T-cell infiltration and its regulatory mechanisms in cancers: insights at single-cell resolution.

Tumor-infiltrating T cells recognize, attack, and clear tumor cells, playing a central role in antitumor immune response. However, certain immune cells can impair this response and help tumor immune escape. Therefore, exploring the factors that influence T-cell infiltration is crucial to understand tumor immunity and improve therapeutic effect of cancer immunotherapy. The use of single-cell RNA sequencing (scRNA-seq) allows the high-resolution analysis of the precise composition of immune cells with different phenotypes and other microenvironmental factors, including non-immune stromal cells and the related molecules in the tumor microenvironment of various cancer types. In this review, we summarized the research progress on T-cell infiltration and the crosstalk of other stromal cells and cytokines during T-cell infiltration using scRNA-seq to provide insights into the mechanisms regulating T-cell infiltration and contribute new perspectives on tumor immunotherapy.

Prediction of Tumor Microenvironment Characteristics and Treatment Response in Lung Squamous Cell Carcinoma by Pseudogene OR7E47P-related Immune Genes.

OBJECTIVE: Pseudogenes are initially regarded as nonfunctional genomic sequences, but some pseudogenes regulate tumor initiation and progression by interacting with other genes to modulate their transcriptional activities. Olfactory receptor family 7 subfamily E member 47 pseudogene (OR7E47P) is expressed broadly in lung tissues and has been identified as a positive regulator in the tumor microenvironment (TME) of lung adenocarcinoma (LUAD). This study aimed to elucidate the correlation between OR7E47P and tumor immunity in lung squamous cell carcinoma (LUSC). METHODS: Clinical and molecular information from The Cancer Genome Atlas (TCGA) LUSC cohort was used to identify OR7E47P-related immune genes (ORIGs) by weighted gene correlation network analysis (WGCNA). Based on the ORIGs, 2 OR7E47P clusters were identified using non-negative matrix factorization (NMF) clustering, and the stability of the clustering was tested by an extreme gradient boosting classifier (XGBoost). LASSO-Cox and stepwise regressions were applied to further select prognostic ORIGs and to construct a predictive model (ORPScore) for immunotherapy. The Botling cohorts and 8 immunotherapy cohorts (the Samstein, Braun, Jung, Gide, IMvigor210, Lauss, Van Allen, and Cho cohorts) were included as independent validation cohorts. RESULTS: OR7E47P expression was positively correlated with immune cell infiltration and enrichment of immune-related pathways in LUSC. A total of 57 ORIGs were identified to classify the patients into 2 OR7E47P clusters (Cluster 1 and Cluster 2) with distinct immune, mutation, and stromal programs. Compared to Cluster 1, Cluster 2 had more infiltration by immune and stromal cells, lower mutation rates of driver genes, and higher expression of immune-related proteins. The clustering performed well in the internal and 5 external validation cohorts. Based on the 7 ORIGs (HOPX, STX2, WFS, DUSP22, SLFN13, GGCT, and CCSER2), the ORPScore was constructed to predict the prognosis and the treatment response. In addition, the ORPScore was a better prognostic factor and correlated positively with the immunotherapeutic response in cancer patients. The area under the curve values ranged from 0.584 to 0.805 in the 6 independent immunotherapy cohorts. CONCLUSION: Our study suggests a significant correlation between OR7E47P and TME modulation in LUSC. ORIGs can be applied to molecularly stratify patients, and the ORPScore may serve as a biomarker for clinical decision-making regarding individualized prognostication and immunotherapy.

Deciphering tumor-infiltrating dendritic cells in the single-cell era.

