High-quality genome assembly of Huazhan and Tianfeng,the parents of an elite rice hybrid Tian-you-hua-zhan

High-quality rice reference genomes have accelerated the comprehensive identification of genome-wide variations and research on functional genomics and breeding. Tian-you-hua-zhan has been a leading hybrid in China over the past decade. Here, de novo genome assembly strategy optimization for the rice indica lines Huazhan (HZ) and Tianfeng (TF), including sequencing platforms, assembly pipelines and sequence depth, was carried out. The PacBio and Nanopore platforms for long-read sequencing were utilized, with the Canu, wtdbg2, SMARTdenovo, Flye, Canu-wtdbg2, Canu-SMARTdenovo and Canu-Flye assemblers. The combination of PacBio and Canu was optimal, considering the contig N50 length, contig number, assembled genome size and polishing process. The assembled contigs were scaffolded with Hi-C data, resulting in two “golden quality” rice reference genomes, and evaluated using the scaffold N50, BUSCO, and LTR assembly index. Furthermore, 42,625 and 41,815 non-transposable element genes were annotated for HZ and TF, respectively. Based on our assembly of HZ and TF, as well as Zhenshan97, Minghui63, Shuhui498 and 9311, comprehensive variations were identified using Nipponbare as a reference. The de novo assembly strategy for rice we optimized and the “golden quality” rice genomes we produced for HZ and TF will benefit rice genomics and breeding research, especially with respect to uncovering the genomic basis of the elite traits of HZ and TF.

     

野葛藤茎的异黄酮类化学成分

从野葛Pueraria lobata(Willd.)Ohwi藤茎中分离得到5个异黄酮类化合物,分别鉴定为:大豆甙元(daidzein),芒柄花异黄酮(formononetin),6,7-二甲氧基-3’,4’-次甲二氧基异黄酮(6,7-dimethoxy-3’,4’-methlenedioxyisoflavone),大豆甙(daidzin)和葛根素(puerarin).     

Rhizobium qilianshanense sp. nov., a novel species isolated from root nodule of Oxytropis ochrocephala Bunge in China

During a study of the diversity and phylogeny of rhizobia isolated from root nodules of Oxytropis ochrocephala grown in the northwest of China, four strains were classified in the genus Rhizobium on the basis of their 16S rRNA gene sequences. These strains have identical 16S rRNA gene sequences, which showed a mean similarity of 94.4 % with the most closely related species, Rhizobium oryzae. Analysis of recA and glnA sequences showed that these strains have less than 88.1 and 88.7 % similarity with the defined species of Rhizobium, respectively. The genetic diversity revealed by ERIC-PCR fingerprinting indicated that the isolates correspond to different strains. Strain CCNWQLS01^T contains Q-10 as the predominant ubiquinone. The major fatty acids were identified as feature 8 (C18: 1ω7c and/or C18: 1ω6c; 67.2 %). Therefore, a novel species Rhizobium qilianshanense sp. nov. is proposed, and CCNWQLS01^T (= ACCC 05747^T = JCM 18337^T) is designated as the type strain.     

Binding of the Heterogeneous Ribonucleoprotein K (hnRNP K) to the Epstein-Barr Virus Nuclear Antigen 2 (EBNA2) Enhances Viral LMP2A Expression

The Epstein-Barr Virus (EBV) -encoded EBNA2 protein, which is essential for the in vitro transformation of B-lymphocytes, interferes with cellular processes by binding to proteins via conserved sequence motifs. Its Arginine-Glycine (RG) repeat element contains either symmetrically or asymmetrically di-methylated arginine residues (SDMA and ADMA, respectively). EBNA2 binds via its SDMA-modified RG-repeat to the survival motor neurons protein (SMN) and via the ADMA-RG-repeat to the NP9 protein of the human endogenous retrovirus K (HERV-K (HML-2) Type 1). The hypothesis of this work was that the methylated RG-repeat mimics an epitope shared with cellular proteins that is used for interaction with target structures. With monoclonal antibodies against the modified RG-repeat, we indeed identified cellular homologues that apparently have the same surface structure as methylated EBNA2. With the SDMA-specific antibodies, we precipitated the Sm protein D3 (SmD3) which, like EBNA2, binds via its SDMA-modified RG-repeat to SMN. With the ADMA-specific antibodies, we precipitated the heterogeneous ribonucleoprotein K (hnRNP K). Specific binding of the ADMA- antibody to hnRNP K was demonstrated using E. coli expressed/ADMA-methylated hnRNP K. In addition, we show that EBNA2 and hnRNP K form a complex in EBV- infected B-cells. Finally, hnRNP K, when co-expressed with EBNA2, strongly enhances viral latent membrane protein 2A (LMP2A) expression by an unknown mechanism as we did not detect a direct association of hnRNP K with DNA-bound EBNA2 in gel shift experiments. Our data support the notion that the methylated surface of EBNA2 mimics the surface structure of cellular proteins to interfere with or co-opt their functional properties.     

A Bayesian Analysis for Identifying DNA Copy Number Variations Using a Compound Poisson Process

To study chromosomal aberrations that may lead to cancer formation or genetic diseases, the array-based Comparative Genomic Hybridization (aCGH) technique is often used for detecting DNA copy number variants (CNVs). Various methods have been developed for gaining CNVs information based on aCGH data. However, most of these methods make use of the log-intensity ratios in aCGH data without taking advantage of other information such as the DNA probe (e.g., biomarker) positions/distances contained in the data. Motivated by the specific features of aCGH data, we developed a novel method that takes into account the estimation of a change point or locus of the CNV in aCGH data with its associated biomarker position on the chromosome using a compound Poisson process. We used a Bayesian approach to derive the posterior probability for the estimation of the CNV locus. To detect loci of multiple CNVs in the data, a sliding window process combined with our derived Bayesian posterior probability was proposed. To evaluate the performance of the method in the estimation of the CNV locus, we first performed simulation studies. Finally, we applied our approach to real data from aCGH experiments, demonstrating its applicability.     

Integrating Multi-Omics for Uncovering the Architecture of Cross-Talking Pathways in Breast Cancer

Cross-talk among abnormal pathways widely occurs in human cancer and generally leads to insensitivity to cancer treatment. Moreover, alterations in the abnormal pathways are not limited to single molecular level. Therefore, we proposed a strategy that integrates a large number of biological sources at multiple levels for systematic identification of cross-talk among risk pathways in cancer by random walk on protein interaction network. We applied the method to multi-Omics breast cancer data from The Cancer Genome Atlas (TCGA), including somatic mutation, DNA copy number, DNA methylation and gene expression profiles. We identified close cross-talk among many known cancer-related pathways with complex change patterns. Furthermore, we identified key genes (linkers) bridging these cross-talks and showed that these genes carried out consistent biological functions with the linked cross-talking pathways. Through identification of leader genes in each pathway, the architecture of cross-talking pathways was built. Notably, we observed that linkers cooperated with leaders to form the fundamentation of cross-talk of pathways which play core roles in deterioration of breast cancer. As an example, we observed that KRAS showed a direct connection to numerous cancer-related pathways, such as MAPK signaling pathway, suggesting that it may be a central communication hub. In summary, we offer an effective way to characterize complex cross-talk among disease pathways, which can be applied to other diseases and provide useful information for the treatment of cancer.