FVM was most commonly high grade and associated with preterm pregnancies, stillbirth, and fetal growth restriction. Large vessel FVM usually occurs in advanced third trimester pregnancies with fetal congenital anomalies, villitis of unknown etiology, and intervillous thrombi but no direct association with abnormal fetal condition.

CONCLUSION

FVM was the most common pattern of placental injury in this material. Proximal FVM was more common than distal FVM, suggesting the sequence of occurrence and the likely umbilical cord compression etiology. CD34 immunostaining doubles the sensitivity of placental examination and frequently upgrades the FVM, making it an important adjunct to placental histology.

Temporal genomic heterogeneity guiding individualized therapy in recurrent non-small cell lung cancer

Introduction

Despite the benefit of adjuvant systemic therapy for patients with resected non-small cell lung cancer (NSCLC), the risk of postoperative recurrence remains high. Our objective was to characterize temporal genetic heterogeneity between primary resected and recurrent tumors, and its impact on treatment outcomes.

Methods

In this study, next-generation sequencing (NGS) testing was performed on tissue specimens and circulating tumor DNA (ctDNA) collected at postoperative recurrence, and results were compared to the genotypes of initial surgical specimens.

Results

Of forty-five patients with matched primary and post-operative recurrent tumors, EGFR status switched in 17 patients (37.8%) at post-operative recurrence and 28 patients (62.2%) had no genotype change (17 mutant, 11 wild-type). Based on the changes of EGFR status, patients were divided into 4 groups. Following subsequent treatment with EGFR TKI o chemotherapy: In group A, with sustained sensitive mutation, the percentage achieving partial response (PR) was the highest, at 72.2%, the median progression-free survival (PFS) was 17 months, and the median overall survival (OS) was 44.0 months respectively; In group B, with genotype changed from wild-type to mutant, 50% achieved PR, PFS was 10 months, and OS was 35 months; In group C, in which mutant status shifted to wild-type or new co-mutation emerged, the percentage achieving PR was 30%, PFS was 9 months, and OS was 35 months. In group D, with sustained wild type, the percentage achieving PR was 27.3%, PFS was 8 months, and OS was 22 months.

Discussion

Genotypic shift between paired primary and post-operative recurrent tumors was not infrequent, and this temporal genomic heterogeneity substantially impacted subsequent treatment outcomes.

Burst and Memory-aware Transformer: capturing temporal heterogeneity

Burst patterns, characterized by their temporal heterogeneity, have been observed across a wide range of domains, encompassing event sequences from neuronal firing to various facets of human activities. Recent research on predicting event sequences leveraged a Transformer based on the Hawkes process, incorporating a self-attention mechanism to capture long-term temporal dependencies. To effectively handle bursty temporal patterns, we propose a Burst and Memory-aware Transformer (BMT) model, designed to explicitly address temporal heterogeneity. The BMT model embeds the burstiness and memory coefficient into the self-attention module, enhancing the learning process with insights derived from the bursty patterns. Furthermore, we employed a novel loss function designed to optimize the burstiness and memory coefficient values, as well as their corresponding discretized one-hot vectors, both individually and jointly. Numerical experiments conducted on diverse synthetic and real-world datasets demonstrated the outstanding performance of the BMT model in terms of accurately predicting event times and intensity functions compared to existing models and control groups. In particular, the BMT model exhibits remarkable performance for temporally heterogeneous data, such as those with power-law inter-event time distributions. Our findings suggest that the incorporation of burst-related parameters assists the Transformer in comprehending heterogeneous event sequences, leading to an enhanced predictive performance.

Associations Between Developmental Stability, Canalization, and Phenotypic Plasticity in Response to Heterogeneous Experience

The processes of developmental stability, canalization, and phenotypic plasticity have ecological and evolutionary significance, and been studied extensively, but mostly separately and thus the relationships between them are not straightforward. Our objective was to better integrate these processes in the context of temporally heterogeneous environments. We did this by investigating the effects of early experience with temporal heterogeneity in water availability on associations between developmental stability, canalization, and phenotypic plasticity. We subjected eight plant species to a first round of alternating inundation and drought vs. constantly moderate water treatments (heterogeneous experience) and a second round of water conditions (to test plasticity). We measured fluctuating asymmetry (FA) in leaf size, intra- and inter-individual variation (CVintra and CVinter), and plasticity (PI) in traits and analyzed correlations between these variables across all species. Results showed little correlations between FA, CVintra and PI, several positive correlations between FA and CVinter in more stressful conditions, especially in as well as positive correlations between CVinter and PI initially and negative correlations between them later. These suggested the complexity of these relationships, which can depend on whether plasticity occurs. Greater inter-individual variation will more likely cooperate with plasticity before or during plastic response, whereas higher canalization may reflect phenotypic convergence. Both higher FA and CVintra can reflect faster growth, while CVintra may also reflect plant growth stage, and the two mechanisms should cooperate in response to environmental challenges. The complexity of these relationships suggests plants deal with environmental variation in elaborate and integrative ways which can be affected by many factors.

