02308nas a2200169 4500008004100000245013500041210006900176260001200245300001200257490000800269520169800277100002501975700002102000700002302021700001802044856007602062 2018 eng d00aIdentification of transcription factors from NF-Y, NAC, and SPL families responding to osmotic stress in multiple tomato varieties0 aIdentification of transcription factors from NFY NAC and SPL fam c09/2018 a441-4500 v2743 a

Identifying osmotic stress-responsive transcription factors (TFs) can facilitate discovery of master regulators mediating salt and/or drought tolerance. To date, few RNA-seq datasets for high resolution time course of salt or drought stress treatments are publicly available for certain crop species. However, such datasets may be available for other crops, and in combination with orthology analysis may be used to infer candidate osmotic stress regulators across distantly related species. Here, we demonstrate the utility of this approach for identification and validation of osmotic stress-responsive transcription factors in tomato. First, we developed physiologically calibrated salt and dehydration-responsive systems for tomato cultivars using real time measurements of transpiration rate and photosynthetic efficiency. Next, we identified differentially expressed TFs in rice using raw RNA-seq datasets for a publicly available salt stress time course. Putative salt stress-responsive TFs in tomato were then inferred based on their orthology with the transcription factors upregulated by salt in rice. Finally, using our osmotic stress system, we experimentally validated stress-responsive expression of predicted tomato candidates representing NUCLEAR FACTOR Y, SQUAMOSA PROMOTER BINDING, and NAC domain TF families. Quantification of transcript copy numbers confirmed that mRNAs encoding all three TFs were strongly upregulated not only by salt but also by drought stress. Induction by both salt and dehydration occurred in a temporal manner across diverse tomato cultivars, suggesting that the identified TFs may play important roles in regulating osmotic stress responses.

1 aFilichkin, Sergei, A1 aAnsariola, Mitra1 aFraser, Valerie, N1 aMegraw, Molly uhttps://www.sciencedirect.com/science/article/abs/pii/S016894521830353401946nas a2200157 4500008004100000245007200041210006900113260001200182300001400194490000700208520144400215100002101659700001801680700002001698856007001718 2018 eng d00aIndeCut evaluates performance of network motif discovery algorithms0 aIndeCut evaluates performance of network motif discovery algorit c05/2018 a1514-15210 v343 a
Motivation
Genomic networks represent a complex map of molecular interactions which are descriptive of the biological processes occurring in living cells. Identifying the small over-represented circuitry patterns in these networks helps generate hypotheses about the functional basis of such complex processes. Network motif discovery is a systematic way of achieving this goal. However, a reliable network motif discovery outcome requires generating random background networks which are the result of a uniform and independent graph sampling method. To date, there has been no method to numerically evaluate whether any network motif discovery algorithm performs as intended on realistically sized datasets—thus it was not possible to assess the validity of resulting network motifs.
 
Results
In this work, we present IndeCut, the first method to date that characterizes network motif finding algorithm performance in terms of uniform sampling on realistically sized networks. We demonstrate that it is critical to use IndeCut prior to running any network motif finder for two reasons. First, IndeCut indicates the number of samples needed for a tool to produce an outcome that is both reproducible and accurate. Second, IndeCut allows users to choose the tool that generates samples in the most independent fashion for their network of interest among many available options.
1 aAnsariola, Mitra1 aMegraw, Molly1 aKoslicki, David uhttps://academic.oup.com/bioinformatics/article/34/9/1514/4721785