Negative Selection Research Articles

Identification of High Erucic Acid Brassica carinata Genotypes through Multi-Trait Stability Index

Brassica carinata is an important and native oilseed crop in Ethiopia. The seed oil from B.carinata attracts global attention for its various industrial applications, mainly due to its high erucic acid levels and its superior agronomic traits. Since the demand for high erucic acid from oilseed brassica has been increasing in the world market due to its wider applications in bio-industries, the breeding target of B. carinata has recently been focused on enhancing its erucic acid. Several high erucic acid B. carinata genotypes have been screened from the pre-breeding activities. Such genotypes, however, need to be tested for their stable performance, for their erucic acid level, and other desirable traits under different environments. The aim of this study was to identify high erucic acid B. carinata genotypes with stable performance in multiple desirable traits. Thirty-two B. carinata genotypes were grown in a randomized complete block design with three replications at three locations for two years. The genotypes were evaluated for nine desirable traits related to seed oil quality (erucic acid and oil content), seed yield, and other agronomic traits. The results showed that the proportion of genotype by environment interaction (GEI) was clearly observed in erucic acid, which led to a stability and mean performance analysis for selecting the most stable and best-performing genotypes for the desired traits. For such an analysis, we used the multi-trait stability index (MTSI) along with the weighted average of absolute score BLUPs (WAASB). As revealed from the MTSI, five genotypes (G13, G18, G10, G22 and G5) were identified as the most stable in erucic acid, oil content, seed yield, and other agronomic traits. The selected genotypes showed on average 45.7% erucic acid, 3185 kg ha−1 seed yield and 45.1% oil content with 4.3%, 25.8% and 6.9% positive selection gain, respectively. The negative selection gain of phenological traits and the plant height of the selected genotypes revealed their early maturity and their lower probability of being affected by lodging. Our findings demonstrated MTSI can be used to select high erucic acid B. carinata with a set of desirable traits, which would facilitate breeding efforts in developing novel and high erucic acid B. carinata varieties. Our results also showed that MTSI is an effective tool for selecting genotypes across different environments due to its unique ability to select multiple traits simultaneously.

Positive selection analysis of Cyt proteins from Bacillus thuringiensis: A conservative trend driven by negative (purifying) selection

Bacillus thuringiensis is a Gram-positive entomopathogenic bacterium that produces different pesticidal proteins: vegetative insecticidal proteins (Vpb1/Vpa2, Vip3, and Vpb4) during vegetative growth, which are secreted to the culture medium, and δ–endotoxins (Cry and Cyt) during sporulation, which accumulate into parasporal crystals. Cyt proteins are the smaller subset of δ–endotoxins targeting Diptera species. While Cry and Vip3 proteins undergo positive selection, our analysis suggests that Cyt proteins evolve following a conservative trend driven negative (purifying) selection.

O-025 An artificial intelligence (AI) model non-invasively evaluates endometrial receptivity from ultrasound images, surpassing endometrial thickness (EMT) in predicting implantation