Dendritic cells (DCs) serve as a pivotal link connecting innate and adaptive immunity by processing tumor-derived antigens and activating T cells. The advent of single-cell sequencing has revolutionized the categorization of DCs, enabling a high-resolution characterization of the previously unrecognized diversity of DC populations infiltrating the intricate tumor microenvironment (TME). The application of single-cell sequencing technologies has effectively elucidated the heterogeneity of DCs present in the tumor milieu, yielding invaluable insights into their subpopulation structures and functional diversity. This review provides a comprehensive summary of the current state of knowledge regarding DC subtypes in the TME, drawing from single-cell studies conducted across various human tumors. We focused on the categorization, functions, and interactions of distinct DC subsets, emphasizing their crucial roles in orchestrating tumor-related immune responses. Additionally, we delve into the potential implications of these findings for the identification of predictive biomarkers and therapeutic targets. Enhanced insight into the intricate interplay between DCs and the TME promises to advance our comprehension of tumor immunity and, in turn, pave the way for the development of more efficacious cancer immunotherapies.

Advancement and Applications of Nanotherapy for Cancer Immune Microenvironment.

Cancer treatment has evolved rapidly due to major advances in tumor immunity research. However, due to the complexity, heterogeneity, and immunosuppressive microenvironment of tumors, the overall efficacy of immunotherapy is only 20%. In recent years, nanoparticles have attracted more attention in the field of cancer immunotherapy because of their remarkable advantages in biocompatibility, precise targeting, and controlled drug delivery. However, the clinical application of nanomedicine also faces many problems concerning biological safety, and the synergistic mechanism of nano-drugs with immunity remains to be elucidated. Our study summarizes the functional characteristics and regulatory mechanisms of nanoparticles in the cancer immune microenvironment and how nanoparticles activate and long-term stimulate innate immunity and adaptive immunity. Finally, the current problems and future development trends regarding the application of nanoparticles are fully discussed and prospected to promote the transformation and application of nanomedicine used in cancer treatment.

Two-step model of paleohexaploidy, ancestral genome reshuffling and plasticity of heat shock response in Asteraceae.

An ancient hexaploidization event in the most but not all Asteraceae plants, may have been responsible for shaping the genomes of many horticultural, ornamental, and medicinal plants that promoting the prosperity of the largest angiosperm family on the earth. However, the duplication process of this hexaploidy, as well as the genomic and phenotypic diversity of extant Asteraceae plants caused by paleogenome reorganization, are still poorly understood. We analyzed 11 genomes from 10 genera in Asteraceae, and redated the Asteraceae common hexaploidization (ACH) event ~70.7-78.6 million years ago (Mya) and the Asteroideae specific tetraploidization (AST) event ~41.6-46.2 Mya. Moreover, we identified the genomic homologies generated from the ACH, AST and speciation events, and constructed a multiple genome alignment framework for Asteraceae. Subsequently, we revealed biased fractionations between the paleopolyploidization produced subgenomes, suggesting the ACH and AST both are allopolyplodization events. Interestingly, the paleochromosome reshuffling traces provided clear evidence for the two-step duplications of ACH event in Asteraceae. Furthermore, we reconstructed ancestral Asteraceae karyotype (AAK) that has 9 paleochromosomes, and revealed a highly flexible reshuffling of Asteraceae paleogenome. Of specific significance, we explored the genetic diversity of Heat Shock Transcription Factors (Hsfs) associated with recursive whole-genome polyploidizations, gene duplications, and paleogenome reshuffling, and revealed that the expansion of Hsfs gene families enable heat shock plasticity during the genome evolution of Asteraceae. Our study provides insights on polyploidy and paleogenome remodeling for the successful establishment of Asteraceae, and is helpful for further communication and exploration of the diversification of plant families and phenotypes.

Single-cell transcriptomics dissects epithelial heterogeneity in HPV+ cervical adenocarcinoma.

