Pathway Mendelian randomization of nucleolar biology (NUC), DNA damage & repair (DDR), & termination-of-adult-lifespan (TAL) expression (in eqtlGen) on four measures of longevity (parental lifespan, healthspan, longevity into the 90th (vs 60th) percentile, & longevity into the 99th (vs 60th) percentile
venn
2021-05-23
Abstract
Venn diagram of overlap between FDR significant findings for nucleolar pathway genes on four measures of longevity.
Contents
- 0.1 Results
- 0.2 Venn diagram of FDR-significant overlap (1 gene): EXOSC6
- 0.3 Venn for NUC P<0.05
- 0.4 Venn for DNA damage and repair (DDR): FDR
- 0.5 Venn for DNA damage and repair (DDR): P<0.05
- 0.6 Venn for termination-of-adult-lifespan (TAL): P<0.05
- 0.7 Overlap between NUC, DDR, and TAL pathway sets?
0.1 Results
No FDR-significant findings for either measure of extreme longevity (longevity into the 90th or 99th percentiles).
50 associations in 6 genes were FDR-significant for the NUC pathway on lifespan
EIF2A EXOSC6 MRPL18 NOM1 NOP14 NSUN5P1
5 27 1 1 11 5 - 214 associations in 12 genes were FDR-significant for the NUC pathway on healthspan
DIEXF EIF6 EXOSC6 MRPL2 MRPL21 MRPS21 MRPS25 NCK1 RPL13 SURF6
3 15 26 8 1 35 1 3 106 4
UBA52 ZNF354A
6 6
0.2 Venn diagram of FDR-significant overlap (1 gene): EXOSC6
setwd("/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100")
bon_life=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/bon_nucs/results/nucs_res.csv')
# UBA52_nuc=bon_life[which(bon_life$exposure=="UBA52"),]
# UBA52_nuc
bon_life_sig_fdr=bon_life[which(bon_life$fdr<0.05),]
dim(bon_life_sig_fdr)## [1] 50 12bon_life_sigp=bon_life[which(bon_life$p<0.05),]
dim(bon_life_sigp)## [1] 10794 12# UBA52_nuc=bon_life_sig[which(bon_life_sig$exposure=="UBA52"),]
# UBA52_nuc
bon_health=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/healthspan/nucs/results/healthspan_nucs_res.csv')
bon_health_sig_fdr=bon_health[which(bon_health$fdr<0.05),]
dim(bon_health_sig_fdr)## [1] 214 12bon_health_sigp=bon_health[which(bon_health$p<0.05),]
dim(bon_health_sigp)## [1] 10925 12bon_90=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/longevity90/nucs/results/longevity90_nucs_res.csv')
bon_90_sig_fdr=bon_90[which(bon_90$fdr<0.05),]
dim(bon_90_sig_fdr)## [1] 0 12bon_90_sigp=bon_90[which(bon_90$p<0.05),]
dim(bon_90_sigp)## [1] 5685 12bon_99=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/longevity99/nucs/results/longevity99_nucs_res.csv')
bon_99_sig_fdr=bon_99[which(bon_99$fdr<0.05),]
dim(bon_99_sig_fdr)## [1] 0 12bon_99_sigp=bon_99[which(bon_99$p<0.05),]
dim(bon_99_sigp)## [1] 5308 12table(bon_99_sigp$exposure)##
## AATF ABT1 APEX1 BYSL CKS2 CNOT6 DAP3 DDX18
## 5 1 7 1 5 30 247 1
## DDX21 DDX31 DDX52 DDX56 DIEXF DIS3 DRD4 EIF2A
## 44 3 1 2 22 1 3 2
## EIF2AK2 EIF2AK4 EIF2D EIF3K EIF4A3 EIF6 EMG1 ERCC2
## 228 6 1 1 2 183 15 28
## ERI1 ERI2 EXOSC1 EXOSC10 EXOSC6 EXOSC7 EXOSC8 EXOSC9
## 1 1 4 19 178 97 2 37
## FAM207A FBLL1 FTSJ3 GEMIN4 GLUL GNL2 GTF2H5 GTF3A
## 2 37 11 6 23 23 10 24
## GTPBP10 GTPBP4 HEATR3 HELB IGHMBP2 IMP3 IMP4 ISG20
## 51 13 5 2 151 1 85 7
## ISG20L2 KAT2B KRI1 LSG1 LYAR MAK16 METTL17 METTL5
## 16 34 3 25 1 3 23 4
## MPHOSPH6 MPV17L2 MRPL10 MRPL15 MRPL18 MRPL19 MRPL2 MRPL21
## 15 1 44 2 1 118 25 195
## MRPL24 MRPL32 MRPL34 MRPL35 MRPL36 MRPL37 MRPL39 MRPL4
## 16 61 24 1 28 1 203 12
## MRPL42 MRPL43 MRPL50 MRPL52 MRPL53 MRPL54 MRPL55 MRPS15
## 34 29 14 15 1 4 181 3
## MRPS16 MRPS17 MRPS21 MRPS25 MRPS26 MRPS34 MRPS35 MRPS6
## 18 48 9 31 2 7 1 18
## MRPS7 MRPS9 MTIF2 MTIF3 MTOR NCK1 NDUFA7 NIP7
## 9 36 5 20 20 168 14 33
## NLE1 NOB1 NOL6 NOL8 NOL9 NOP10 NOP14 NOP16
## 7 4 35 4 8 2 1 2
## NOP58 NPM3 NSA2 NSUN4 NSUN5P1 NSUN5P2 NUP88 NVL
## 1 2 14 115 4 24 78 4
## PELO PES1 PIH1D1 PNPT1 POLR1A POLR1B POP5 PPARGC1A
## 59 1 11 1 3 24 8 55
## PWP1 PWP2 RBFA RCL1 RNASEL RPF2 RPL10A RPL12
## 8 1 4 1 8 2 2 45
## RPL13 RPL13A RPL14 RPL17 RPL28 RPL3 RPL31 RPL36
## 21 114 10 11 8 10 3 1
## RPL37 RPL37A RPL8 RPL9 RPLP0 RPP40 RPS12 RPS14
## 1 1 6 124 25 12 11 1
## RPS15A RPS23 RPS24 RPS25 RPS26 RPS27L RPS5 RPS8
## 1 233 15 21 2 2 21 90
## RPS9 RPUSD3 RPUSD4 RRNAD1 RRP12 RRP15 RRP36 RRP7A
## 1 7 8 16 113 27 20 3
## RRP8 RSL24D1 SURF6 TEX10 TFB1M TFB2M THUMPD1 TRMT112
## 56 6 6 7 1 15 9 9
## TRMT61B UBA52 USP36 UTP14C UTP15 UTP18 UTP23 WDR18
## 11 6 16 14 1 1 2 10
## WDR43 WDR55 WRN XRCC5 XRN2 YBEY ZNF622 ZNHIT3
## 11 233 6 1 169 9 3 2
## ZNHIT6
## 22x_nuc_fdr <- list(
lifespan = bon_life_sig_fdr$id.exposure,