Abstract Study question Can an AI image-based model be trained to predict whether an endometrium, prior to progesterone, is receptive for successful embryo implantation from ultrasound images? Summary answer An endometrial receptivity AI model, utilizing ultrasound images and clinical features, is predictive of successful implantation and outperforms endometrial thickness as a predictor of implantation. What is known already Despite its importance in successful embryo implantation and subsequent live birth, endometrial receptivity is difficult to measure. The standard of care at some clinics is to cancel an embryo transfer if EMT is measuring less than 7 mm on ultrasound assessment – however, achieving an EMT threshold does not guarantee success, even with euploid blastocysts. Currently available receptivity tests (e.g. endometrial receptivity assays) are unreliable and have not shown significant improvements in reproductive outcomes, necessitating the development of new evaluation methods for endometrial receptivity. AI can potentially address this gap in clinical care and understanding, aiming to increase patient success. Study design, size, duration 79,602 ultrasound images (40,910 patients) of the endometrium, on the day of progesterone start according to patient’s frozen embryo transfer cycle, were retrospectively collected from 4 clinic networks including 70 clinic locations. PGT-A outcomes and blastocyst quality were available for 15,466 and 36,070 blastocysts respectively, with 14,538 having labels for both. Different image samples (based on embryo quality) were selected to train and test several AI models, with implantation (positive beta-hCG) as a binary outcome. Participants/materials, setting, methods Three criteria for negative (implantation) class sample selection were tested for receptivity model development: 1) high- or medium-quality and/or euploid blastocysts; 2) high-quality blastocysts; 3) all blastocysts. Models were ensembles consisting of an image-based deep learning (DL)-model and a feature-based machine learning (ML)-model. Model performance was measured by Area-under-the-curve (AUC), sensitivity, and specificity. Feature importance from the ML model was assessed, while receptivity model performance was compared to the power of EMT to predict implantation. Main results and the role of chance A receptivity model trained on scenario 1) (n = 27,424) achieved AUC 0.613, sensitivity 0.716, and specificity 0.439 on a test set of 9197 samples, in predicting implantation. Another receptivity model trained on scenario 2) (n = 25,625) achieved AUC 0.627, sensitivity 0.637, and specificity 0.543 on a test set of 8642. Whereas a third receptivity model trained on scenario 3) (n = 31,238) was selected for further analysis as it attained the best performance with AUC 0.631, sensitivity 0.628, and specificity 0.556 on a test set of 10,422. The ensemble model also utilizes relevant clinical features, which were ranked by importance to model predictions: EMT; progesterone blood test value; age at transfer; previous total embryo transfers; days between ultrasound date and transfer date; age at retrieval; and oocyte origin. EMT was assessed for its ability to predict implantation at thresholds between 5–20 mm. The threshold that best separates positive and negative implantation was determined by evaluating AUC on a validation set of 5682. A threshold of 8.8 mm achieved an AUC 0.576, sensitivity 0.694, and specificity 0.455 in predicting implantation on a test set of 5686. However, the receptivity model AUC (0.631) was significantly higher (p < 0.001; DeLong test for differences in AUC), outperforming EMT predictability. Limitations, reasons for caution The endometrial receptivity model was built and tested on retrospective frozen embryo transfer data. Results should be corroborated in prospective and non-selection studies, as well as in multiple geographical locations (all clinics included reside in the United States). The dataset requires greater diversification, with a greater representation of EMT (<7mm). Wider implications of the findings This study indicates that an AI model can be built to predict implantation from ultrasound images and clinical features, surpassing current standards - EMT alone. Further experimentation, with additional clinical features, may improve performance to facilitate development of a model that can accurately predict the gold-standard of live birth. Trial registration number Not applicable

The evolution of ultraconserved elements in vertebrates.

Ultraconserved elements (UCEs) were discovered two decades ago, arbitrarily defined as sequences that are identical over a length ≥200 bp in the human, mouse and rat genomes. The definition was subsequently extended to sequences ≥100 bp identical in at least three of five mammalian genomes (including dog and cow), and shown to have undergone rapid expansion from ancestors in fish and strong negative selection in birds and mammals. Since then, many more genomes have become available, allowing better definition and more thorough examination of UCE distribution and evolutionary history. We developed a fast and flexible analytical pipeline for identifying UCEs in multiple genomes, dedUCE, which allows manipulation of minimum length, sequence identity, and number of species with a detectable UCE according to specified parameters. We suggest an updated definition of UCEs as sequences ≥100 bp and ≥97% sequence identity in ≥50% of placental mammal orders (12813 UCEs). By mapping UCEs to ∼200 species we find that placental UCEs appeared early in vertebrate evolution, well before land colonisation, suggesting the evolutionary pressures driving UCE selection were present in aquatic environments in the Cambrian-Devonian periods. Most (>90%) UCEs likely appeared after the divergence of gnathostomes from jawless predecessors, were largely established in sequence identity by early Sarcopterygii evolution - before the divergence of lobe-finned fishes from tetrapods - and became near fixed in the amniotes. UCEs are mainly located in the introns of protein-coding and non-coding genes involved in neurological and skeletomuscular development, enriched in regulatory elements, and dynamically expressed throughout embryonic development.

Sequence diversity of apidaecin-like peptides arresting the terminating ribosome.

