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Identification and remediation of biases in the activity of RNA ligases in small-RNA deep sequencing.

ABSTRACT: Deep sequencing of small RNAs (sRNA-seq) is now the gold standard for small RNA profiling and discovery. Biases in sRNA-seq have been reported, but their etiology remains unidentified. Through a comprehensive series of sRNA-seq experiments, we establish that the predominant cause of the bias is the RNA ligases. We further demonstrate that RNA ligases have strong sequence-specific biases which distort the small RNA profiles considerably. We have devised a pooled adapter strategy to overcome this bias, and validated the method through data derived from microarray and qPCR. In light of our findings, published small RNA profiles, as well as barcoding strategies using adapter-end modifications, may need to be revisited. Importantly, by providing a wide spectrum of substrate for the ligase, the pooled-adapter strategy developed here provides a means to overcome issues of bias, and generate more accurate small RNA profiles.

SUBMITTER: Jayaprakash AD

PROVIDER: S-EPMC3241666 | biostudies-literature | 2011 Nov

REPOSITORIES: biostudies-literature

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Identification and remediation of biases in the activity of RNA ligases in small-RNA deep sequencing.

Jayaprakash Anitha D AD Jabado Omar O Brown Brian D BD Sachidanandam Ravi R

Nucleic acids research 20110902 21

Deep sequencing of small RNAs (sRNA-seq) is now the gold standard for small RNA profiling and discovery. Biases in sRNA-seq have been reported, but their etiology remains unidentified. Through a comprehensive series of sRNA-seq experiments, we establish that the predominant cause of the bias is the RNA ligases. We further demonstrate that RNA ligases have strong sequence-specific biases which distort the small RNA profiles considerably. We have devised a pooled adapter strategy to overcome this ...[more]

PMID: 21890899

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Project description:Maize streak Reunion virus (MSRV) is a member of the Mastrevirus genus in the family Geminiviridae. Of the diverse and increasing number of mastrevirus species found so far, only Wheat dwarf virus and Sweetpotato symptomless virus 1 have been discovered in China. Recently, a novel, unbiased approach based on deep sequencing of small interfering RNAs followed by de novo assembly of siRNA, has greatly offered opportunities for plant virus identification.Samples collected from maize leaves was deep sequencing for virus identification. Subsequently, the assay of PCR, rolling circle amplification and Southern blot were used to confirm the presence of a mastrevirus.Maize streak Reunion virus Yunnan isolate (MSRV-[China:Yunnan 06:2014], abbreviated to MSRV-YN) was identified from maize collected from Yunnan Province, China, by small RNA deep sequencing. The complete genome of this virus was ascertained as 2,880 nucleotides long by conventional sequencing. A phylogenetic analysis showed it shared 96.3 % nucleotide sequence identity with the isolate of Maize streak Reunion virus from La Reunion Island. To our knowledge, this is the first identification of MSRV in China. Analyses of the viral derived small interfering RNAs (vsiRNAs) profile showed that the most abundant MSRV-YN vsiRNAs were 21, 22 and 24 nt long and biased for A and G at their 5' terminal residue. There was a slightly higher representation of MSRV-YN siRNAs derived from the virion-sense strand genome than the complementary-sense strand genome. Moreover, MSRV-YN vsiRNAs were not uniformly distributed along the genome, and hotspots were detected in the movement protein and coat protein-coding region.A mastrevirus MSRV-YN collected in Yunnan Province, China, was identified by small RNA deep sequencing. This vsiRNAs profile derived from MSRV-YN was characterized, which might contribute to get an insight into the host RNA silencing defense induced by MSRV-YN, and provide guidelines on designing antiviral strategies using RNAi against MSRV-YN.

Project description:BackgroundMicroRNAs (miRNAs) are one of the functional non-coding small RNAs involved in the epigenetic control of the plant genome. Although plants contain both evolutionary conserved miRNAs and species-specific miRNAs within their genomes, computational methods often only identify evolutionary conserved miRNAs. The recent sequencing of the Brassica rapa genome enables us to identify miRNAs and their putative target genes. In this study, we sought to provide a more comprehensive prediction of B. rapa miRNAs based on high throughput small RNA deep sequencing.ResultsWe sequenced small RNAs from five types of tissue: seedlings, roots, petioles, leaves, and flowers. By analyzing 2.75 million unique reads that mapped to the B. rapa genome, we identified 216 novel and 196 conserved miRNAs that were predicted to target approximately 20% of the genome's protein coding genes. Quantitative analysis of miRNAs from the five types of tissue revealed that novel miRNAs were expressed in diverse tissues but their expression levels were lower than those of the conserved miRNAs. Comparative analysis of the miRNAs between the B. rapa and Arabidopsis thaliana genomes demonstrated that redundant copies of conserved miRNAs in the B. rapa genome may have been deleted after whole genome triplication. Novel miRNA members seemed to have spontaneously arisen from the B. rapa and A. thaliana genomes, suggesting the species-specific expansion of miRNAs. We have made this data publicly available in a miRNA database of B. rapa called BraMRs. The database allows the user to retrieve miRNA sequences, their expression profiles, and a description of their target genes from the five tissue types investigated here.ConclusionsThis is the first report to identify novel miRNAs from Brassica crops using genome-wide high throughput techniques. The combination of computational methods and small RNA deep sequencing provides robust predictions of miRNAs in the genome. The finding of numerous novel miRNAs, many with few target genes and low expression levels, suggests the rapid evolution of miRNA genes. The development of a miRNA database, BraMRs, enables us to integrate miRNA identification, target prediction, and functional annotation of target genes. BraMRs will represent a valuable public resource with which to study the epigenetic control of B. rapa and other closely related Brassica species. The database is available at the following link: http://bramrs.rna.kr [1].

Dataset Information

Identification and remediation of biases in the activity of RNA ligases in small-RNA deep sequencing.

Publications

Identification and remediation of biases in the activity of RNA ligases in small-RNA deep sequencing.

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