Plant genome and transcriptome annotations: from misconceptions to simple solutions

Bolger, Marie E.; Arsova, Borjana; Usadel, Björn

doi:10.1093/bib/bbw135

Cited by 67 publications

(74 citation statements)

References 121 publications

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“…In addition to using established techniques such as BUSCO, comparing the whole plant gene set data against the backdrop of closely related species promises to become a versatile tool (Bolger et al, 2017) and the comparison can be largely automated (Lohse et al, 2014;Lyons and Freeling, 2008).…”

Section: Genome Assemblies Made Cheaper and Easiermentioning

confidence: 99%

“…To date, the genomes of ;200 plant species have been published (www.plabipd.de) (Bolger et al, 2017), yet sequencing plant genomes remains comparatively difficult due to their large sizes and high repeat content (Jiao and Schneeberger, 2017). Long-range data are extremely valuable for resolving repetitive genomic regions and several new technologies have made substantial advances in this area.…”

Section: Introductionmentioning

confidence: 99%

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De Novo Assembly of a New Solanum pennellii Accession Using Nanopore Sequencing

et al. 2017

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Updates in nanopore technology have made it possible to obtain gigabases of sequence data. Prior to this, nanopore sequencing technology was mainly used to analyze microbial samples. Here, we describe the generation of a comprehensive nanopore sequencing data set with a median read length of 11,979 bp for a self-compatible accession of the wild tomato species Solanum pennellii. We describe the assembly of its genome to a contig N50 of 2.5 MB. The assembly pipeline comprised initial read correction with Canu and assembly with SMARTdenovo. The resulting raw nanopore-based de novo genome is structurally highly similar to that of the reference S. pennellii LA716 accession but has a high error rate and was rich in homopolymer deletions. After polishing the assembly with Illumina reads, we obtained an error rate of <0.02% when assessed versus the same Illumina data. We obtained a gene completeness of 96.53%, slightly surpassing that of the reference S. pennellii. Taken together, our data indicate that such long read sequencing data can be used to affordably sequence and assemble gigabase-sized plant genomes.

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Section: Genome Assemblies Made Cheaper and Easiermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

De Novo Assembly of a New Solanum pennellii Accession Using Nanopore Sequencing

et al. 2017

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“…The assembled transcriptomes selected as references for differential gene expression (TRINITY guided , see criteria later) was annotated using Trinotate, a pipeline for functional annotation of transcriptomes (Bolger, Arsova, & Usadel, 2017). First, similarities to known proteins were detected by a BLASTX search (Camacho et al, 2009) (e ≤ 1e−5) against two comprehensive protein databases: Swiss-Prot (Boeckmann et al, 2005) and UniRef90 (The UniProt Consortium, 2015) obtained from UniProt (available on Mar 8, 2018).…”

Section: Functional Annotation and Identification Of Contaminants Onmentioning

confidence: 99%

Utilization of tissue ploidy level variation inde novotranscriptome assembly ofPinus sylvestris

Ojeda

Mattila

Ruttink

et al. 2018

Preprint

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Compared to angiosperms, gymnosperms lag behind in the availability of assembled and annotated genomes. Most genomic analyses in gymnosperms, especially conifer tree species, rely on the use of de novo assembled transcriptomes. However, the level of allelic redundancy and transcript fragmentation in these assembled transcriptomes, and their effect on downstream applications have not been fully investigated. Here, we assessed three assembly strategies, including the utility of haploid (megagametophyte) tissue during de novo assembly as single-allele guides, for six individuals and five different tissues in Pinus sylvestris. We then contrasted haploid and diploid tissue genotype calls obtained from the assembled transcriptomes to evaluate the extent of paralog mapping. The use of the haploid tissue during assembly increased its completeness without reducing the number of assembled transcripts. Our results suggest that current strategies that rely on available genomic resources as guidance to minimize allelic redundancy are less effective than the application of strategies that cluster redundant assembled transcripts. The strategy yielding the lowest levels of allelic redundancy among the assembled transcriptomes assessed here was the generation of SuperTranscripts with Lace followed by CD-HIT clustering. However, we still observed some levels of heterozygosity (multiple gene fragments per transcript reflecting allelic redundancy) in this assembled transcriptome on the haploid tissue, indicating that further filtering is required before using these assemblies for downstream applications. We discuss the influence of allelic redundancy when these reference transcriptomes are used to select regions for probe design of exome capture baits and for estimation of population genetic diversity.

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“…There are many tools available that automatically annotate genes using ontologies such as the Mercator automated annotation tool (Lohse et al ., ), BLAST2GO (Conesa and Gotz, ), KEGG Automatic Annotation Server (KAAS) (Moriya et al ., ), and TRAPID (Van Bel et al ., ) (reviewed in Bolger et al ., 2017a). The overarching goal of these tools is the rapid automatic annotation of genes to a high standard, approaching that of manual annotation.…”

Section: Introductionmentioning

confidence: 99%

Computational aspects underlying genome to phenome analysis in plants

et al. 2019

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Summary Recent advances in genomics technologies have greatly accelerated the progress in both fundamental plant science and applied breeding research. Concurrently, high‐throughput plant phenotyping is becoming widely adopted in the plant community, promising to alleviate the phenotypic bottleneck. While these technological breakthroughs are significantly accelerating quantitative trait locus (QTL) and causal gene identification, challenges to enable even more sophisticated analyses remain. In particular, care needs to be taken to standardize, describe and conduct experiments robustly while relying on plant physiology expertise. In this article, we review the state of the art regarding genome assembly and the future potential of pangenomics in plant research. We also describe the necessity of standardizing and describing phenotypic studies using the Minimum Information About a Plant Phenotyping Experiment (MIAPPE) standard to enable the reuse and integration of phenotypic data. In addition, we show how deep phenotypic data might yield novel trait−trait correlations and review how to link phenotypic data to genomic data. Finally, we provide perspectives on the golden future of machine learning and their potential in linking phenotypes to genomic features.

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Plant genome and transcriptome annotations: from misconceptions to simple solutions

Cited by 67 publications

References 121 publications

De Novo Assembly of a New Solanum pennellii Accession Using Nanopore Sequencing

De Novo Assembly of a New Solanum pennellii Accession Using Nanopore Sequencing

Utilization of tissue ploidy level variation inde novotranscriptome assembly ofPinus sylvestris

Computational aspects underlying genome to phenome analysis in plants

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