The Proline-rich Antimicrobial Peptide (PrAMP) apidaecin (Api) inhibits translation by binding in the ribosomal nascent peptide exit tunnel, trapping release factors RF1 or RF2, and arresting ribosomes at stop codons. To explore the extent of sequence variations of the native 18-amino acid Api that allows it to preserve its activity, we screened a library of synthetic mutant Api genes expressed in bacterial cells, resulting in nearly 350000 peptide variants with multiple substitutions. By applying orthogonal negative and positive selection strategies, we identified a number of multi-substituted Api variants capable of arresting ribosomes at stop codons. Our findings underscore the critical contribution of specific amino acid residues of the peptide for its on-target function while significantly expanding the variety of PrAMPs acting on the terminating ribosome. Additionally, some of the tested synthesized multi-substituted Api variants exhibit improved antibacterial activity compared to that of the wild type PrAMP and may constitute the starting point to develop clinically useful antimicrobials.

High-fidelity CRISPR/Cas12a dual-crRNA screening reveals novel synergistic interactions in hepatocellular carcinoma.

: CRISPR/Cas12a-based combinational screening has shown remarkable potential for identifying genetic interactions. Here, we describe an innovative method for combinational genetic screening with rapid construction of a dual-CRISPR RNA (crRNA) library using gene splicing through overlap extension PCR (SOE PCR) and the adoption of CeCas12a, which we previously identified with strict PAM recognition and low off-targeting to guarantee fidelity and efficiency. The custom-pooled SOE crRNA array (SOCA) library for double-knockout screening could be conveniently constructed in the laboratory for widespread use, and the CeCas12a-mediated high-fidelity screen displayed good performance even under a negative selection screen. By designing a SOCA dual-crRNA library that covered most of the kinase and metabolism-associated gene targets of FDA-approved drugs implicated in hepatocellular carcinoma (HCC) tumourigenesis, novel cross-talk between the two gene sets was negatively selected to inhibit HCC cell growth in vitro and in vivo and was validated using virtual double-knockdown screening based on TCGA databases. Thus, this rapid, efficient and high-fidelity double-knockout screening system is promising for systemically identifying potential genetic interactions between multiple gene sets or combinations of FDA- approved drugs for clinical translational medicine in the future.

Unlocking the secrets of Hofbauer cells in placental (patho-) physiology: Isolation and quality assessment in human term placenta

IntroductionHofbauer cells (HBCs) are macrophages of fetal origin that reside in the villous tissue. They are the only immune cells within healthy villi. While HBCs perform innate immune functions such as phagocytosis and antigen presentation, they are increasingly recognized for their diverse roles in placental physiology e.g. vascular functionality, tissue homeostasis, tolerance. Consequently, HBCs are of utmost interest in a variety of non-physiological placental conditions. IsolationVillous tissue is collected freshly after delivery and finely minced. The resulting tissue is digested in a two-step process, using Trypsin/DNase to separate cytotrophoblasts and collagenase/DNase to penetrate deeper into the villous stroma, containing HBCs, and obtain a single cell suspension. After a density gradient centrifugation, the corresponding cell layer is collected and subjected to negative immune selection of HBCs, yielding unaffected cells that have not been activated during the isolation process. Quality controlIn addition to a classical immunocytochemistry (ICC) approach including macrophage markers, and markers for potentially contaminating cell types (e.g. fibroblasts, muscle, mesenchymal cells), we have developed a multi-color flow cytometry (FC) panel. This panel assesses Hofbauer cell purity and polarization states more accurately and comprehensively than qualitative ICC, using percentage analysis of parent cells to estimate the expression levels of specific markers. DiscussionThe presented protocol allows us to isolate HBCs in significant numbers and high purity, even from placentae compromised by preeclampsia (PE) with limited placental volume. We have successfully developed and implemented this protocol to study healthy, diabetic and PE macrophages, aiding a better understanding of the underlying placental pathophysiology at the cellular level.

