- Research article
- Open Access
Genome sequencing of evolved aspergilli populations reveals robust genomes, transversions in A. flavus, and sexual aberrancy in non-homologous end-joining mutants
BMC Biology volume 17, Article number: 88 (2019)
Aspergillus spp. comprises a very diverse group of lower eukaryotes with a high relevance for industrial applications and clinical implications. These multinucleate species are often cultured for many generations in the laboratory, which can unknowingly propagate hidden genetic mutations. To assess the likelihood of such events, we studied the genome stability of aspergilli by using a combination of mutation accumulation (MA) lines and whole genome sequencing.
We sequenced the whole genomes of 30 asexual and 10 sexual MA lines of three Aspergillus species (A. flavus, A. fumigatus and A. nidulans) and estimated that each MA line accumulated mutations for over 4000 mitoses during asexual cycles. We estimated mutation rates of 4.2 × 10−11 (A. flavus), 1.1 × 10−11 (A. fumigatus) and 4.1 × 10−11 (A. nidulans) per site per mitosis, suggesting that the genomes are very robust. Unexpectedly, we found a very high rate of GC → TA transversions only in A. flavus. In parallel, 30 asexual lines of the non-homologous end-joining (NHEJ) mutants of the three species were also allowed to accumulate mutations for the same number of mitoses. Sequencing of these NHEJ MA lines gave an estimated mutation rate of 5.1 × 10−11 (A. flavus), 2.2 × 10−11 (A. fumigatus) and 4.5 × 10−11 (A. nidulans) per base per mitosis, which is slightly higher than in the wild-type strains and some ~ 5–6 times lower than in the yeasts. Additionally, in A. nidulans, we found a NHEJ-dependent interference of the sexual cycle that is independent of the accumulation of mutations.
We present for the first time direct counts of the mutation rate of filamentous fungal species and find that Aspergillus genomes are very robust. Deletion of the NHEJ machinery results in a slight increase in the mutation rate, but at a rate we suggest is still safe to use for biotechnology purposes. Unexpectedly, we found GC→TA transversions predominated only in the species A. flavus, which could be generated by the hepatocarcinogen secondary metabolite aflatoxin. Lastly, a strong effect of the NHEJ mutation in self-crossing was observed and an increase in the mutations of the asexual lines was quantified.
The taxon of filamentous fungi comprises organisms of great importance for human daily life, as friends or foes. As friends, we take advantage of the capabilities of filamentous fungi to produce enzymes and compounds of interest to humans, such as pharmaceuticals. Some of these enzymes have proved to be highly useful in the production of bio-energy [1, 2] and fungal natural products impactful in many applications such as the antifungal echinocandins . Within the filamentous fungi group, aspergilli are widely used for biotechnological applications in industry. In particular, they have become model organisms to study different aspects of the bio-energy production, such as the production of cellulolytic enzymes useful for bioethanol production [4,5,6], the carbon-regulation of these enzymes [4, 7] and natural product synthesis as drug sources [3, 8, 9]. These studies rely on two important aspects of the biology of aspergilli: their fantastic features for fermentation purposes and the genetic amenability of the genus. The availibilty of many genome sequences of Aspergillus species makes this group of fungi very useful for comparative genomics [10,11,12]. As foes, some Aspergillus species are pathogens of humans, animals and/or plants, or appear as dangerous contaminants of crops before or after the harvest. They are capable of producing an ample diversity of secondary metabolites, such as the carcinogen aflatoxin [13,14,15,16].
