About twenty-five years after the sequencing of the first fungal genome and a dozen years after the first plant pathogenic fungi genomes were sequenced, unprecedented international efforts have led to an impressive collection of genomes available for the community of mycologists in international databases (Goffeau et al. 1996, Dean et al. 2005; Spatafora et al. 2017). For instance, to date, the Joint Genome Institute Mycocosm database has collected more than 2,100 fungal genomes over the fungal tree of life (https://mycocosm.jgi.doe.gov). Such resources are paving the way for comparative genomics, population genomics and phylogenomics to address a large panel of questions regarding the biology and the ecology of fungal species. Early on, population genomics applied to pathogenic fungi revealed a great diversity of genome content and organization and a wide variety of variants and rearrangements (Raffaele and Kamoun 2012, Hartmann 2022). Such plasticity raises questions about how to choose a representative genome to serve as an ideal reference to address pertinent biological questions.

Cryphonectria parasitica is a fungal pathogen that is infamous for the devastation of chestnut forests in North America after its accidental introduction more than a century ago (Anagnostakis 1987). Since then, it has been a quarantine species under surveillance in various parts of the world. As for other fungi causing diseases on forest trees, the study of adaptation to its host in the forest ecosystem and of its reproduction and dissemination modes is more complex than for crop-targeting pathogens. A first reference genome was published in 2020 for the chestnut blight fungus C. parasitica strain EP155 in the frame of an international project with the DOE JGI (Crouch et al. 2020). Another genome was then sequenced from the French isolate YVO003, which showed a few differences in the assembly suggesting possible rearrangements (Demené et al. 2019). Here the sequencing of a third isolate ESM015 from the native area of C. parasitica in Japan allows to draw broader comparative analysis and particularly to compare between native and introduced isolates (Demené et al. 2022).

Demené and collaborators report on a new genome sequence using up-to-date long-read sequencing technologies and they provide an improved genome assembly. Comparison with previously published C. parasitica genomes did not reveal dramatic changes in the overall chromosomal landscapes, but large rearrangements could be spotted. Despite these rearrangements, the genome content and organization – i.e. genes and repeats – remain stable, with a limited number of genes gains and losses. As in any fungal plant pathogen genome, the repertoire of candidate effectors predicted among secreted proteins was more particularly scrutinized. Such effector genes have previously been reported in other pathogens in repeat-enriched plastic genomic regions with accelerated evolutionary rates under the pressure of the host immune system (Raffaele and Kamoun 2012). Demené and collaborators established a list of priority candidate effectors in the C. parasitica gene catalog likely involved in the interaction with the host plant which will require more attention in future functional studies. Six major inter-chromosomal translocations were detected and are likely associated with double break strands repairs. The authors speculate on the possible effects that these translocations may have on gene organization and expression regulation leading to dramatic phenotypic changes in relation to introduction and invasion in new continents and the impact regarding sexual reproduction in this fungus (Demené et al. 2022).

I recommend this article not only because it is providing an improved assembly of a reference genome for C. parasitica, but also because it adds diversity in terms of genome references availability, with a third high-quality assembly. Such an effort in the tree pathology community for a pathogen under surveillance is of particular importance for future progress in post-genomic analysis, e.g. in further genomic population studies (Hartmann 2022). 

References

Anagnostakis SL (1987) Chestnut Blight: The Classical Problem of an Introduced Pathogen. Mycologia, 79, 23–37. https://doi.org/10.2307/3807741

Crouch JA, Dawe A, Aerts A, Barry K, Churchill ACL, Grimwood J, Hillman BI, Milgroom MG, Pangilinan J, Smith M, Salamov A, Schmutz J, Yadav JS, Grigoriev IV, Nuss DL (2020) Genome Sequence of the Chestnut Blight Fungus Cryphonectria parasitica EP155: A Fundamental Resource for an Archetypical Invasive Plant Pathogen. Phytopathology®, 110, 1180–1188. https://doi.org/10.1094/PHYTO-12-19-0478-A