Genetic diversity and population structure of grapevine Roditis leaf discoloration‐associated virus in Turkey vineyards

AbstractGrapevine Roditis leaf discoloration‐associated virus (GRLDaV) is a type of virus that infects grapevines. This research aimed to determine the prevalence of GRLDaV in Turkey vineyards and investigate the genetic diversity and population structure of the selected viral isolates from Turkey compared to isolates from other countries. In this study, 800 shoot samples from Turkey vineyards were collected in late spring and autumn from different regions. The samples were analysed by RT‐PCR targeting the partial RNaseH‐like gene region of the virus genome. The overall prevalence of GRLDaV was 8.1% among the samples. Phylogenetic analysis of the GRLDaV genome showed that the GRLDaV isolates were clustered into two major lineages. The nucleotide diversity (π) value of Group I, including only Mediterranean isolates, was lower than Group II, suggesting little variation among isolates. Even though π values were low among the geographical regions in Turkey, the region with the highest nucleotide diversity was the Aegean population, followed by the Eastern and Mediterranean populations. Comparison between nonsynonymous and synonymous substitutions showed that negative selection acts on synonymous amino acids. Along with neutrality tests and gene flow analyses, it was emphasized that genetic drift played an important role in shaping the GRLDaV populations. This study provides important information on the prevalence and genetic diversity of GRLDaV in Turkey vineyards. The findings will help to develop better strategies to manage and control this virus, which can cause significant economic losses in grape industries.

Update: Induction of Inflammatory Bowel Disease in Immunodeficient Mice by Injection of Naïve CD4+ T cells (T Cell Transfer Model of Colitis).

The intestinal inflammation induced by injection of naïve CD4+ T cells into lymphocyte-deficient hosts (more commonly known as the T cell transfer model of colitis) shares many features of idiopathic inflammatory bowel disease (IBD) in humans, such as epithelial cell hyperplasia, crypt abscess formation, and dense lamina propria lymphocyte infiltration. As such, it provides a useful tool for studying mucosal immune regulation as it relates to the pathogenesis and treatment of IBD in humans. In the IBD model described here, colitis is induced in Rag (recombination-activating gene)-deficient mice by reconstitution of these mice with naïve CD4+CD45RBhi T cells through adoptive T cell transfer. Although different recipient hosts of cell transfer can be used, Rag-deficient mice are the best characterized and support studies that are both flexible and reproduceable. As described in the Basic Protocol, in most studies the transferred cells consist of naïve CD4+ T cells (CD45RBhi T cells) derived by fluorescence-activated cell sorting from total CD4+ T cells previously purified using immunomagnetic negative selection beads. In a Support Protocol, methods to characterize colonic disease progression are described, including the monitoring of weight loss and diarrhea and the histological assessment of colon pathology. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Induction of IBD in Rag-deficient mice by the transfer of naïve CD4+CD45RBhi T cells Support Protocol: Monitoring development of colitis.

Epigenetic diversity of genes with copy number variations among natural populations of the three-spined stickleback.

Duplicated genes provide the opportunity for evolutionary novelty and adaptive divergence. In many cases, having more gene copies increases gene expression, which might facilitate adaptation to stressful or novel environments. Conversely, overexpression or misexpression of duplicated genes can be detrimental and subject to negative selection. In this scenario, newly duplicate genes may evade purifying selection if they are epigenetically silenced, at least temporarily, leading them to persist in populations as copy number variations (CNVs). In animals and plants, younger gene duplicates tend to have higher levels of DNA methylation and lower levels of gene expression, suggesting epigenetic regulation could promote the retention of gene duplications via expression repression or silencing. Here, we test the hypothesis that DNA methylation variation coincides with young duplicate genes that are segregating as CNVs in six populations of the three-spined stickleback that span a salinity gradient from 4 to 30 PSU. Using reduced-representation bisulfite sequencing, we found DNA methylation and CNV differentiation outliers rarely overlapped. Whereas lineage-specific genes and young duplicates were found to be highly methylated, just two gene CNVs showed a significant association between promoter methylation level and copy number, suggesting that DNA methylation might not interact with CNVs in our dataset. If most new duplications are regulated for dosage by epigenetic mechanisms, our results do not support a strong contribution from DNA methylation soon after duplication. Instead, our results are consistent with a preference to duplicate genes that are already highly methylated.

