The larger your sample size the more statistical power you will tend to have, meaning you can detect differences with smaller magnitudes. The question you should ask alongside the calculation of a p-value is what magnitude difference is biologically meaningful. For example, if you have a significant p-value but an average difference in genome size of 1 kb I don't suspect that it's biologically interesting.
Going back to your test choice, your test should reflect the parameter that interests you the most. For example, a KS test is sensitive to distribution shape, so you could have the case of identical means but a significant p-value, the conclusion of which might not be terribly interesting or relevant to your question. Just make sure the test used is in line with your parameter of interest.