Probabilistic error correction for RNA sequencing

Le, Hai-Son; Schulz, Marcel H.; McCauley, Brenna M. M.; Hinman, Veronica F.; Bar‐Joseph, Ziv

doi:10.1093/nar/gkt215

Cited by 79 publications

(97 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The holothurian P. parvimensis was developed as an experimental developmental system only recently, once improved methods for spawning animals were established (38,39). Those earlier studies revealed that P. parvimensis has an alx1-expressing PMC-like cell lineage that produces a small larval spicule.…”

Section: Resultsmentioning

confidence: 99%

Paleogenomics of echinoids reveals an ancient origin for the double-negative specification of micromeres in sea urchins

Thompson

Erkenbrack

Hinman

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

View full text Add to dashboard Cite

Establishing a timeline for the evolution of novelties is a common, unifying goal at the intersection of evolutionary and developmental biology. Analyses of gene regulatory networks (GRNs) provide the ability to understand the underlying genetic and developmental mechanisms responsible for the origin of morphological structures both in the development of an individual and across entire evolutionary lineages. Accurately dating GRN novelties, thereby establishing a timeline for GRN evolution, is necessary to answer questions about the rate at which GRNs and their subcircuits evolve, and to tie their evolution to paleoenvironmental and paleoecological changes. Paleogenomics unites the fossil record and all aspects of deep time, with modern genomics and developmental biology to understand the evolution of genomes in evolutionary time. Recent work on the regulatory genomic basis of development in cidaroid echinoids, sand dollars, heart urchins, and other nonmodel echinoderms provides an ideal dataset with which to explore GRN evolution in a comparative framework. Using divergence time estimation and ancestral state reconstructions, we have determined the age of the double-negative gate (DNG), the subcircuit which specifies micromeres and skeletogenic cells in Strongylocentrotus purpuratus. We have determined that the DNG has likely been used for euechinoid echinoid micromere specification since at least the Late Triassic. The innovation of the DNG thus predates the burst of post-Paleozoic echinoid morphological diversification that began in the Early Jurassic. Paleogenomics has wide applicability for the integration of deep time and molecular developmental data, and has wide utility in rigorously establishing timelines for GRN evolution.evolution | evo-devo | euechinoid | cidaroid | gene regulatory networks

show abstract

Section: Resultsmentioning

confidence: 99%

Paleogenomics of echinoids reveals an ancient origin for the double-negative specification of micromeres in sea urchins

Thompson

Erkenbrack

Hinman

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Error correction has been shown to significantly improve the quality of de novo assembly of both genomes ) and transcriptomes (MacManes & Eisen 2013). Due to the significant benefits from error correction in de novo assembly, a number of tools are available to perform this task; many of them have been summarized in a recent review (Yang et al 2013a), yet new tools are still being developed (Ilie & Molnar 2013;Le et al 2013;Liu et al 2013b;Marcais et al 2013;Nikolenko et al 2013;Sleep et al 2013), including ones that are specially tailored for data sets with highly uneven coverage (e.g. SEECER for transcriptome data and BAYESHAMMER for single-cell sequencing studies).…”

Section: Box 2 Adapter and Quality Trimming Tools For Hts Sequence Rementioning

confidence: 99%

Prevention, diagnosis and treatment of high‐throughput sequencing data pathologies

Zhou

Rokas

2014

Molecular Ecology

View full text Add to dashboard Cite

High-throughput sequencing (HTS) technologies generate millions of sequence reads from DNA/RNA molecules rapidly and cost-effectively, enabling single investigator laboratories to address a variety of 'omics' questions in nonmodel organisms, fundamentally changing the way genomic approaches are used to advance biological research. One major challenge posed by HTS is the complexity and difficulty of data quality control (QC). While QC issues associated with sample isolation, library preparation and sequencing are well known and protocols for their handling are widely available, the QC of the actual sequence reads generated by HTS is often overlooked. HTS-generated sequence reads can contain various errors, biases and artefacts whose identification and amelioration can greatly impact subsequent data analysis. However, a systematic survey on QC procedures for HTS data is still lacking. In this review, we begin by presenting standard 'health check-up' QC procedures recommended for HTS data sets and establishing what 'healthy' HTS data look like. We next proceed by classifying errors, biases and artefacts present in HTS data into three major types of 'pathologies', discussing their causes and symptoms and illustrating with examples their diagnosis and impact on downstream analyses. We conclude this review by offering examples of successful 'treatment' protocols and recommendations on standard practices and treatment options. Notwithstanding the speed with which HTS technologies -and consequently their pathologies -change, we argue that careful QC of HTS data is an important -yet often neglected -aspect of their application in molecular ecology, and lay the groundwork for developing a HTS data QC 'best practices' guide.