The intra- and intertumoral heterogeneity of epithelial cells in human papillomavirus (HPV+ ) cervical adenocarcinoma (CEAD) remains largely unknown. To investigate this issue, we performed single-cell RNA sequencing on 19 229 epithelial cells sorted from three tumor samples of three patients with HPV+ CEAD. Six epithelial subclusters (Epi1-Epi6) were identified that showed distinct gene expression. Among these, Epi1 and Epi4 had apparent tumor hallmarks and metabolic activities. Epi1 was highly enriched in hallmarks of hypoxia, IL2/STAT5 signaling, retinol metabolism, glycolysis, and arachidonic acid metabolism, while Epi4 was highly enriched in hallmarks of G2M checkpoint, E2F targets, DNA repair, PI3K/AKT/MTOR signaling, glycolysis, fatty acid degradation, TCA cycle, and glutathione metabolism. We also investigated intertumoral epithelial heterogeneity and found that Patient 1 was highly enriched for KRAS signaling and angiogenesis, while Patient 2 was highly enriched for epithelial-mesenchymal transition and TGF-ß signaling, and Patient 3 was highly enriched for hypoxia, DNA repair, G2M checkpoint, and E2F targets. Using single-cell RNA sequencing, we revealed the intra- and intertumoral heterogeneity of epithelial cells in HPV+ CEAD, providing insights into the importance of personalized treatment for patients with HPV+ CEAD.

Single-cell RNA-sequencing reveals radiochemotherapy-induced innate immune activation and MHC-II upregulation in cervical cancer.

Radiochemotherapy (RCT) is a powerful treatment for cervical cancer, which affects not only malignant cells but also the immune and stromal compartments of the tumor. Understanding the remodeling of the local ecosystem induced by RCT would provide valuable insights into improving treatment strategies for cervical cancer. In this study, we applied single-cell RNA-sequencing to paired pre- and post-RCT tumor biopsies from patients with cervical cancer and adjacent normal cervical tissues. We found that the residual population of epithelial cells post-RCT showed upregulated expression of MHC class II genes. Moreover, RCT led to the accumulation of monocytic myeloid-derived suppressor cells with increased pro-inflammatory features and CD16+ NK cells with a higher cytotoxic gene expression signature. However, subclusters of T cells showed no significant increase in the expression of cytotoxic features post-RCT. These results reveal the complex responses of the tumor ecosystem to RCT, providing evidence of activation of innate immunity and MHC-II upregulation in cervical cancer.

Immune landscape of viral cancers: Insights from single-cell sequencing.

Viral infections trigger a wide range of immune responses thought to drive tumorigenesis and malignant progression. Dissecting virus-induced changes in the tumor immune microenvironment (TIME) is therefore crucial to identify key leukocyte populations that may represent novel targets for cancer therapy. Single-cell sequencing approaches have now been widely applied to the analysis of various tumors, thus enabling multiomics characterization of the highly heterogeneous TIME that bulk-sequencing cannot fully elucidate. In this review, we summarized key recent findings from sequencing studies of the immune infiltrate and antitumor response in virus-associated cancers at single cell resolution. Additionally, we also reviewed recent developments in immunotherapy for virus-associated cancers. We anticipate that the strategic use of single-cell sequencing will advance our understanding of the TIME of viral cancers, leading to the development of more potent novel treatments.

Single Nickel Atom Catalysts Enable Fast Polysulfide Redox for Safe and Long-Cycle Lithium-Sulfur Batteries.

Lithium-sulfur (Li-S) batteries have attracted great interest due to their low cost, high theoretical energy density, and environmental friendliness. However, the sluggish conversion of lithium polysulfides (LiPS) to S and Li2 S during the charge/discharge process leads to unsatisfactory rate performance of lower to 0.1 C (1 C = 1675 mA g-1 ) especially for Li-S pouch batteries, thus hindering their practical applications in high power batteries. Here, well-defined and monodispersed Ni single-atom catalysts (SACs) embedded in highly porous nitrogen-doped graphitic carbons (NiSA-N-PGC) are designed and synthesized to form Ni-N4 catalytic sites at the atomic level. When serving as a bifunctional electrocatalyst, the Ni-N4 catalytic sites cannot only promote the interfacial conversion redox of LiPS by accelerating the transformation kinetics, but also suppress the undesirable shuttle effect by immobilizing LiPS. These findings are verified by both experimental results and DFT theoretical calculations. Furthermore, Li ions show low diffusion barrier on the surface of Ni-N4 sites, resulting in enhanced areal capacity of batteries. As a result, the Li-S battery delivers stable cycling life of more than 600 cycles with 0.069% capacity decay per cycle at a rate of 0.5 C. More importantly, the Li-S pouch cells with NiSA-N-PGC show an initial capacity of 1299 mAh g-1 at a rate of 0.2 C even with high sulfur loading of 6 mg cm-2 . This work opens up an avenue for developing single-atom catalysts to accelerate the kinetic conversion of LiPS for highly stable Li-S batteries.

