porium fulvum), pine pathogen Dothistroma
septosporum, and maize pathogen Bipolaris
maydis (formerly known as Cochliobolus heterostrophus) (Goodwin et al. 2011; de Wit et al.
2012; Condon et al. 2013). P. fulva and D. septosporum are closely related but have very different host plants (tomato and pine,
respectively) and lifestyles (hemibiotroph and
necrotroph, respectively). Genome sequencing
revealed the evolution of a gene cluster
involved in the production of dothistromin
toxin by D. septosporum, as well as effector
genes specific to P. fulva. Comparing the two
genomes suggests that these pathogens had a
common ancestral host but have since diverged
into different hosts and lifestyles by a differentiation in gene content, pseudogenization, as
well as gene regulation (de Wit et al. 2012).
More generally, a comparative analysis of members of the class Dothideomycetes showed that
genome evolution follows a pattern of frequent
short intra-chromosomal inversions and few
inter-chromosomal rearrangements (Hane
et al. 2011; Ohm et al. 2012).
In contrast to plant pathogens, mycorrhizal
fungi form a symbiosis that is beneficial to the
plant host. Generally, during this symbiosis the
fungus provides micronutrients to the plant,
while the plant provides carbohydrates (sugars
produced by photosynthesis) to the fungus.
This mycorrhizal lifestyle evolved independently several times across the fungal kingdom,
in species as diverse as the mushroom-forming
Basidiomycete Laccaria bicolor, the Dothideomycete Cenococcum geophilum, and the Pe ´rigord black truffle Tuber melanosporum
(Martin et al. 2008, 2010; Peter et al. 2016).
Although there are many differences between
these mycorrhizal fungi, a general pattern is
that (compared to their non-mycorrhizal relatives) the number of plant cell wall degrading
CAZymes decreased, while the number of
lineage-specific genes increased (especially
genes that were differentially expressed during
symbiosis). Nevertheless, mycorrhizal fungi
have retained a unique set of CAZymes, which
suggests that they are still capable of degrading
lignocellulose and therefore are not fully reliant
on their plant host (Kohler et al. 2015; Martino
et al. 2018).
The genus Trichoderma contains several
mycoparasitic species that promote plant
growth. To some extent this can be explained
by the fact that they parasitise on deleterious
plant pathogens. However, several strains also
induce root branching and increase shoot biomass (Kubicek et al. 2011; Druzhinina et al.
2011; Contreras-Cornejo et al. 2016).
V. Conclusions
This chapter described recent improvements in
sequencing technologies that are used to
sequence fungal genomes. As these sequencing
technologies mature further, it will soon be
trivial and affordable to obtain a high-quality
telomere-to-telomere assembly. Accurate gene
prediction and data analysis is still a challenge,
although algorithms and pipelines continue to
improve. Currently fungal genome sequencing
is already affordable to small labs and individual researchers. For those who are interested in
starting with fungal genome sequencing, the
following pipeline has proven to work very
well in my lab (as an example): we routinely
sequence fungal genomes using Illumina (occasionally supplemented with long read from
Oxford Nanopore) and genome assembly is
done with SPAdes (Bankevich et al. 2012).
Gene prediction is preferably done with
BRAKER in combination with RNA-Seq
expression data (Hoff et al. 2016). Basic functional annotation is done with InterProScan
(Hunter et al. 2009) and supplemented with
other algorithms, depending on the scientific
questions.
Important next steps include a functional
genomics approach, which relies heavily on an
accurate genome sequence. In functional genomics, high-throughput (sequencing-based)
techniques are used in an effort to assign function to elements of the genome (usually genes).
These techniques may include RNA-Seq (to
study gene expression), ChIP-Seq (to study various aspects of epigenetics), as well as highthroughput gene inactivations. Gene inactivations and other genome editing approaches
have been greatly facilitated by the develop9 Fungal Genomics
215
septosporum, and maize pathogen Bipolaris
maydis (formerly known as Cochliobolus heterostrophus) (Goodwin et al. 2011; de Wit et al.
2012; Condon et al. 2013). P. fulva and D. septosporum are closely related but have very different host plants (tomato and pine,
respectively) and lifestyles (hemibiotroph and
necrotroph, respectively). Genome sequencing
revealed the evolution of a gene cluster
involved in the production of dothistromin
toxin by D. septosporum, as well as effector
genes specific to P. fulva. Comparing the two
genomes suggests that these pathogens had a
common ancestral host but have since diverged
into different hosts and lifestyles by a differentiation in gene content, pseudogenization, as
well as gene regulation (de Wit et al. 2012).
More generally, a comparative analysis of members of the class Dothideomycetes showed that
genome evolution follows a pattern of frequent
short intra-chromosomal inversions and few
inter-chromosomal rearrangements (Hane
et al. 2011; Ohm et al. 2012).
In contrast to plant pathogens, mycorrhizal
fungi form a symbiosis that is beneficial to the
plant host. Generally, during this symbiosis the
fungus provides micronutrients to the plant,
while the plant provides carbohydrates (sugars
produced by photosynthesis) to the fungus.
This mycorrhizal lifestyle evolved independently several times across the fungal kingdom,
in species as diverse as the mushroom-forming
Basidiomycete Laccaria bicolor, the Dothideomycete Cenococcum geophilum, and the Pe ´rigord black truffle Tuber melanosporum
(Martin et al. 2008, 2010; Peter et al. 2016).
Although there are many differences between
these mycorrhizal fungi, a general pattern is
that (compared to their non-mycorrhizal relatives) the number of plant cell wall degrading
CAZymes decreased, while the number of
lineage-specific genes increased (especially
genes that were differentially expressed during
symbiosis). Nevertheless, mycorrhizal fungi
have retained a unique set of CAZymes, which
suggests that they are still capable of degrading
lignocellulose and therefore are not fully reliant
on their plant host (Kohler et al. 2015; Martino
et al. 2018).
The genus Trichoderma contains several
mycoparasitic species that promote plant
growth. To some extent this can be explained
by the fact that they parasitise on deleterious
plant pathogens. However, several strains also
induce root branching and increase shoot biomass (Kubicek et al. 2011; Druzhinina et al.
2011; Contreras-Cornejo et al. 2016).
V. Conclusions
This chapter described recent improvements in
sequencing technologies that are used to
sequence fungal genomes. As these sequencing
technologies mature further, it will soon be
trivial and affordable to obtain a high-quality
telomere-to-telomere assembly. Accurate gene
prediction and data analysis is still a challenge,
although algorithms and pipelines continue to
improve. Currently fungal genome sequencing
is already affordable to small labs and individual researchers. For those who are interested in
starting with fungal genome sequencing, the
following pipeline has proven to work very
well in my lab (as an example): we routinely
sequence fungal genomes using Illumina (occasionally supplemented with long read from
Oxford Nanopore) and genome assembly is
done with SPAdes (Bankevich et al. 2012).
Gene prediction is preferably done with
BRAKER in combination with RNA-Seq
expression data (Hoff et al. 2016). Basic functional annotation is done with InterProScan
(Hunter et al. 2009) and supplemented with
other algorithms, depending on the scientific
questions.
Important next steps include a functional
genomics approach, which relies heavily on an
accurate genome sequence. In functional genomics, high-throughput (sequencing-based)
techniques are used in an effort to assign function to elements of the genome (usually genes).
These techniques may include RNA-Seq (to
study gene expression), ChIP-Seq (to study various aspects of epigenetics), as well as highthroughput gene inactivations. Gene inactivations and other genome editing approaches
have been greatly facilitated by the develop9 Fungal Genomics
215