Genome dynamics in mosses: Extensive synteny coexists with a highly dynamic gene space

Kirbis, Alexander; Rahmatpour, Nasim; Dong, Shanshan; Jin, Yu; Gessel, Nico van; Waller, Manuel; Reski, Ralf; Lang, Daniel; Rensing, Stefan A.; Temsch, Eva M.; Wegrzyn, Jill L.; Goffinet, Bernard; Liu, Yang; Szövényi, Péter

doi:10.1101/2022.05.17.492078

Cited by 3 publications

(11 citation statements)

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“…The BUSCO completeness scores remained relatively the same, with BR (SR/RM2+) being 1% higher than BR (SR) in Arabidopsis , Funaria , and Populus . The marginal improvement observed in these genomes could be related to the structure and type of LTRs, such as the better identification of divergent Ty1‐copia elements described in the Funaria genome (Kirbis et al, 2022). Although we did not include genomes with excessive repeat estimates (>70%), our results indicated that the optional LTRStruct module was not beneficial.…”

Section: Discussionmentioning

confidence: 99%

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Welcome to the big leaves: Best practices for improving genome annotation in non‐model plant genomes

et al. 2023

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PremiseRobust standards to evaluate quality and completeness are lacking in eukaryotic structural genome annotation, as genome annotation software is developed using model organisms and typically lacks benchmarking to comprehensively evaluate the quality and accuracy of the final predictions. The annotation of plant genomes is particularly challenging due to their large sizes, abundant transposable elements, and variable ploidies. This study investigates the impact of genome quality, complexity, sequence read input, and method on protein‐coding gene predictions.MethodsThe impact of repeat masking, long‐read and short‐read inputs, and de novo and genome‐guided protein evidence was examined in the context of the popular BRAKER and MAKER workflows for five plant genomes. The annotations were benchmarked for structural traits and sequence similarity.ResultsBenchmarks that reflect gene structures, reciprocal similarity search alignments, and mono‐exonic/multi‐exonic gene counts provide a more complete view of annotation accuracy. Transcripts derived from RNA‐read alignments alone are not sufficient for genome annotation. Gene prediction workflows that combine evidence‐based and ab initio approaches are recommended, and a combination of short and long reads can improve genome annotation. Adding protein evidence from de novo assemblies, genome‐guided transcriptome assemblies, or full‐length proteins from OrthoDB generates more putative false positives as implemented in the current workflows. Post‐processing with functional and structural filters is highly recommended.DiscussionWhile the annotation of non‐model plant genomes remains complex, this study provides recommendations for inputs and methodological approaches. We discuss a set of best practices to generate an optimal plant genome annotation and present a more robust set of metrics to evaluate the resulting predictions.

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Section: Discussionmentioning

confidence: 99%

“…(Raymond et al, 2018), thale cress ( Arabidopsis thaliana TAIR 10) (Cheng et al, 2017), and a bryophyte, the common cord‐moss ( Funaria hygrometrica Hedw.) (Kirbis et al, 2022) (Appendix ). The genomes were selected to represent two model systems ( Populus L. and Arabidopsis Heynh.)…”

Section: Methodsmentioning

confidence: 99%

Welcome to the big leaves: Best practices for improving genome annotation in non‐model plant genomes

et al. 2023

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“…The BUSCO completeness scores remained relatively the same, with BR (SR/RM2+) being 1% higher than BR (SR) in Arabidopsis, Funaria and Populus . The marginal improvement observed in these genomes could be related to the structure and type of LTRs, for example, better identification of divergent Ty1-copia elements described in the Funaria genome (Kirbis et al ., 2022). While we did not include genomes with excessive repeat estimates (>70%), our results indicated that the optional LTRStruct module was not beneficial.…”

Section: Discussionmentioning

confidence: 99%

“…Five plant genomes were chosen for this study, including Chinese tuliptree ( Liriodendron chinense ) (Chen et al 2019), black cottonwood ( Populus trichocarpa v3) (Tuskan et al 2006), Chinese rose ( Rosa chinensis ) (Raymond et al 2018), thale cress ( Arabidopsis thaliana TAIR 10) (Cheng et al 2017), and a bryophyte, the common cord-moss ( Funaria hygrometrica ) (Kirbis et al ., 2022) (Table S1). The public assembly and annotation for each species were accessed from NCBI and genome completeness was estimated by searching the genome and annotation for the conserved single-copy orthologs in the Embryophyta odb10 BUSCO v.5.0.0 (Simão et al ., 2015).…”