Dean RA, Talbot NJ, Ebbole DJ, Farman ML, Mitchell TK, Orbach MJ, Thon M, Kulkarni R, Xu J-R, Pan H, Read ND, Lee Y-H, Carbone I, Brown D, Oh YY, Donofrio N, Jeong JS, Soanes DM, Djonovic S, Kolomiets E, Rehmeyer C, Li W, Harding M, Kim S, Lebrun M-H, Bohnert H, Coughlan S, Butler J, Calvo S, Ma L-J, Nicol R, Purcell S, Nusbaum C, Galagan JE, Birren BW (2005) The genome sequence of the rice blast fungus Magnaporthe grisea. Nature, 434, 980–986. https://doi.org/10.1038/nature03449

Demené A., Laurent B., Cros-Arteil S., Boury C. and Dutech C. 2022. Chromosomal rearrangements with stable repertoires of genes and transposable elements in an invasive forest-pathogenic fungus. bioRxiv, 2021.03.09.434572, ver.6 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2021.03.09.434572

Goffeau A, Barrell BG, Bussey H, Davis RW, Dujon B, Feldmann H, Galibert F, Hoheisel JD, Jacq C, Johnston M, Louis EJ, Mewes HW, Murakami Y, Philippsen P, Tettelin H, Oliver SG (1996) Life with 6000 Genes. Science, 274, 546–567. https://doi.org/10.1126/science.274.5287.546

Hartmann FE (2022) Using structural variants to understand the ecological and evolutionary dynamics of fungal plant pathogens. New Phytologist, 234, 43–49. https://doi.org/10.1111/nph.17907

Raffaele S, Kamoun S (2012) Genome evolution in filamentous plant pathogens: why bigger can be better. Nature Reviews Microbiology, 10, 417–430. https://doi.org/10.1038/nrmicro2790

Spatafora JW, Aime MC, Grigoriev IV, Martin F, Stajich JE, Blackwell M (2017) The Fungal Tree of Life: from Molecular Systematics to Genome-Scale Phylogenies. Microbiology Spectrum, 5, 5.5.03. https://doi.org/10.1128/microbiolspec.FUNK-0053-2016

A wide variety of systems have evolved to control mating compatibility in sexual organisms. Their genetic determinism and the factors controlling their evolution represent fascinating questions in evolutionary biology and genomics. The plant Phillyrea angustifolia (Oleaeceae family) represents an exciting model organism, as it displays two distinct and rare mating compatibility systems [1]: 1) males and hermaphrodites co-occur in populations of this shrub (a rare system called androdioecy), while the evolution and maintenance of purely hermaphroditic plants or mixtures of females and hermaphrodites (a system called gynodioecy) are easier to explain [2]; 2) a homomorphic diallelic self-incompatibility system acts in hermaphrodites, while such systems are usually multi-allelic, as rare alleles are advantageous, being compatible with all other alleles. Previous analyses of crosses brought some interesting answers to these puzzles, showing that males benefit from the ability to mate with all hermaphrodites regardless of their allele at the self-incompatibility system, and suggesting that both sex and self incompatibility are determined by XY-like genetic systems, i.e. with each a dominant allele; homozygotes for a single allele and heterozygotes therefore co-occur in natural populations at both sex and self-incompatibility loci [3].

Here, Carré et al. used genotyping-by-sequencing to build a genome linkage map of P. angustifolia [4]. The elegant and original use of a probabilistic model of segregating alleles (implemented in the SEX-DETector method) allowed to identify both the sex and self-incompatibility loci [4], while this tool was initially developed for detecting sex-linked genes in species with strictly separated sexes (dioecy) [5]. Carré et al. [4] confirmed that the sex and self-incompatibility loci are located in two distinct linkage groups and correspond to XY-like systems. A comparison with the genome of the closely related Olive tree indicated that their self-incompatibility systems were homologous. Such a XY-like system represents a rare genetic determination mechanism for self-incompatibility and has also been recently found to control mating types in oomycetes [6].

