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Background: Chrysanthemum is one kind of ornamental plant well-known and widely used in the world. However, its quality and production were severely affected by low temperature conditions in winter and early spring periods. Therefore, we used the RNA-Seq platform to perform a de novo transcriptome assembly to analyze chrysanthemum (Dendranthema grandiflorum) transcription response to low temperature. Results: Using Illumina sequencing technology, a total of 86,444,237 high-quality clean reads and 93,837 unigenes were generated from four libraries: T01, controls; T02, 4 °C cold acclimation (CA) for 24 h; T03, − 4 °C freezing treatments for 4 h with prior CA; and T04, − 4 °C freezing treatments for 4 h without prior CA. In total, 7583 differentially expressed genes (DEGs) of 36,462 annotated unigenes were identified. We performed GO and KEGG pathway enrichment analyses, and excavated a group of important cold-responsive genes related to low temperature sensing and signal transduction, membrane lipid stability, reactive oxygen species (ROS) scavenging and osmoregulation. These genes encode many key proteins in plant biological processes, such as protein kinases, transcription factors, fatty acid desaturase, lipid-transfer proteins, antifreeze proteins, antioxidase and soluble sugars synthetases. We also verified expression levels of 10 DEGs using quantitative real-time polymerase chain reaction (qRT-PCR). In addition, we performed the determination of physiological indicators of chrysanthemum treated at low temperature, and the results were basically consistent with molecular sequencing results. Conclusion: In summary, our study presents a genome-wide transcript profile of Dendranthema grandiflorum var. jinba and provides insights into the molecular mechanisms of D. grandiflorum in response to low temperature. These data contributes to our deeper relevant researches on cold tolerance and further exploring new candidate genes for chilling-tolerance and freezing-tolerance chrysanthemum molecular breeding. [ABSTRACT FROM AUTHOR]

Background: Lysine acetylation in proteins is a ubiquitous and conserved post-translational modification, playing a critical regulatory role in almost every aspect of living cells. Although known for many years, its function remains elusive in Fusarium graminearum, one of the most important necrotrophic plant pathogens with huge economic impact. Results: By the combination of affinity enrichment and high-resolution LC-MS/MS analysis, large-scale lysine acetylome analysis was performed. In total, 577 lysine acetylation sites matched to 364 different proteins were identified. Bioinformatics analysis of the acetylome showed that the acetylated proteins are involved in a wide range of cellular functions and exhibit diverse subcellular localizations. Remarkably, 10 proteins involved in the virulence or DON (deoxynivalenol) biosynthesis were found to be acetylated, including 4 transcription factors, 4 protein kinases and 2 phosphatases. Protein-protein interaction network analysis revealed that acetylated protein complexes are involved in diversified interactions. Conclusions: This work provides the first comprehensive survey of a possible lysine acetylome in F. graminearum and reveals previously unappreciated roles of lysine acetylation in the regulation of diverse biological processes. This work provides a resource for functional analysis of acetylated proteins in filamentous fungi. [ABSTRACT FROM AUTHOR]

Background: microRNAs (miRNAs) play an essential role in the post-transcriptional gene regulation in plants and animals. They regulate a wide range of biological processes by targeting messenger RNAs (mRNAs). Evidence suggests that miRNAs and mRNAs interact collectively in gene regulatory networks. The collective relationships between groups of miRNAs and groups of mRNAs may be more readily interpreted than those between individual miRNAs and mRNAs, and thus are useful for gaining insight into gene regulation and cell functions. Several computational approaches have been developed to discover miRNA-mRNA regulatory modules (MMRMs) with a common aim to elucidate miRNA-mRNA regulatory relationships. However, most existing methods do not consider the collective relationships between a group of miRNAs and the group of targeted mRNAs in the process of discovering MMRMs. Our aim is to develop a framework to discover MMRMs and reveal miRNA-mRNA regulatory relationships from the heterogeneous expression data based on the collective relationships. Results: We propose DIscovering COllective group RElationships (DICORE), an effective computational framework for revealing miRNA-mRNA regulatory relationships. We utilize the notation of collective group relationships to build the computational framework. The method computes the collaboration scores of the miRNAs and mRNAs on the basis of their interactions with mRNAs and miRNAs, respectively. Then it determines the groups of miRNAs and groups of mRNAs separately based on their respective collaboration scores. Next, it calculates the strength of the collective relationship between each pair of miRNA group and mRNA group using canonical correlation analysis, and the group pairs with significant canonical correlations are considered as the MMRMs. We applied this method to three gene expression datasets, and validated the computational discoveries. Conclusions: Analysis of the results demonstrates that a large portion of the regulatory relationships discovered by DICORE is consistent with the experimentally confirmed databases. Furthermore, it is observed that the top mRNAs that are regulated by the miRNAs in the identified MMRMs are highly relevant to the biological conditions of the given datasets. It is also shown that the MMRMs identified by DICORE are more biologically significant and functionally enriched. [ABSTRACT FROM AUTHOR]

Background: Members of Comamonas testosteroni are environmental microorganisms that are usually found in polluted environment samples. They utilize steroids and aromatic compounds but rarely sugars, and show resistance to multiple heavy metals and multiple drugs. However, comprehensive genomic analysis among the C. testosteroni strains is lacked. Results: To understand the genome bases of the features of C. testosteroni, we sequenced 10 strains of this species and analyzed them together with other related published genome sequences. The results revealed that: 1) the strains of C. testosteroni have genome sizes ranging from 5.1 to 6.0 Mb and G + C contents ranging from 61.1% to 61.8%. The pan-genome contained 10,165 gene families and the core genome contained 3,599 gene families. Heap's law analysis indicated that the pan-genome of C. testosteroni may be open (a = 0.639); 2) by analyzing 31 phenotypes of 11 available C. testosteroni strains, 99.4% of the genotypes (putative genes) were found to be correlated to the phenotypes, indicating a high correlation between phenotypes and genotypes; 3) gene clusters for nitrate reduction, steroids degradation and metal and multi-drug resistance were found and were highly conserved among all the genomes of this species; 4) the genome similarity of C. testosteroni may be related to the geographical distances. Conclusions: This work provided an overview on the genomes of C. testosteroni and new genome resources that would accelerate the further investigations of this species. Importantly, this work focused on the analysis of potential genetic determinants for the typical characters and found high correlation between the phenotypes and their corresponding genotypes. [ABSTRACT FROM AUTHOR]