Single-cell RNA-sequencing dissects cellular heterogeneity and identifies two tumor-suppressing immune cell subclusters in HPV-related cervical adenosquamous carcinoma.

The intratumor heterogeneity of human papillomavirus (HPV)-related cervical cancer remains poorly defined. We performed single-cell RNA sequencing on 18 046 individual cells derived from two HPV-related cervical adenosquamous carcinoma samples to analyze the transcriptional heterogeneity of both epithelial and immune constituents, identifying seven epithelial (Epi1-7) and 11 immune subclusters. Based on expression of known cervical cancer markers, Epi1-2 primarily displayed features of adenocarcinoma, whereas Epi3-6 were instead characterized by features of squamous carcinoma. Our analyses also revealed that hypoxia and Kirsten rat sarcoma viral oncogene signaling were highly represented within Epi1; metabolic pathways mediating glycolysis and oxidative phosphorylation were enriched in Epi2-4; while Epi5 was enriched in p53 pathway components and features of epithelial-mesenchymal transition. Moreover, CD8+ FGFBP2+ T cells and FGFBP2+ natural killer cells were found to display high levels of cytotoxic effectors (GZMA, GZMB, GNLY, and PRF1) and low levels of inhibitory markers (PDCD1, TIGIT, and CTLA4), such that tumor infiltration by these populations was positively associated with survival in a cohort of n = 165 patients with HPV-related cervical cancer from The Cancer Genome Atlas database (p = 0.017 and 0.014, respectively). These results shed new light on the intratumor heterogeneity of HPV-related cervical adenosquamous carcinoma, which will help to refine diagnostic and treatment approaches.

GGDB: A Grameneae genome alignment database of homologous genes hierarchically related to evolutionary events.

The genomes of Gramineae plants have been preferentially sequenced owing to their economic value. These genomes are often quite complex, for example harboring many duplicated genes, and are the main source of genetic innovation and often the result of recurrent polyploidization. Deciphering these complex genome structures and linking duplicated genes to specific polyploidization events are important for understanding the biology and evolution of plants. However, efforts have been hampered by the complexity of analyzing these genomes. Here, we analyzed 29 well-assembled and up-to-date Gramineae genome sequences by hierarchically relating duplicated genes in collinear regions to specific polyploidization or speciation events. We separated duplicated genes produced by each event, established lists of paralogous and orthologous genes, and ultimately constructed an online database, GGDB (http://www.grassgenome.com/). Homologous gene lists from each plant and between plants can be displayed, searched, and downloaded from the database. Interactive comparison tools are deployed to demonstrate homology among user-selected plants and to draw genome-scale or local alignment figures and gene-based phylogenetic trees corrected by exploiting gene collinearity. Using these tools and figures, users can easily detect structural changes in genomes and explore the effects of paleo-polyploidy on crop genome structure and function. The GGDB will provide a useful platform for improving our understanding of genome changes and functional innovation in Gramineae plants.

Cancer mutation profiles predict ICIs efficacy in patients with non-small cell lung cancer.