healthspan = bon_health_sig_fdr$id.exposure
)
ggVennDiagram(x_nuc_fdr)
ggsave("venn.png", units="in", width=6, height=4, dpi=300)
# exposures common to both measures of longevity
nuc_life_health_fdr=Reduce(intersect, list(bon_life_sig_fdr$id.exposure, bon_health_sig_fdr$id.exposure))
nuc_life_health_fdr## [1] "EXOSC6"# All fdr significant exposures
#x_nuc_fdr[1:2]0.3 Venn for NUC P<0.05
105 genes overlapped between the four measures of longevity.
setwd("/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100")
bon_life=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/bon_nucs/results/nucs_res.csv')
bon_life_sig=bon_life[which(bon_life$p<0.05),]
dim(bon_life_sig)## [1] 10794 12bon_health=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/healthspan/nucs/results/healthspan_nucs_res.csv')
bon_health_sig=bon_health[which(bon_health$p<0.05),]
dim(bon_health_sig)## [1] 10925 12bon_90=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/longevity90/nucs/results/longevity90_nucs_res.csv')
bon_90_sig=bon_90[which(bon_90$p<0.05),]
dim(bon_90_sig)## [1] 5685 12bon_99=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/longevity99/nucs/results/longevity99_nucs_res.csv')
bon_99_sig=bon_99[which(bon_99$p<0.05),]
dim(bon_99_sig)## [1] 5308 12x_nuc <- list(
lifespan = bon_life_sig$id.exposure,
healthspan = bon_health_sig$id.exposure,
long90 = bon_90_sig$id.exposure,
long99 = bon_99_sig$exposure
)
ggVennDiagram(x_nuc)
ggsave("venn_p05.png", units="in", width=6, height=4, dpi=300)
# NUC exposures common to all measures of longevity
nuc_four=Reduce(intersect, list(bon_life_sig$id.exposure, bon_health_sig$id.exposure,
bon_90_sig$id.exposure,bon_99_sig$exposure))
nuc_four## [1] "NOP14" "MRPL18" "EXOSC6" "EIF2A" "RRP15" "EIF2AK4"
## [7] "MRPS16" "RPL28" "SURF6" "WDR55" "NIP7" "MRPS6"
## [13] "TRMT112" "YBEY" "DAP3" "IMP4" "NOP10" "RPL10A"
## [19] "XRN2" "NPM3" "MRPS7" "WRN" "RPS23" "RPS26"
## [25] "MRPL10" "GTPBP10" "MRPL2" "MRPL42" "NDUFA7" "EIF6"
## [31] "NOP58" "RPF2" "RPP40" "MRPL21" "POLR1B" "MRPL55"
## [37] "GTF2H5" "CKS2" "HEATR3" "EMG1" "MRPL34" "CNOT6"
## [43] "MRPS21" "USP36" "MRPL54" "RPS8" "NSUN4" "RPL13A"
## [49] "PES1" "NOL9" "RPS9" "DDX56" "RPL13" "DDX52"
## [55] "POP5" "WDR18" "NSUN5P2" "RPL8" "ERCC2" "PWP1"
## [61] "METTL5" "RRP7A" "IMP3" "PELO" "MRPS34" "MRPS9"
## [67] "NOL6" "MRPL36" "PPARGC1A" "EIF3K" "RRP12" "RPS5"
## [73] "EIF2AK2" "NCK1" "LYAR" "DIEXF" "NUP88" "RNASEL"
## [79] "IGHMBP2" "MPHOSPH6" "GEMIN4" "TFB1M" "RRP36" "THUMPD1"
## [85] "BYSL" "RPL9" "GTF3A" "KAT2B" "MRPL52" "FTSJ3"
## [91] "RPL17" "MRPL43" "NSA2" "RPL12" "NVL" "GTPBP4"
## [97] "MRPS25" "TEX10" "MRPL19" "MRPL32" "DDX31" "PIH1D1"
## [103] "RPUSD4" "ZNHIT6" "EXOSC7"# All P<0.05 significant exposures
# x[1:4]0.4 Venn for DNA damage and repair (DDR): FDR
## [1] 112072 12## [1] 722 12## [1] 0.006442287## [1] 115636 12## [1] 1192 12## [1] 0.01030821
## [1] "DCLRE1B" "USP28" "UBA52" "INO80E" "PPP4C" "SMC6"0.5 Venn for DNA damage and repair (DDR): P<0.05
setwd("/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100")
bon_life_ddr=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/ddr/results/ddr_res.csv')
dim(bon_life_ddr) #112072## [1] 112072 12bon_life_ddr_sigp=bon_life_ddr[which(bon_life_ddr$p<0.05),]
dim(bon_life_ddr_sigp) # 11511## [1] 11511 1211511/112072## [1] 0.1027108bon_health_ddr=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/ddr/healthspan/results/ddr_res.csv')
dim(bon_health_ddr) #115636## [1] 115636 12bon_health_ddr_sigp=bon_health_ddr[which(bon_health_ddr$p<0.05),]
dim(bon_health_ddr_sigp) #10523## [1] 10523 1210523/1115636## [1] 0.009432288bon_90_ddr=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/ddr/longevity90/results/ddr_res.csv')
dim(bon_90_ddr) #122449 ## [1] 122449 12bon_90_ddr_sig_fdr=bon_90_ddr[which(bon_90_ddr$fdr<0.05),]
