Diet preferences based on sequence read count: The role of species interaction in tissue bias correction.

High-throughput sequencing and metabarcoding techniques provide a unique opportunity to study predator-prey relationships. However, in animal dietary preference studies, how to properly correct tissue bias within the sequence read count and the role of interactions between co-occurring species in metabarcoding mixtures remain largely unknown. In this study, we propose two categories of tissue bias correction indices: sequence read count number per unit tissue (SCN) and its ratio form (SCN ratio). By constructing plant mock communities with different numbers of co-occurring species in metabarcoding mixtures and conducting feeding trails on captive sika deer (Cervus nippon), we demonstrate the features of the SCN and SCN ratio, evaluate their correction effects and assess the role of species interactions during tissue bias correction. Tissue differences between species are defined as the differential ability to generate sequence counts. Our study suggests that pure tissue differences among species without a species interaction is not an optimal correction index for many biomes with limited tissue differences among species. Species interactions in mixtures may amplify tissue differences, which is beneficial for tissue bias correction. However, caution must be taken because varied species interactions among communities may increase the risk of worse correction. Correction effects based on the SCN and SCN ratio are comparable, but the SCN is less influenced by control species than the SCN ratio. Based on our study, several suggestions are provided for future animal diet studies or other high-throughput sequencing studies containing tissue bias.