Although immune checkpoint inhibitors (ICIs) have produced remarkable responses in non-small cell lung cancer (NSCLC) patients, receivers still have a relatively low response rate. Initial response assessment by conventional imaging and evaluation criteria is often unable to identify whether patients can achieve durable clinical benefit from ICIs. Overall, there are sparse effective biomarkers identified to screen NSCLC patients responding to this therapy. A lot of studies have reported that patients with specific gene mutations may benefit from or resist to immunotherapy. However, the single gene mutation may be not effective enough to predict the benefit from immunotherapy for patients. With the advancement in sequencing technology, further studies indicate that many mutations often co-occur and suggest a drastic transformation of tumour microenvironment phenotype. Moreover, co-mutation events have been reported to synergise to activate or suppress signalling pathways of anti-tumour immune response, which also indicates a potential target for combining intervention. Thus, the different mutation profile (especially co-mutation) of patients may be an important concern for predicting or promoting the efficacy of ICIs. However, there is a lack of comprehensive knowledge of this field until now. Therefore, in this study, we reviewed and elaborated the value of cancer mutation profile in predicting the efficacy of immunotherapy and analysed the underlying mechanisms, to provide an alternative way for screening dominant groups, and thereby, optimising individualised therapy for NSCLC patients.

Guanylate-Binding Protein 1 as a Potential Predictor of Immunotherapy: A Pan-Cancer Analysis.

Background: Mainstream application of cancer immunotherapy is hampered by the low response rate of most cancer patients. A novel immunotherapeutic target or a biomarker predicting response to immunotherapy needs to be developed. Guanylate-binding protein 1 (GBP1) is an interferon (IFN)-inducible guanosine triphosphatases (GTPases) involving inflammation and infection. However, the immunological effects of GBP1 in pan-cancer patients are still obscure. Methods: Using large-scale public data, we delineated the landscape of GBP1 across 33 cancer types. The correlation between GBP1 expression or mutation and immune cell infiltration was estimated by ESTIMATE, TIMER, xCell, and quanTIseq algorithms. GBP1-related genes and proteins were subjected to function enrichment analysis. Clustering analysis explored the relationship between GBP1 expression and anti-tumor immune phenotypes. We assessed the patient's response to immunotherapy using the tumor immune dysfunction and exclusion (TIDE) score and immunophenoscore (IPS). Furthermore, we validated the predictive power of GBP1 expression in four independent immunotherapy cohorts. Results: GBP1 was differentially expressed in tumors and normal tissues in multiple cancer types. Distinct correlations existed between GBP1 expression and prognosis in cancer patients. GBP1 expression and mutation were positively associated with immune cell infiltration. Function enrichment analysis showed that GBP1-related genes were enriched in immune-related pathways. Positive correlations were also observed between GBP1 expression and the expression of immune checkpoints, as well as tumor mutation burden (TMB). Pan-cancer patients with higher GBP1 expression were more inclined to display "hot" anti-tumor immune phenotypes and had lower TIDE scores and higher immunophenoscore, suggesting that these patients had better responses to immunotherapy. Patients with higher GBP1 expression exhibited improved overall survival and clinical benefits in immunotherapy cohorts, including the Gide et al. cohort [area under the curve (AUC): 0.813], the IMvigor210 cohort (AUC: 0.607), the Lauss et al. cohort (AUC: 0.740), and the Kim et al. cohort (AUC: 0.793). Conclusion: This study provides comprehensive insights into the role of GBP1 in a pan-cancer manner. We identify GBP1 expression as a predictive biomarker for immunotherapy, potentially enabling more precise and personalized immunotherapeutic strategies in the future.

BACH1: A Potential Predictor of Survival in Early-Stage Lung Adenocarcinoma.

