Transcriptome is a project that people love and hate. The experimental threshold is low, but it is the hardest hit area for the proliferation of articles. People always ask me, can the transcription group still publish articles now? Let me take an article published in BMC Genomics on May 4th, 2020 as an example. The topic is: Transcriptome ome analysis returns to the responsibility of rapid defense where phytotoxic wheat aphids feed, and discusses in detail how difficult it is to send transcriptome articles in 2020. How to send? Let's take a look at the specific content of this article: experimental introduction: This paper studies the rapid defense response of wheat seedlings after being eaten by wheat aphids. After feeding for 2, 6, 12, 24 and 48 h, the leaves of seedlings (three replicates) were taken for transcriptome sequencing, chlorophyll determination, H2O2 accumulation determination and NADPH inhibitor treatment to further explore the defense mechanism of oxygen production after wheat bite. Experimental results:

1.？ The transcriptome analysis results of this part of wheat aphids after feeding show a comparative routine, mainly through PCA analysis to see the sample correlation and processing effect, and introduce the overall situation of differential genes. As shown in the figure below:

2. Differential Gene GO Analysis The author annotated GO according to the up-regulated and down-regulated gene sets, and discussed the enrichment of up-regulated and down-regulated gene sets according to the time points, as shown in the following figure:

3.？ Changes of chlorophyll content in wheat leaves after feeding by Aphis graminis from the analysis of differential genes GO, it can be seen that feeding by Aphis graminis has a negative regulatory effect on the photosynthesis process, light capture and photosynthetic system-related genes of wheat, so the author measured the changes of chlorophyll content in wheat leaves after feeding, as shown in the following figure:

4.？ Gene expression of salicylic acid and jasmonic acid related defense pathway in wheat leaves after feeding by wheat aphid: phenylalanine ammonia-lyase (PAL) gene involved in SA biosynthesis was significantly up-regulated at different time points, but the expression level gradually decreased with the increase of feeding time; Three lipoxygenase (LOX) genes in jasmonic acid metabolic pathway were significantly up-regulated. The WRKY transcription factor regulated by MAPKs also showed up-regulation, as shown in the following figure:

5.？ Changes of hydrogen peroxide accumulation and antioxidant enzyme activity in wheat leaves after aphid feeding: Aphid feeding significantly increased the expression of active oxygen scavenging genes; In addition, wheat leaves were stained with 3,3'-diaminobenzidine (DAB), and H2O2 accumulated 2 hours after feeding, and the number and size of spots gradually increased with the extension of feeding time, as shown in the following figure:

6. Effects of inhibiting NADPH oxidase on H2O2 accumulation and defense response in wheat leaves. DPI is a NADPH oxidase inhibitor, which can not only significantly inhibit oxygen production caused by food intake, but also significantly down-regulate the expression level of defense response genes in wheat leaves.

The above is all the achievements of this paper. Looking back, the experimental design is not complicated and the content is not too much. Why can others publish it but you are rejected? We should know that the influence factor of BMC Genomics in both fields is 3.5 points, which is also the existence that many people yearn for but can't get.

How difficult will it be to send transcriptome articles in 2020? From this article, we can see that the article is not as difficult as you think. I try to extract the following points from it, hoping to learn from you.

1. The experimental design is relatively reasonable, and the levels are progressive. The sampling points basically correspond to the three-level cascade reaction of plant defense, and the subsequent analysis and discussion levels are clear.

2. Transcriptome is only a part of the experiment, and the era of listing the results in the conventional way is over. Just like in this paper, in addition to transcriptome, the author further measured physiological indicators, such as chlorophyll content, oxygen production and gene-related traits, to make the results more convincing.

3. The introduction of transcriptome data should not be vague, and some related genes should be extracted and displayed in combination with other physiological and biochemical indicators, such as the genes related to light capture, light and movement with down-regulated chlorophyll content in this paper; Changes of H2O2 accumulation and antioxidant enzyme activity.

4. The essence of the paper is in the discussion part. You can cite other people's data to prove your results, which can be widely cited. Papers generally don't go wrong! To read the original text intensively, please click "Read the original text" at the end of the text.

How difficult will it be to send transcriptome articles in 2020? In fact, the hard part is that you refuse to change your mind. Times are different, and the old routine is out of date. The problem that many teachers are facing now is not that they don't have data in their hands, nor that they can't write papers, but that they can't understand the data and have no way to analyze it. How can they send articles without breaking this stalk? ! I recommend a video tutorial "Interpretation of Transcriptome Analysis Results" to you, which can easily solve the problem that you can't understand the data of Transcriptome Results.

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More skills learning links:

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More bioinformatics courses:

1. Articles are getting harder and harder to send? Because you didn't find new ideas. Sending 2-4 articles on gene family analysis is simple and quick. Learning link: practical course of gene family analysis and interpretation of gene family literature thought.

2. Don't know much about the transcriptome data? Can't read the chart? Click on the link to learn to deeply interpret the data result file, and learn the link: interpret the transcription group (with reference) results; Interpretation of Transcriptome (No Reference) Results

3. Transcriptome data mining skills -WGCNA, improve the grade of your article, learn link: WGCNA- weighted gene * * * expression network analysis

4. How to mine transcriptome data? Learning link: data mining and transcriptome literature interpretation after transcriptome standard analysis

5. Microbe 16S/ITS/ 18S analysis principle and result interpretation, OTU network diagram, cell diagram and network diagram course.

6. Introduction to biological information to mastery of compulsory basic courses, learning links: linux system use, perl introduction to mastery, perl language advanced, R language drawing.

7. Medical-related data mining courses can publish articles without experiments. Learning links: TCGA- differential gene analysis, GEO chip data mining, GSEA enrichment analysis course, TCGA clinical data survival analysis, TCGA- transcription factor analysis, TCGA-ceRNA regulatory network analysis.

8. Links to other courses: independent analysis of second-generation sequencing transcriptome data, uploading of NCBI data, and interpretation of second-generation sequencing data.