Firstly i do data normalization then i used limma for differential expression ,   list of top 10 up and top 10 down regulated degs were retrieved by using R on linux suse but the desired coloumn names of top 10 up and down regulated degs are : GeneID, Gene symbol, pvalue, FDR) how can i retrieve this by using R code kindly help me out.

library(limma)
plotPCA(eset.rma, groups =as.numeric(pData(d1)[,1]),groupnames =levels(pData(d1)[,1]))
pData(d1)[,1 ]
group<- factor r(pData(d1)[,1 ]a(d1)[,1])), levels =levels(pData(d1)[,1]))
 fit1 <-lmFit(eset.rma, design)
fit1 <-eBayes(fit1)
tab50 <- topTable(fit1, coef = 2, adjust = "fdr",n = 50)
head(tab50, n=2)
               logFC  AveExpr        t      P.Value    adj.P.Val        B
211597_s_at 5.237952 3.289023 24.49186 2.866308e-08 0.0006386993 7.199561
211964_at   3.519962 2.686838 21.69393 6.866511e-08 0.0007650324 6.862590

probeList <- rownames(exprs(eset.rma));
if (require(hgu133a.db) & require(annotate))
{
geneSymbol <- getSYMBOL(probeList, 'hgu133a.db')
geneName <- sapply(lookUp(probeList, 'hgu133a.db',
'GENENAME'), function(x) x[1])
EntrezID <- sapply(lookUp(probeList, 'hgu133a.db',
'ENTREZID'), function(x) x[1])
} 

> head(UP_annotated_table,n=10)
               logFC  AveExpr        t      P.Value    adj.P.Val        B
211597_s_at 5.237952 3.289023 24.49186 2.866308e-08 0.0006386993 7.199561
211964_at   3.519962 2.686838 21.69393 6.866511e-08 0.0007650324 6.862590
213243_at   3.841436 2.474788 18.58363 2.083929e-07 0.0015478733 6.354825
203038_at   4.317340 2.869763 16.56840 4.729030e-07 0.0026344242 5.920133
206385_s_at 2.208070 2.065396 14.51531 1.209436e-06 0.0053899727 5.358531
203675_at   3.300579 3.157668 13.04972 2.560907e-06 0.0073778832 4.861905
206806_at   1.692654 2.687724 12.65547 3.175768e-06 0.0073778832 4.711820
219737_s_at 3.908562 4.850929 12.45853 3.544425e-06 0.0073778832 4.633940
204891_s_at 4.645051 4.962788 12.24253 4.005545e-06 0.0073778832 4.546204
203865_s_at 2.774819 2.887660 12.15133 4.220348e-06 0.0073778832 4.508410
            FoldChange DownS/Norm
211597_s_at             37.738164
211964_at               11.471339
213243_at               14.334659
203038_at               19.936496
206385_s_at              4.620569
203675_at                9.853111
206806_at                3.232508
219737_s_at             15.017388
204891_s_at             25.020713
203865_s_at              6.843903

> head(DOWN_annotated_table,n=10)
                logFC  AveExpr          t      P.Value   adj.P.Val        B
204684_at   -3.539326 3.620389 -13.315721 2.222307e-06 0.007377883 4.958978
216033_s_at -2.403346 4.327960 -12.273627 3.935154e-06 0.007377883 4.558988
202552_s_at -2.020307 2.209275 -11.877579 4.947546e-06 0.007377883 4.392222
210978_s_at -2.301755 7.564961 -11.614257 5.783444e-06 0.007580735 4.276433
212063_at   -4.553384 6.169763 -10.282190 1.342784e-05 0.012712866 3.623785
203085_s_at -4.992403 6.162288 -10.143841 1.473638e-05 0.013134834 3.548972
202912_at   -4.312281 5.258749  -9.675439 2.036186e-05 0.015181843 3.284779
209200_at   -1.469112 3.378761  -9.607122 2.136946e-05 0.015181843 3.244786
201160_s_at -2.883515 8.534621  -9.254994 2.754286e-05 0.017535360 3.032466
200931_s_at -2.003982 4.598302  -9.117905 3.047180e-05 0.018861198 2.946915
            FoldChange DownS/Norm
204684_at              -11.626345
216033_s_at             -5.290285
202552_s_at             -4.056700
210978_s_at             -4.930573
212063_at              -23.480377
203085_s_at            -31.831941
202912_at              -19.866713
209200_at               -2.768515
201160_s_at             -7.379456
200931_s_at             -4.011057

If you are already using affycoretools, then

eset.rma <- annotateEset(eset.rma, hgu133a.db)

And then proceed with limma. The annotation will automatically be added to your topTable output.

Thankyou for your response, i get the desired output but while using the code it generated some error.

library(affy)
library(affycoretools)
d1<-ReadAffy()
pData(d1)<-read.table("PhenoData.txt",row.names=1,header = T,sep="\t");
pData(d1)
d1
> eset.rma <- rma(d1)
Background correcting
Normalizing
Calculating Expression

> eset.rma <- annotateEset(eset.rma, hgu133a.db)
'select()' returned 1:many mapping between keys and columns
'select()' returned 1:many mapping between keys and columns
'select()' returned 1:many mapping between keys and columns