Leveraging multiple transcriptome assembly methods for improved gene structure annotation

Venturini, Luca; Caim, Shabhonam; Kaithakottil, Gemy; Mapleson, Daniel; Swarbreck, David

doi:10.1093/gigascience/giy093

Cited by 155 publications

(123 citation statements)

References 43 publications

(55 reference statements)

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“…We downloaded coding sequences from the C. hirsuta genomic resources web site http://chi.mpipz.mpg.de/download/annotations/carhr38.cds.fa and mapped to C. amara using gmap. The resulting sam file was converted to bam-format, sorted and indexed via samtools (v. 1.7) 58 , and then converted to GTF-format via the 'convert' script in Mikado (v1.2.3) 67 which was subsequently used to build a snpEFF (v. 4.3) 68 database. We overlapped the candidate minimum rank sum SNPs with candidate SNPs from fineMAV analysis and annotated each SNP identified by both methods with gene to which it belongs.…”

Section: Window-based Selection Scan Using a Quartet Designmentioning

confidence: 99%

Genomic novelty and process-level convergence in adaptation to whole genome duplication

Bohutínská

Alston

Monnahan

et al. 2020

Preprint

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Whole genome duplication (WGD) occurs across kingdoms and can promote adaptation. However, the sudden increase in chromosome number, as well as immediate changes in cellular physiology, are traumatic to conserved cellular processes. Previous work in Arabidopsis arenosa revealed a clearly coordinated genomic response to WGD, involving a set of functionally and physically interacting proteins mediating crossover number and distribution during prophase I of meiosis. Here we ask: is this highly coordinated coevolutionary shift repeated in other species? We also test globally for convergence for all processes under selection in independent cases of adaptation to WGD, as other processes were under selection in A. arenosa and may be common to other independent adaptation events following WGD. Taking advantage of a well-characterised diploid/autopolyploid system, Cardamine amara, we test our hypothesis that convergence will be detected in the form of directional selection. We also investigate at what level convergence may be evident: identical genes, networks, or analogous processes. To do this we performed a genome scan between diploid and autotetraploid populations, while utilising a quartet-based sampling design to minimise false positives. Among the genes exhibiting the strongest signatures of selection in C. amara autotetraploids we detect an enrichment for DNA maintenance, chromosome organisation, and meiosis, as well as stress signalling. We find that gene-level convergence between the independent WGD adaptation events in C. amara and A. arenosa is negligible, with no more orthologous genes in common than would be expected by chance. In contrast to this, however, we observe very strong convergence at the level of functional processes and homologous (but not orthologous) genes. Taken together, our results indicate that these two autopolyploids survived the challenges attendant to WGD by modifying similar or identical processes through different molecular players and gives the first insight into the salient adaptations required to cope with a genome-doubled state.

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Section: Window-based Selection Scan Using a Quartet Designmentioning

confidence: 99%

Genomic novelty and process-level convergence in adaptation to whole genome duplication

Bohutínská

Alston

Monnahan

et al. 2020

Preprint

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“…Chinese Spring genome sequence was annotated as described in [25]. Briefly, two gene prediction pipelines were used (TriAnnot: developed at GDEC Institute [INRA-UCA Clermont-Ferrand]; the pipeline developed at Helmholtz Center Munich [PGSB]) and the two annotations were integrated (pipeline established at Earlham Institute [43]) to achieve a single high-quality gene set. TE modeling was achieved through a similarity search approach based on the ClariTeRep curated databank of repeated elements [44], developed specifically for the wheat genome, and with the CLARITE program that was developed to model TEs and reconstruct their nested structure [17].…”

