The paper introduces SINA (SILVA Incremental Aligner), a method for aligning ribosomal RNA (rRNA) gene sequences using a combination of k-mer searching and partial order alignment (POA). SINA is designed to handle high-throughput alignment demands while maintaining high accuracy. The method is evaluated against other commonly used high-throughput MSA programs, PyNAST and mothur, using benchmark datasets from the BRaIBase III project and the SILVA rRNA databases. SINA demonstrates superior accuracy, achieving higher Q scores in all benchmarks compared to PyNAST and mothur. The algorithm's performance is further enhanced by using multiple reference sequences and dynamically selecting a fixed number of sequences for the alignment template. SINA is implemented in C++ and is available for download, offering a versatile tool for accurate high-throughput MSA.The paper introduces SINA (SILVA Incremental Aligner), a method for aligning ribosomal RNA (rRNA) gene sequences using a combination of k-mer searching and partial order alignment (POA). SINA is designed to handle high-throughput alignment demands while maintaining high accuracy. The method is evaluated against other commonly used high-throughput MSA programs, PyNAST and mothur, using benchmark datasets from the BRaIBase III project and the SILVA rRNA databases. SINA demonstrates superior accuracy, achieving higher Q scores in all benchmarks compared to PyNAST and mothur. The algorithm's performance is further enhanced by using multiple reference sequences and dynamically selecting a fixed number of sequences for the alignment template. SINA is implemented in C++ and is available for download, offering a versatile tool for accurate high-throughput MSA.