Stand biomass of Pinus sylvestris var. mongolica plantations benefits from high density monocultures in the boreal zone

Pinus sylvestris var. mongolica (P. sylvestris) plantations are extensively established in the boreal zone. Increasing stand biomass of these plantations can effectively enhance carbon stock, which is crucial for mitigating climate change. However, the current understanding of optimizing plantation strategies to maximize stand biomass is primarily derived from experiments in tropical and subtropical zones, which is difficult to extend to the boreal due to substantial climatic differences. Based on a comprehensive dataset from 1,076 sample plots of P. sylvestris plantations in the boreal zone of China, we evaluated the effects of tree species richness and stand density on tree height, diameter at breast height (DBH), and stand biomass to investigate the optimal plantation strategy. Furthermore, we examined how these effects changed with stand age and investigated their relative importance. We found that monocultures at a high stand density of 2,000–2,500 ​ha−1 were the optimal plantation strategy to maximize stand biomass (107.5 ​Mg·ha−1), and this held true at almost all stand ages. Unfortunately, this strategy resulted in low species richness and small individual trees (10.6 ​m height and 9.8 ​cm DBH), thus presenting a trade-off. In addition, as stand age increased, the effect of tree species richness on stand biomass shifted from positive to negative, but the effect of stand density was always positive. Overall, stand age had the greatest effect on stand biomass, followed by stand density and then tree species richness. Our findings reveal a distinct plantation strategy for optimizing stand biomass of P. sylvestris plantations in the boreal zone. More importantly, this study highlights that (1) maximizing stand biomass in the boreal zone may compromise tree species richness; (2) net effects of tree species richness on stand biomass are not always positive, as negative selection effects offset positive complementary effects.

Plant Kinesin Repertoires Expand with New Domain Architecture and Contract with the Loss of Flagella.

Kinesins are eukaryotic microtubule motor proteins subdivided into conserved families with distinct functional roles. While many kinesin families are widespreadin eukaryotes, each organismal lineage maintains a unique kinesin repertoire composed of many families with distinct numbers of genes. Previous genomic surveys indicated that land plant kinesin repertoires differ markedly from other eukaryotes. To determine when repertoires diverged during plant evolution, we performed robust phylogenomic analyses of kinesins in 24 representative plants, two algae, two animals, and one yeast. These analyses show that kinesin repertoires expand and contract coincident with major shifts in the biology of algae and land plants. One kinesin family and five subfamilies, eachdefined by unique domain architectures, emerged in the green algae. Four of those kinesin groups expanded in ancestors of modern land plants, while six other kinesin groups were lost in the ancestors of pollen-bearing plants. Expansions of different kinesin families and subfamilies occurred in moss and angiosperm lineages. Other kinesin families remained stable and did not expand throughout plant evolution. Collectively these data support a radiation of kinesin domain architectures in algae followed by differential positive and negative selection on kinesins families and subfamilies in different lineages of land plants.

PRIMITI: A computational approach for accurate prediction of miRNA-target mRNA interaction

Current medical research has been demonstrating the roles of miRNAs in a variety of cellular mechanisms, lending credence to the association between miRNA dysregulation and multiple diseases. Understanding the mechanisms of miRNA is critical for developing effective diagnostic and therapeutic strategies. miRNA-mRNA interactions emerge as the most important mechanism to be understood despite their experimental validation constraints. Accordingly, several computational models have been developed to predict miRNA-mRNA interactions, albeit presenting limited predictive capabilities, poor characterisation of miRNA-mRNA interactions, and low usability. To address these drawbacks, we developed PRIMITI, a PRedictive model for the Identification of novel miRNA-Target mRNA Interactions. PRIMITI is a novel machine learning model that utilises CLIP-seq and expression data to characterise functional target sites in 3’-untranslated regions (3’-UTRs) and predict miRNA-target mRNA repression activity. The model was trained using a reliable negative sample selection approach and the robust extreme gradient boosting (XGBoost) model, which was coupled with newly introduced features, including sequence and genetic variation information. PRIMITI achieved an area under the receiver operating characteristic (ROC) curve (AUC) up to 0.96 for a prediction of functional miRNA-target site binding and 0.96 for a prediction of miRNA-target mRNA repression activity on cross-validation and an independent blind test. Additionally, the model outperformed state-of-the-art methods in recovering miRNA-target repressions in an unseen microarray dataset and in a collection of validated miRNA-mRNA interactions, highlighting its utility for preliminary screening. PRIMITI is available on a reliable, scalable, and user-friendly web server at https://biosig.lab.uq.edu.au/primiti.

