diff --git a/releasenotes/notes/fix-sequence-protocol-e95246e864cc850a.yaml b/releasenotes/notes/fix-sequence-protocol-e95246e864cc850a.yaml
new file mode 100644
index 000000000..4bfb6fe37
--- /dev/null
+++ b/releasenotes/notes/fix-sequence-protocol-e95246e864cc850a.yaml
@@ -0,0 +1,10 @@
+---
+fixes:
+  - |
+    Fixed an issue with the custom sequence return types,
+    :class:`~.BFSSuccessors`, :class:`~.NodeIndices`, :class:`~.EdgeList`,
+    :class:`~.WeightedEdgeList`, :class:`~.EdgeIndices`, and :class:`~.Chains`
+    where they previosuly were missing certain attributes that prevented them
+    being used as a sequence for certain built-in functions such as
+    ``reversed()``.
+    Fixed `#696 <https://github.com/Qiskit/rustworkx/issues/696>`__.
diff --git a/src/iterators.rs b/src/iterators.rs
index 3a403d492..b6e496cc5 100644
--- a/src/iterators.rs
+++ b/src/iterators.rs
@@ -475,7 +475,7 @@ impl PyConvertToPyArray for Vec<(usize, usize, PyObject)> {
 macro_rules! custom_vec_iter_impl {
     ($name:ident, $data:ident, $T:ty, $doc:literal) => {
         #[doc = $doc]
-        #[pyclass(module = "rustworkx")]
+        #[pyclass(module = "rustworkx", sequence)]
         #[derive(Clone)]
         pub struct $name {
             pub $data: Vec<$T>,
diff --git a/tests/rustworkx_tests/test_custom_return_types.py b/tests/rustworkx_tests/test_custom_return_types.py
index 8abf87ae2..2362f125b 100644
--- a/tests/rustworkx_tests/test_custom_return_types.py
+++ b/tests/rustworkx_tests/test_custom_return_types.py
@@ -174,6 +174,12 @@ def test_slices_negatives(self):
         self.assertEqual([2, 3], slice_return)
         self.assertEqual([], indices[-1:-2])
 
+    def test_reversed(self):
+        indices = self.dag.node_indices()
+        reversed_slice = indices[::-1]
+        reversed_elems = list(reversed(indices))
+        self.assertEqual(reversed_slice, reversed_elems)
+
     def test_numpy_conversion(self):
         res = self.dag.node_indexes()
         np.testing.assert_array_equal(np.asarray(res, dtype=np.uintp), np.array([0, 1]))