show abstract

“…In the present study I chose SEECER (LE et al 2013) to correct potential sequencing errors in our dataset before transcriptome assembly. Oases, Trans-ABySS have their own way to merge multiple k-mers.…”

Section: Reads Correction and Filteringmentioning

confidence: 99%

“…Analyzer was reported to be up to 3.8% (LE et al 2013), proper quality control should be executed to assure the accuracy of data analysis. A common approach to control reads error rates is to trim off bad quality bases from read ends.…”

Section: Rnaseq Reads Error Correctionmentioning

confidence: 99%

“…A recent study has examined different ways of RNASeq reads error correction and showed that RNAseq assembly using error-corrected reads could improve assembly quality . Here, I chose SEECER (SEquencing Error CorrEction in Rna-seq data) (LE et al 2013), a software specifically designed for RNAseq data error correction, to correct potential errors in our RNAseq data.…”

Section: Rnaseq Reads Error Correctionmentioning

confidence: 99%

See 1 more Smart Citation

Developing genomic resources for an emerging ecological model species Senecio lautus

Liu¹

View full text Add to dashboard Cite

Next generation sequencing (NGS) technologies have seen successful applications in ecology and evolutionary biology. The ever expanded applications of NGS to non-model organisms in the wild populations make it possible to address important ecological and evolutionary questions at larger and more precise scales. These questions vary from deciphering the genetic basis of traits underlying rapid ecological adaptation and speciation to identifying the genome wide differentiation patterns of populations at different divergence stages. The later question can only be answered when the whole genome of the species is available. The Australian groundsel, i.e., Senecio lautus is a good system to study ecological speciation. This species complex consists of multiple ecotypes adapting to different environments, among which the Dune and Headland ecotypes occur proximately to each other in several coastal localities of Australia, displaying very contrasting morphologies despite being interfertile. Phylogenetic analyses supported independent origination of each Dune and Headland pairs and ecological studies have correlated phenotypic difference with environmental adaptation. Here I used methylation filtration to develop gene space and transcriptome sequencing (RNAseq) to construct reference transcriptome for this species. I explored multiple strategies to optimize the final results in terms of assembly completeness, accuracy and contiguity. For gene space sequence assembly, I found hybridizing results from different assemblers used for assembling specific data type is better than combining results from hybrid assemblers (i.e., assemblers assembling all types of data at once). In the case of transcriptome assembly, I found the multiple spectrum assembly strategy (i.e., multiple assembly parameters and multiple assemblers) reconstructed more genes, but introduced more redundancy, complicating downstream analyses such as gene family reconstruction, phylogenetic and population genetics analyses. I also found that redundancy reduction based on expression level is better than the other methods. I used gene space assembly as reference sequences to detect the genome wide divergence patterns of multiple Dune and Headland ecotypes and found that geographic distance affects the magnitude of genetic differentiation between populations, but not the genomic divergence patterns. Applying pooled RNAseq to four S. lautus ecotypes allows population genomics and molecular evolution analyses leading to the finding of short divergence time among these ecotypes and candidate genes that have potentially contributed to adaptive divergence of S. lautus. Moreover, I also found decoupled differential gene expression and coding sequence divergence patterns, suggesting the rapid divergence of S. lautus has been achieved through evolution at both levels. These works are essential to shape S. lautus up as an excellent system to study ecological speciation with gene flow.

show abstract

Probabilistic error correction for RNA sequencing

Cited by 79 publications

References 52 publications

Paleogenomics of echinoids reveals an ancient origin for the double-negative specification of micromeres in sea urchins

Paleogenomics of echinoids reveals an ancient origin for the double-negative specification of micromeres in sea urchins

Prevention, diagnosis and treatment of high‐throughput sequencing data pathologies

Developing genomic resources for an emerging ecological model species Senecio lautus

Contact Info

Product

Resources

About