dim(bon_90_ddr_sig_fdr)## [1] 0 12bon_90_ddr_sigp=bon_90_ddr[which(bon_90_ddr$p<0.05),]
dim(bon_90_ddr_sigp) #8241## [1] 8241 128241/122449 ## [1] 0.06730149bon_99_ddr=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/ddr/longevity99/results/ddr_res.csv')
dim(bon_99_ddr)#121826 ## [1] 121826 12bon_99_ddr_sig_fdr=bon_99_ddr[which(bon_99_ddr$fdr<0.05),]
dim(bon_99_ddr_sig_fdr)## [1] 0 12bon_99_ddr_sigp=bon_99_ddr[which(bon_99_ddr$p<0.05),]
dim(bon_99_ddr_sigp) #7427## [1] 7427 127427/121826 ## [1] 0.060964ddr_x <- list(
lifespan = bon_life_ddr_sigp$id.exposure,
healthspan = bon_health_ddr_sigp$id.exposure,
long90 = bon_90_ddr_sigp$id.exposure,
long99 = bon_99_ddr_sigp$exposure
)
ggVennDiagram(ddr_x)
ggsave("venn_ddr_life_health_long90_long99p.png", units="in", width=6, height=4, dpi=300)
# exposures common to all DDR and measures of longevity
ddr_life_health_overlap_p=Reduce(intersect, list(bon_life_ddr_sigp$id.exposure, bon_health_ddr_sigp$id.exposure, bon_90_ddr_sigp$id.exposure, bon_99_ddr_sigp$exposure))
ddr_life_health_overlap_p## [1] "DCLRE1B" "RAD52" "PMS2P3" "USP28" "MLH3" "AXIN2"
## [7] "RMI2" "NEIL2" "KDM4B" "INO80E" "PPP4C" "RFWD3"
## [13] "POLR2J" "POLM" "ERCC3" "SMC6" "UBQLN4" "FANCD2"
## [19] "WRN" "PMS2P5" "MC1R" "ASCC2" "RMI1" "SPIRE1"
## [25] "MCM6" "ASCC3" "NUCKS1" "GTF2H5" "TREX1" "WDR48"
## [31] "PRMT6" "GINS2" "UVSSA" "ANKLE1" "BABAM1" "SMUG1"
## [37] "ALKBH1" "RAD51C" "TRIP12" "SIRT1" "PPIE" "ERCC8"
## [43] "NUDT1" "RPA1" "MGMT" "ATRIP" "EXO5" "PSME4"
## [49] "ACD" "ACTR5" "RRM2B" "DDX11" "ERCC5" "BLM"
## [55] "XRCC3" "HMGN1" "DNA2" "RAD54B" "PPP5C" "POLR2E"
## [61] "UIMC1" "USP3" "FIGNL1" "HINFP" "FAN1" "ERCC2"
## [67] "CIB1" "BRCA1" "CDC7" "UNG" "TFIP11" "USP47"
## [73] "CHAF1A" "PARP2" "EME2" "PARP10" "PARP1" "ASCC1"
## [79] "ZSWIM7" "MAPK8" "SPIRE2" "NFRKB" "IGHMBP2" "MDC1"
## [85] "INO80C" "ERCC1" "RFC5" "ZNF365" "XPC" "FANCA"
## [91] "MAGEF1" "RCHY1" "RNF138" "NPAS2" "BARD1" "RAD21"
## [97] "MUTYH" "EP300" "PMS2" "RFC4" "LIG3" "COPS3"
## [103] "SMARCAD1" "MSH3" "JMY" "RAD50" "MCM5" "CHD1L"
## [109] "BTG2" "ZFYVE26" "PARK7" "RAD23A" "LIG1" "NBN"
## [115] "RNASEH2A" "GTF2H3" "ASF1A" "SMC5" "APTX" "NSMCE4A"
## [121] "ATXN3" "MCM3" "EEPD1" "RIF1" "HERC2" "MGME1"
## [127] "TRIM28"# All p05 significant exposures
# ddr_x[1:4]0.6 Venn for termination-of-adult-lifespan (TAL): P<0.05
setwd("/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100")
bon_life_tal=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/tal/results/tal_res.csv')
dim(bon_life_tal) #5472## [1] 5472 12bon_life_tal_sigp=bon_life_tal[which(bon_life_tal$p<0.05),]
dim(bon_life_tal_sigp) #978## [1] 978 12978/5472## [1] 0.1787281bon_health_tal=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/tal/healthspan/results/tal_res.csv')
dim(bon_health_tal) #6705## [1] 6705 12bon_health_tal_sigp=bon_health_tal[which(bon_health_tal$p<0.05),]
dim(bon_health_tal_sigp) #289## [1] 289 12289/6705## [1] 0.04310216bon_90_tal=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/tal/longevity90/results/tal_res.csv')
dim(bon_90_tal) #7065## [1] 7065 12bon_90_tal_sigp=bon_90_tal[which(bon_90_tal$p<0.05),]
dim(bon_90_tal_sigp) #820## [1] 820 12820/7065## [1] 0.1160651bon_99_tal=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/tal/longevity99/results/tal_res.csv')
dim(bon_99_tal)#7058## [1] 7058 12bon_99_tal_sigp=bon_99_tal[which(bon_99_tal$p<0.05),]
dim(bon_99_tal_sigp) #1063## [1] 1063 121063/7058## [1] 0.1506092tal_x <- list(
lifespan = bon_life_tal_sigp$id.exposure,
healthspan = bon_health_tal_sigp$id.exposure,
long90 = bon_90_tal_sigp$id.exposure,
long99 = bon_99_tal_sigp$id.exposure
)
ggVennDiagram(tal_x)
ggsave("venn_tal_life_health_long90_long99p.png", units="in", width=6, height=4, dpi=300)
# exposures common to all measures of longevity
tal_life_health_overlap_p=Reduce(intersect, list(bon_life_tal_sigp$id.exposure, bon_health_tal_sigp$id.exposure, bon_90_tal_sigp$id.exposure, bon_99_tal_sigp$id.exposure))
tal_life_health_overlap_p## [1] "GBA" "INPP5D" "TREX1" "CNOT6" "RAD54B" "PELO"# All p<0.05 significant exposures
#tal_x[1:4]0.7 Overlap between NUC, DDR, and TAL pathway sets?
