Eukaryotic regulatory small RNAs (sRNAs) play significant roles in many fundamental cellular processes. As such, they have emerged as useful biomarkers for diseases and cell differentiation states. sRNA-based biomarkers outperform traditional messenger RNA-based biomarkers by testing fewer targets with greater accuracy and providing earlier detection for disease states. Therefore, expression profiling of sRNAs is fundamentally important to further advance the understanding of biological processes, as well as diagnosis and treatment of diseases. High-throughput sequencing (HTS) is a powerful approach for both sRNA discovery and expression profiling. Here, we discuss the general considerations for sRNA-based HTS profiling methods from RNA preparation to sequencing library construction, with a focus on the causes of systematic error. By examining the enzymatic manipulation steps of sRNA expression profiling, this paper aims to demystify current HTS-based sRNA profiling approaches and to aid researchers in the informed design and interpretation of profiling experiments. 1. Introduction RNA in eukaryotic cells can be classified into five categories: ribosomal RNAs (rRNA), transfer RNAs (tRNA), messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and small RNAs (sRNAs). Over 90% of the total RNA molecules present in a cell are rRNA and tRNA, while sRNAs account for ~1% or less. Eukaryotic regulatory sRNAs are a subset of sRNAs ranging in size from ~20 to 30？nt and include microRNAs (miRNAs), small interfering RNAs (siRNAs), and piwi-interacting RNAs (piRNAs). The functions of these regulatory sRNAs are conserved from plants to animals, which imply their involvement in fundamental cellular processes [1]. Discovery and profiling of these regulatory sRNAs are of primary interest to unravel their regulatory functions. High-throughput sequencing (HTS) has revolutionized the study of sRNAs by simultaneously accelerating their discovery and revealing their expression patterns. As we have learned from microarray-based sRNA expression profiling [2, 3], key steps in HTS-based profiling workflows warrant careful consideration in order to either avoid introducing systematic error or to guide interpretation of results. In this paper, we discuss preparation of sRNAs for profiling by HTS and enzymatic manipulation upstream of sequencing library preparation. The purpose of enzymatic manipulation is either to improve representation and reduce bias or to specifically focus on subsets of sRNAs based on end modifications. Furthermore, we review the activities of the enzymes
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