This study [4] paves the way for identifying the genes controlling the sex and self-incompatibility phenotypes and for understanding why and how self-incompatibility is only expressed in hermaphrodites and not in males. It will also be fascinating to study more finely the degree and extent of genomic differentiation at these two loci and to assess whether recombination suppression has extended stepwise away from the sex and self-incompatibility loci, as can be expected under some hypotheses, such as the sheltering of deleterious alleles near permanently heterozygous alleles [7]. Furthermore, the co-occurrence in P. angustifolia of sex and mating types can contribute to our understanding of the factor controlling their evolution [8].

References

[1] Saumitou-Laprade P, Vernet P, Vassiliadis C, Hoareau Y, Magny G de, Dommée B, Lepart J (2010) A Self-Incompatibility System Explains High Male Frequencies in an Androdioecious Plant. Science, 327, 1648–1650. https://doi.org/10.1126/science.1186687

[2] Pannell JR, Voillemot M (2015) Plant Mating Systems: Female Sterility in the Driver’s Seat. Current Biology, 25, R511–R514. https://doi.org/10.1016/j.cub.2015.04.044

[3] Billiard S, Husse L, Lepercq P, Godé C, Bourceaux A, Lepart J, Vernet P, Saumitou-Laprade P (2015) Selfish male-determining element favors the transition from hermaphroditism to androdioecy. Evolution, 69, 683–693. https://doi.org/10.1111/evo.12613

[4] Carre A, Gallina S, Santoni S, Vernet P, Gode C, Castric V, Saumitou-Laprade P (2021) Genetic mapping of sex and self-incompatibility determinants in the androdioecious plant Phillyrea angustifolia. bioRxiv, 2021.04.15.439943, ver. 7 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2021.04.15.439943

[5] Muyle A, Käfer J, Zemp N, Mousset S, Picard F, Marais GA (2016) SEX-DETector: A Probabilistic Approach to Study Sex Chromosomes in Non-Model Organisms. Genome Biology and Evolution, 8, 2530–2543. https://doi.org/10.1093/gbe/evw172

[6] Dussert Y, Legrand L, Mazet ID, Couture C, Piron M-C, Serre R-F, Bouchez O, Mestre P, Toffolatti SL, Giraud T, Delmotte F (2020) Identification of the First Oomycete Mating-type Locus Sequence in the Grapevine Downy Mildew Pathogen, Plasmopara viticola. Current Biology, 30, 3897-3907.e4. https://doi.org/10.1016/j.cub.2020.07.057

[7] Jay P, Tezenas E, Giraud T (2021) A deleterious mutation-sheltering theory for the evolution of sex chromosomes and supergenes. bioRxiv, 2021.05.17.444504. https://doi.org/10.1101/2021.05.17.444504

[8] Billiard S, López-Villavicencio M, Devier B, Hood ME, Fairhead C, Giraud T (2011) Having sex, yes, but with whom? Inferences from fungi on the evolution of anisogamy and mating types. Biological Reviews, 86, 421–442. https://doi.org/10.1111/j.1469-185X.2010.00153.x

In their paper, Guiglielmoni et al. propose we pick up our snorkels and palms and take "A deep dive into genome assemblies of non-vertebrate animals" (1). Indeed, while numerous assembly-related tools were developed and tested for human genomes (or at least vertebrates such as mice), very few were tested on non-vertebrate animals so far. Moreover, most of the benchmarks are aimed at raw assembly tools, and very few offer a guide from raw reads to an almost finished assembly, including quality control and phasing.

This huge and exhaustive review starts with an overview of the current sequencing technologies, followed by the theory of the different approaches for assembly and their implementation. For each approach, the authors present some of the most representative tools, as well as the limits of the approach.