Section: Methodsmentioning

confidence: 99%

“…Five plant genomes were chosen for this study, including Chinese tuliptree ( Liriodendron chinense ) (Chen et al 2019), black cottonwood ( Populus trichocarpa v3) (Tuskan et al 2006), Chinese rose ( Rosa chinensis ) (Raymond et al 2018), thale cress ( Arabidopsis thaliana TAIR 10) (Cheng et al 2017), and a bryophyte, the common cord-moss ( Funaria hygrometrica ) (Kirbis et al, 2022) (Table S1). The genomes were selected to represent two model systems ( Populus and Arabidopsis ) with well curated structural annotations and three non-model systems that exclusively used computational techniques to produce the annotations.…”

Section: Methodsmentioning

confidence: 99%

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Welcome to the big leaves: best practices for improving genome annotation in non-model plant genomes

Vuruputoor

Monyak

Fetter

et al. 2022

Preprint

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Premise of the study: Robust standards to evaluate quality and completeness are lacking for eukaryotic structural genome annotation. Genome annotation software is developed with model organisms and does not typically include benchmarking to comprehensively evaluate the quality and accuracy of the final predictions. Plant genomes are particularly challenging with their large genome sizes, abundant transposable elements (TEs), and variable ploidies. This study investigates the impact of genome quality, complexity, sequence read input, and approach on protein-coding gene prediction. Methods: The impact of repeat masking, long-read, and short-read inputs, de novo, and genome-guided protein evidence was examined in the context of the popular BRAKER and MAKER workflows for five plant genomes. Annotations were benchmarked for structural traits and sequence similarity. Results: Benchmarks that reflect gene structures, reciprocal similarity search alignments, and mono-exonic/multi-exonic gene counts provide a more complete view of annotation accuracy. Transcripts derived from RNA-read alignments alone are not sufficient for genome annotation. Gene prediction workflows that combine evidence-based and ab initio approaches are recommended, and a combination of short and long-reads can improve genome annotation. Adding protein evidence from de novo or genome-guided approaches generates more false positives as implemented in the current workflows. Post-processing with functional and structural filters is highly recommended. Discussion: While annotation of non-model plant genomes remains complex, this study provides recommendations for inputs and methodological approaches. We discuss a set of best practices to generate an optimal plant genome annotation, and present a more robust set of metrics to evaluate the resulting predictions.

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Crossroads of assembling a moss genome: navigating contaminants and horizontal gene transfer in the mossPhyscomitrellopsis africana

Vuruputoor,

Starovoitov,

Cai

et al. 2023

Preprint

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The first reference genome assembly of the mossPhyscomitrellopsis africana, a rare narrow endemic terricolous species from southeastern coastal forests of South Africa, is presented here. Phylogenetically,Physcomitrellopsis africanabridges the major evo-devo moss modelsPhyscomitrium patensandFunaria hygrometrica, which diverged from their common ancestor 60-80 million years ago. ThePhyscomitrellopsis africanagenome was assembled with both long Nanopore reads (73x) and short Illumina reads (163x). The 440 Mb assembly comprises 2,396 contigs and 23,493 protein-coding genes (BUSCO: C:96.0%[D:13.9%]), including two unique genes of putative microbial origin absent in close relatives. While the informatic approaches to genome assembly are becoming more standardized, best practices for contamination detection are less defined. The long reads sequenced for thePhyscomitrellopsis africanagenome contained approximately 12% contamination originating from microbial sources. This study describes the informatic processes employed to distinguish contaminants from candidate horizontal gene transfer events. Following the assembly and annotation, examination of whole genome duplication, and patterns of gene family expansion and contraction, were conducted. The genome bears signatures of two whole genome duplications shared withPhyscomitrium patensandF. hygrometrica. Comparative analyses of gene family evolution revealed contractions associated with the light harvesting regulatory network inPhyscomitrellopsis africanain comparison toPhyscomitrium patensandF. hygrometrica. This first high-quality African bryophyte genome provides insights into genome evolution and HGT in an understudied moss lineage.Article SummaryThe first draft genome of the rare moss,Physcomitrellopsis africana, endemic to South Africa’s southeastern coastal forests, is presented here. The 440 Mb genome fills a critical phylogenetic gap, enabling the first comparative analysis of the genomes of three moss species that diverge over the last 60-80 million years. The analysis uncovered 23,493 genes and provides new insights into genome evolution and gene family expansion/contraction in mosses. Rigorous contaminant filtering also identified two genes uniquely acquired through horizontal gene transfer.

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Genome dynamics in mosses: Extensive synteny coexists with a highly dynamic gene space

Cited by 3 publications

References 160 publications

Welcome to the big leaves: Best practices for improving genome annotation in non‐model plant genomes

Welcome to the big leaves: Best practices for improving genome annotation in non‐model plant genomes

Welcome to the big leaves: best practices for improving genome annotation in non-model plant genomes

Crossroads of assembling a moss genome: navigating contaminants and horizontal gene transfer in the mossPhyscomitrellopsis africana

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