2021-05-10-tadaA-report

ASD

新功能注释的effect size

X:不显著,显著

  • spidex中去除nonsynonymous, protein-truncating 的部分,X
  • RBP-Var中likely to affect RBP-binding 的变异位点,
  • RBP的每个子类的结合区域,hnRNPL
  • RNA modifications, including m6a, m1a, m5c, and m7g, etc.,
  • miRNA, X
  • radar rbp variants with high scores, X

functional analysis

gene level

SNV model: 80个风险基因,其中8个基因没有任何DNM,因此将其去除

indel model: 在SNV的基础上,新找出17个新基因,其功能富集结果如下:

gNkvAx.png

SNV + INDEL model: 27 novel genes (not in the list of 102 genes)

GO

gNAU8U.png

DisGeNET (gene-disease association)

gNEQJK.png

下一步计划: 着重以下类别,进一步分析novel genes的致病机制。

gene traits

1) Neurodevelopmental Disorders; 2) Specific learning disability; 3) Cognition Disorders

4) Developmental Disabilities; 5) Forgetful; 6) Memory impairment

molecular

1) RNA-splicing; 2) cell morphogenesis involved in neuron differentiation

mutation level

着重transcriptional or post-transcriptional regulatory variants

问题

当一个变异有多重注释,如何确定是哪种起作用,如何确认哪种途径的影响大?

CHD

effect size of all annotations

  • fix pi as 0.05

有显著effect size的功能注释:

In [3]:
readRDS("/storage11_7T/fuy/TADA-A/CHD/sig_0510_all_annota_rr.rds")
A data.frame: 16 × 5
rr.lstupper.lstlower.lstidxannota
<dbl><dbl><dbl><int><chr>
31.6876062.192012 1.18320074 3ccrs.allchrom.gt90
51.8148822.339178 1.29058489 5RADAR_RBP_top5%
62.1946272.734925 1.65432873 61_2_ct.dbSNP.RBP-Var
102.4305483.074458 1.7866371410deepsea_89_joint
111.7387953.155253 0.3223377611deepsea_10-12_joint
121.8132932.139593 1.4869917112mpc12
132.0586412.554155 1.5631268313mpc2
142.3076272.803729 1.8115246514PPI.PPH2_D.HVAR
152.0351332.225165 1.8450998515primateAI_MVP_joint
162.0307932.296126 1.7654596416spidex
172.9440044.195226 1.6927819417DS_AG
182.4721563.889113 1.0551986118DS_DG
202.1563314.376120-0.0634571420DS_DL
212.2837682.944003 1.6235342521ptv.0-05
223.0396573.769662 2.3096524622ptv.05-995
233.7017284.160876 3.2425800123ptv.995

SNV model: identified 20 risk genes, of which 8 are novel genes

for these novel genes:

GO

gNn98P.png

DisGeNET (gene-disease association)

gNnkDg.png

下一步计划:

1) 确认known CHD risk genes的范畴,目前不同文章里面使用的不统一

2) novel genes和known CHD risk genes一起做PPI

3) 结合以上GO,DisGeNET富集的类别,找出novel genes作用的通路

4) 针对所有找出的risk CHD genes,试图从transcriptional or post-trans regulatory角度解析DNM的致病机制。