The authors additionally present all the steps required to obtain an almost complete assembly at a chromosome-scale, with all the different technologies currently available for scaffolding, QC, and phasing, and the way these tools can be applied to non-vertebrates animals. Finally, they propose some useful advice on the choice of the different approaches (but not always tools, see below), and advocate for a robust genome database with all information on the way the assembly was obtained.

This review is a very complete one for now and is a very good starting point for any student or scientist interested to start working on genome assembly, from either model or non-model organisms. However, the authors do not provide a list of tools or a benchmark of them as a recommendation. Why? Because such a proposal may be obsolete in less than a year.... Indeed, with the explosion of the 3rd generation of sequencing technology, assembly tools (from different steps) are constantly evolving, and their relative performance increases on a monthly basis. In addition, some tools are really efficient at the time of a review or of an article, but are not further developed later on, and thus will not evolve with the technology. We have all seen it with wonderful tools such as Chiron (2) or TopHat (3), which were very promising ones, but cannot be developed further due to the stop of the project, the end of the contract of the post-doc in charge of the development, or the decision of the developer to switch to another paradigm. Such advice would, therefore, need to be constantly updated.

Thus, the manuscript from Guiglielmoni et al will be an almost intemporal one (up to the next sequencing revolution at last), and as they advocated for a more informed genome database, I think we should consider a rolling benchmarking system (tools, genome and sequence dataset) allowing to keep the performance of the tools up-to-date, and to propose the best set of assembly tools for a given type of genome.

References

1. Guiglielmoni N, Rivera-Vicéns R, Koszul R, Flot J-F (2022) A Deep Dive into Genome Assemblies of Non-vertebrate Animals. Preprints, 2021110170, ver. 3 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.20944/preprints202111.0170

2. Teng H, Cao MD, Hall MB, Duarte T, Wang S, Coin LJM (2018) Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning. GigaScience, 7, giy037. https://doi.org/10.1093/gigascience/giy037

3. Trapnell C, Pachter L, Salzberg SL (2009) TopHat: discovering splice junctions with RNA-Seq. Bioinformatics, 25, 1105–1111. https://doi.org/10.1093/bioinformatics/btp120

Biological systems depend on finely tuned interactions of their components. Thus, regulating these components is critical for the system's functionality. In prokaryotic cells, riboswitches are regulatory elements controlling transcription or translation. Riboswitches are RNA molecules that are usually located in the 5′-untranslated region of protein-coding genes. They generate secondary structures leading to the regulation of the expression of the downstream protein-coding gene (Kavita and Breaker, 2022). Riboswitches are very versatile and can bind a wide range of small molecules; in many cases, these are metabolic byproducts from the gene’s enzymatic or signaling pathway. Their versatility and abundance in many species make them attractive for synthetic biological circuits. One class that has been drawing the attention of synthetic biologists is toehold switches (Ekdahl et al., 2022; Green et al., 2014). These are single-stranded RNA molecules harboring the necessary elements for translation initiation of the downstream gene: a ribosome-binding site and a start codon. Conformation change of toehold switches is triggered by an RNA molecule, which enables translation.

To exploit the most out of toehold switches, automation of their design would be highly advantageous. Cisneros and colleagues (Cisneros et al., 2022) developed a tool, “Toeholder”, that automates the design of toehold switches and performs in silico tests to select switch candidates for a target gene. Toeholder is an open-source tool that provides a comprehensive and automated workflow for the design of toehold switches. While web tools have been developed for designing toehold switches (To et al., 2018), Toeholder represents an intriguing approach to engineering biological systems by coupling synthetic biology with computational biology. Using molecular dynamics simulations, it identified the positions in the toehold switch where hydrogen bonds fluctuate the most. Identifying these regions holds great potential for modifications when refining the design of the riboswitches. To be effective, toehold switches should provide a strong ON signal and a weak OFF signal in the presence or the absence of a target, respectively. Toeholder nicely ranks the candidate toehold switches based on experimental evidence that correlates with toehold performance (based on good ON/OFF ratios).