Regional and age-related diversity of human mature oligodendrocytes

Morphological and emerging molecular studies have provided evidence for heterogeneity within the oligodendrocyte population. To address the regional and age-related heterogeneity of human mature oligodendrocytes (MOLs) we applied single-cell RNA sequencing to cells isolated from cortical/subcortical, subventricular zone brain tissue samples, and thoracolumbar spinal cord samples. Unsupervised clustering of cells identified transcriptionally distinct MOL subpopulations across regions. Spinal cord MOLs, but not microglia, exhibited cell-type-specific upregulation of immune-related markers compared to the other adult regions. SVZ MOLs showed an upregulation of select number of development-linked transcription factors compared to other regions; however, pseudotime trajectory analyses did not identify a global developmental difference. Age-related analysis of cortical/subcortical samples indicated that pediatric MOLs, especially from under age 5, retain higher expression of genes linked to development and to immune activity with pseudotime analysis favoring a distinct developmental stage. Our regional and age-related studies indicate heterogeneity of MOL populations in the human CNS that may reflect developmental and environmental influences.

Identifying risk clusters for African swine fever in Korea by developing statistical models

Introduction

African swine fever (ASF) is a disease with a high mortality rate and high transmissibility. Identifying high-risk clusters and understanding the transmission characteristics of ASF in advance are essential for preventing its spread in a short period of time. This study investigated the spatial and temporal heterogeneity of ASF in the Republic of Korea by analyzing surveillance data on wild boar carcasses.

Methods

We observed a distinct annual propagation pattern, with the occurrence of ASF-infected carcasses trending southward over time. We developed a rank-based statistical model to evaluate risk by estimating the average weekly number of carcasses per district over time, allowing us to analyze and identify risk clusters of ASF. We conducted an analysis to identify risk clusters for two distinct periods, Late 2022 and Early 2023, utilizing data from ASF-infected carcasses. To address the underestimation of risk and observation error due to incomplete surveillance data, we estimated the number of ASF-infected individuals and accounted for observation error via different surveillance intensities.

Results

As a result, in Late 2022, the risk clusters identified by observed and estimated number of ASF-infected carcasses were almost identical, particularly in the northwestern Gyeongbuk region, north Chungbuk region, and southwestern Gangwon region. In Early 2023, we observed a similar pattern with numerous risk clusters identified in the same regions as in Late 2022.

Discussion

This approach enhances our understanding of ASF spatial dynamics. Additionally, it contributes to the epidemiology and study of animal infectious diseases by highlighting areas requiring urgent and focused intervention. By providing crucial data for the targeted allocation of resources for disease management and preventive measures, our findings lay vital groundwork for improving ASF management strategies, ultimately aiding in the containment and control of this devastating disease.

Circulating tumour DNA detects somatic variants contributing to spatial and temporal intra-tumoural heterogeneity in head and neck squamous cell carcinoma

Background

As circulating tumour DNA (ctDNA) liquid biopsy analysis is increasingly incorporated into modern oncological practice, establishing the impact of genomic intra-tumoural heterogeneity (ITH) upon data output is paramount. Despite advances in other cancer types the evidence base in head and neck squamous cell carcinoma (HNSCC) remains poor. We sought to investigate the utility of ctDNA to detect ITH in HNSCC.

Methods

In a pilot cohort of 9 treatment-naïve HNSCC patients, DNA from two intra-tumoural sites (core and margin) was whole-exome sequenced. A 9-gene panel was designed to perform targeted sequencing on pre-treatment plasma cell-free DNA and selected post-treatment samples.

