AutomAted RepeaT Identifier (AARTI): A tool to identify common, polymorphic, and unique microsatellites

pSATdb 2.0: a database of organellar common, polymorphic, and unique microsatellites

Microsatellites, or simple sequence repeats (SSRs), are repetitive DNA sequences typically composed of 1-6 nucleotides. These repetitive sequences are found in almost all genomes, including chloroplasts and mitochondria, and are widely distributed throughout the genomes. Microsatellites are highly polymorphic, and their length may differ from species to species. Consequently, microsatellites are widely used as molecular markers and play pivotal roles in various biological research. However, comprehensive information about the length variation of microsatellites in various organellar genome sequences is not available. Therefore, to provide mined information and explore the variability in the length of microsatellites across species, we developed a comprehensive resource named pSATdb 2.0 (polymorphic microSATellites database; https://bioinfo.icgeb.res.in/psatdb/ ). This upgraded version of its predecessor pSATdb provides comprehensive information on the frequency and distribution of 348,894 microsatellites identified in organellar genome sequences. These sequences originate from 15,681 organisms spanning 3252 genera within Metazoa and Viridiplantae. Remarkably, pSATdb 2.0 is the only database that offers information on common and polymorphic microsatellites detected between organisms, along with unique microsatellites specific to each genus. Furthermore, this database features unrestricted access and includes pioneer functionalities such as Advanced Search, BLAST, and JBrowse, which facilitate user-specific microsatellite search and its visualization within the database. The pSATdb holds immense potential for the research community to support diverse studies, including genetic diversity, genetic mapping, marker-assisted selection, and comparative population investigations.

MegaSSR: a web server for large scale microsatellite identification, classification, and marker development

Next-generation sequencing technologies have opened new avenues for using genomic data to study and develop molecular markers and improve genetic resources. Simple Sequence Repeats (SSRs) as genetic markers are increasingly used in molecular diversity and molecular breeding programs that require bioinformatics pipelines to analyze the large amounts of data. Therefore, there is an ongoing need for online tools that provide computational resources with minimal effort and maximum efficiency, including automated development of SSR markers. These tools should be flexible, customizable, and able to handle the ever-increasing amount of genomic data. Here we introduce MegaSSR (https://bioinformatics.um6p.ma/MegaSSR), a web server and a standalone pipeline that enables the design of SSR markers in any target genome. MegaSSR allows users to design targeted PCR-based primers for their selected SSR repeats and includes multiple tools that initiate computational pipelines for SSR mining, classification, comparisons, PCR primer design, in silico PCR validation, and statistical visualization. MegaSSR results can be accessed, searched, downloaded, and visualized with user-friendly web-based tools. These tools provide graphs and tables showing various aspects of SSR markers and corresponding PCR primers. MegaSSR will accelerate ongoing research in plant species and assist breeding programs in their efforts to improve current genomic resources.

Scan-Find-Scan-Model: Discrete Site-Targeted Suppressor Design Strategy for Amyloid-β

Alzheimer's disease is undoubtedly the most well-studied neurodegenerative disease. Consequently, the amyloid-β (Aβ) protein ranks at the top in terms of getting attention from the scientific community for structural property-based characterization. Even after decades of extensive research, there is existing volatility in terms of understanding and hence the effective tackling procedures against the disease that arises due to the lack of knowledge of both specific target- and site-specific drugs. Here, we develop a multidimensional approach based on the characterization of the common static-dynamic-thermodynamic trait of the monomeric protein, which efficiently identifies a small target sequence that contains an inherent tendency to misfold and consequently aggregate. The robustness of the identification of the target sequence comes with an abundance of a priori knowledge about the length and sequence of the target and hence guides toward effective designing of the target-specific drug with a very low probability of bottleneck and failure. Based on the target sequence information, we further identified a specific mutant that showed the maximum potential to act as a destabilizer of the monomeric protein as well as enormous success as an aggregation suppressor. We eventually tested the drug efficacy by estimating the extent of modulation of binding affinity existing within the fibrillar form of the Aβ protein due to a single-point mutation and hence provided a proof of concept of the entire protocol.