1. What Information is Available in the KnockTF2.0?
Transcription factors (TFs), transcription co-factors (TcoFs) and their target genes have essential functions in diseases and biological processes. Recent advances in the area of high-throughput techniques have led to the rapid accumulation of gene expression profile data before/after T(co)F knockdown/knockout in multiple species. Here, we develop KnockTF 2.0 (http://www.licpathway.net/KnockTF/index.html), which aims to provide comprehensive T(co)F knockdown/knockout dataset resource across multiple tissue/cell types of different species and extend genetic and epigenetic annotations from multiple perspectives.
2. What Datasets are Included in the KnockTF2.0?
The current version of KnockTF stores 1468 manually curated RNA-seq and microarray datasets associated with 613 TFs and 172 TcoFs disrupted by different knockdown/knockout techniques and across multiple tissue/cell types in humans, mice, Arabidopsis thaliana and Zea mays. Specifically, KnockTF 2.0 contained 344 T(co)F knockdown/knockout datasets in mice, 37 datasets in Arabidopsis thaliana and 1 dataset in Zea mays, and also extended 1086 T(co)F knockdown/knockout datasets in humans.
For more detailed statistics, please see the “Statistics” page.
3. Database Content and Construction
KnockTF 2.0 not only provides comprehensive gene expression information for T(co)F target genes of interest, but also collects upstream pathway information for T(co)Fs and various functional annotation information for downstream target genes, such as GO/KEGG pathway enrichment, hierarchical clustering analysis and differentially expressed analysis. Furthermore, KnockTF 2.0 collects the detailed and abundant (epi)genetic annotation information for T(co)F target genes, including super-enhancers, enhancers, transcription factor binding sites (TFBSs), common SNPs, risk SNPs, LD SNPs, expression quantitative trait locus (eQTL), methylation sites, DNase I hypersensitivity sites (DHSs), chromatin interactions, chromatin accessibility regions, CRISPR/Cas9 target sites, and topologically associating domains (TADs).
KnockTF 2.0 provides a conveniently, user-friendly interface for querying, browsing, analyzing and downloading detailed information about gene expression profiles of T(co)F knockdown/knockout datasets.
4.How to Use the KnockTF2.0?

The “Browse” page is organized as an interactive table for quickly searching for T(co)F knockdown/knockout datasets and customizing filters using “Species”, “Molecular Type”, “Data Source”, “Biosample Type”, “Tissue Type”, “TF Superclass” and “TF”. Users can click the “Show entries” in a dropdown menu to change the number of records displayed per page. To view details of a given T(co)F knockdown/knockout dataset, users can click on “Dataset ID”. Users can download the entire browse table by clicking on the download button.

4.3.1 Subnetwork Analysis

KnockTF 2.0 constructed a T(co)F-differentially expressed gene (DEG) network by combining all T(co)F-DEG pairs (FC≥3/2 & FC≤2/3) of the T(co)F knockdown/knockout datasets. Users can submit a gene list to locate a transcriptional regulatory subnetwork. The subnetwork consists of submitted genes and their one-step neighbors within T(co)F-DEG network. T(co)F-target gene relationships supported by the ChIP-seq data have bold edges in the subnetwork. Users can choose subnetwork size displays by filtering the number of the most important T(co)F-DEG pairs. KnockTF 2.0 also provides topological features of subnetwork genes including degree, betweenness and closeness.

4.3.2 T(co)F Enrichment

Users can submit a gene list and set (FDR-adjusted) P-value for T(co)F enrichment. KnockTF 2.0 maps submitted genes to the T(co)F-DEG network and performs hypergeometric test between submitted genes and all DEGs regulated by each T(co)F. The T(co)Fs under the threshold of (FDR-adjusted) P-value user sets are considered the most important T(co)Fs that significantly regulate the submitted genes.

4.3.3 T(co)F Enrichment(GSEA)

KnockTF 2.0 embedded the popular gene set enrichment analysis (GSEA) algorithm to perform the enrichment analysis of T(co)F target genes. Based on the T(co)F-target gene pairs identified from T(co)F knockdown/knockout profiles and T(co)F ChIP-seq/motif data as the background gene sets, users can input the differential gene rank list and select relevant parameters (including gene set size, permutation times, P-value/adjust P-value cutoffs and species) to perform T(co)F enrichment analysis, visualize and download analysis results.

4.3.4 Pathway downstream analysis

KnockTF 2.0 manually collected 2,881 pathways from 10 pathway databases, and innovatively reconstructed traditional signaling pathways by integrating T(co)F-target gene relationships from T(co)F knockdown/knockout datasets. Users enter a list of genes of interest and select relevant parameters, KnockTF 2.0 can map them into the reconstructed signaling pathway map model. Hypergeometric test is used for calculating the statistical significance of the intersection between the input gene nodes and the T(co)Fs in the terminal of each pathway. Then, KnockTF 2.0 will identify the significant pathways, label the terminal downstream T(co)Fs of pathways, and obtain the regulatory axes of the genes of interest, including pathway genes, T(co)Fs and their downstream target genes.

Gene expression profile of each dataset from human, mouse, arabidopsis thaliana and zea mays can be downloaded in the “Download” page. Users can also obtain differential expression information of genes, the promoter/super-enhancer/typical enhancer regions and the corresponding (epi)genetic annotation information of target genes. In addition, KnockTF 2.0 supports export of query results for each search result page.

The datasets are respectively classified by different knock-methods and tissue types in the “Statistics” page. The number of DEGs in each T(co)F knockdown/knockout dataset is also provided.
5. Frequently Asked Questions

5.1 Why are showing no results available somewhere?

Reply: Because there is no corresponding function annotation or no significant annotation results for this TF/T(co)F/gene.

5.2 Why the same T(co)F disrupted by the same knockdown/knockout technique appears in different datasets?

Reply: Because these datasets may be from different species, different profiles, different platforms or different biosamples. In KnockTF 2.0, there are two data sources. If data source is GEO/SRA, six conditions are used to uniquely determine a dataset, including species, TF/TcoF, knockdown/knockout technique, biosample name, series (GSE) and platform (GPL); if data source is ENCODE, four conditions are used to uniquely determine a dataset, including TF, knockdown/knockout technique, biosample name and experiment accession.

5.3 Which kinds of species are stored in the database?

Reply: The current version of KnockTF stores T(co)F knockdown/knockout datasets in mouse, arabidopsis thaliana and zea mays, and also expanded the scale of T(co)F knockdown/knockout datasets in human.

5.4 Why might web pages load slowly?

Reply: KnockTF 2.0 has advanced storage technology and sufficient bandwidth to meet the needs of most users for the speed of web page loading. However, it is not excluded that few users have poor user experience due to network reasons.
6.Development Environment
The current version of KnockTF was developed using MySQL 5.7.17 (http://www.mysql.com) and runs on a Linux-based Apache Web server (http://www.apache.org). We used PHP 7.0 (http://www.php.net) for server-side scripting. We designed and built the interactive interface using Bootstrap v3.3.7 (https://v3.bootcss.com) and JQuery v2.1.1 (http://jquery. com). We used ECharts (http://echarts.baidu.com) and D3 (https://d3js.org) as a graphical visualization framework, and JBrowse (http://jbrowse.org) is the genome browser framework. We recommend using a modern web browser that supports the HTML5 standard such as Firefox, Google Chrome, Safari, Opera or IE 9.0+ for the best display.
The KnockTF 2.0 database is freely available to the research community using the web link (https://bio.liclab.net/KnockTF/index.php). Users are not required to register or login to access features in the database.