diff --git a/PRO-seq/PRO-seq.snakefile b/PRO-seq/PRO-seq.snakefile
index fba53191274d181eb6e8491909f53bcbece054f6..c1d503002d387fd3edd79e481a493a6aa7e402fc 100644
--- a/PRO-seq/PRO-seq.snakefile
+++ b/PRO-seq/PRO-seq.snakefile
@@ -169,7 +169,7 @@ ID_LISTS = [
     "germline_specific",
     "histone",
     "spermatogenic_Ortiz_2014", "oogenic_Ortiz_2014",
-    "piRNA_dependent_prot_si_down4_WR_RT_top200", "piRNA_dependent_prot_si_22G_down4",
+    "piRNA_dependent_prot_si_22G_down4_top200", "piRNA_dependent_prot_si_22G_down4",
     "csr1_prot_si_supertargets_common"]
 annot_dir = config["annot_dir"]
 gene_lists_dir = "/pasteur/entites/Mhe/bli/Gene_lists"
@@ -197,9 +197,11 @@ NORM_TYPES = ["protein_coding", "median_ratio_to_pseudo_ref"]
 assert set(NORM_TYPES).issubset(set(SIZE_FACTORS))
 
 # For metagene analyses
-META_MARGIN = 300
+#META_MARGIN = 300
+META_MARGIN = 0
 META_SCALE = 2000
-UNSCALED_INSIDE = 500
+#UNSCALED_INSIDE = 500
+UNSCALED_INSIDE = 0
 #META_MIN_LEN = 1000
 META_MIN_LEN = 2 * UNSCALED_INSIDE
 MIN_DIST = 2 * META_MARGIN
@@ -332,10 +334,11 @@ rule all:
             trimmer=TRIMMERS, norm_type=NORM_TYPES, orientation=["all"]),
         #expand(OPJ(output_dir, "{trimmer}", "figures", aligner, "{lib}_mean", "{orientation}_on_merged_isolated_%d_{biotype}_min_%d_meta_profile.pdf" % (MIN_DIST, META_MIN_LEN)), trimmer=TRIMMERS, lib=LIBS, orientation=["all"], biotype=["protein_coding"]),
         #expand(OPJ(output_dir, "{trimmer}", "figures", aligner, "{lib}_mean", "{orientation}_on_merged_isolated_%d_{biotype}_min_%d_meta_profile.pdf" % (MIN_DIST, META_MIN_LEN)), trimmer=TRIMMERS, lib=LIBS, orientation=["all"], biotype=METAGENE_BIOTYPES),
+        # TODO: Add metagene profiles similar to small RNA-seq
         expand(OPJ(
             output_dir, "{trimmer}", "figures", aligner, "{lib}_by_{norm_type}_mean",
             "{orientation}_on_merged_isolated_%d_{biotype}_min_%d_meta_profile.pdf" % (MIN_DIST, META_MIN_LEN)),
-            trimmer=TRIMMERS, lib=LIBS, norm_type=NORM_TYPES, orientation=["all"],
+            trimmer=TRIMMERS, lib=LIBS, norm_type=NORM_TYPES, orientation=["all", "fwd", "rev"],
             biotype=METAGENE_BIOTYPES),
 
 
@@ -1654,6 +1657,7 @@ def meta_params(wildcards):
         raise NotImplementedError("Metagene analyses for %s not implemented." % biotype)
 
 
+# TODO: make scripts to generate bed given gene names and one to plot the metaprofile
 rule plot_meta_profile_mean:
     input:
         bigwig = rules.merge_bigwig_reps.output.bw,