Riboswitches are highly appealing for a broad range of applications, including pharmaceutical and medical purposes (Blount and Breaker, 2006; Giarimoglou et al., 2022; Tickner and Farzan, 2021), thanks to their adaptability and inexpensiveness. The Toeholder tool developed by Cisneros and colleagues is expected to promote the implementation of toehold switches into these various applications.

References

Blount KF, Breaker RR (2006) Riboswitches as antibacterial drug targets. Nature Biotechnology, 24, 1558–1564. https://doi.org/10.1038/nbt1268

Cisneros AF, Rouleau FD, Bautista C, Lemieux P, Dumont-Leblond N, ULaval 2019 T iGEM (2022) Toeholder: a Software for Automated Design and In Silico Validation of Toehold Riboswitches. bioRxiv, 2021.11.09.467922, ver. 3 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2021.11.09.467922

Ekdahl AM, Rojano-Nisimura AM, Contreras LM (2022) Engineering Toehold-Mediated Switches for Native RNA Detection and Regulation in Bacteria. Journal of Molecular Biology, 434, 167689. https://doi.org/10.1016/j.jmb.2022.167689

Giarimoglou N, Kouvela A, Maniatis A, Papakyriakou A, Zhang J, Stamatopoulou V, Stathopoulos C (2022) A Riboswitch-Driven Era of New Antibacterials. Antibiotics, 11, 1243. https://doi.org/10.3390/antibiotics11091243

Green AA, Silver PA, Collins JJ, Yin P (2014) Toehold Switches: De-Novo-Designed Regulators of Gene Expression. Cell, 159, 925–939. https://doi.org/10.1016/j.cell.2014.10.002

Kavita K, Breaker RR (2022) Discovering riboswitches: the past and the future. Trends in Biochemical Sciences. https://doi.org/10.1016/j.tibs.2022.08.009

Tickner ZJ, Farzan M (2021) Riboswitches for Controlled Expression of Therapeutic Transgenes Delivered by Adeno-Associated Viral Vectors. Pharmaceuticals, 14, 554. https://doi.org/10.3390/ph14060554

To AC-Y, Chu DH-T, Wang AR, Li FC-Y, Chiu AW-O, Gao DY, Choi CHJ, Kong S-K, Chan T-F, Chan K-M, Yip KY (2018) A comprehensive web tool for toehold switch design. Bioinformatics, 34, 2862–2864. https://doi.org/10.1093/bioinformatics/bty216

The genomics era has pushed forward our understanding of fungal biology. Much progress has been made in unraveling new gene functions and pathways, as well as the evolution or adaptation of fungi to their hosts or environments through population studies (Hartmann et al. 2019; Gladieux et al. 2018). Closing gaps more systematically in draft genomes using the most recent long-read technologies now seems the new standard, even with fungal species presenting complex genome structures (e.g. large and highly repetitive dikaryotic genomes; Duan et al. 2022). Understanding the genomic dynamics underlying host specialization in phytopathogenic fungi is of utmost importance as it may open new avenues to combat diseases. A strong host specialization is commonly observed for biotrophic and hemi-biotrophic fungal species or for necrotrophic fungi with a narrow host range, whereas necrotrophic fungi with broad host range are considered generalists (Liang and Rollins, 2018; Newman and Derbyshire, 2020). However, some degrees of specialization towards given hosts have been reported in generalist fungi and the underlying mechanisms remain to be determined.

