Data workflow

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ChIP-Seq pipeline

   Reads from ChIP-Seq libraries were aligned to the assembly using bwa(Li and Durbin, 2009) mem algorithm. Mapped reads with a MAPQ quality score below 30 and PCR duplicates were filtered using SAMTools(Li et al., 2009) to ensure high-quality aligned data. For analysis of H3K4me3, H3K27ac, and RNAPII libraries, narrow-peak calling settings were used in MACS2 (2.1.0)(Zhang et al., 2008) : macs2 callpeak -t input file -c control file -f BAM -n output peak file -B -g 3.6e+8. For analysis of H3K9me2, H3K4me1, and H3K27me3 libraries, broad-peak mode was used in MACS2 with FDR < 0.1. RSC was set to > 0.8, and NSC was set to > 1.05 to assess the quality of each ChIP-Seq dataset; FRiP was used to assess the peak quality in the dataset

ATAC-Seq FAIRE-Seq MNase-Seq pipeline

  For FAIRE-Seq ATAC-Seq MNase-Seq data, two independent libraries were created for each tissue or species . The alignment process was similar to that for ChIP-Seq. Peaks were identified using MACS2 with the following settings: macs2 callpeak -t input file --nomodel --shift -100 --extsize 200 -f BAM -n output peak file -B -q 0.05 -g 3.6e+8.

RNA-Seq pipeline

   Sequence quality of RNA-Seq libraries was evaluated using FastQC, and the adapter sequences and low-quality reads were filtered using Trimmomatic(Bolger et al., 2014). The cleaned reads were mapped to the reference genome using TopHat2(Kim et al., 2013), and gene expression was quantified using Cufflinks (Trapnell et al., 2012).

BS-Seq pipeline

   The sequence quality of the whole-genome bisulfite sequencing (WGBS) libraries was evaluated using FastQC, and the adapter sequences and low-quality reads were filtered using Trimmomatic. The cleaned reads were then mapped to the reference genome using BatMeth2(Zhou et al., 2019). The uniquely mapped reads were used for further analysis. Individual cytosines with coverage of at least 3 were considered for methylation-level calling.

ChIA-PET pipeline

   ChIA-PET data were processed with updated ChIA-PET Tool(V3)(Li et al., 2019) software, a JAVA-based package for automatic processing of ChIA-PET sequence data, including linker filtering, read mapping, redundancy removal, protein-binding sites, and chromatin interaction identification.

Hi-C pipeline

    Hi-C paired-end reads were aligned to genomes using the HiC-Pro(Servant et al., 2015) pipeline. Default settings were used to remove duplicate reads, assign reads to MboI restriction fragments, filter for valid interactions, and generate binned interaction matrices.

References

Li, H., and Durbin, R. (2009). Fast and accurate short read alignment with Burrows–Wheeler transform. bioinformatics 25:1754-1760.

Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., and Durbin, R. (2009). The sequence alignment/map format and SAMtools. Bioinformatics 25:2078-2079

Zhang, Y., Liu, T., Meyer, C.A., Eeckhoute, J., Johnson, D.S., Bernstein, B.E., Nusbaum, C., Myers, R.M., Brown, M., Li, W., et al. (2008). Model-based Analysis of ChIP-Seq (MACS). Genome Biology 9:R137.

Bolger, A.M., Lohse, M., and Usadel, B. (2014). Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114-2120.

Kim, D., Pertea, G., Trapnell, C., Pimentel, H., Kelley, R., and Salzberg, S.L. (2013). TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biology 14:R36.

Trapnell, C., Roberts, A., Goff, L., Pertea, G., Kim, D., Kelley, D.R., Pimentel, H., Salzberg, S.L., Rinn, J.L., and Pachter, L. (2012). Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nature protocols 7:562-578.

Zhou, Q., Lim, J.-Q., Sung, W.-K., and Li, G. (2019). An integrated package for bisulfite DNA methylation data analysis with Indel-sensitive mapping. BMC bioinformatics 20:1-11.

Li, G., Sun, T., Chang, H., Cai, L., Hong, P., and Zhou, Q. (2019b). Chromatin Interaction Analysis with Updated ChIA-PET Tool (V3). Genes 10:554.

Servant, N., Varoquaux, N., Lajoie, B.R., Viara, E., Chen, C.-J., Vert, J.-P., Heard, E., Dekker, J., and Barillot, E. (2015). HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome biology 16:259.