Evolution of Yin and Yang isoforms of a chromatin remodeling subunit precedes the creation of two genes

Genes can encode multiple isoforms, broadening their functions and providing a molecular substrate to evolve phenotypic diversity. Evolution of isoform function is a potential route to adapt to new environments. Here we show that de novo, beneficial alleles in the nurf-1 gene became fixed in two laboratory lineages of C. elegans after isolation from the wild in 1951, before methods of cryopreservation were developed. nurf-1 encodes an ortholog of BPTF, a large (>300 kD) multidomain subunit of the NURF chromatin remodeling complex. Using CRISPR-Cas9 genome editing and transgenic rescue, we demonstrate that in C. elegans, nurf-1 has split into two, largely non-overlapping isoforms (NURF-1.D and NURF-1.B, which we call Yin and Yang, respectively) that share only two of 26 exons. Both isoforms are essential for normal gametogenesis but have opposite effects on male/female gamete differentiation. Reproduction in hermaphrodites, which involves production of both sperm and oocytes, requires a balance of these opposing Yin and Yang isoforms. Transgenic rescue and genetic position of the fixed mutations suggest that different isoforms are modified in each laboratory strain. In a related clade of Caenorhabditis nematodes, the shared exons have duplicated, resulting in the split of the Yin and Yang isoforms into separate genes, each containing approximately 200 amino acids of duplicated sequence that has undergone accelerated protein evolution following the duplication. Associated with this duplication event is the loss of two additional nurf-1 transcripts, including the long-form transcript and a newly identified, highly expressed transcript encoded by the duplicated exons. We propose these lost transcripts are non-functional side products necessary to transcribe the Yin and Yang transcripts in the same cells. Our work demonstrates how gene sharing, through the production of multiple isoforms, can precede the creation of new, independent genes.National Institute of General Medical Sciences R01GM114170 Patrick T McGrat National Institute of General Medical Sciences R01GM121688 Ronald E Ellis.The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.S

Learn by Oneself: Exploiting Weight-Sharing Potential in Knowledge Distillation Guided Ensemble Network

Recent CNNs (convolutional neural networks) have become more and more compact. The elegant structure design highly improves the performance of CNNs. With the development of knowledge distillation technique, the performance of CNNs gets further improved. However, existing knowledge distillation guided methods either rely on offline pretrained high-quality large teacher models or online heavy training burden. To solve the above problems, we propose a feature-sharing and weight-sharing based ensemble network (training framework) guided by knowledge distillation (EKD-FWSNet) to make baseline models stronger in terms of representation ability with less training computation and memory cost involved. Specifically, motivated by getting rid of the dependence of offline pretrained teacher model, we design an end-to-end online training scheme to optimize EKD-FWSNet. Motivated by decreasing the online training burden, we only introduce one auxiliary classmate branch to construct multiple forward branches, which will then be integrated as ensemble teacher to guide baseline model. Compared to previous online ensemble training frameworks, EKD-FWSNet can provide diverse output predictions without relying on increasing auxiliary classmate branches. Motivated by maximizing the optimization power of EKD-FWSNet, we exploit the representation potential of weight-sharing blocks and design efficient knowledge distillation mechanism in EKD-FWSNet. Extensive comparison experiments and visualization analysis on benchmark datasets (CIFAR-10/100, tiny-ImageNet, CUB-200 and ImageNet) show that self-learned EKD-FWSNet can boost the performance of baseline models by large margin, which has obvious superiority compared to previous related methods. Extensive analysis also proves the interpretability of EKD-FWSNet. Our code is available at https://github.com/cv516Buaa/EKD-FWSNet

Speculation on optimal numbers of examined lymph node for early-stage epithelial ovarian cancer from the perspective of stage migration

IntroductionIn early-stage epithelial ovarian cancer (EOC), how to perform lymphadenectomy to avoid stage migration and achieve reliable targeted excision has not been explored in depth. This study comprehensively considered the stage migration and survival to determine appropriate numbers of examined lymph node (ELN) for early-stage EOC and high-grade serous ovarian cancer (HGSOC).MethodsFrom the Surveillance, Epidemiology, and End Results database, we obtained 10372 EOC cases with stage T1M0 and ELN ≥ 2, including 2849 HGSOC cases. Generalized linear models with multivariable adjustment were used to analyze associations between ELN numbers and lymph node stage migration, survival and positive lymph node (PLN). LOESS regression characterized dynamic trends of above associations followed by Chow test to determine structural breakpoints of ELN numbers. Survival curves were plotted using Kaplan-Meier method.ResultsMore ELNs were associated with more node-positive diseases, more PLNs and better prognosis. ELN structural breakpoints were different in subgroups of early-stage EOC, which for node stage migration or PLN were more than those for improving outcomes. The meaning of ELN structural breakpoint varied with its location and the morphology of LOESS curve. To avoid stage migration, the optimal ELN for early-stage EOC was 29 and the minimal ELN for HGSOC was 24. For better survival, appropriate ELN number were 13 and 8 respectively. More ELNs explained better prognosis only at a certain range.DiscussionNeither too many nor too few numbers of ELN were ideal for early-stage EOC and HGSOC. Excision with appropriate numbers of lymph node draining the affected ovary may be more reasonable than traditional sentinel lymph node resection and systematic lymphadenectomy