These are the GO sets for NUC, DDR, and TAL (prior to reading into MR).
# Read-in NUC genes
combo4=read.csv('/n/home04/cdadams/MR-eqtlGen-long/combo4.csv')
combo4$gene## [1] "NOP53" "WDR12" "BOP1"
## [4] "TSR1" "BMS1" "RRS1"
## [7] "RSL24D1" "NSA2" "BRIX1"
## [10] "NOP10" "URB2" "NIP7"
## [13] "TSR3" "RPF1" "RBIS"
## [16] "SBDS" "MRRF" "LAS1L"
## [19] "CKS1B" "CKS2" "RPF2"
## [22] "MTG2" "GFM2" "RBFA"
## [25] "MRPL39" "RPS10P5" "MRPS2"
## [28] "SURF6" "MRPL22" "MALSU1"
## [31] "RPL10L" "RPLP0P6" "RPL3L"
## [34] "TSR2" "NOP16" "RRP15"
## [37] "HEATR3" "MRPL36" "MRPL10"
## [40] "PPAN" "RPL26L1" "RPL7L1"
## [43] "MRPL20" "MRPS7" "VCX"
## [46] "NSUN4" "MPV17L2" "DDX28"
## [49] "DHX30" "MRPS11" "MRPL1"
## [52] "PAK1IP1" "SRFBP1" "EBNA1BP2"
## [55] "NOM1" "RRP7BP" "LTV1"
## [58] "RRP7A" "LOC102724159" "SDAD1"
## [61] "PWP2" "GNL2" "DDX31"
## [64] "RPUSD1" "TEX10" "THUMPD1"
## [67] "RRNAD1" "FCF1" "METTL15P1"
## [70] "WDR55" "ESF1" "URS00003B7E88_9606"
## [73] "URS00006D8FF2_9606" "URS0000547024_9606" "URS00005B510E_9606"
## [76] "URS0000153780_9606" "URS0000697636_9606" "URS0000D5B596_9606"
## [79] "URS0000229D6D_9606" "KRR1" "GTPBP10"
## [82] "UTP14A" "RRP1" "RPUSD2"
## [85] "PIH1D2" "URS0000051A30_9606" "URS0001A04CEF_9606"
## [88] "MRPL49" "MRPL35" "MRPL46"
## [91] "MRPS31" "MRPL30" "MRPL37"
## [94] "MRPL52" "MRPS12" "MRPL16"
## [97] "MRPL28" "MRPL4" "MRPL9"
## [100] "MRPL32" "MRPL2" "MRPS14"
## [103] "MRPL23" "MRPL57" "MRPL19"
## [106] "MRPL11" "MRPS16" "MRPL43"
## [109] "MRPS18C" "MRPS24" "MRPS17"
## [112] "MRPS33" "MRPS6" "MRPS34"
## [115] "MRPS21" "MRPL34" "MRPL17"
## [118] "MRPL33" "MRPL42" "MRPL21"
## [121] "MRPL47" "MRPL24" "MRPL27"
## [124] "MRPS5" "MRPS22" "MRPL51"
## [127] "MRPL14" "MRPL55" "MRPL54"
## [130] "MRPS18A" "MRPS18B" "MRPL41"
## [133] "MRPS30" "MRPL3" "MRPS15"
## [136] "SHQ1" "EIF2A" "MTERF3"
## [139] "RPL35A" "A0A0U1RQV5" "MRTO4"
## [142] "MDN1" "ERAL1" "NSUN3"
## [145] "EFL1" "RPSA" "RPS28"
## [148] "RPS15" "RPL6" "MRPL45"
## [151] "MRPL48" "CHCHD1" "MRPL53"
## [154] "MRPS28" "MRPL40" "MRPL50"
## [157] "MRPS10" "MRPL38" "GTF3A"
## [160] "WDR46" "ZNHIT6" "WDR74"
## [163] "NIFK" "MAK16" "NOL10"
## [166] "URB1" "RRP36" "DDX52"
## [169] "UTP3" "RSL1D1" "WDR3"
## [172] "UTP23" "UTP6" "FAM207A"
## [175] "KRI1" "LTO1" "PES1"
## [178] "METTL17" "NOB1" "FASTKD2"
## [181] "LSG1" "MRPL15" "MRPL18"
## [184] "MRPS9" "DAP3" "MRPS35"
## [187] "MRPS36" "RPS5" "RPLP0"
## [190] "RPS27" "RPL3" "RPL23A"
## [193] "RPL10A" "RPS10" "RPS21"
## [196] "RPL7A" "MRM1" "C1D"
## [199] "MRM3" "RRP9" "IMP3"
## [202] "ISG20L2" "FDXACB1" "RRP12"
## [205] "NPM3" "DDX27" "NOP58"
## [208] "DDX10" "WDR18" "UTP18"
## [211] "MRM2" "WDR36" "UTP11"
## [214] "WBP11" "PDCD11" "NOL8"
## [217] "SENP3" "NSUN5P1" "DDX51"
## [220] "NOC4L" "NSUN5P2" "METTL15"
## [223] "MPHOSPH6" "NOP56" "YBEY"
## [226] "UTP14C" "IMP4" "PIN4"
## [229] "SNU13" "MTERF4" "NDUFA7"
## [232] "MRPS27" "RPL35" "RPS25"
## [235] "RPS24" "RPL7" "RPS17"
## [238] "RPS16" "RPS8" "RPL14"
## [241] "EIF2D" "MCTS1" "NOP2"