The Polish version of the Process-Based Assessment Tool (PBAT)-The measure of processes of change in psychological interventions.

The aim of this study was to conduct a Polish adaptation of Process-Based Assessment Tool (PBAT), to be used primarily for measurement of the processes of change occurring within psychological interventions, regardless of the therapeutic approach. PBAT includes a set of statements related to negative and positive behaviors in the domains of selection, variation, and retention, as it is theoretically embedded in the evolutionary approach. The tool's construction was determined by resolving the issue of ergodic error, hence employs an idiographic approach. A total of 602 (319 F, 281 M) participants in the age 18-85 took part in the study. Apart from the original 21 PBAT items, two additional items related to self-care vs. self-impatience were tested. The included criterion variables related to the assessment of individual functioning in terms of distress (sadness, anxiety, stress, anger, lack of social support), health (health and vitality levels), the fulfillment or frustration of autonomy, connection, and competence need, as well as well-being (life-satisfaction and sense of professional burnout). The machine learning Boruta algorithm was utilized. PBAT items significantly predicted criterion variables. Positive selection behaviors were strongest predictors of Health, Vitality, Life-satisfaction as well as satisfaction of autonomy, connection and competence needs. Negative selection behaviors were strongest predictors of distress, lack of social support, work burnout as well as the frustration of autonomy, connection and competence needs. Overall, the PBAT items were more predictive of variables encompassing negative aspects of functioning than positive aspects or well-being. The overall relationships and conclusions are consistent with those obtained in the original study. The Polish version of PBAT is recommended for use in further scientific research and therapeutic processes.

Detection of dual-methylated BRCA1/BRCA2 cell-free DNA for ovarian cancer on an aptamer-based integrated microfluidic system

A new screening strategy has been developed to select nucleic acid aptamer probes with an “in vivo-like” systematic evolution of ligands by exponential enrichment (SELEX) process featuring positive, negative selection and in vivo-like selection steps. One methylation-specific aptamer with high affinity and specificity was selected and it could capture methylated cell-free DNA (cfDNA) from unfiltered blood of ovarian cancer (OvCa) patients. This aptamer was conjugated onto magnetic beads and integrated into a new microfluidic chip for rapid and automatic detection and quantification of two prevalent methylated tumor suppressor genes, breast cancer type 1 and 2 susceptibility protein (BRCA 1/2), in the molecular profile of OvCa. The assay was conducted under physiological conditions that mimic the microenvironment of cancer patients at 25–37 °C, with a low pH value (5.5) and/or high blood ion levels, without requiring additional sample preparation steps. The results of this study could be extrapolated to the direct detection of methylated cfDNA at levels as low as 1 pM in blood or plasma. Not only was DNA methylation observed in OvCa patients, but it was also detected in many other types of cancer; it is therefore considered an important factor in carcinogenesis. Hence, it is inferred that this screened aptamer should not only be used for OvCa diagnosis but also for multiple cancer epigenetic detection and drug development research in the future.

