SRAminer: a tool for Sequence Read Archive data mining that rapidly finds sequence matches to hidden targets

The exponential growth of nucleic acid sequence datasets stored in the Sequence Read Archive (SRA) of the National Center for Biotechnology Information (NCBI) public repository presents significant opportunities and challenges. This raw SRA data offers petabyte-scale records of global living matter but is not yet optimized for rapid large-scale searching and extraction of matching sequences, such as genes and gene variants or hidden microbial taxa. To address this challenge, we developed a software tool that searches and analyzes large sets of SRA datasets (up to 1,000,000 runs) with user-defined keywords (e.g., organisms, habitats, title words, sequencing strategy, project, or platform). The tool employs iterative BLAST searches, intensive computational analysis, and iterative BLAST-assembly to reconstruct genes and genomes from target-matched reads. Key findings include the identification of: 92 Wolbachia-positive SRA runs from 332,754 plant-parasitic nematode and rhizosphere samples, 61 pathogenic bacteria-positive SRA runs from 945 hospital wastewater treatment plant samples, 3 Salmonella enterica serovar Typhi-positive SRA runs from 221 associated bacterial samples, and 8 Burkholderia pseudomallei -positive SRA runs from 42,469 soil metagenomes. This software tool, which we name SRAminer (freely available at URL of the software), effectively streamlines the exploration of massive sequence archives, enabling efficient identification of genes and genomes of interest. We anticipate this tool will accelerate research into poorly studied genes and organisms, in complex biological systems and could have widespread applications in environmental and clinical microbiology, medicine and forensics, agriculture and food safety, and pathogen surveillance.