## [244] "NOP9" "DHX37" "MRPS26"
## [247] "C12orf65" "NOL9" "DDX18"
## [250] "NOP14" "DIEXF" "NGDN"
## [253] "TBL3" "RCL1" "BYSL"
## [256] "EMG1" "UTP4" "DCAF13"
## [259] "FTSJ3" "ZNHIT3" "MRPS23"
## [262] "MRPS25" "RPL27" "RPS2"
## [265] "RPS9" "DHX29" "TACO1"
## [268] "RPL38" "NMD3" "XPO1"
## [271] "ERI1" "MRPL13" "NDUFAB1"
## [274] "TRMT61B" "RPP30" "RPP38"
## [277] "DDX47" "POP7" "ERI3"
## [280] "DDX56" "GAR1" "POP4"
## [283] "DDX49" "ERI2" "FRG1"
## [286] "RPP25" "DIMT1" "POP5"
## [289] "NOL6" "MPHOSPH10" "HELQ"
## [292] "GEMIN4" "RPL24" "SRP19"
## [295] "EIF6" "RPL5" "RPL10"
## [298] "RPS19" "RPS27L" "RPS14"
## [301] "RPS23" "DENR" "EIF3K"
## [304] "MTIF3" "MRPL44" "MRPL58"
## [307] "NOL11" "HEATR1" "RPP40"
## [310] "UTP20" "ZNF622" "NHP2"
## [313] "RIOK1" "LSM6" "TRAF7"
## [316] "NLE1" "ABT1" "RPS6"
## [319] "RPL11" "WDR43" "WDR75"
## [322] "RIOX2" "REXO4" "METTL5"
## [325] "ZCCHC4" "TFB2M" "BUD23"
## [328] "SART1" "EXOSC1" "TRMT112"
## [331] "FBL" "MTREX" "DIS3"
## [334] "RPUSD4" "RPUSD3" "FBLL1"
## [337] "BMT2" "TFB1M" "UTP15"
## [340] "PELP1" "NUP88" "MRPL12"
## [343] "NUDT16" "GADD45GIP1" "RIOK2"
## [346] "CUL4B" "GNL3L" "EIF3H"
## [349] "NUFIP1" "EIF3C" "GEMIN5"
## [352] "LARP4" "RPL26" "RPS7"
## [355] "GTPBP4" "NVL" "HELB"
## [358] "OXA1L" "PTCD3" "SERP1"
## [361] "MAIP1" "FXR2" "EXOSC7"
## [364] "PWP1" "METTL16" "NAF1"
## [367] "NSUN5" "MYBBP1A" "XRN2"
## [370] "AATF" "ZNF658" "ISG20"
## [373] "RRP8" "RRP1B" "EXOSC8"
## [376] "EXOSC4" "EXOSC5" "GLUL"
## [379] "PA2G4" "DDX54" "URS000075C8FA_9606"
## [382] "RPL13A" "ABCE1" "RAN"
## [385] "C1QBP" "GTF2H5" "SF1"
## [388] "NPM1" "CUL4A" "RIOK3"
## [391] "KAT2B" "NAA10" "PELO"
## [394] "MTIF2" "ETF1" "IGHMBP2"
## [397] "AURKAIP1" "PYM1" "SEC61A1"
## [400] "NAT10" "NOC2L" "DDX3X"
## [403] "LETM1" "APOD" "PNPT1"
## [406] "ERCC2" "EIF5AL1" "SHFL"
## [409] "EXOSC10" "DROSHA" "DDX21"
## [412] "EXOSC9" "NOLC1" "LYAR"
## [415] "TENT4B" "SUV39H1" "EXOSC2"
## [418] "DDX17" "EXOSC6" "RNASEL"
## [421] "DKC1" "XRCC5" "PIH1D1"
## [424] "RICTOR" "RPL23" "EIF5A2"
## [427] "EIF5A" "UBA52" "RPS27A"
## [430] "EIF4A3" "CHD7" "EXOSC3"
## [433] "EIF2S1" "TSC1" "DHX9"
## [436] "RPS3" "FMR1" "RACK1"
## [439] "PRKDC" "PTEN" "NCK1"
## [442] "EIF2AK2" "BAG6" "EIF2AK4"
## [445] "PPARGC1A" "APEX1" "HSPA5"
## [448] "MTOR" "ZC3H12A" "PINX1"
## [451] "MCRS1" "POLR1A" "WRN"
## [454] "TERT" "kcne2-kcnh2_human" "gins_human"
## [457] "CSDE1" "CNOT6" "DRD4"
## [460] "DRD3" "DRD2" "ZNF354A"
## [463] "POLR1B" "USP36" "RPL12"
## [466] "RPL13" "RPL15" "RPL17"
## [469] "RPL18" "RPL18A" "RPL19"
## [472] "RPL21" "RPL22" "RPL27A"
## [475] "RPL28" "RPL29" "RPL30"
## [478] "RPL31" "RPL32" "RPL34"
## [481] "RPL36" "RPL36A" "RPL37"
## [484] "RPL37A" "RPL39" "RPL4"
## [487] "RPL41" "RPL8" "RPL9"
## [490] "RPS11" "RPS12" "RPS13"
## [493] "RPS15A" "RPS18" "RPS20"
## [496] "RPS26" "RPS29" "RPS3A"# Read-in the ddr genes
ddr=read.csv('/n/holylfs/LABS/lemos_lab/Users/cdadams/MR-eqtlGen-long/bon_genesets_100/ddr/data/ddr_vec.csv')
