“…Nevertheless, this approach is not without limitations. Factors such as the expensive nature of RNA-seq, coupled with constraints in conducting a limited number of experiments and repetitions per research project, hinder comprehensive data collection due to imposed restrictions [ 10 ]. Fig.…”
“…Nevertheless, this approach is not without limitations. Factors such as the expensive nature of RNA-seq, coupled with constraints in conducting a limited number of experiments and repetitions per research project, hinder comprehensive data collection due to imposed restrictions [ 10 ]. Fig.…”
“…In 1974, Brenner chose to use Caenorhabditis elegans as a model organism to study development and neuroscience [ 3 ]. Now it is an important model organism in research fields such as aging and development [ 4 , 5 , 6 ].…”
BACKGROUND: Caenorhabditis elegans is a widely used model animal. Chemotaxis assay is one of the experiments that study the effects of different chemicals on nematodes. It is mainly used to study the effects of different chemicals on the perception behavior of nematodes. By conducting this experiment, not only can the neurotoxicity of chemicals be reflected, but also the impact of chemicals on physiological functions regulated by the nervous system, such as nematode feeding behavior and basic motor ability. OBJECTIVE: The experiment of detecting the response of nematode to chemicals is also a common method of chemical toxicity testing based on nematode models. In the analysis of worm tendency behavior, manual operations are generally used. Manually processing a large number of worms under a microscope is very time-consuming and labor-intensive. The current quantitative methods for nematode chemotaxis experiments are not only time-consuming and labor-intensive, but also biased in experimental results due to differences in judgment standards among experimenters. The automatic and efficient quantification method for nematode chemotaxis experiments is a very important technical difficulty in the field of nematode experiments. METHODS: Here, we have designed an automatic quantification method for nematode chemotaxis experiments by incorporating image acquisition and processing techniques into the nematode experiment. RESULTS: The experimental results show that the Pearson correlation coefficient between manual and automatic counting results is 0.978. CONCLUSION: This proves the effectiveness of our method. Applying the automatic measurement method to replace manual counting by the experimenter can improve work efficiency, and reduce errors in human counting operations.
“…The rapid increase in the number of experiments on whole-genome profiling of gene expression under different conditions and the availability of their results in functional genomics databases such as Gene Expression Omnibus (GEO) (Clough, Barrett, 2016) or BioStudies (Sarkans et al, 2021) open a wide space for comparative analysis of experimental results from different studies aimed at generalizing them across studies using meta-analysis (Cahan et al, 2007;Rung, Brazma, 2013;Keel, Lindholm-Perry, 2022). Such an approach allows not only to extract the most robust differentially expressed genes (DEGs) (Freire-Rios et al, 2020), but also to increase sample size to identify weak patterns (Bairakdar et al, 2023) or to test hypotheses that could not be investigated in individual studies (Sudmant et al, 2015;Winter et al, 2019).…”
Meta-analysis of transcriptomic data from different experiments has become increasingly prevalent due to a significantly increasing number of genome-wide experiments investigating gene expression changes under various conditions. Such data integration provides greater accuracy in identifying candidate genes and allows testing new hypotheses, which could not be validated in individual studies. To increase the relevance of experiment integration, it is necessary to optimize the selection of experiments. In this paper, we propose a set of quantitative indicators for a comprehensive comparative description of transcriptomic data. These indicators can be easily visualized and interpreted. They include the number of differentially expressed genes (DEGs), the proportion of experiment-specific (unique) DEGs in each data set, the pairwise similarity of experiments in DEG composition and the homogeneity of DEG profiles. For automatic calculation and visualization of these indicators, we have developed the program InterTransViewer. We have used InterTransViewer to comparatively describe 23 auxin- and 16 ethylene- or 1-aminocyclopropane-1-carboxylic acid (ACC)-induced transcriptomes in Arabidopsis thaliana L. We have demonstrated that analysis of the characteristics of individual DEG profiles and their pairwise comparisons based on DEG composition allow the user to rank experiments in the context of each other, assess the tendency towards their integration or segregation, and generate hypotheses about the influence of non-target factors on the transcriptional response. As a result, InterTransViewer identifies potentially homogeneous groups of experiments. Subsequent estimation of the profile homogeneity within these groups using resampling and setting a significance threshold helps to decide whether these data are appropriate for meta-analysis. Overall, InterTransViewer makes it possible to efficiently select experiments for meta-analysis depending on its task and methods.
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