Table 2.

General considerations for the development of PCR-based methods (from Bustin et al., 2009; Campos-Herrera et al., 2010; van Pelt-Verkuil et al., 2010; Pompanon et al., 2012) and comparison between the two most extended methods in belowground studies: real time qPCR and DNA barcoding using next generation sequencing.

Experimental steps	Concept	Common considerations	Real time qPCR	Next generation sequencing
Design “in silico”	Selection of the target sequence	Adequate and meaningful for the study; check availability in the system to be able to compare with known species	ITS rDNA, D2D3, COI	SSU, LSU, sometimes ITS, customized
	Coverage and resolution	Range of taxa susceptible to be amplified	Species-specific	Generalistic, amplify broad taxonomic groups
	Primer and amplicon equilibrium	The length and composition of the primers will affect the specificity of the amplification; secondary structures should be avoided; the PCR product, the amplicon, should be into the range for optimal amplification	80–250 bp	200–600 bp, depending on the plataform
	Amplification efficiency	The efficiency might depend on the quality of the DNA (degradated, inhibitors presented, etc.)	Might be improved by adding some reactives (i.e., BSA or DMSO) or by diluting the DNA
Sample preparation	Design and sampling strategy	Include biological and technical replicates; tagging and multiplexing approaches available	Different dyes for multiplexing	Different molecular tags to separate treatments
	DNA extraction	Multiple kits available; desirable, verify the quality and quantity by electrophoresis or spectrophotometric systems (nano-drop)	–	–
Optimize reaction	PCR conditions	Experimental establishment of annealing temperature, time for extension, number of cycles; check for possible inhibitors	Important the number of cycles in nested qPCR experiments	–
	Sensitivity and specificity	Check the lowest number of amplicons detected of the target species/taxonomic group (dynamic range)	Important for quantification. Serial dilutions of the target DNA will serve for defining the limit of accurate detection for our standard curve	Important to establish the minimum taxonomic unit detected
Data analysis and validation of the experiments	Type of generated data	Units or type of quantification	Detection and quantification of the target organisms. Absolute quantification is possible if a standard curve is included in the run; relative quantification is possible among target species	Molecular operational taxonomic units (MOTUs). Special care need to be taken for the detection of “chimera” sequences, as a subproduct of amplification that provide a non real sequence
	Taxa assignation	Identification with species or taxonomic group with known identity and possible defined ecological traits	Amplifications are compared with the positive control, the DNA from the known target organisms; additionally, postsequencing analysis can be performed and comparison with reference database	Comparison with reference database (i.e., GenBank, IBOL, EMBL, DDBJ or customized for specific studies)
	Repeatability, reproducibility, and accuracy	Measurement of the intra-assay variance, inter-assay variance and difference between experimental measurement and actual values, respectively	Critical to compare measurements from a run to another	Desirable, although costly