Passing a timezone-aware string to pd.to_datetime creates a timezone-naive Timestamp 
#### Code Sample

```python
>>> pd.to_datetime('2017-01-01T15:00:00-05:00')
... Timestamp('2017-01-01 20:00:00')  # This is a timezone-naive Timestamp, but was converted to UTC
```
#### Problem description

Given a timezone-aware string (e.g., in ISO8601 format), `pd.to_datetime` converts the string to UTC time, but doesn't set the `tzinfo` to UTC.

This makes it difficult to differentiate between string that are truly timezone-naive strings (e.g., '2017-01-01') and timezone-aware strings (e.g., '2017-01-01T15:00:00-05:00').

#### Expected Output

Option 1: Convert the string to UTC (current behavior) and also set the timezone to UTC:
```python
>>> pd.to_datetime('2017-01-01T15:00:00-05:00')
... Timestamp('2017-01-01 20:00:00+0000', tz='UTC')
```

Option 2: Don't convert to UTC and retain timezone. This is the behavior of `dateutil.parser.parse`:
```python
>>> pd.to_datetime(parser.parse('2017-01-01T15:00:00-0500'))
... Timestamp('2017-01-01 15:00:00-0500', tz='tzoffset(None, -18000)')
```

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

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.5.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.1.35-pv-ts1
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.20.3
pytest: 3.1.2
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.1
xarray: None
IPython: 6.1.0
sphinx: 1.6.2
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.3.0
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.7
xlrd: 1.0.0
xlwt: None
xlsxwriter: 0.9.6
lxml: None
bs4: 4.6.0
html5lib: 0.999
sqlalchemy: 1.1.11
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None
</details>
