18Multi-gene and genomic datasets have become commonplace in the field of 19 phylogenetics, but many of the existing tools are not designed for such datasets, 20 which makes the analysis time-consuming and tedious. We therefore present 21 PhyloSuite, a user-friendly workflow desktop platform dedicated to streamlining 22 molecular sequence data management and evolutionary phylogenetics studies. It 23 employs a plugin-based system that integrates a number of useful phylogenetic and 24 bioinformatic tools, thereby streamlining the entire procedure, from data acquisition 25 to phylogenetic tree annotation, with the following features: (i) point-and-click and 26 drag-and-drop graphical user interface, (ii) a workspace to manage and organize 27 molecular sequence data and results of analyses, (iii) GenBank entries extraction and 28 comparative statistics, (iv) a phylogenetic workflow with batch processing capability, 29(v) elaborate bioinformatic analysis for mitochondrial genomes. The aim of 30 PhyloSuite is to enable researchers to spend more time playing with scientific 31 questions, instead of wasting it on conducting standard analyses. The compiled binary 32 of PhyloSuite is available under the GPL license at 33 https://github.com/dongzhang0725/PhyloSuite/releases, implemented in Python and 34 runs on Windows, Mac OSX and Linux. 35 36 37 Advancements in next-generation sequencing technologies (Metzker, 2009) have 38 resulted in a huge increase in the amount of genetic data available through public 39 databases. While this opens a multitude of research possibilities, retrieving and 40 managing such large amounts of data may be difficult and time-consuming for 41 researchers who are not computer-savvy. A standard analytical procedure for 42 phylogenetic analysis is: selecting and downloading GenBank entries, extracting 43 target genes (for multi-gene datasets, such as organelle genomes) and/or mining other 44 data, sequence alignment, alignment optimization, concatenation of alignments (for 45 multi-gene datasets), selection of best-fit partitioning schemes and evolutionary 46 models, phylogeny reconstruction, and finally visualization and annotation of the 47 phylogram. This can be very time-consuming if different programs have to be 48 employed for different steps, especially as they often have different input file format 49 requirements, and sometimes even require manual file tweaking. Therefore, 50 multifunctional, workflow-type software packages are becoming increasingly needed 51 by a broad range of evolutionary biologists (Smith, 2015). Specifically, as single-gene 52 datasets are rapidly being replaced by multi-gene or genomic datasets as a tool of 53 choice for phylogenetic reconstruction (Degnan and Rosenberg, 2009; Rivera-Rivera 54 and Montoya-Burgos, 2016), automated gene extraction from genomic data and batch 55 manipulation in some of the above steps, like alignment, are becoming a necessity. 56 Although there are several tools in existence, designed to streamline this process 57 by incorporat...

The ascomycete Fusarium graminearum is a destructive fungal pathogen of wheat (Triticum aestivum). To better understand how this pathogen proliferates within the host plant, we tracked pathogen growth inside wheat coleoptiles and then examined pathogen gene expression inside wheat coleoptiles at 16, 40, and 64 h after inoculation (HAI) using laser capture microdissection and microarray analysis. We identified 344 genes that were preferentially expressed during invasive growth in planta. Gene expression profiles for 134 putative plant cell wall-degrading enzyme genes suggest that there was limited cell wall degradation at 16 HAI and extensive degradation at 64 HAI. Expression profiles for genes encoding reactive oxygen species (ROS)-related enzymes suggest that F. graminearum primarily scavenges extracellular ROS before a later burst of extracellular ROS is produced by F. graminearum enzymes. Expression patterns of genes involved in primary metabolic pathways suggest that F. graminearum relies on the glyoxylate cycle at an early stage of plant infection. A secondary metabolite biosynthesis gene cluster was specifically induced at 64 HAI and was required for virulence. Our results indicate that F. graminearum initiates infection of coleoptiles using covert penetration strategies and switches to overt cellular destruction of tissues at an advanced stage of infection.

Flower induction in apple (Malus domestica Borkh.) is regulated by complex gene networks that involve multiple signal pathways to ensure flower bud formation in the next year, but the molecular determinants of apple flower induction are still unknown. In this research, transcriptomic profiles from differentiating buds allowed us to identify genes potentially involved in signaling pathways that mediate the regulatory mechanisms of flower induction. A hypothetical model for this regulatory mechanism was obtained by analysis of the available transcriptomic data, suggesting that sugar-, hormone- and flowering-related genes, as well as those involved in cell-cycle induction, participated in the apple flower induction process. Sugar levels and metabolism-related gene expression profiles revealed that sucrose is the initiation signal in flower induction. Complex hormone regulatory networks involved in cytokinin (CK), abscisic acid (ABA) and gibberellic acid pathways also induce apple flower formation. CK plays a key role in the regulation of cell formation and differentiation, and in affecting flowering-related gene expression levels during these processes. Meanwhile, ABA levels and ABA-related gene expression levels gradually increased, as did those of sugar metabolism-related genes, in developing buds, indicating that ABA signals regulate apple flower induction by participating in the sugar-mediated flowering pathway. Furthermore, changes in sugar and starch deposition levels in buds can be affected by ABA content and the expression of the genes involved in the ABA signaling pathway. Thus, multiple pathways, which are mainly mediated by crosstalk between sugar and hormone signals, regulate the molecular network involved in bud growth and flower induction in apple trees.