In my experience (Genomics) this is simply not true. Python has caught on over the last 5 or so years, but prior to that Perl was the defacto language for genetic analysis. Its still quite heavily used. Perl is not a paragon of simplicity and clarity.
I feel like trying out various languages/frameworks would affect compsci labs a lot less than other fields, since the students probably have some foundational knowledge of languages and have already learned a few before getting there. Might be easier for them to pick up new ones.
(a) While I'm being honest that my observations are based on the fields I have experience, there is no such justification that "It is true broadly for computation in academia" in your comment.
(b) Interpreting "niche" as "small" (especially given your "true broadly" claim): Computational genetics is huge in terms of funding dollars and number of researchers.