I performed comprehensive analysis for profiling of APA patterns in single-cell resolution by 10x Genomics scRNA-seq data in collaboration with Fly Cell Atlas (FCA) project. By discovering and leveraging cell-specific patterns of 3' isoforms, we illustrate many ways in which broadly expressed genes can still contribute to defining cell states, whether they be different types of post-mitotic cells such as neurons and gametes, to stages along the differentiation of various types of stem cells. This study is the first single cell resolution analysis to permit variable utilization of both tandem 3’ UTRs (TUTR-APA) and alternative last exons (ALE-APA), which generates distinct coding isoforms with completely different 3’UTRs amongst isoforms.