Epigenomics


1.CHIPSeq

2.Bisulfite Seq

3.ATACSeq

1. CHIPSeq

In this experiment, using CHIPSeq, we mapped the KU70,
NCL binding sites in the genome of human monocytes.

Analysis

1. Pipeline
2. Methods view or download
3. Results Download SICER and MACS data

CHIPSeq results are incorporated in UCSC Browser

MACS/SICER output mapping file was incorporaed into UCSC
browser to view the position of KU70 and NCL binding region.
In the user supplied track (red arrow), the veriticle lines
indicate the binding site in ITGAM gene (here it is shown).
However, these verticle lines is npresent in all over the genome
where these proteins bind in the monocytes.











KU70/NCL mapping in SNP rs1143679 in ITGAM

Here the previous picture is shown in 'ZOOM IN'
to see the exact boundaries of bindings of these
proteins at nucleotides level.The boundaries
are so precise, it can exactly show to detrmine
whether an SNP is bound or not.Here We wished to see
whether a SNP, rs1143679 of ITGAM in bound with NCL
and KU70, because we identified these 2 proteins binds
with this SNP carrying nucleotides using EMSA followed
by MAss spectrometric sequencing.







Generation of Global Genomic Map of KU70/NCL binding region

In this way, We generated global maps for binding
KU70, NCL and EBF1 in the genome of human monocytes.



2. BisulfiteSeq

In this experiment, we performed the bisulfite
DNA sequencing using monocyte DNA from normal, moderate
and severely affected lupus patients. After analyzing the bisulfite
DNA sequence using BISSNP, we incorporated the methyl
Cytosine modified mapping file in a methyl DNA mapping browser.
CG island.

Analysis

1. Pipeline
2. Methods

3. Results

Methylated DNA map in UCSC Browser

Here we show the region of ITGAM gene and compare the
result of two neighbouring CG island.One of them is
showing sequencial methylation at C as it goes
moderate to severe.





Conclusion

Using bisulfite DNA sequencing, it is possible to identify the extent of methylation at the cytosine residue in different stages (e.g. moderate, severe etc) of a disease processes



3. ATACSeq

In this experiment, we did ATAC Seq with lupus and
normal monocytes to see the differences in open chromatin
and correlate with RNAseq results. We also did the experiments with
lupus monocytes with an edited SNP in ITGAM gene. Here we
show some of the rsults.

Analysis

1. Pipeline
2. Methods view or download
3. Results

ATACSeq correlated with RNASeq

A heatmap of ATAC Seq and RNASeq are shown here. The
correlation is evident from the result as genes with open
chromatin are more expressed










TSS start sites are correlated with ATAC Seq open chromatin

These analysis shows the relation between open chromatin
and transcription start sites in normal, lupus monocytes
and SNP edited lupus monocytes. Open chromatin position
in ATAC seq are correlated or populated in the TSS of the
expressed genes.











The difference in number of TSS with open chromatin in normal and lupus

A gene ontogeny (GO) is shown for open chromatin region(a).
Also, here the number of TSS with open chromatin changes in lupus.
b)Normal d)Lupus













ATACseq and RNAseq view for individual genes in normal and upus patients

The profile view of ATACSeq and RNAseq of some of the
interesting genes are shown. The expression of these genes
are considerably corelated with open chromatin of ATACSeq

Conclusion

Here ATACSeq is well correlated with the expression profile
of RNASeq. ATACSeq is a useful tool for strenghthening
RNAseq results and it gives a global view of open chromatin
changes status in a disease processes