In a random forest with several decision trees, why are the root nodes for the different decision trees not necessarily the same?

Each attribute in a dataset must be used as a root node for one decision tree.

Individual decision trees in a random forest are meant to make overall predictions based on the attribute at the node.

Researchers choose the root nodes in a random forest based on experience.

Attributes considered for the splits in the decision trees are selected at random.