BUG: DataFrameGroupBy.__getitem__ fails to propagate dropna=True
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [x] (optional) I have confirmed this bug exists on the master branch of pandas.

xref #35014 

Creating a separate issue as the `dropna=True` requires a different fix to `dropna=False`  (resolved by #35078)

#### Problem description

The setup is:
``` python
In [1]: import pandas as pd                                                                                                                    
In [2]: df = pd.DataFrame({"A": [0, 0, 1, None], "B": [1, 2, 3, None]})                                                                        
In [3]: gb = df.groupby("A", dropna=True)                                                                                                      
```
All three of these commands:
``` python
In [4]: gb['B'].transform(len)                                                                                                                 
In [5]: gb[['B']].transform(len)                                                                                                               
In [6]: gb.transform(len)                                                                                                                      
```
generate a variant of this error
``` python
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-4-3bae7d67a46f> in <module>
----> 1 gb['B'].transform(len)

/workspaces/pandas-arw2019/pandas/core/groupby/generic.py in transform(self, func, engine, engine_kwargs, *args, **kwargs)
    487 
    488         if not isinstance(func, str):
--> 489             return self._transform_general(
    490                 func, *args, engine=engine, engine_kwargs=engine_kwargs, **kwargs
    491             )

/workspaces/pandas-arw2019/pandas/core/groupby/generic.py in _transform_general(self, func, engine, engine_kwargs, *args, **kwargs)
    556 
    557         result.name = self._selected_obj.name
--> 558         result.index = self._selected_obj.index
    559         return result
    560 

/workspaces/pandas-arw2019/pandas/core/generic.py in __setattr__(self, name, value)
   5167         try:
   5168             object.__getattribute__(self, name)
-> 5169             return object.__setattr__(self, name, value)
   5170         except AttributeError:
   5171             pass

/workspaces/pandas-arw2019/pandas/_libs/properties.pyx in pandas._libs.properties.AxisProperty.__set__()
     64 
     65     def __set__(self, obj, value):
---> 66         obj._set_axis(self.axis, value)

/workspaces/pandas-arw2019/pandas/core/series.py in _set_axis(self, axis, labels, fastpath)
    422         if not fastpath:
    423             # The ensure_index call above ensures we have an Index object
--> 424             self._mgr.set_axis(axis, labels)
    425 
    426     # ndarray compatibility

/workspaces/pandas-arw2019/pandas/core/internals/managers.py in set_axis(self, axis, new_labels)
    214 
    215         if new_len != old_len:
--> 216             raise ValueError(
    217                 f"Length mismatch: Expected axis has {old_len} elements, new "
    218                 f"values have {new_len} elements"

ValueError: Length mismatch: Expected axis has 3 elements, new values have 4 elements
```
#### Expected Output

All three should return:
``` python                                                                                                                 
Out[9]: 
   B
0  2
1  2
2  1
```

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : 9843926e39dee88f689afc51cbf0f2fdc232dcd3
python           : 3.8.3.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-42-generic
Version          : #46-Ubuntu SMP Fri Jul 10 00:24:02 UTC 2020
machine          : x86_64
processor        : 
byteorder        : little
LC_ALL           : C.UTF-8
LANG             : C.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.2.0.dev0+54.g9843926e3
numpy            : 1.18.5
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 49.1.0.post20200704
Cython           : 0.29.21
pytest           : 5.4.3
hypothesis       : 5.19.0
sphinx           : 3.1.1
blosc            : None
feather          : None
xlsxwriter       : 1.2.9
lxml.etree       : 4.5.2
html5lib         : 1.1
pymysql          : None
psycopg2         : 2.8.5 (dt dec pq3 ext lo64)
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: None
bs4              : 4.9.1
bottleneck       : 1.3.2
fsspec           : 0.7.4
fastparquet      : 0.4.0
gcsfs            : 0.6.2
matplotlib       : 3.2.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.4
pandas_gbq       : None
pyarrow          : 0.17.1
pytables         : None
pyxlsb           : None
s3fs             : 0.4.2
scipy            : 1.5.0
sqlalchemy       : 1.3.18
tables           : 3.6.1
tabulate         : 0.8.7
xarray           : 0.15.1
xlrd             : 1.2.0
xlwt             : 1.3.0
numba            : 0.50.1
</details>