In Situ and Ex Situ Conservation of Ornamental Geophytes in Poland

The protection of biological diversity in nature and in agriculture, including the production of ornamental crops, has become increasingly important in Poland as well as worldwide. The Convention on Biological Diversity, signed in 1992 at the Earth Summit of the UN in Rio de Janeiro and ratified by the Polish government in 1995, imposed new regulations related to the protection of nature and the genetic resources of cultivated crops in Poland. The conservation of the genera, varieties and cultivars of ornamental geophytes—a group of plants of great interest from a botanical and physiological, but also a horticultural point of view—takes place in situ (both in nature and in the places of cultivation) and through the establishment of ex situ gene banks and collections. The natural genetic resources of ornamental geophytes include species from the genera Allium, Fritillaria, Gladiolus, Iris, Leucojum, Lilium and Muscari, among others, and more than a dozen species are protected by law due to varying degrees of threats. Botanical gardens play an essential role in the conservation of endangered species. Their activities focus on genus monitoring, managing ex situ gene banks (including National Collections), developing propagation methods and carrying out their reintroduction. In order to protect the national genetic resources of cultivated plants, the National Centre for Plant Genetic Resources at the Plant Breeding and Acclimatisation Institute—National Research Institute, under the auspices of the Ministry of Agriculture and Rural Development, was established. Concerning ornamental geophytes, the National Centre coordinates two field collections of cultivars of the genera Gladiolus, Lilium, Narcissus and Tulipa, which are of great economic importance and have a long tradition of breeding in Poland. The first one is located at the National Institute of Horticultural Research in Skierniewice (central Poland), and the second one is at the Experimental Substation of Variety Testing in Lisewo (northern Poland). The history of tulip collections in Poland dates back to the 1960s. At that time, the first breeding work for this species began. The collection of bulbous crops in Skierniewice is currently one of the largest in Poland, with a total of 934 accessions. Most of them are tulips (522) and lilies (222). Other plants in the collection in Skierniewice are gladiolus and narcissus. The most valuable accessions are grown under special protection (tunnels with dense nets) to guard against insects and maintain a mild climate inside. The genetic resources of the ornamental bulb plant collection in Lisewo currently consist of 611 accessions, mainly tulips (358), daffodils (121) and gladioli (132). All bulbous crops in both collections (Skierniewice and Lisewo) are grown in accordance with all principles of agrotechnics (negative field selection, fertilisation, soil maintenance). A particularly important task of botanical gardens, universities, research institutes and the National Centre is leading research on the methods of storage for survival organs, in vitro cultures and cryopreservation. We have discovered that the various activities for the species conservation of ornamental geophytes require a great deal of constantly deepening knowledge and extraordinary measures, including frequent monitoring of the effects of the applied measures.

Frequency-dependent selection of neoantigens fosters tumor immune escape and predicts immunotherapy response

Cancer is an evolutionary process shaped by selective pressure from the microenvironments. However, recent studies reveal that certain tumors undergo neutral evolution where there is no detectable fitness difference amongst the cells following malignant transformation. Here, through computational modeling, we demonstrate that negative frequency-dependent selection (or NFDS), where the immune response against cancer cells depends on the clonality of neoantigens, can lead to an immunogenic landscape that is highly similar to neutral evolution. Crucially, NFDS promotes high antigenic heterogeneity and early immune evasion in hypermutable tumors, leading to poor responses to immune checkpoint blockade (ICB) therapy. Our model also reveals that NFDS is characterized by a negative association between average clonality and total burden of neoantigens. Indeed, this unique feature of NFDS is common in the whole-exome sequencing (WES) datasets (357 tumor samples from 275 patients) from four melanoma cohorts with ICB therapy and a non-small cell lung cancer (NSCLC) WES dataset (327 tumor samples from 100 patients). Altogether, our study provides quantitative evidence supporting the theory of NFDS in cancer, explaining the high prevalence of neutral-looking tumors. These findings also highlight the critical role of frequency-dependent selection in devising more efficient and predictive immunotherapies.

Bidirectional Feature Fusion and Enhanced Alignment based Multimodal Semantic Segmentation for Remote Sensing Images

Image–text multimodal deep semantic segmentation leverages the fusion and alignment of image and text information and provides more prior knowledge for segmentation tasks. It is worth exploring image–text multimodal semantic segmentation for remote sensing images. In this paper, we propose a bidirectional feature fusion and enhanced alignment-based multimodal semantic segmentation model (BEMSeg) for remote sensing images. Specifically, BEMSeg first extracts image and text features by image and text encoders, respectively, and then the features are provided for fusion and alignment to obtain complementary multimodal feature representation. Secondly, a bidirectional feature fusion module is proposed, which employs self-attention and cross-attention to adaptively fuse image and text features of different modalities, thus reducing the differences between multimodal features. For multimodal feature alignment, the similarity between the image pixel features and text features is computed to obtain a pixel–text score map. Thirdly, we propose a category-based pixel-level contrastive learning on the score map to reduce the differences among the same category’s pixels and increase the differences among the different categories’ pixels, thereby enhancing the alignment effect. Additionally, a positive and negative sample selection strategy based on different images is explored during contrastive learning. Averaging pixel values across different training images for each category to set positive and negative samples compares global pixel information while also limiting sample quantity and reducing computational costs. Finally, the fused image features and aligned pixel–text score map are concatenated and fed into the decoder to predict the segmentation results. Experimental results on the ISPRS Potsdam, Vaihingen, and LoveDA datasets demonstrate that BEMSeg is superior to comparison methods on the Potsdam and Vaihingen datasets, with improvements in mIoU ranging from 0.57% to 5.59% and 0.48% to 6.15%, and compared with Transformer-based methods, BEMSeg also performs competitively on LoveDA dataset with improvements in mIoU ranging from 0.37% to 7.14%.