ddr=as.data.frame(ddr)
ddr$gene## [1] "DDB1" "DDB2" "msh2-msh3_human"
## [4] "MDC1" "ddb1-ddb2_human" "XRCC1"
## [7] "ERCC4" "SPIDR" "XRCC4"
## [10] "REV1" "RAD50" "XRCC3"
## [13] "XRCC2" "RAD52" "SWI5"
## [16] "MSH2" "MLH3" "MSH6"
## [19] "MSH3" "MLH1" "HUS1B"
## [22] "PMS2" "HUS1" "GADD45A"
## [25] "XPC" "PWWP3A" "ERCC6"
## [28] "DCLRE1A" "XPA" "ERCC8"
## [31] "ERCC1" "ALKBH8" "RAD9A"
## [34] "RAD9B" "RAD54L" "RAD54B"
## [37] "RAD51" "M0R2N6" "RAD51D"
## [40] "ERCC5" "RAD51B" "RAD51C"
## [43] "XRCC5" "XRCC6" "POLK"
## [46] "MMS19" "DDX11" "ERCC6L2"
## [49] "SFR1" "ERCC3" "NUDT16L1"
## [52] "ERCC2" "ALKBH1" "TREX2"
## [55] "TREX1" "DNTT" "PMS2P11"
## [58] "POLN" "DCLRE1B" "RTEL1"
## [61] "MRE11" "DCLRE1C" "POLD3"
## [64] "PMS2P3" "PMS2P5" "PMS2P1"
## [67] "PMS2P2" "MSH5" "PMS1"
## [70] "RAD23B" "POLL" "POLQ"
## [73] "BRIP1" "MPG" "BRME1"
## [76] "HELB" "LIG1" "MSH4"
## [79] "POLM" "MUTYH" "MCM9"
## [82] "LIG3" "POLH" "POLD4"
## [85] "POLD2" "POLB" "MCM8"
## [88] "POLI" "TDP1" "RAD23A"
## [91] "OGG1" "RAD21" "POLD1"
## [94] "ALKBH2" "SPRTN" "FBH1"
## [97] "REV3L" "UNG" "LIG4"
## [100] "RBBP8" "NEIL3" "MGMT"
## [103] "TDP2" "RECQL" "PRIMPOL"
## [106] "RECQL4" "RECQL5" "RAD21L1"
## [109] "MCM5" "MCM4" "MCM6"
## [112] "POLE2" "GINS4" "GINS2"
## [115] "PARP3" "PARP1" "CHD1L"
## [118] "RPA1" "POLG" "MCM3"
## [121] "MCM2" "MCM7" "KIN"
## [124] "POLA1" "NEIL2" "PARP2"
## [127] "POLE" "NEIL1" "IGHMBP2"
## [130] "TOPBP1" "SMUG1" "PIF1"
## [133] "APEX2" "PRKDC" "POLR2I"
## [136] "POLR2C" "POLR2B" "TDG"
## [139] "APEX1" "DNA2" "RFC2"
## [142] "RFC4" "RFC3" "RFC5"
## [145] "POLR2A" "POLR2G" "ZRANB3"
## [148] "POLG2" "POLR2D" "WDHD1"
## [151] "DMAP1" "BLM" "WRN"
## [154] "POLR2J" "MCMDC2" "DMC1"
## [157] "POLR2F" "POLR2K" "POLR2E"
## [160] "POLR2L" "POLR2H" "SMARCAL1"
## [163] "FANCB" "FAM168A" "RAD51AP2"
## [166] "RPA3" "CYREN" "ZSWIM7"
## [169] "RPA2" "PARPBP" "AUNIP"
## [172] "btr_human" "RPA4" "nua4_human"
## [175] "RADX" "HROB" "CUL4B"
## [178] "ercc1-xpf_human" "WDR48" "SHLD2"
## [181] "SHLD1" "SHLD3" "RNF138"
## [184] "MRNIP" "RMI2" "NSMCE1"
## [187] "PAXX" "SWSAP1" "pcna_human-1"
## [190] "RNF169" "ZCWPW1" "COPS6"
## [193] "COPS4" "COPS7B" "COPS7A"
## [196] "RFWD3" "FAN1" "MMS22L"
## [199] "TONSL" "RAD51AP1" "MUS81"
## [202] "USP51" "TFIP11" "CUL4A"
## [205] "FANCD2" "UBQLN4" "Q6ZNB5"
## [208] "LOC100133315" "KHDC3L" "OOEP"
## [211] "TEX15" "PNKP" "ube2n-ube2v2_human"
## [214] "IFFO1" "FAAP100" "FAAP24"
## [217] "SMCHD1" "BABAM1" "BRCC3"
## [220] "ABRAXAS1" "BABAM2" "FAAP20"
## [223] "ku70_80_human" "INIP" "KLHL15"
## [226] "MAGEF1" "HELQ" "PPP4C"
## [229] "PPP4R2" "NTHL1" "APLF"
## [232] "FANCE" "GGN" "FANCF"
## [235] "EME2" "TP53BP1" "PARG"
## [238] "WRNIP1" "PCNA" "AP5S1"
## [241] "ZFYVE26" "AP5Z1" "EME1"
## [244] "ALKBH3" "eme2-mus81_human" "eme1-mus81_human"
## [247] "GTF2H3" "TICRR" "MGME1"
## [250] "WRAP53" "COPS3" "SMC6"
## [253] "NSMCE4A" "EXD2" "TIMELESS"
## [256] "ATRIP" "SLF1" "APTX"
## [259] "USP1" "TMEM161A" "SETMAR"
