I performed gene enrichment analysis using GO.db. It gave me back some GOs with up and down genes but it doesn't say what those genes are. Any idea how to do that? I didn't have any problem with the code, I just don't know what to do after that. This is what I have done so far

qlf<- glmQLFTest(fit, contrast = contr.matrix[,10])
go <- goana(qlf, species = "Mm")
topGO_2000 <- topGO(go, n=2000, truncate=2000)
topGO_2000 <-topGO_2000 %>%
  filter( P.Up < 0.001 | P.Down < 0.001)

sessionInfo()
R version 4.0.2 (2020-06-22)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.7

Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
 [1] grid      stats4    parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] Rgraphviz_2.34.0     topGO_2.42.0         SparseM_1.81         graph_1.68.0         org.Mm.eg.db_3.12.0 
 [6] GO.db_3.12.1         AnnotationDbi_1.52.0 IRanges_2.24.1       S4Vectors_0.28.1     biomaRt_2.46.3      
[11] forcats_0.5.1        stringr_1.4.0        dplyr_1.0.5          purrr_0.3.4          readr_1.4.0         
[16] tidyr_1.1.3          tibble_3.1.1         ggplot2_3.3.3        tidyverse_1.3.1      RColorBrewer_1.1-2  
[21] RTN_2.15.2           edgeR_3.32.1         limma_3.46.0         Biobase_2.50.0       BiocGenerics_0.36.1 

loaded via a namespace (and not attached):
 [1] colorspace_2.0-0            ellipsis_0.3.1              class_7.3-17                rio_0.5.26                 
 [5] XVector_0.30.0              GenomicRanges_1.42.0        fs_1.5.0                    rstudioapi_0.13            
 [9] proxy_0.4-25                bit64_4.0.5                 fansi_0.4.2                 lubridate_1.7.10           
[13] xml2_1.3.2                  splines_4.0.2               cachem_1.0.4                jsonlite_1.7.2             
[17] broom_0.7.6                 kernlab_0.9-29              dbplyr_2.1.1                pheatmap_1.0.12            
[21] compiler_4.0.2              httr_1.4.2                  backports_1.2.1             assertthat_0.2.1           
[25] Matrix_1.2-18               fastmap_1.1.0               cli_2.5.0                   prettyunits_1.1.1          
[29] tools_4.0.2                 igraph_1.2.6                gtable_0.3.0                glue_1.4.2                 
[33] GenomeInfoDbData_1.2.4      rappdirs_0.3.3              tinytex_0.31                Rcpp_1.0.6                 
[37] carData_3.0-4               cellranger_1.1.0            vctrs_0.3.7                 xfun_0.22                  
[41] openxlsx_4.2.3              rvest_1.0.0                 lifecycle_1.0.0             statmod_1.4.35             
[45] XML_3.99-0.6                zlibbioc_1.36.0             MASS_7.3-51.6               scales_1.1.1               
[49] minet_3.48.0                hms_1.0.0                   MatrixGenerics_1.2.1        SummarizedExperiment_1.20.0
[53] pwr_1.3-0                   curl_4.3                    memoise_2.0.0               viper_1.24.0               
[57] segmented_1.3-4             stringi_1.5.3               RSQLite_2.2.7               e1071_1.7-6                
[61] zip_2.1.1                   GenomeInfoDb_1.26.7         rlang_0.4.10                pkgconfig_2.0.3            
[65] matrixStats_0.58.0          bitops_1.0-7                lattice_0.20-41             bit_4.0.4                  
[69] tidyselect_1.1.0            magrittr_2.0.1              R6_2.5.0                    snow_0.4-3                 
[73] generics_0.1.0              DelayedArray_0.16.3         DBI_1.1.1                   pillar_1.6.0               
[77] haven_2.4.1                 foreign_0.8-80              withr_2.4.2                 mixtools_1.2.0             
[81] survival_3.1-12             abind_1.4-5                 RCurl_1.98-1.3              RedeR_1.38.0               
[85] modelr_0.1.8                crayon_1.4.1                car_3.0-10                  KernSmooth_2.23-17         
[89] utf8_1.2.1                  BiocFileCache_1.14.0        progress_1.2.2              locfit_1.5-9.4             
[93] readxl_1.3.1                data.table_1.14.0           blob_1.2.1                  reprex_2.0.0               
[97] openssl_1.4.3               munsell_0.5.0               askpass_1.1

A very similar question has been recently asked and answered (!) on Biostars: https://www.biostars.org/p/484651/ Please post here if it worked for you as well (or not).