However, the evolution of aspergilli is still understudied. One of the main problems studying the evolution of fitness in filamentous fungi is the concept of an individual  (see Fig. 1a for a diagram for the morphological structure of a filamentous fungus). Thus, most evolutionary studies in filamentous fungi involved the comparison between different species or extremely laborious phenotypic analysis in combination with genetic techniques, e.g. RFLP analysis . Some previous studies have shown that filamentous fungal evolution can be assessed experimentally under laboratory conditions [19, 20]. Using mutation accumulating (MA) lines for 40 generations, the base pair mutation rate in Aspergillus nidulans was estimated to be 2.26 × 10−10 using the classical Bateman-Mukai method . The recent availability of the genome sequences can boost the study of filamentous fungal evolution in a laboratory experiment to a level never experienced before. So far, evolution experiments in filamentous fungi have considered growth rates as a measurement of fitness. However, variations in growth rate could be the result of a physiological adaptation to the established growth conditions rather than the consequence of genome evolution.
The stability of genomes highly depends on the lifestyle and the complexity of each organism. Whereas viruses have very dynamic genomes, eukaryotic genomes are highly stable and eukaryotes do not cope well with insults to the genome. Yet cells are continuously exposed to DNA damaging agents. Therefore, the stability of the genome relies on a complex molecular machinery that repairs the damage. One such example of DNA repair machinery is the non-homologous end-joining (NHEJ), which joins two DNA molecules that had suffered double-strand breaks (DSBs) [22,23,24]. Thus, a doubt arose with the discovery of the NHEJ genes in filamentous fungi and the use of the NHEJ deletions as genetic tools . The underlying fundamental question behind the doubt is what is the role of the NHEJ system in the stability of an eukaryotic genome. Although this is a fundamental question in biology, the knowledge has direct consequences on biotechnology with the use of NHEJ mutants to generate new fungal strains with desired genetic modifications. The fungal homologues of the KU70 and KU80 required for NHEJ were first identified in Neurospora crassa . Following the spectacular results of N. crassa ∆ku70 strains as genetic tools, NHEJ mutants have been constructed in many other fungal species (for some examples, see [26,27,28,29,30,31]). N. crassa NHEJ mutants are more sensitive to bleomycin, a compound producing double-strand DNA breaks , although an A. nidulans NHEJ mutant did not appear to show increase sensitivity to this drug . However, there is an additional body of data generated in fungi that suggests that the KU70/KU80 heterodimer plays additional roles. For example, N. crassa and Aspergillus fumigatus mutants, but not A. nidulans, are more sensitive to agents producing point mutations [25, 33, 34], which were presumed to get repaired using different mechanisms. They are telomere-associated proteins contributing to the formation of heterochromatin in the telomeres . In A. nidulans, NkuAKU70 appears to regulate telomere position effects . Both ku70 and ku80 homologues were found to be overexpressed during asexual reproduction (conidiation) in a histone acetyltransferase mutant, suggesting that they are involved in the maintenance of genome stability in conidia, DNA repair or the responses to DNA stress . In haploid cells, as Aspergillus species normally propagate, DNA repair by homologous recombination (HR) of double-strand breaks is only possible in S and G2 phases of the cell cycle, when a sister chromatid is available. Therefore, the repair of double-strand breaks is expected to be more error-prone in a haploid because of the higher likelihood of using NHEJ repair.
As these additional roles of the KU70/KU80 heterodimer on fungal biology and potentially DNA stability have emerged, it is prudent for the academic community and industry to determine if the NHEJ mutants display concerning genome instability properties. A stable genome is especially important for biotechnology applications, where much time and money is spent to optimize processes and a small change in yield can have large financial consequences. In addition to insights on Aspergillus genome evolution and stability, we expect our results will be widely applicable to other fungi where the use of NHEJ mutants is expanding [28, 38, 39]. Therefore, and considering that strains lacking KU70/KU80 are commonplace in biotechnology, we decided to test the global consequences of such mutants for the stability of the genome. We studied the genome stability of aspergilli by using a combination of MA lines and whole genome sequencing (WGS). We found that Aspergillus genomes are very robust and the deletion of the NHEJ machinery results in a slight increase in the mutation rate, but at a rate, which we postulate, is still safe to use for biotechnology purposes.