## [262] "RIF1" "SLF2" "NHEJ1"
## [265] "RFC1" "H2AX" "ASCC1"
## [268] "EXO5" "ASCC2" "RAD18"
## [271] "FOXM1" "CETN2" "inip-ints3-nabp2_human"
## [274] "EID3" "INO80D" "CINP"
## [277] "ADPRS" "UVSSA" "TRIP12"
## [280] "PALB2" "RMI1" "KDM4D"
## [283] "NABP1" "ASCC3" "OTUB1"
## [286] "OTUB2" "CGAS" "SEM1"
## [289] "inip-ints3-nabp1_human" "ZNF365" "ARID2"
## [292] "MBD4" "PCLAF" "TEX12"
## [295] "SPATA22" "FUS" "pp4_human-2b"
## [298] "UIMC1" "POT1" "CDC45"
## [301] "TERF2IP" "MAD2L2" "FIGNL1"
## [304] "USP43" "FAM111A" "SMARCAD1"
## [307] "FANCM" "USP28" "CHEK2"
## [310] "HMGA2" "CHAF1B" "CHAF1A"
## [313] "RHNO1" "AQR" "HSF2BP"
## [316] "CHEK1" "DEK" "TERF2"
## [319] "HPF1" "FEN1" "MEIOB"
## [322] "ACTR5" "RNF8" "SLX1A"
## [325] "NBN" "NABP2" "KDM4B"
## [328] "SLX4" "GTF2H2" "KMT5C"
## [331] "KMT5B" "ATR" "BRCA2"
## [334] "EYA3" "RBX1" "SYCP1"
## [337] "CDC7" "H3-4" "RNF168"
## [340] "ATP23" "HMGN1" "GTF2H1"
## [343] "RPAIN" "ISY1" "GTF2H4"
## [346] "RAD17" "NPAS2" "GTF2H5"
## [349] "RNASEH2A" "ANKLE1" "NFRKB"
## [352] "DTL" "CLSPN" "EYA4"
## [355] "PARP9" "FANCG" "FANCI"
## [358] "PIAS4" "UBC" "ETAA1"
## [361] "ENDOV" "INO80B" "INO80C"
## [364] "INO80E" "KASH5" "USP10"
## [367] "UBE2V2" "ESCO2" "POLDIP2"
## [370] "HDAC10" "INO80" "TEX264"
## [373] "VCPIP1" "ACD" "CEBPG"
## [376] "COPS2" "SMC5" "ZNF830"
## [379] "UBE2L6" "EMSY" "EEPD1"
## [382] "PDS5B" "GEN1" "FBXO6"
## [385] "SPIRE2" "DTX3L" "UBE2T"
## [388] "CETN1" "MARF1" "FANCL"
## [391] "TNKS1BP1" "KDM1A" "TRAIP"
## [394] "UBE2N" "UBR5" "FMN2"
## [397] "SPIRE1" "SIX6OS1" "KAT5"
## [400] "PARP4" "HMCES" "ZBTB7A"
## [403] "XAB2" "FTO" "NSD2"
## [406] "PRPF19" "SSRP1" "COPS8"
## [409] "GPS1" "H4-16" "SETD2"
## [412] "GTF2H2C" "ACTR8" "FANCC"
## [415] "USP45" "HERC2" "TFPT"
## [418] "PDS5A" "H2AW" "SPO11"
## [421] "EYA1" "APBB1" "WAS"
## [424] "KAT7" "REC8" "MORF4L1"
## [427] "ACTR2" "SMC1A" "RPS3"
## [430] "CENPX" "CENPS" "BTG2"
## [433] "SHPRH" "TCEA1" "ATM"
## [436] "SIRT7" "NUCKS1" "WDR33"
## [439] "CDCA5" "BRCA1" "RAD1"
## [442] "CBX8" "INTS3" "REXO4"
## [445] "PAXIP1" "CDKN2D" "UBB"
## [448] "RPS27A" "UBA52" "TRIM28"
## [451] "SAMHD1" "EXO1" "GTF2I"
## [454] "KDM2A" "USP47" "NSMCE2"
## [457] "TIGAR" "PRKCG" "CDK2"
## [460] "CEP164" "FH" "UBE2U"
## [463] "TINF2" "COPS5" "UVRAG"
## [466] "RCHY1" "EYA2" "BOD1L1"
## [469] "TWIST1" "MNAT1" "ATRX"
## [472] "SIRT1" "HINFP" "HSF1"
## [475] "PPIE" "rrm1-rrm2b_human" "TTC5"
## [478] "CDK7" "UBE2V1" "TERF1"
## [481] "TRRAP" "SLC30A9" "EP300"
## [484] "CCNH" "CDC14B" "FZR1"
## [487] "TAOK3" "ASF1A" "PML"
## [490] "USP7" "PRDM9" "CDC5L"
## [493] "YY1" "ALKBH5" "FANCA"
## [496] "SMC3" "EPC2" "TP53"
## [499] "PRRX1" "DOT1L" "SUPT16H"
## [502] "USP3" "KPNA2" "TP73"
## [505] "NUDT1" "NSMCE3" "KIF22"
## [508] "TENT4A" "BAZ1B" "TRIM25"
## [511] "PARP10" "SIRT6" "CDK9"
## [514] "DHX9" "ACTL6A" "RNF113A"
## [517] "BCCIP" "UBE2W" "SMARCA5"
## [520] "MTA1" "PAGR1" "NOP53"
## [523] "UBE2B" "ZBTB1" "AXIN2"
## [526] "MEIOC" "UBE2A" "HMGB1"
## [529] "NIPBL" "TAOK1" "TNP1"
