Parallel and Space-efficient Construction of Burrows-Wheeler Transform and Suffix Array for Big Genome Data Next-generation sequencing technologies have led to the sequencing of more and more genomes, propelling related research into the era of big data. In this paper, we present ParaBWT, a parallelized Burrows-Wheeler transform (BWT) and suffix array construction algorithm for big genome data. In ParaBWT, we have investigated a progressive construction approach to constructing the BWT of single genome sequences in linear space complexity, but with a small constant factor. This approach has been further parallelized using multi-threading based on a master-slave coprocessing model. After gaining the BWT, the suffix array is constructed in a memory-efficient manner. The performance of ParaBWT has been evaluated using two sequences generated from two human genome assemblies: the Ensembl Homo sapiens assembly and the human reference genome. Our performance comparison to FMDindex and Bwt-disk reveals that on 12 CPU cores, ParaBWT runs up to 2.2× faster than FMD-index and up to 99.0× faster than Bwt-disk. BWT construction algorithms for very long genomic sequences are time consuming and (due to their incremental nature) inherently difficult to parallelize. Thus, their parallelization is challenging and even relatively small speedups like the ones of our method over FMD-index are of high importance to research.