diff --git a/pandas/core/groupby/grouper.py b/pandas/core/groupby/grouper.py
index 6263d5337f42f..a509acb3604e1 100644
--- a/pandas/core/groupby/grouper.py
+++ b/pandas/core/groupby/grouper.py
@@ -99,6 +99,13 @@ class Grouper:
 
         .. versionadded:: 1.1.0
 
+    dropna : bool, default True
+        If True, and if group keys contain NA values, NA values together with
+        row/column will be dropped. If False, NA values will also be treated as
+        the key in groups.
+
+        .. versionadded:: 1.2.0
+
     Returns
     -------
     A specification for a groupby instruction
@@ -820,7 +827,9 @@ def is_in_obj(gpr) -> bool:
         groupings.append(Grouping(Index([], dtype="int"), np.array([], dtype=np.intp)))
 
     # create the internals grouper
-    grouper = ops.BaseGrouper(group_axis, groupings, sort=sort, mutated=mutated)
+    grouper = ops.BaseGrouper(
+        group_axis, groupings, sort=sort, mutated=mutated, dropna=dropna
+    )
     return grouper, exclusions, obj
 
 
diff --git a/pandas/core/groupby/ops.py b/pandas/core/groupby/ops.py
index b3f91d4623c84..17539cdf451e3 100644
--- a/pandas/core/groupby/ops.py
+++ b/pandas/core/groupby/ops.py
@@ -87,6 +87,7 @@ def __init__(
         group_keys: bool = True,
         mutated: bool = False,
         indexer: Optional[np.ndarray] = None,
+        dropna: bool = True,
     ):
         assert isinstance(axis, Index), axis
 
@@ -97,6 +98,7 @@ def __init__(
         self.group_keys = group_keys
         self.mutated = mutated
         self.indexer = indexer
+        self.dropna = dropna
 
     @property
     def groupings(self) -> List["grouper.Grouping"]:
diff --git a/pandas/tests/groupby/test_groupby_dropna.py b/pandas/tests/groupby/test_groupby_dropna.py
index deb73acbb158a..cd6c17955c18d 100644
--- a/pandas/tests/groupby/test_groupby_dropna.py
+++ b/pandas/tests/groupby/test_groupby_dropna.py
@@ -162,6 +162,14 @@ def test_groupby_dropna_series_by(dropna, expected):
     tm.assert_series_equal(result, expected)
 
 
+@pytest.mark.parametrize("dropna", (False, True))
+def test_grouper_dropna_propagation(dropna):
+    # GH 36604
+    df = pd.DataFrame({"A": [0, 0, 1, None], "B": [1, 2, 3, None]})
+    gb = df.groupby("A", dropna=dropna)
+    assert gb.grouper.dropna == dropna
+
+
 @pytest.mark.parametrize(
     "dropna,df_expected,s_expected",
     [