## [532] "MC1R" "SFPQ" "RRM2B"
## [535] "JMY" "MCRS1" "ZMPSTE24"
## [538] "SETX" "DDX1" "BACH1"
## [541] "UFD1" "ISG15" "NPLOC4"
## [544] "RNF111" "UHRF1" "RUVBL1"
## [547] "HMGB2" "MORF4L2" "BARD1"
## [550] "NPM1" "COMMD1" "RUVBL2"
## [553] "SMG1" "CDK1" "PSMD14"
## [556] "UPF1" "SUMO1" "UFL1"
## [559] "TRIP13" "BAP1" "PRMT6"
## [562] "URS0000170CF4_9606" "CHRNA4" "PTTG1"
## [565] "KDM4A" "NONO" "PPP5C"
## [568] "HUWE1" "MAPK8" "VCP"
## [571] "UBXN1" "ATXN3" "FGF10"
## [574] "UBE2D3" "MEN1" "UCHL5"
## [577] "CSNK1E" "ABL1" "PSME4"
## [580] "CIB1" "EGFR" "STUB1"
## [583] "PARK7"# Read-in the tal genes
tal=fread("http://golr-aux.geneontology.io/solr/select?defType=edismax&qt=standard&indent=on&wt=csv&rows=100000&start=0&fl=bioentity,bioentity_label&facet=true&facet.mincount=1&facet.sort=count&json.nl=arrarr&facet.limit=25&hl=true&hl.simple.pre=%3Cem%20class=%22hilite%22%3E&hl.snippets=1000&csv.encapsulator=&csv.separator=%09&csv.header=false&csv.mv.separator=%7C&fq=document_category:%22bioentity%22&fq=taxon_subset_closure_label:%22Homo%20sapiens%22&facet.field=source&facet.field=taxon_subset_closure_label&facet.field=type&facet.field=panther_family_label&facet.field=annotation_class_list_label&facet.field=regulates_closure_label&q=GO:0008340&qf=bioentity%5E2&qf=bioentity_label_searchable%5E2&qf=bioentity_name_searchable%5E1&qf=bioentity_internal_id%5E1&qf=synonym_searchable%5E1&qf=isa_partof_closure_label_searchable%5E1&qf=regulates_closure%5E1&qf=regulates_closure_label_searchable%5E1&qf=panther_family_searchable%5E1&qf=panther_family_label_searchable%5E1&qf=taxon_label_searchable%5E1", header=FALSE)
colnames(tal)<- c('annot','gene')
tal=as.data.frame(tal)
tal$gene## [1] "TFCP2L1" "IDE" "TP53"
## [4] "RAD54L" "TREX1" "GBA"
## [7] "CGAS" "MSH2" "COQ7"
## [10] "INPP5D" "LRRK2" "GHRHR"
## [13] "PRDM2" "MSH6" "LEP"
## [16] "ZMPSTE24" "RAD54B" "kcne2-kcnh2_human"
## [19] "gins_human" "CSDE1" "PELO"
## [22] "CNOT6" "DRD4" "DRD3"
## [25] "DRD2"# GO overlap in the three pathways (prior to removal of genes in MR)
overlap3=Reduce(intersect, list(combo4$gene, ddr$gene, tal$gene))
overlap3## character(0)# Overlap between ddr and NUC
overlap_ddr_nuc=Reduce(intersect, list(combo4$gene, ddr$gene))
overlap_ddr_nuc## [1] "NOP53" "HELQ" "REXO4" "CUL4B" "HELB" "GTF2H5" "NPM1"
## [8] "CUL4A" "IGHMBP2" "ERCC2" "XRCC5" "UBA52" "RPS27A" "DHX9"
## [15] "RPS3" "PRKDC" "APEX1" "MCRS1" "WRN"# Overlap between tal and NUC
overlap_tal_nuc=Reduce(intersect, list(combo4$gene, tal$gene))
overlap_tal_nuc## [1] "PELO" "kcne2-kcnh2_human" "gins_human"
## [4] "CSDE1" "CNOT6" "DRD4"
## [7] "DRD3" "DRD2"# Overlap between tal and ddr
overlap_ddr_tal=Reduce(intersect, list(ddr$gene, tal$gene))
overlap_ddr_tal## [1] "MSH2" "MSH6" "RAD54L" "RAD54B" "TREX1" "CGAS" "TP53"
## [8] "ZMPSTE24"# Venn of overlap in the three pathways from the GO searches
go_3 <- list(
NUC = combo4$gene,
DDR = ddr$gene,
TAL = tal$gene
)
ggVennDiagram(go_3)
ggsave("venn_GO_3.png", units="in", width=6, height=4, dpi=300)