Epidemiological Characterization and Genetic Variation of the SARS-CoV-2 Delta Variant in Palestine.

The emergence of new SARS-CoV-2 variants in Palestine highlights the need for continuous genetic surveillance and accurate screening strategies. This case series study aimed to investigate the geographic distribution and genetic variation of the SARS-CoV-2 Delta Variant in Palestine in August 2021. Samples were collected at random in August 2021 (n = 571) from eight districts in the West Bank, Palestine. All samples were confirmed as positive for COVID-19 by RT-PCR. The samples passed the quality control test and were successfully sequenced using the ARTIC protocol. The Delta Variant was revealed to have four dominant lineages: B.1.617 (19%), AY.122 (18%), AY.106 (17%), and AY.121 (13%). The study revealed eight significant purely spatial clusters (p < 0.005) distributed in the northern and southern parts of Palestine. Phylogenetic analysis of SARS-CoV-2 genomes (n = 552) showed no geographically specific clades. The haplotype network revealed three haplogroups without any geographic distribution. Chronologically, the Delta Variant peak in Palestine was shortly preceded by the one in the neighboring Israeli community and shortly followed by the peak in Jordan. In addition, the study revealed an extremely intense transmission network of the Delta Variant circulating between the Palestinian districts as hubs (SHR ≈ 0.5), with Al-Khalil, the district with the highest prevalence of COVID-19, witnessing the highest frequency of transitions. Genetic diversity analysis indicated closely related haplogroups, as haplotype diversity (Hd) is high but has low nucleotide diversity (π). However, nucleotide diversity (π) in Palestine is still higher than the global figures. Neutrality tests were significantly (p < 0.05) low, including Tajima's D, Fu-Li's F, and Fu-Li's D, suggesting one or more of the following: population expansion, selective sweep, and natural negative selection. Wright's F-statistic (Fst) showed genetic differentiation (Fst > 0.25) with low to medium gene flow (Nm). Recombination events were minimal between clusters (Rm) and between adjacent sites (Rs). The study confirms the utility of the whole genome sequence as a surveillance system to track the emergence of new SARS-CoV-2 variants for any possible geographical association and the use of genetic variation analysis and haplotype networking to delineate any minimal change or slight deviation in the viral genome from a reference strain.

Global evolutionary dynamics of virulence genes in ST11-KL47 carbapenem-resistant Klebsiella pneumoniae

ST11-KL47 is a hypervirulent carbapenem-resistant Klebsiella pneumoniae (CRKP) that is highly prevalent in China and poses a major public health risk. To investigate the evolutionary dynamics of virulence genes in this subclone, we analysed 78 sequenced isolates obtained from a long-term study across 29 centres from 17 cities in China. Virulence genes were located in large hybrid pNDM-Mar-like plasmids (length: ∼266 kilobases) rather than in classical pK2044-like plasmids. These hybrid plasmids, derived from the fusion of pK2044 and pNDM-Mar plasmids mediated by insertion sequence (IS) elements (such as ISKpn28 and IS26), integrated virulence gene fragments into the chromosome. Analysis of 217 sequences containing the special IncFIB (pNDM-Mar) replicon using public databases indicated that these plasmids typically contained T4SS-related and multiple antimicrobial resistance genes, were present in 24 countries, and were found in humans, animals, and the environment. Notably, the chromosomal integration of virulence genes was observed in strains across five countries across two continents. In vivo and in vitro models showed that the large hybrid plasmid increased the host fitness cost while increasing virulence. Conversely, virulence genes transferred to chromosomes resulted in increased fitness and lower virulence. In conclusion, virulence genes in the plasmids of ST11-KL47 CRKP are evolving, driven by adaptive negative selection, to enable vertical chromosomal inheritance along with conferring a survival advantage and low pathogenicity.