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Interestingly, at later stages of seed development (i.e. 14 and 28 DAA), these probe sets did not show much difference in expression between good and poor quality varieties.
Using gene-specific two-way ANOVA analysis, 110 probe sets were identified for processing quality showing at least 10-fold differential expression between good and poor quality varieties.
In this study a high increase in differential expression of GBSS from early (about 7-fold at 7 DAA) to late maturity (about 93 fold at 28 DAA) was observed between good and poor quality varieties.
Genome-wide transcriptome analysis was done between good and poor quality varieties at three seed developmental stages (7, 14, and 28 DAA) to identify the candidate genes whose expressions changed due to quality, development, and interaction (quality x development).
Fold change analysis of the expression data of the 35,472 probe sets identified 236 probe sets, whose expressions were at least 10-fold between good and poor quality varieties in at least one of the three sources of variations [quality, development, and interaction (quality x development)] (Table 2).
Total 219 probe sets were identified for seed development whose expression changed at least ten-fold between good and poor quality varieties in at least one of the three condition pairs ('Good-7 DAA' vs 'Poor-7 DAA', 'Good-14 DAA' vs 'Poor-14 Dand, and 'Good-28 DAA' vs 'Poor-28 DAA') (Table 2, see Additional file 3, Figures 1 and 2B).
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The differential expression of the two candidate genes, pre-α/β-gliadin and γ-gliadin between good and poor chapatti quality varieties was validated by quantitative real time PCR.
Furthermore rural residents are more likely to believe they had restricted access to food resources, higher food costs, and poor quality and variety [ 53, 72].
Most of the SNPs found by comparing ESTs to cpDNA sequences will be based on the use of different varieties, or on poor quality sequencing data.
The cause for the poor quality of groundwater is attributable to variety of reasons including interaction between water, soluble minerals, salts, and anthropogenic pollution (Codling et al. 2014; Subba Rao et al. 2016).
Poor quality, variability in methodology, inconsistency of results, and a variety of proxies for prostate cancer progression make firm conclusions hard to draw.
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