Results

Rates of genomic ITH among the 9 patients was high. COSMIC variants from 19 TCGA HNSCC genes demonstrated an 86.9% heterogeneity rate (present in one tumour sub-site only). Across all patients, cell-free DNA (ctDNA) identified 12.9% (range 7.5-19.8%) of tumour-specific variants, of which 55.6% were specific to a single tumour sub-site only. CtDNA identified 79.0% (range: 55.6-90.9%) of high-frequency variants (tumour VAF>5%). Analysis of ctDNA in serial post-treatment blood samples in patients who suffered recurrence demonstrated dynamic changes in both tumour-specific and acquired variants that predicted recurrence ahead of clinical detection.

Conclusion

We demonstrate that a ctDNA liquid biopsy identified spatial genomic ITH in HNSCC and reliably detected high-frequency driver mutations. Serial sampling allowed post-treatment surveillance and early identification of treatment failure.

Identification of geographic clusters for temporal heterogeneity with application to dengue surveillance

Identifying transmission of hot spots with temporal trends is important for reducing infectious disease propagation. Cluster analysis is a particularly useful tool to explore underlying stochastic processes between observations by grouping items into categories by their similarity. In a study of epidemic propagation, clustering geographic regions that have similar time series could help researchers track diffusion routes from a common source of an infectious disease. In this article, we propose a two‐stage scan statistic to classify regions into various geographic clusters by their temporal heterogeneity. The proposed scan statistic is more flexible than traditional methods in that contiguous and nonproximate regions with similar temporal patterns can be identified simultaneously. A simulation study and data analysis for a dengue fever infection are also presented for illustration.

Construction of a nomogram model based on biomarkers for liver metastasis in non-small cell lung cancer

BACKGROUND

Patients with non-small cell lung cancer (NSCLC) with liver metastasis have a poor prognosis, and there are no reliable biomarkers for predicting disease progression. Currently, no recognized and reliable prediction model exists to anticipate liver metastasis in NSCLC, nor have the risk factors influencing its onset time been thoroughly explored.

METHODS

This study conducted a retrospective analysis of 434 NSCLC patients from two hospitals to assess the association between the risk and timing of liver metastasis, as well as several variables.

RESULTS

The patients were divided into two groups: those without liver metastasis and those with liver metastasis. We constructed a nomogram model for predicting liver metastasis in NSCLC, incorporating elements such as T stage, N stage, M stage, lack of past radical lung cancer surgery, and programmed death ligand 1 (PD-L1) levels. Furthermore, NSCLC patients with wild-type EGFR, no prior therapy with tyrosine kinase inhibitors (TKIs), and no prior radical lung cancer surgery showed an elevated risk of early liver metastasis.

CONCLUSION

In conclusion, the nomogram model developed in this study has the potential to become a simple, intuitive, and customizable clinical tool for assessing the risk of liver metastasis in NSCLC patients following validation. Furthermore, it provides a framework for investigating the timing of metachronous liver metastasis.

Quantitative evaluation of the drivers of species richness in a Mediterranean ecosystem (Cape, South Africa)

BACKGROUND AND AIMS

Mediterranean ecosystems have a high vascular plant species richness (SR) relative to their surface area. This SR, representing the balance between speciation and extinction, has been attributed to multiple mechanisms that result in both high rates of speciation and/or low rates of extinction. An abiding question is, however, what is special about Mediterranean ecosystems that enables this high SR? Apart from the long-term climatic stability of the region, SR has also been related to resource availability, the many individuals hypothesis, resource spatial heterogeneity, temporal heterogeneity and biotic feedbacks.

METHODS

Spatial patterns of species richness were related to climatic, edaphic and biotic variables and to spatial variability within the Greater Cape Floristic Region (GCFR) of South Africa. Boosted regression tree models were used to explore the strength of relationships between SR and environmental predictors related to each hypothesized mechanism.

KEY RESULTS

Water availability (i.e. precipitation) was a stronger predictor of SR than potential evapotranspiration or temperature. Scarcity of nutrients was also related to SR. There was no indication that SR was related to the density of individuals and only temporal heterogeneity induced by fire was related to SR. Spatial heterogeneities of climatic, edaphic and biotic variables were strongly associated with SR. Biotic interactions remain difficult to assess, although we have some evidence for a putative role in regulating SR.

CONCLUSIONS

While the lack of ecosystem-resetting disturbances (e.g. glaciation) is undoubtedly a key requirement for high species accumulation, predictably, no one explanation holds the key to understanding SR. In the GCFR high SR is the product of a combination of adequate water, nutrient scarcity, spatial and temporal heterogeneity, and possibly biotic feedbacks.