MA lines, sequencing and identification of the mutations
Three different aspergilli species have been selected based on their different characteristics and relevance in the aspergilli community: A. nidulans, A. flavus and A. fumigatus. All species were already sequenced before this work started, and they have genome sizes ranging between 29.4 and 36.8 Mb [11, 40]. Ten independent MA lines for each strain (wild type and ∆ku70 of each species) were set up by picking ten individual isolated colonies as described in the “Materials and methods” section, and the strains were allowed to accumulate mutations by growing in complete media for 60 passages (Fig. 1b). Based on the nuclear division time in A. nidulans and previous calculations [19, 41] we estimated that nuclei underwent 4032 mitotic divisions. This strategy allowed the 10 populations of each strain to accumulate mutations independently from each other along the passages (Fig. 1b). Samples were taken at time 0 (controls) and at the end of the MA experiment for WGS.
The starting strains before the MA lines were established, together with 2 of the 10 independent MA lines set at the beginning and all the 10 independent MA lines after the 60 growth passages were employed for DNA isolation. There were several reasons for sequencing the populations at passage 0. First, the ∆ku70 deletion strain of A. fumigatus is in the strain D141, a mat1-1 isolate (rather than in the mat1-2 strain Af293, which was the sequenced one). Sequencing of the controls at time 0 solved this issue and also provided the sequence of D141 strain, which was largely syntenic to the Af293 genome. In the case of A. nidulans, the strains employed in this work are derived from the sequenced wild-type strain FGSC4. The DNA from all the populations was sequenced with 100× coverage on average. This coverage was selected to allow the identification of mutations that were present at low frequency and not fixed in the (nuclear) populations yet. Previous reports using average coverages of 44× and 62×, which are lower than ours, calculated a false-positive error close to zero by Sanger sequencing [42, 43]. Using this strategy, we were able to identify mutations with a frequency as low as 10% that were unique to one population (Fig. 2a).
Globally in the MA lines, we identified a total of 122 single nucleotide variants (SNVs) and 17 insertions/deletions (indels) in A. flavus, 27 SNVs and 10 indels in A. fumigatus and 75 SNVs and 29 indels in A. nidulans. Out of those mutations, the wild-type MA lines accumulated 58 SNVs and 5 indel in A. flavus, 10 SNVs and 2 indels in A. fumigatus and 32 SNVs and 18 indels in A. nidulans. Aspergillus species like other filamentous fungi are multicellular and multinucleated organisms, i.e. the hyphal filament consists of connected cell compartments, each containing several nuclei (Fig. 1a). Consequently, for the estimation of the mutation rate, we need to consider nuclear divisions (mitoses) rather than cell divisions as previously employed for unicellular eukaryotes [42,43,44,45,46,47]. As mentioned above, the estimation of the number of mitoses is complicated in the case of filamentous fungi. Our calculations of the number of mitoses are based on previous cell cycle studies performed by Bergen and Morris on liquid media , which did not differ substantially from studies by Kaminskyj and Hamer  on solid media. The number of nuclear divisions occurring during conidiophore development was not taken into account because the division times and nuclear dynamics in the stalk and vesicle cells are not well characterized. This is partially compensated by the fact that the samples for the cultures passages were taken from the conidiation edge of the colony, which is far behind from the real growing colony front. This strategy to estimate the number of mitoses during the growth passages has been previously carried out by Schoustra et al. . This approach gave a total mutation rate of 4.2 × 10−11 ± 5.6 × 10−12 (A. flavus), 1.1 × 10−11 ± 4.1 × 10−12 (A. fumigatus) and 4.1 × 10−11 ± 6.4 × 10−12 (A. nidulans) per base per mitosis and an average mutation rate for all three species of 3.1 × 10−11 ± 5.4 × 10−12 per base per mitosis revealing that indeed Aspergillus genomes are very robust in comparison to yeasts and higher eukaryotes. The distribution of mutations across the MA lines was consistent with a uniform distribution (Kolmogorov-Smirnov test (K-S test); P = 0.93, 0.31 and 0.91 for A. flavus, A. fumigatus and A. nidulans, respectively).