PURPOSE: Recent researches showed the vital role of BACH1 in promoting the metastasis of lung cancer. We aimed to explore the value of BACH1 in predicting the overall survival (OS) of early-stage (stages I-II) lung adenocarcinoma. Patients and Methods. Lung adenocarcinoma cases were screened from the Cancer Genome Atlas (TCGA) database. Functional enrichment analysis was performed to obtain the biological mechanisms of BACH1. Gene set enrichment analysis (GSEA) was performed to identify the difference of biological pathways between high- and low-BACH1 groups. Univariate and multivariate COX regression analysis had been used to screen prognostic factors, which were used to establish the BACH1 expression-based prognostic model in the TCGA dataset. The C-index and time-dependent AUC curve were used to evaluate predictive power of the model. External validation of prognostic value was performed in two independent datasets from Gene Expression Omnibus (GEO). Decision analysis curve was finally used to evaluate clinical usefulness of the BACH1-based model beyond pathologic stage alone. RESULTS: BACH1 was an independent prognostic factor for lung adenocarcinoma. High-expression BACH1 cases had worse OS. BACH1-based prognostic model showed an ideal C-index and t-AUC and validated by two GEO datasets, independently. More importantly, the BACH1-based model indicated positive clinical applicability by DCA curves. CONCLUSION: Our research confirmed that BACH1 was an important predictor of prognosis in early-stage lung adenocarcinoma. The higher the expression of BACH1, the worse OS of the patients.

Illegitimate Recombination between Duplicated Genes Generated from Recursive Polyploidizations Accelerated the Divergence of the Genus Arachis.

The peanut (Arachis hypogaea L.) is the leading oil and food crop among the legume family. Extensive duplicate gene pairs generated from recursive polyploidizations with high sequence similarity could result from gene conversion, caused by illegitimate DNA recombination. Here, through synteny-based comparisons of two diploid and three tetraploid peanut genomes, we identified the duplicated genes generated from legume common tetraploidy (LCT) and peanut recent allo-tetraploidy (PRT) within genomes. In each peanut genome (or subgenomes), we inferred that 6.8-13.1% of LCT-related and 11.3-16.5% of PRT-related duplicates were affected by gene conversion, in which the LCT-related duplicates were the most affected by partial gene conversion, whereas the PRT-related duplicates were the most affected by whole gene conversion. Notably, we observed the conversion between duplicates as the long-lasting contribution of polyploidizations accelerated the divergence of different Arachis genomes. Moreover, we found that the converted duplicates are unevenly distributed across the chromosomes and are more often near the ends of the chromosomes in each genome. We also confirmed that well-preserved homoeologous chromosome regions may facilitate duplicates' conversion. In addition, we found that these biological functions contain a higher number of preferentially converted genes, such as catalytic activity-related genes. We identified specific domains that are involved in converted genes, implying that conversions are associated with important traits of peanut growth and development.

Postoperative Radiotherapy for Patients With Resectable Stage III-N2 Non-Small Cell Lung Cancer: A Systematic Review and Meta-Analysis.

PURPOSE: For resectable cases of stage III-N2 non-small cell lung cancer (NSCLC), the best treatment after surgery is still uncertain. The effect of postoperative radiotherapy (PORT) is controversial. Thus, we performed this updated meta-analysis to reassess the data of PORT in stage III-N2 NSCLC patients, to figure out whether these patients can benefit from PORT. METHODS: We conducted searches of the published literature in EMBASE, PubMed, and the Cochrane Library for relevant randomized control trials (RCTs) comparing PORT group with the non-PORT group in NSCLC patients at stage III-N2. These studies allowed the prior chemotherapy in the treatment. We extracted the data from these articles and used the hazard ratios (HRs) and their 95% confidence intervals (CIs) as summary statistics for estimating the effect of PORT on overall survival (OS), disease-free survival (DFS), local-regional recurrence-free survival (LRFS). RESULT: The analyses of seven randomized controlled trials (1,318 participants) show no benefit of PORT on survival (HR, 0.87; 95% CI, 0.71 to 1.07; p = 0.18) but a significantly different effect of PORT on DFS (HR, 0.83; 95% CI, 0.71 to 0.97; p = 0.02) and LRFS (HR, 0.64; 95% CI, 0.50 to 0.81; p = 0.0003). There is not enough evidence of a difference in the effect on survival by the utility of chemotherapy along with PORT though subgroup analysis of no chemotherapy group, concurrent chemoradiotherapy and sequential chemoradiotherapy group. Even in trials with 3D-CRT radiation technique, the pooled analysis shows no benefit of PORT on survival in patients with stage III-N2 NSCLC (data is not shown). CONCLUSION: Our findings illustrate that in the postoperative treatment for patients with stage III-N2 NSCLC, PORT contributes to a significantly increased DFS and LR and may not associate with an improved OS, indicating a cautious selection.