Botrytis cinerea is a polyphagous necrotrophic phytopathogen with a particularly wide host range and it is notably responsible for grey mould disease on many fruits, such as tomato and grapevine. Because of its importance as a plant pathogen, its relatively small genome size and its taxonomical position, it has been targeted for early genome sequencing and a first reference genome was provided in 2011 (Amselem et al. 2011). Other genomes were subsequently sequenced for other strains, and most importantly a gapless assembled version of the initial reference genome B05.10 was provided to the community (van Kan et al. 2017). This genomic resource has supported advances in various aspects of the biology of B. cinerea such as the production of specialized metabolites, which plays an important role in host-plant colonization, or more recently in the production of small RNAs which interfere with the host immune system, representing a new class of non-proteinaceous virulence effectors (Dalmais et al. 2011; Weiberg et al. 2013).

In the present study, Simon et al. (2022) use PacBio long-read sequencing for Sl3 and Vv3 strains, which represent genetic clusters in B. cinerea populations found on tomato and grapevine. The authors combined these complete and high-quality genome assemblies with the B05.10 reference genome and population sequencing data to perform a comparative genomic analysis of specialization towards the two host plants. Transposable elements generate genomic diversity due to their mobile and repetitive nature and they are of utmost importance in the evolution of fungi as they deeply reshape the genomic landscape (Lorrain et al. 2021). Accessory chromosomes are also known drivers of adaptation in fungi (Möller and Stukenbrock, 2017). Here, the authors identify several genomic features such as the presence of different sets of accessory chromosomes, the presence of differentiated repertoires of transposable elements, as well as related small RNAs in the tomato and grapevine populations, all of which may be involved in host specialization. Whereas core chromosomes are highly syntenic between strains, an accessory chromosome validated by pulse-field electrophoresis is specific of the strains isolated from grapevine. Particularly, they show that two particular retrotransposons are discriminant between the strains and that they allow the production of small RNAs that may act as effectors. The discriminant accessory chromosome of the Vv3 strain harbors one of the unraveled retrotransposons as well as new genes of yet unidentified function.

I recommend this article because it perfectly illustrates how efforts put into generating reference genomic sequences of higher quality can lead to new discoveries and allow to build strong hypotheses about biology and evolution in fungi. Also, the study combines an up-to-date genomics approach with a classical methodology such as pulse-field electrophoresis to validate the presence of accessory chromosomes. A major input of this investigation of the genomic determinants of B. cinerea is that it provides solid hints for further analysis of host-specialization at the population level in a broad-scale phytopathogenic fungus.

References

Amselem J, Cuomo CA, Kan JAL van, Viaud M, Benito EP, Couloux A, Coutinho PM, Vries RP de, Dyer PS, Fillinger S, Fournier E, Gout L, Hahn M, Kohn L, Lapalu N, Plummer KM, Pradier J-M, Quévillon E, Sharon A, Simon A, Have A ten, Tudzynski B, Tudzynski P, Wincker P, Andrew M, Anthouard V, Beever RE, Beffa R, Benoit I, Bouzid O, Brault B, Chen Z, Choquer M, Collémare J, Cotton P, Danchin EG, Silva CD, Gautier A, Giraud C, Giraud T, Gonzalez C, Grossetete S, Güldener U, Henrissat B, Howlett BJ, Kodira C, Kretschmer M, Lappartient A, Leroch M, Levis C, Mauceli E, Neuvéglise C, Oeser B, Pearson M, Poulain J, Poussereau N, Quesneville H, Rascle C, Schumacher J, Ségurens B, Sexton A, Silva E, Sirven C, Soanes DM, Talbot NJ, Templeton M, Yandava C, Yarden O, Zeng Q, Rollins JA, Lebrun M-H, Dickman M (2011) Genomic Analysis of the Necrotrophic Fungal Pathogens Sclerotinia sclerotiorum and Botrytis cinerea. PLOS Genetics, 7, e1002230. https://doi.org/10.1371/journal.pgen.1002230

Dalmais B, Schumacher J, Moraga J, Le Pêcheur P, Tudzynski B, Collado IG, Viaud M (2011) The Botrytis cinerea phytotoxin botcinic acid requires two polyketide synthases for production and has a redundant role in virulence with botrydial. Molecular Plant Pathology, 12, 564–579. https://doi.org/10.1111/j.1364-3703.2010.00692.x