Plant and prokaryotic TIR domains generate distinct cyclic ADPR NADase products

Toll/interleukin-1 receptor (TIR) domain proteins function in cell death and immunity. In plants and bacteria, TIR domains are often enzymes that produce isomers of cyclic adenosine 5′-diphosphate–ribose (cADPR) as putative immune signaling molecules. The identity and functional conservation of cADPR isomer signals is unclear. A previous report found that a plant TIR could cross-activate the prokaryotic Thoeris TIR–immune system, suggesting the conservation of plant and prokaryotic TIR-immune signals. Here, we generate autoactive Thoeris TIRs and test the converse hypothesis: Do prokaryotic Thoeris TIRs also cross-activate plant TIR immunity? Using in planta and in vitro assays, we find that Thoeris and plant TIRs generate overlapping sets of cADPR isomers and further clarify how plant and Thoeris TIRs activate the Thoeris system via producing 3′cADPR. This study demonstrates that the TIR signaling requirements for plant and prokaryotic immune systems are distinct and that TIRs across kingdoms generate a diversity of small-molecule products

Construction of a cross-species cell landscape at single-cell level.

Individual cells are basic units of life. Despite extensive efforts to characterize the cellular heterogeneity of different organisms, cross-species comparisons of landscape dynamics have not been achieved. Here, we applied single-cell RNA sequencing (scRNA-seq) to map organism-level cell landscapes at multiple life stages for mice, zebrafish and Drosophila. By integrating the comprehensive dataset of > 2.6 million single cells, we constructed a cross-species cell landscape and identified signatures and common pathways that changed throughout the life span. We identified structural inflammation and mitochondrial dysfunction as the most common hallmarks of organism aging, and found that pharmacological activation of mitochondrial metabolism alleviated aging phenotypes in mice. The cross-species cell landscape with other published datasets were stored in an integrated online portal-Cell Landscape. Our work provides a valuable resource for studying lineage development, maturation and aging

Histone deacetylase 9 promotes endothelial to mesenchymal transition and an unfavorable atherosclerotic plaque phenotype

Endothelial-mesenchymal transition (EndMT) is associated with various cardiovascular diseases and in particular with atherosclerosis and plaque instability. However, the molecular pathways that govern EndMT are poorly defined. Specifically, the role of epigenetic factors and histone deacetylases (HDACs) in controlling EndMT and the atherosclerotic plaque phenotype remains unclear. Here, we identified histone deacetylation, specifically that mediated by HDAC9 (a class IIa HDAC), as playing an important role in both EndMT and atherosclerosis. Using in vitro models, we found class IIa HDAC inhibition sustained the expression of endothelial proteins and mitigated the increase in mesenchymal proteins, effectively blocking EndMT. Similarly, ex vivo genetic knockout of Hdac9 in endothelial cells prevented EndMT and preserved a more endothelial-like phenotype. In vivo, atherosclerosis-prone mice with endothelial-specific Hdac9 knockout showed reduced EndMT and significantly reduced plaque area. Furthermore, these mice displayed a more favorable plaque phenotype, with reduced plaque lipid content and increased fibrous cap thickness. Together, these findings indicate that HDAC9 contributes to vascular pathology by promoting EndMT. Our study provides evidence for a pathological link among EndMT, HDAC9, and atherosclerosis and suggests that targeting of HDAC9 may be beneficial for plaque stabilization or slowing the progression of atherosclerotic disease

iSky:Efficient and Progressive Skyline Computing in a Structured P2P Network

An interesting problem in peer-based data management is efficient support for skyline queries within a multi-attribute space. A skyline query retrieves from a set of multidimensional data points a subset of interesting points, compared to which no other points are better Skyline queries play an important role in multi-criteria decision making and user preference applications. In this paper we address the skyline computing problem in a structured P2P network. We exploit the iMinMax(theta) transformation to map high-dimensional data points to 1-dimensional values. All transformed data points are then distributed on a structured P2P network called BATON, where all peers are virtually organized as a balanced binary search tree. Subsequently, a progressive algorithm is proposed to compute skyline in the distributed P2P network. Further, we propose an adaptive skyline filtering technique to reduce both processing cost and communication cost during distributed skyline computing. Our performance study, with both synthetic and real datasets, shows that the proposed approach can dramatically reduce transferred data volume and gain quick response time.Computer Science, Theory & MethodsEICPCI-S(ISTP)