TY - CHAP
T1 - Illuminating lncRNA Function Through Target Prediction
AU - Chiu, Hua Sheng
AU - Somvanshi, Sonal
AU - Chen, Ting-Wen
AU - Sumazin, Pavel
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2021/8/21
Y1 - 2021/8/21
N2 - Most of the transcribed human genome codes for noncoding RNAs (ncRNAs), and long noncoding RNAs (lncRNAs) make for the lion’s share of the human ncRNA space. Despite growing interest in lncRNAs, because there are so many of them, and because of their tissue specialization and, often, lower abundance, their catalog remains incomplete and there are multiple ongoing efforts to improve it. Consequently, the number of human lncRNA genes may be lower than 10,000 or higher than 200,000. A key open challenge for lncRNA research, now that so many lncRNA species have been identified, is the characterization of lncRNA function and the interpretation of the roles of genetic and epigenetic alterations at their loci. After all, the most important human genes to catalog and study are those that contribute to important cellular functions—that affect development or cell differentiation and whose dysregulation may play a role in the genesis and progression of human diseases. Multiple efforts have used screens based on RNA-mediated interference (RNAi), antisense oligonucleotide (ASO), and CRISPR screens to identify the consequences of lncRNA dysregulation and predict lncRNA function in select contexts, but these approaches have unresolved scalability and accuracy challenges. Instead—as was the case for better-studied ncRNAs in the past—researchers often focus on characterizing lncRNA interactions and investigating their effects on genes and pathways with known functions. Here, we focus most of our review on computational methods to identify lncRNA interactions and to predict the effects of their alterations and dysregulation on human disease pathways.
AB - Most of the transcribed human genome codes for noncoding RNAs (ncRNAs), and long noncoding RNAs (lncRNAs) make for the lion’s share of the human ncRNA space. Despite growing interest in lncRNAs, because there are so many of them, and because of their tissue specialization and, often, lower abundance, their catalog remains incomplete and there are multiple ongoing efforts to improve it. Consequently, the number of human lncRNA genes may be lower than 10,000 or higher than 200,000. A key open challenge for lncRNA research, now that so many lncRNA species have been identified, is the characterization of lncRNA function and the interpretation of the roles of genetic and epigenetic alterations at their loci. After all, the most important human genes to catalog and study are those that contribute to important cellular functions—that affect development or cell differentiation and whose dysregulation may play a role in the genesis and progression of human diseases. Multiple efforts have used screens based on RNA-mediated interference (RNAi), antisense oligonucleotide (ASO), and CRISPR screens to identify the consequences of lncRNA dysregulation and predict lncRNA function in select contexts, but these approaches have unresolved scalability and accuracy challenges. Instead—as was the case for better-studied ncRNAs in the past—researchers often focus on characterizing lncRNA interactions and investigating their effects on genes and pathways with known functions. Here, we focus most of our review on computational methods to identify lncRNA interactions and to predict the effects of their alterations and dysregulation on human disease pathways.
KW - LongHorn
KW - Noncoding RNA
KW - Systems biology
KW - Target prediction
KW - lncRNA
UR - http://www.scopus.com/inward/record.url?scp=85113847645&partnerID=8YFLogxK
U2 - 10.1007/978-1-0716-1697-0_22
DO - 10.1007/978-1-0716-1697-0_22
M3 - Chapter
C2 - 34417758
AN - SCOPUS:85113847645
T3 - Methods in Molecular Biology
SP - 263
EP - 295
BT - Methods in Molecular Biology
PB - Humana Press Inc.
ER -