Exception when executing task graph with HighLevelGraph after a shuffle

**Describe the issue**:

In https://github.com/geopandas/dask-geopandas/issues/303, dask-geopandas has a report that its custom `sjoin` method fails with a TypeError under some conditions. Internally, that method [constructs a HighLevelGraph](https://github.com/geopandas/dask-geopandas/blob/19e0110d86a0c67df0067947d99327a0bdbca2b0/dask_geopandas/sjoin.py#L109).

The observed failure is a `TypeError` raised by geopandas because dask fails to substitute the concrete (geo)DataFrame for the key `(name, partition_number)` when executing the task graph.

I've managed to produce a dask / dask-expr only version:

**Minimal Complete Verifiable Example**:

```python
import dask.dataframe as dd
import pandas as pd
import dask
import dask_expr

dask.config.set(scheduler="single-threaded")

l1 = dd.from_pandas(pd.DataFrame({"a": [1, 2], "b": [0, 0]}), npartitions=1).shuffle("a")
r1 = dd.from_pandas(pd.DataFrame({"a": [1, 3], "c": [1, 1]}), npartitions=1).shuffle("a")

def func(left, right):
assert isinstance(left, pd.DataFrame), f"Wrong type {left}"
return pd.merge(left, right, how="inner")

dsk = {}
name = "myjoin-" + dask.base.tokenize(l1, r1, ensure_deterministic=True)
for i in range(1):
dsk[(name, i)] = (
func,
(l1._name, i),
(r1._name, i),
)

divisions = [None] * (len(dsk) + 1)
g1 = dask.highlevelgraph.HighLevelGraph.from_collections(name, dsk, dependencies=[l1, r1])
x1 = dask_expr.from_graph(g1, func(l1._meta, r1._meta), divisions, dsk.keys(), "myjoin")
x1.compute()
```

That fails with

```pytb
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
Cell In[3], line 30
28 g1 = dask.highlevelgraph.HighLevelGraph.from_collections(name, dsk, dependencies=[l1, r1])
29 x1 = dask_expr.from_graph(g1, func(l1._meta, r1._meta), divisions, dsk.keys(), "myjoin")
---> 30 x1.compute()

File [~/gh/geopandas/dask-geopandas/.direnv/python-3.10/lib/python3.10/site-packages/dask_expr/_collection.py:477](http://127.0.0.1:8889/~/gh/geopandas/dask-geopandas/.direnv/python-3.10/lib/python3.10/site-packages/dask_expr/_collection.py#line=476), in FrameBase.compute(self, fuse, **kwargs)
475 out = out.repartition(npartitions=1)
476 out = out.optimize(fuse=fuse)
--> 477 return DaskMethodsMixin.compute(out, **kwargs)

File [~/gh/geopandas/dask-geopandas/.direnv/python-3.10/lib/python3.10/site-packages/dask/base.py:376](http://127.0.0.1:8889/~/gh/geopandas/dask-geopandas/.direnv/python-3.10/lib/python3.10/site-packages/dask/base.py#line=375), in DaskMethodsMixin.compute(self, **kwargs)
352 def compute(self, **kwargs):
353 """Compute this dask collection
354
355 This turns a lazy Dask collection into its in-memory equivalent.
(...)
374 dask.compute
375 """
--> 376 (result,) = compute(self, traverse=False, **kwargs)
377 return result

File [~/gh/geopandas/dask-geopandas/.direnv/python-3.10/lib/python3.10/site-packages/dask/base.py:662](http://127.0.0.1:8889/~/gh/geopandas/dask-geopandas/.direnv/python-3.10/lib/python3.10/site-packages/dask/base.py#line=661), in compute(traverse, optimize_graph, scheduler, get, *args, **kwargs)
659 postcomputes.append(x.__dask_postcompute__())
661 with shorten_traceback():
--> 662 results = schedule(dsk, keys, **kwargs)
664 return repack([f(r, *a) for r, (f, a) in zip(results, postcomputes)])

Cell In[3], line 14, in func(left, right)
13 def func(left, right):
---> 14 assert isinstance(left, pd.DataFrame), f"Wrong type {left}"
15 return pd.merge(left, right, how="inner")

AssertionError: Wrong type ('rearrangebycolumn-8e5135a4ed46029cf9bb3c4bc7eff32e', 0)
```

As I mentioned, the `shuffle` there is important. Without that shuffle, things work fine.

**Anything else we need to know?**:

I'll take a look at this today.

**Environment**:

- Dask version: '2024.8.1'
- dask-expr version: '1.1.11'

Run the minimal complete verifiable example with Dask 2024.8.1 and dask-expr 1.1.11, then inspect the HighLevelGraph construction in dask_geopandas/sjoin.py and the dask_expr.from_graph call. Trace how shuffle keys are resolved during x1.compute(); done means the graph substitutes concrete DataFrames and the example completes without the TypeError.

Written by the indexing model from the issue text.