Besides their basic principle, an overview of particular methods and tools is provided. Although these strategies do not require prior knowledge, they have higher demands on the length of sequences. In this review, we describe the strategies within the second approach. The first type classifies the DNA fragments by performing a standard homology inference against a reference database, while the latter performs the reference-free binning by applying clustering techniques on features extracted from the sequences. There are currently two types of binning methods: taxonomy dependent and taxonomy independent. On the other hand, the output of whole metagenomic shotgun sequencing is mixture of short DNA fragments belonging to various genomes, therefore this approach requires more sophisticated computational algorithms for clustering of related sequences, commonly referred to as sequence binning. With the advancement of sequencing techniques, the main focus shifted to the whole metagenome shotgun sequencing, which allows much more detailed analysis of the metagenomic data, including reconstruction of novel microbial genomes and to gain knowledge about genetic potential and metabolic capacities of whole environments. In the past, these issues were mostly addressed by the use of amplicon sequencing of a target gene because of reasonable price and easier computational postprocessing of the bioinformatic data. One of main steps in a study of microbial communities is resolving their composition, diversity and function. Here, we introduce the new version of our Toolkit and its application to the analysis of proteins. For instance, our popular remote homology detection server, HHpred, now allows pairwise comparison of two sequences or alignments and offers additional profile HMMs for several model organisms and domain databases. Recently, we replaced the first version of the Toolkit, which was released in 2005 and had served around 2.5 million queries, with an entirely new version, focusing on improved features for the comprehensive analysis of proteins, as well as on promoting teaching. This breadth has made the Toolkit an important resource for experimental biology and for teaching bioinformatic inquiry. It currently offers 34 interconnected external and in-house tools, whose functionality covers sequence similarity searching, alignment construction, detection of sequence features, structure prediction, and sequence classification. The MPI Bioinformatics Toolkit ( ) is a free, one-stop web service for protein bioinformatic analysis. These results provide important insights into the salt tolerance induced by AMF and a solid basis for the future enhancement of plant tolerance to salinity stress. Moreover, the identification of alternative splicing (AS) events indicated a more comprehensive response to AMF at the post-transcriptional level, which mainly occurs in genes involved in cell wall-related processes, transport, regulation of transcription, and response to abiotic stimulus. Furthermore, 23 differentially expressed transcription factors (TFs) were identified in the NI + S and AMF + S comparison, which are known to be associated with plant abiotic and biotic stress responses and regulation. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses revealed that these transcripts mainly involved the regulation of ROS-scavenging capacity, water and nutrient status, and cell wall synthesis and modification. Based on Venn diagram analysis, 391 DETs were specially regulated by AMF under salinity stress rather than under optimal growth conditions, which may be linked to the salinity stress adaptation mediated by AMF. A total of 6124 differentially expressed transcripts (DETs) were determined. Here, we performed transcriptome sequencing using the Oxford Nanopore Technologies (ONT) MinION platform for asparagus ( Asparagus officinalis L.) roots with 4 treatments: non-inoculated plants under optimal growth conditions (NI), inoculated plants under optimal growth conditions (AMF), non-inoculated plants under salinity stress conditions (NI + S), and inoculated plants under salinity stress conditions (AMF + S). A systematic study on plant responses to AMF under salinity stress may provide insights into the acquired salt tolerance. Arbuscular mycorrhizal fungi (AMF) can improve the salt tolerance of host plants. Soil salinity is one of the most serious abiotic stresses that limit agricultural productivity and the distribution of crops worldwide.
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