There are probably three alternatives here. First, you could go to the Agilent website and try to figure out if there are any material differences between the v2 and v3 versions of this array, and if there are none, you could just use the v2 data on Ensembl to annotate your data.
Second, you could NOT go to the Agilent website (in my interactions with the Agilent website, this appears to be the more sane argument, but ymmv), but simply assume there aren't many differences of note, and just go ahead and use the v2 data on Ensembl. That appears to work to some extent:
> z <- read.table("039494_D_GeneList_20150612.txt", header = TRUE, sep = "\t", fill = T)
## this is the Agilent file for the v3 array. Let's try to annotate the first 50 or so.
> getBM(c("efg_agilent_sureprint_g3_ge_8x60k_v2", "hgnc_symbol","entrezgene"), "efg_agilent_sureprint_g3_ge_8x60k_v2", as.character(z[1:50,1]), mart)
efg_agilent_sureprint_g3_ge_8x60k_v2 hgnc_symbol entrezgene
1 A_33_P3339253 LAGE3P1 NA
2 A_33_P3393543 NA
3 A_33_P3495120 CCDC141 285025
4 A_33_P3217307 ZBTB8OS 339487
5 A_24_P453544 SURF1 6834
6 A_33_P3261463 LINC00982 440556
7 A_33_P3335915 SYNE1 23345
8 A_33_P3339253 APTX 54840
9 A_24_P931964 NA
10 A_33_P3679768 DPCR1 135656
11 A_33_P3347301 NA
12 A_33_P3212415 ZNF44 51710
13 A_33_P3295228 ZBTB7A 51341
14 A_33_P3411980 ABI3BP 25890
15 A_33_P3416797 144203
16 A_33_P3416797 408186
17 A_33_P3392740 ATOH8 84913
So that seems to work OK, I guess. Although we sure did seem to lose lots of probes. Adding in the ensembl_transcript_id (results not shown) bumped it up to 25, but that's still 50% that aren't getting annotated. But whatever.
The third alternative would be to use what Agilent gives us and just make our own ChipDb package for this array. Note that I went to Agilent's website and got the file I read in. We first need to write out the first two columns of that file, which contains the probe ID followed by the GenBank ID.
> write.table(z[,1:2], "thefile.txt", col.names = FALSE, row.names = FALSE, quote = FALSE, sep = "\t")
## now make the package
> makeDBPackage("HUMANCHIP_DB", affy = FALSE, prefix = "agilentwhatevs", fileName = "thefile.txt", baseMapType = "gbNRef", version = "0.0.1")
Creating package in ./agilentwhatevs.db
We can now install and use this package. You might use a less snarky name for yours... Note that you have to set the repos to NULL so you don't try to get things from CRAN, and if you are on Windows or MacOS, you have to say it's a source package as well.
> install.packages("agilentwhatevs.db/", repos = NULL, type = "source")
## Now we can annotate the top 50 probes like above.
> rslts <- select(agilentwhatevs.db, as.character(z[1:50,1]), c("SYMBOL","ENTREZID"))
'select()' returned 1:1 mapping between keys and columns
PROBEID SYMBOL ENTREZID
1 A_33_P3696965 <NA> <NA>
2 A_21_P0014788 <NA> <NA>
3 A_33_P3451458 LINC01617 101926947
4 A_33_P3210760 <NA> <NA>
5 A_33_P3339253 <NA> <NA>
6 A_21_P0014878 <NA> <NA>
> apply(rslts[,2:3], 2, function(x) sum(!is.na(x)))
So that's a bit better, but it appears there is a lot of speculative content on this array, so it is still pretty sparse. But anyway, there you go.