OPTIMIR, a novel algorithm for integrating available genome-wide genotype data into miRNA sequence alignment analysis

Abstract

Next-generation sequencing is an increasingly popular and efficient approach to characterize the full set of microRNAs (miRNAs) present in human biosamples. MiRNAs' detection and quantification still remain a challenge as they can undergo different posttranscriptional modifications and might harbor genetic variations (polymiRs) that may impact on the alignment step. We present a novel algorithm, OPTIMIR, that incorporates biological knowledge on miRNA editing and genome-wide genotype data available in the processed samples to improve alignment accuracy. OPTIMIR was applied to 391 human plasma samples that had been typed with genome-wide genotyping arrays. OPTIMIR was able to detect genotyping errors, suggested the existence of novel miRNAs and highlighted the allelic imbalance expression of polymiRs in heterozygous carriers. OPTIMIR is written in python, and freely available on the GENMED website (http://www.genmed.fr/ index.php/fr/) and on Github (github.com/FlorianThibord/OptimiR).

Paired-end small RNA sequencing reveals a possible overestimation in the isomiR sequence repertoire previously reported from conventional single read data analysis

“…For miRNAs analysis at the isomiR resolution level, XICRA allows the user to use either miraligner [ 26 ], sRNAbench from sRNAtoolbox [ 27 ] or OPTIMIR [ 28 ]. Each software uses different strategies and might produce different results [ 36 ].…”

“…As a prerequisite, the pipeline had to be capable of handling both SR and PE reads. It takes compressed fastq files as input, performs a quality check, trims and merges reads in the same pair, maps them using third party tools, such as miraligner [ 26 ], sRNAbench [ 27 ] or OPTIMIR [ 28 ], and generates a gtf file for each sample using miRTOP to annotate isomiRs adopting the latest proposed naming consensus by ‘license plate’ unique identifiers. The pipeline tests for differential expression DE to identify which isomiRs are significantly upregulated or downregulated between conditions.…”

Paired-end small RNA sequencing reveals a possible overestimation in the isomiR sequence repertoire previously reported from conventional single read data analysis

“…For miRNAs analysis at the isomir resolution level, XICRA allows the user to use either miraligner [26], sRNAbench from sRNAtoolbox [27] or OPTIMIR [28]. Each software uses different strategies and might produce different results [35].…”

“…As a prerequisite, the pipeline had to be capable of handling both SR and PE reads. It takes compressed fastq les as input, performs a quality check, trims and merges reads in the same pair, maps them using third party tools, such as miraligner [26], sRNAbench [27] or OPTIMIR [28], and generates a gtf le for each sample using miRTOP to annotate isomirs adopting the latest proposed naming consensus by 'license plate' unique identi ers. The pipeline tests for differential expression DE to identify which isomirs are signi cantly upregulated or downregulated between conditions.…”

Extracellular microRNA 3’ end modification across diverse body fluids

“…1A). While other methods to identify miRNA sequence variations exist [28][29][30][31][32][33][34][35][36] , our method aims to improve the mapping strategies and reduce false positive modifications (Methods). Briefly, in the mapping steps, we sequentially trim the ends of unmapped reads (separately for 3' and 5' ends) and check for one or more consecutive NTAs.…”