Duan H, Jones AW, Hewitt T, Mackenzie A, Hu Y, Sharp A, Lewis D, Mago R, Upadhyaya NM, Rathjen JP, Stone EA, Schwessinger B, Figueroa M, Dodds PN, Periyannan S, Sperschneider J (2022) Physical separation of haplotypes in dikaryons allows benchmarking of phasing accuracy in Nanopore and HiFi assemblies with Hi-C data. Genome Biology, 23, 84. https://doi.org/10.1186/s13059-022-02658-2

Gladieux P, Condon B, Ravel S, Soanes D, Maciel JLN, Nhani A, Chen L, Terauchi R, Lebrun M-H, Tharreau D, Mitchell T, Pedley KF, Valent B, Talbot NJ, Farman M, Fournier E (2018) Gene Flow between Divergent Cereal- and Grass-Specific Lineages of the Rice Blast Fungus Magnaporthe oryzae. mBio, 9, e01219-17. https://doi.org/10.1128/mBio.01219-17

Hartmann FE, Rodríguez de la Vega RC, Carpentier F, Gladieux P, Cornille A, Hood ME, Giraud T (2019) Understanding Adaptation, Coevolution, Host Specialization, and Mating System in Castrating Anther-Smut Fungi by Combining Population and Comparative Genomics. Annual Review of Phytopathology, 57, 431–457. https://doi.org/10.1146/annurev-phyto-082718-095947

Liang X, Rollins JA (2018) Mechanisms of Broad Host Range Necrotrophic Pathogenesis in Sclerotinia sclerotiorum. Phytopathology®, 108, 1128–1140. https://doi.org/10.1094/PHYTO-06-18-0197-RVW

Lorrain C, Oggenfuss U, Croll D, Duplessis S, Stukenbrock E (2021) Transposable Elements in Fungi: Coevolution With the Host Genome Shapes, Genome Architecture, Plasticity and Adaptation. In: Encyclopedia of Mycology (eds Zaragoza Ó, Casadevall A), pp. 142–155. Elsevier, Oxford. https://doi.org/10.1016/B978-0-12-819990-9.00042-1

Möller M, Stukenbrock EH (2017) Evolution and genome architecture in fungal plant pathogens. Nature Reviews Microbiology, 15, 756–771. https://doi.org/10.1038/nrmicro.2017.76

Newman TE, Derbyshire MC (2020) The Evolutionary and Molecular Features of Broad Host-Range Necrotrophy in Plant Pathogenic Fungi. Frontiers in Plant Science, 11. https://doi.org/10.3389/fpls.2020.591733

Simon A, Mercier A, Gladieux P, Poinssot B, Walker A-S, Viaud M (2022) Botrytis cinerea strains infecting grapevine and tomato display contrasted repertoires of accessory chromosomes, transposons and small RNAs. bioRxiv, 2022.03.07.483234, ver. 4 peer-reviewed and recommended by Peer Community in Genomics. https://doi.org/10.1101/2022.03.07.483234

Van Kan JAL, Stassen JHM, Mosbach A, Van Der Lee TAJ, Faino L, Farmer AD, Papasotiriou DG, Zhou S, Seidl MF, Cottam E, Edel D, Hahn M, Schwartz DC, Dietrich RA, Widdison S, Scalliet G (2017) A gapless genome sequence of the fungus Botrytis cinerea. Molecular Plant Pathology, 18, 75–89. https://doi.org/10.1111/mpp.12384

Weiberg A, Wang M, Lin F-M, Zhao H, Zhang Z, Kaloshian I, Huang H-D, Jin H (2013) Fungal Small RNAs Suppress Plant Immunity by Hijacking Host RNA Interference Pathways. Science, 342, 118–123. https://doi.org/10.1126/science.1239705