A saturated genetic linkage map of autotetraploid alfalfa (Medicago sativa L.) developed using genotyping-by-sequencing is highly syntenous with the Medicago truncatula genome.

A genetic linkage map is a valuable tool for quantitative trait locus mapping, map-based gene cloning, comparative mapping, and whole-genome assembly. Alfalfa, one of the most important forage crops in the world, is autotetraploid, allogamous, and highly heterozygous, characteristics that have impeded the construction of a high-density linkage map using traditional genetic marker systems. Using genotyping-by-sequencing (GBS), we constructed low-cost, reasonably high-density linkage maps for both maternal and paternal parental genomes of an autotetraploid alfalfa F1 population. The resulting maps contain 3591 single-nucleotide polymorphism markers on 64 linkage groups across both parents, with an average density of one marker per 1.5 and 1.0 cM for the maternal and paternal haplotype maps, respectively. Chromosome assignments were made based on homology of markers to the M. truncatula genome. Four linkage groups representing the four haplotypes of each alfalfa chromosome were assigned to each of the eight Medicago chromosomes in both the maternal and paternal parents. The alfalfa linkage groups were highly syntenous with M. truncatula, and clearly identified the known translocation between Chromosomes 4 and 8. In addition, a small inversion on Chromosome 1 was identified between M. truncatula and M. sativa. GBS enabled us to develop a saturated linkage map for alfalfa that greatly improved genome coverage relative to previous maps and that will facilitate investigation of genome structure. GBS could be used in breeding populations to accelerate molecular breeding in alfalfa

Comparative proteomic analysis of leaves at different ages in allotriploid populus

Triploid poplar trees have been shown to have a number of growth advantages, especially much bigger leaves that contribute greatly to the increased biomass. In this study, we focused on the relationships between leaf age and leaf metabolism in triploids. We performed comparative proteomic analysis of the 5th (FDR5), 10th (FDR10), and 25th (FDR25) leaves from the apical meristems in allotriploids originated from first-division restitution (FDR). A total of 1970, 1916, and 1850 proteins were identified in the FDR5, FDR10, and FDR25, respectively. Principle component analysis (PCA) and differentially accumulated protein (DAP) analysis showed that FDR10 and FDR25 displayed higher similarities of protein accumulation patterns as compared to FDR5. MapMan enrichment analysis showed that several primary metabolic pathways or processes were significantly enriched in the DAPs. For example, photosynthesis, major CHO metabolism, glycolysis, N metabolism, redox, C1-metabolism, DNA, and protein turnover were significantly altered in both FDR10 and FDR25 compared with FDR5. In addition, amino acid metabolism and gluconeogenesis/glyoxylate cycle also underwent significant changes in FDR25 compared with FDR5. However, only amino acid metabolism was significantly enriched in the DAPs between FDR25 and FDR10. Further, DAP accumulation pattern analysis implied that FDR5, FDR10, and FDR25 were placed in the young, mature, and primary senescence stages of leaves. The most DAPs involved in the light reaction, photorespiration, Calvin cycle, starch and sucrose metabolism, pentose phosphate pathway (OPP), tricarboxylic acid (TCA) cycle, N metabolism, and C1-metabolism displayed higher accumulation in both FDR10 and FDR25 compared to FDR5. However, the most DAPs that are involved in cell wall and lipid metabolism, tetrapyrrole synthesis, nucleotide metabolism exhibited lower accumulation in both FDR10 and FDR25. Almost all DAPs between FDR-10 and FDR-25 showed a dramatic decrease in FDR25. KEGG enrichment analysis showed that carbon metabolism was altered significantly at different leaf ages. DAPs that are involved in carbon metabolism were predicted as different points in protein–protein interaction (PPI) networks from the STRING database. Finally, inconsistent transcript and protein abundance was found for DAPs, indicating the presence of posttranscriptional regulation during leaf-age progression process

3,3′-(m-Phenyl­enedi­oxy)diphthalonitrile

In the title compound, C22H10N4O2, the dihedral angles between the mean planes of the central benzene ring and the pendant rings are 79.20 (6) and 80.29 (6)°. The dihedral angle between the pendant rings is 10.27 (7)°

Growth-regulating factor 5 (GRF5)-mediated gene regulatory network promotes leaf growth and expansion in poplar

Although polyploid plants have larger leaves than their diploid counterparts, the molecular mechanisms underlying this difference (or trait) remain elusive. Differentially expressed genes (DEGs) between triploid and full-sib diploid poplar trees were identified from two transcriptomic data sets followed by a gene association study among DEGs to identify key leaf growth regulators. Yeast one-hybrid system, electrophoretic mobility shift assay, and dual-luciferase assay were employed to substantiate that PpnGRF5-1 directly regulated PpnCKX1. The interactions between PpnGRF5-1 and growth-regulating factor (GRF)-interacting factors (GIFs) were experimentally validated and a multilayered hierarchical regulatory network (ML-hGRN)-mediated by PpnGRF5-1 was constructed with top-down graphic Gaussian model (GGM) algorithm by combining RNA-sequencing data from its overexpression lines and DAP-sequencing data. PpnGRF5-1 is a negative regulator of PpnCKX1. Overexpression of PpnGRF5-1 in diploid transgenic lines resulted in larger leaves resembling those of triploids, and significantly increased zeatin and isopentenyladenine in the apical buds and third leaves. PpnGRF5-1 also interacted with GIFs to increase its regulatory diversity and capacity. An ML-hGRN-mediated by PpnGRF5-1 was obtained and could largely elucidate larger leaves. PpnGRF5-1 and the ML-hGRN-mediated by PpnGRF5-1 were underlying the leaf growth and development

