Shopping in Virtual Reality (VR) contains numerous advantages, such as detailed product diagnosticity and virtually unlimited store space. It also provides superior hedonic features compared to traditional online shopping. However, Recommender Systems (RSs), which are commonly used to assist users in finding preferred products in online shopping, have not yet been extensively researched in VR shopping. It is crucial to understand how users experience RSs and perceive the recommendation results within VR stores. To address the research gaps, we compared three presentation methods (Arrow, Highlight, Swap) with varying levels of perceptibility for an RS in VR shopping. A within-subject study (N=14) revealed that the methods with higher perceptibility enhanced user experiences, reduced perceived workload, and garnered more preferences. Additionally, we examined the effects of these presentation designs on sense of agency and trust in RS, with a focus on the interaction between trust and users' prior trust. Our study contributes to the design of RS interfaces and the future implementation of Trustworthy Recommender Systems (TRS) in VR shopping.