Dynamic poly(A)-tail tuning is a central mechanism to control eukaryotic mRNA translation and stability. A more comprehensive understanding of poly(A)-tail-tuned regulation requires an unbiased abundance quantification of the poly(A)-tail length-sorted transcripts on the common-used high-throughput sequencing platforms. However, current methods have limitations due to each method-specified complicated setups and elaborate library-preparing plan-introduced biases. Here we describe the Central Limit Theorem (CLT)-managed RNA-seq (CLT-seq) as a simple homopolymer-sequencing concept. Since the anchor-free oligo(dT) equiprobably bound to and rapidly unbound from any low-affinity binding complementary segment of the poly(A) tail till it was primed by a coincident-loading transcriptase, the CLT mechanism enables the CLT-shortened poly(T) lengths that correspond to poly(A) tail to distribute normally. Based on the well-fitted pseudoguassion-derived poly(A)-poly(T) conversion model, the actual poly(A)-tail profile is reconstructed from the acquired poly(T)-length profile through matrix operations. The CLT-seq followed a simple procedure without pre-treatment, enrichment, and selection of the total RNA and the CLT-shortened poly(T) stretches are more compatible with existing sequencing platforms. This conceptual approach facilitates the straightforward homopolymer base-calling and features the unbiased RNA-seq. Therefore, the CLT-seq provides unbiased, robust, and cost-efficient transcriptome-wide poly(A)-tail profiling. We demonstrate that the CLT-seq on the most common Illumina platform delivers high-quality poly(A)-tail profiling at a transcriptome-wide scale in human cellular contexts. We find that the poly(A)-tail-tuned ncRNA regulation underwent a dynamic complex process as the mRNA.