Section: Te Modeling Using Claritementioning

confidence: 99%

Impact of transposable elements on genome structure and evolution in bread wheat

Wicker¹,

Gundlach

Spannagl

et al. 2018

Preprint

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Background: Transposable elements (TEs) are ubiquitous components of genomes and they are the main contributors to genome evolution. The reference sequence of the hexaploid 2 bread wheat (Triticum aestivum L.) genome enabled for the first time a comprehensive genomewide view of the dynamics of TEs that have massively proliferated in the A, B, and D subgenomes.Results: TEs represent 85% of the genome. We traced back TE amplification dynamics in the evolutionary history of wheat and did not find large bursts in the wake of either the tetraor the hexaploidization. Despite the massive turnover of TEs since A, B, and D diverged, 76% of TE families are present in similar proportions in the three subgenomes. Moreover, spacing between homeologous genes was also conserved. TE content around genes is very different from the TE space comprising large intergenic regions and families that are enriched or depleted from gene promoters are the same in the three subgenomes. Conclusions:The chromosome-scale assembly of the wheat genome provided an unprecedented genome-wide view of the organization and impact of TEs in such a complex genome. Our results suggest that TEs play a role at the structural level and that the overall chromatin structure is likely under selection pressure.The genome of bread wheat (Triticum aestivum L.), one of the most important crop species, has also undergone massive TE amplification with over 85% of it being derived from such repeat elements. It is an allohexaploid comprised of three subgenomes (termed A, B, and D) that have diverged from a common ancestor around 2-3 million years ago (according to molecular dating of chloroplast DNA [16]) and hybridized within the last half million years. This led to the formation of a complex, redundant, and allohexaploid genome. These characteristics make the wheat genome by far the largest and most complex genome that has been sequenced and assembled into near complete chromosomes so far. They, however, also make wheat a unique system to study the impact of TE activity on genome structure, function and organization.Previously only one reference sequence quality wheat chromosome was available which we annotated using our automated TE annotation pipeline (CLARITE) [17,18]. However, it was unknown whether the TE content of chromosome 3B was typical of all wheat chromosomes and how TE content varied between the A, B, and D subgenomes. Therefore, in this study, we address the contribution of TEs to wheat genome evolution at a chromosome-wide scale. We report on the comparison of the three A-B-D subgenomes in terms of TE content and proliferation dynamics. We show that, although TEs have been completely reshuffled since A-B-D diverged, their proportions are quite conserved between subgenomes. In addition, the TE landscape in the direct vicinity of genes is very similar between the three subgenomes. Our results strongly suggest that TEs play a role at the structural level, and that the overall chromatin structure is likely under selection pressure. We also identified TE fa...

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“…com/urmi-21/pyrpipe/tree/master/case_ studies/Athaliana_transcript_assembly E. Integrating pyrpipe scripts within a workflow management system. We embedded pyrpipe into the Snakemake workflow management system (6), and used it to download human RNA-Seq data with SRAtools, quality filter the data with BBDuk (15), align reads with Hisat2 (12), assemble transcripts with StringTie (13) and Cufflinks (17), and merge the multiple assemblies with Mikado (18). Case study: https://github.com/urmi-21/ pyrpipe/tree/master/case_studies/Human_ annotation_snakemake F. Prediction of Zea mays orphan genes.…”

Section: Case Studies C Prediction Of Long Non-coding Rnas (Lncrnas)mentioning

confidence: 99%

pyrpipe: a python package for RNA-Seq workflows

Singh

Seetharam

et al. 2020

Preprint

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Implementing RNA-Seq analysis pipelines is challenging as data gets bigger and more complex. With the availability of terabytes of RNA-Seq data and continuous development of analysis tools, there is a pressing requirement for frameworks that allow for fast and efficient development, modification, sharing and reuse of workflows. Scripting is often used, but it has many challenges and drawbacks. We have developed a python package, python RNA-Seq Pipeliner (pyrpipe) that enables straightforward development of flexible, reproducible and easy-to-debug computational pipelines purely in python, in an object-oriented manner. pyrpipe provides high level APIs to popular RNA-Seq tools. Pipelines can be customized by integrating new python code, third-party programs, or python libraries. Researchers can create checkpoints in the pipeline or integrate pyrpipe into a workflow management system, thus allowing execution on multiple computing environments. pyrpipe produces detailed analysis, and benchmark reports which can be shared or included in publications. pyrpipe is implemented in python and is compatible with python versions 3.6 and higher. All source code is available at https://github.com/urmi-21/pyrpipe; the package can be installed from the source or from PyPi (https://pypi.org/project/ pyrpipe).

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Leveraging multiple transcriptome assembly methods for improved gene structure annotation

Cited by 155 publications

References 43 publications

Genomic novelty and process-level convergence in adaptation to whole genome duplication

Genomic novelty and process-level convergence in adaptation to whole genome duplication

Impact of transposable elements on genome structure and evolution in bread wheat

pyrpipe: a python package for RNA-Seq workflows

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