H2CGL: Modeling Dynamics of Citation Network for Impact Prediction

The potential impact of a paper is often quantified by how many citations it will receive. However, most commonly used models may underestimate the influence of newly published papers over time, and fail to encapsulate this dynamics of citation network into the graph. In this study, we construct hierarchical and heterogeneous graphs for target papers with an annual perspective. The constructed graphs can record the annual dynamics of target papers' scientific context information. Then, a novel graph neural network, Hierarchical and Heterogeneous Contrastive Graph Learning Model (H2CGL), is proposed to incorporate heterogeneity and dynamics of the citation network. H2CGL separately aggregates the heterogeneous information for each year and prioritizes the highly-cited papers and relationships among references, citations, and the target paper. It then employs a weighted GIN to capture dynamics between heterogeneous subgraphs over years. Moreover, it leverages contrastive learning to make the graph representations more sensitive to potential citations. Particularly, co-cited or co-citing papers of the target paper with large citation gap are taken as hard negative samples, while randomly dropping low-cited papers could generate positive samples. Extensive experimental results on two scholarly datasets demonstrate that the proposed H2CGL significantly outperforms a series of baseline approaches for both previously and freshly published papers. Additional analyses highlight the significance of the proposed modules. Our codes and settings have been released on Github (https://github.com/ECNU-Text-Computing/H2CGL)Comment: Accepted by IP&

Up-regulation of fas reverses cisplatin resistance of human small cell lung cancer cells

<p>Abstract</p> <p>Background/Aim</p> <p>Fas/FasL system is a major regulator of apoptosis. The mechanisms by which Fas mediates cisplatin resistance remain unclear. The aim of this study is to explore the effect of Fas over-expression on cisplatin resistance of small cell lung cancer cells and its possible mechanisms.</p> <p>Materials and methods</p> <p>Fas was over-expressed in H446/CDDP cells by infection with the adenoviruses containing Fas. Sensitivity of Fas-overexpressed H446/CDDP cells to cisplatin was evaluated using MTT assay. Expressions of Fas, GST-π and ERCC1 were detected by RT-PCR and Western blot analysis. Apoptosis rate was examined by FACS.</p> <p>Results</p> <p>Over-expression of Fas in H446/CDDP cells significantly decreased the expressions of GST-π and ERCC1 at mRNA and protein levels, and increased the cell apoptosis. Furthermore, up-regulation of Fas significantly decreased the tolerance of H446/CDDP cells to cisplatin.</p> <p>Conclusion</p> <p>Over-expression of Fas reverses drug resistance of H446/CDDP cells, possibly due to the increased cell sensitivity to apoptosis and the decreased expressions of GST-π and ERCC1.</p

Effect of fucoidan on B16 murine melanoma cell melanin formation and apoptosis

Background：Fucoidan is a complex sulfated polysaccharide extracted from brown seaweed and has a wide variety of biological activities. It not only inhibits cancer cell growth but also inhibits tyrosinase in vitro. Therefore, it is of interest to investigate the effect of fucoidan on B16 murine melanoma cells as the findings may provide new insights into the underlying mechanism regarding the inhibition of melanin formation by fucoidan. In the present study, we aimed to investigate the anti-melanogenic effect of fucoidan and its inhibitory effect on B16 cells.Materials and Methods: The influence of fucoidan on B16 melanoma cells and cellular tyrosinase was examined. Cell viability was examined by the cell counting kit-8 assay. Cellular tyrosinase activity and melanin content were determined using spectrophotometric methods and protein expression was analyzed by immunoblotting. Morphological changes in B16 melanoma cells were examined by phase contrast microscopy and apoptosis was analyzed by flow cytometry.Results: In vitro studies were performed using cell viability analysis and showed that fucoidan significantly decreased viable cell number in a dose-response manner with an IC50 of 550 ±4.3 μg/mL. Cell morphology was altered and significant apoptosis was induced when cells were exposed to 550 μg/mL fucoidan for 48 h.Conclusion: This study provides substantial evidence to show that fucoidan inhibits B16 melanoma cell proliferation and cellular tyrosinase activity. Fucoidan may be useful in the treatment of hyperpigmentation and as a skin-whitening agent in the cosmetics industry.Keywords: B16 melanoma cells, Fucoidan, Melanogenesis, Tyrosinas

EmoGen: Eliminating Subjective Bias in Emotional Music Generation

Music is used to convey emotions, and thus generating emotional music is important in automatic music generation. Previous work on emotional music generation directly uses annotated emotion labels as control signals, which suffers from subjective bias: different people may annotate different emotions on the same music, and one person may feel different emotions under different situations. Therefore, directly mapping emotion labels to music sequences in an end-to-end way would confuse the learning process and hinder the model from generating music with general emotions. In this paper, we propose EmoGen, an emotional music generation system that leverages a set of emotion-related music attributes as the bridge between emotion and music, and divides the generation into two stages: emotion-to-attribute mapping with supervised clustering, and attribute-to-music generation with self-supervised learning. Both stages are beneficial: in the first stage, the attribute values around the clustering center represent the general emotions of these samples, which help eliminate the impacts of the subjective bias of emotion labels; in the second stage, the generation is completely disentangled from emotion labels and thus free from the subjective bias. Both subjective and objective evaluations show that EmoGen outperforms previous methods on emotion control accuracy and music quality respectively, which demonstrate our superiority in generating emotional music. Music samples generated by EmoGen are available via this link:https://ai-muzic.github.io/emogen/, and the code is available at this link:https://github.com/microsoft/muzic/.Comment: 12 pages, 7 page