RNA integrity. A small marker height is desired, indicating only small amounts of RNA have been degraded and proceeded to the smallest lengths, indicated by the short marker. If a large number is found here, that indicates that large amounts of the rRNAs have been degraded to small pieces that would be found closer to this marker. This situation can be seen in the 'poor quality' RNA electropherogram found in figure 2, where the height of the peak over the marker (far left) is very large, so the RNA has been greatly degraded. In prokaryotic samples, the algorithm is somewhat different, but the Agilent 2100 Bioanalyzer Expert software is able to calculate RIN for prokaryotic samples now as well. The difference likely arises from the fact that, while mammalian samples have 28S and 18S ribosomal RNAs as their predominant species, prokaryotic RNAs have the sizes shifted slightly smaller, to 23S and 16S, so the algorithm must be shifted to accommodate that. Another crucial fact about calculating prokaryotic RNA integrity numbers is that RIN has not been validated to the extent that it has for eukaryotic RNA. It has been shown that higher RIN values correlate with better downstream results in eukaryotes, but this hasn't been done as extensively for prokaryotes, so it may mean less in prokaryotes. These electropherograms for calculating RIN are done using the Agilent Bioanalyzer machine, which is capable of performing electrophoresis and generating the electropherograms. The Agilent 2100 software is uniquely able to perform the RIN software, as the exact algorithm is proprietary, so there are additional important RNA electropherogram features that are used in its calculation that are not publicly available. References External links RIN information from Agilent Technologies RIN article in BMC Molecular Biology Gene expression summary from Nature to help show why we need RIN RIN explanation from Agilent Technologies, with several examples of electropherograms at various RIN values Gel electrophoresis simulation from the University of Utah to help visualize how the electropherograms are produced Bioinformatics Bioinformatics software Gene expression Molecular biology RNA