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Microbial populations provide nitrogen cycling ecosystem services at the nexus of agriculture, environmental quality and climate change. Denitrification, in particular, impacts socio-environmental systems in both positive and negative ways, through reduction of aquatic and atmospheric nitrogen pollution, but also reduction of soil fertility and production of greenhouse gases. However, denitrification rates are quite variable in time and space, and therefore difficult to model. Microbial ecology is working to improve the predictive ecology of denitrifiers by quantifying and describing the diversity of microbial functional groups. However, metagenomic sequencing has revealed previously undescribed diversity within these functional groups, and highlighted a need to reevaluate coverage of existing DNA primers for denitrification functional genes. We provide here a comprehensive in silico evaluation of primer sets that target diagnostic genes in the denitrification pathway. This analysis makes use of current DNA sequence data available for each functional gene. It contributes a comparative analysis of the strengths and limitations of each primer set for describing denitrifier functional groups. This analysis identifies genes for which development of new tools is needed, and aids in interpretation of existing datasets, both of which will facilitate application of molecular methods to further develop the predictive ecology of denitrifiers.