Oncolytic Adenovirus: Prospects for Cancer Immunotherapy.

Immunotherapy has moved to the forefront of modern oncologic treatment in the past few decades. Various forms of immunotherapy currently are emerging, including oncolytic viruses. In this therapy, viruses are engineered to selectively propagate in tumor cells and reduce toxicity for non-neoplastic tissues. Adenovirus is one of the most frequently employed oncolytic viruses because of its capacity in tumor cell lysis and immune response stimulation. Upregulation of immunostimulatory signals induced by oncolytic adenoviruses (OAds) might significantly remove local immune suppression and amplify antitumor immune responses. Existing genetic engineering technology allows us to design OAds with increasingly better tumor tropism, selectivity, and antitumor efficacy. Several promising strategies to modify the genome of OAds have been applied: capsid modifications, small deletions in the pivotal viral genes, insertion of tumor-specific promoters, and addition of immunostimulatory transgenes. OAds armed with tumor-associated antigen (TAA) transgenes as cancer vaccines provide additional therapeutic strategies to trigger tumor-specific immunity. Furthermore, the combination of OAds and immune checkpoint inhibitors (ICIs) increases clinical benefit as evidence shown in completed and ongoing clinical trials, especially in the combination of OAds with antiprogrammed death 1/programed death ligand 1 (PD-1/PD-L1) therapy. Despite remarkable antitumor potency, oncolytic adenovirus immunotherapy is confronted with tough challenges such as antiviral immune response and obstruction of tumor microenvironment (TME). In this review, we focus on genomic modification strategies of oncolytic adenoviruses and applications of OAds in cancer immunotherapy.

Paleo-polyploidization in Lycophytes.

Lycophytes and seed plants constitute the typical vascular plants. Lycophytes have been thought to have no paleo-polyploidization although the event is known to be critical for the fast expansion of seed plants. Here, genomic analyses including the homologous gene dot plot analysis detected multiple paleo-polyploidization events, with one occurring approximately 13-15 million years ago (MYA) and another about 125-142 MYA, during the evolution of the genome of Selaginella moellendorffii, a model lycophyte. In addition, comparative analysis of reconstructed ancestral genomes of lycophytes and angiosperms suggested that lycophytes were affected by more paleo-polyploidization events than seed plants. Results from the present genomic analyses indicate that paleo-polyploidization has contributed to the successful establishment of both lineages-lycophytes and seed plants-of vascular plants.

Polyploidy Index and Its Implications for the Evolution of Polyploids.

Polyploidy has contributed to the divergence and domestication of plants; however, estimation of the relative roles that different types of polyploidy have played during evolution has been difficult. Unbalanced and balanced gene removal was previously related to allopolyploidies and autopolyploidies, respectively. Here, to infer the types of polyploidies and evaluate their evolutionary effects, we devised a statistic, the Polyploidy-index or P-index, to characterize the degree of divergence between subgenomes of a polyploidy, to find whether there has been a balanced or unbalanced gene removal from the homoeologous regions. Based on a P-index threshold of 0.3 that distinguishes between known or previously inferred allo- or autopolyploidies, we found that 87.5% of 24 angiosperm paleo-polyploidies were likely produced by allopolyploidizations, responsible for establishment of major tribes such as Poaceae and Fabaceae, and large groups such as monocots and eudicots. These findings suggest that >99.7% of plant genomes likely derived directly from allopolyploidies, with autopolyploidies responsible for the establishment of only a few small genera, including Glycine, Malus, and Populus, each containing tens of species. Overall, these findings show that polyploids with high divergence between subgenomes (presumably allopolyploids) established the major plant groups, possibly through secondary contact between previously isolated populations and hybrid vigor associated with their re-joining.