The ∆ku70 deletion mutants of the three species accumulated a slightly higher number of mutations: 64 SNVs and 12 indels in A. flavus, 17 SNVs and 8 indels in A. fumigatus and 43 SNVs and 11 indels in A. nidulans (Fig. 2b), which gives an estimate of a total mutation rate of 5.1 × 10−11 ± 4.7 × 10−12, 2.2 × 10−11 ± 3.8 × 10−12 and 4.5 × 10−11 ± 8.1 × 10−12 per base per mitosis for A. flavus, A. fumigatus and A. nidulans, respectively, and an average mutation rate for all three species of 3.9 × 10−11 ± 5.5 × 10−12 per base per mitosis. The distribution of mutations across the MA lines of the ∆ku70 mutants was also consistent with a uniform distribution (K-S test; P = 1.00, 0.77 and 0.97 for A. flavus, A. fumigatus and A. nidulans, respectively). The differences between the wild-type and the ∆ku70 mutant strains for each species are not statistically significant (two-way ANOVA with Tukey’s post hoc test, P = 0.675 for each pair of strains; two-tailed t test, P = 0.33, P = 0.14 and P = 0.67 for A. flavus, A. fumigatus and A. nidulans, respectively). However, if we did not consider the different species, and we take into account only the genetic background combining the data from the three wild-type strains and the data from the three ∆ku70 strains, then the differences between the wild-type and the mutant backgrounds are statistically significant (two-way ANOVA with Tukey’s post hoc test, P = 0.025), suggesting that the NHEJ has a role in the genome stability of aspergilli.
Distribution of mutations
The concept of an individual in filamentous fungi is a matter of debate and the definition of a physical individual has been even considered a “hopeless task” . Therefore, we considered our MA lines as populations of nuclei. Thanks to the high coverage of the sequencing, it was possible to detect mutations present in as low as 10% of the nuclei. A boxplot representation of the frequency of all the mutations in the six strains showed that there were a larger proportion of mutations that were not fixed in the ∆ku70 mutants than in the wild-type strain, suggesting that the mutations in the ∆ku70 mutants keep appearing at a slightly faster rate than in the wild-type strain (Additional file 1: Figure S1).
The distribution of single nucleotide mutations in the eight chromosomes appeared to be random and not statistically different from the expected number according to their sizes (K-S test; P = 0.92 and 0.92 for A. fumigatus wild-type and ∆ku70 mutant, and 0.92 and 1.00 for A. nidulans wild-type and ∆ku70 mutant, respectively) (Additional file 2: Figure S2). In the particular case of A. flavus, this analysis was complicated because the 138 contigs are not assigned to specific chromosomes. We tried to map these contigs to the chromosomes of the closely related species A. oryzae with little success. Therefore, we performed the analysis asking the question whether the mutations were uniformly distributed in the 138 contigs using the K-S test. In this case, we found that P < 0.001, meaning that the mutations were not uniformly distributed. Further analysis revealed that all the mutations were located in 20 contigs, which account for 99.25% of the total length of the genome, while the other 118 contigs only provide the remaining 0.75% of the genome, and consequently represent a minor portion of the genome. We repeated the test using only the 20 big contigs accounting for 99.25% of the genome and containing the mutations. In this case, P = 0.68 suggests that the distribution of mutations is random in these 20 contigs and in the genome of A. flavus.
Single nucleotide mutations and spectrum
Out of the 280 total number of mutations, we identified a total of 224 substitutions after filtering and confirmation by visual inspection, of which 58, 10 and 32 were found in wild-type A. flavus, A. fumigatus and A. nidulans, respectively, and 64, 17 and 43 were found in the ∆ku70 mutants of A. flavus, A. fumigatus and A. nidulans, respectively. That gives a base-substitution mutation rate of 3.9 × 10−11 ± 4.6 × 10−12 (A. flavus WT), 8.9 × 10−12 ± 3.2 × 10−12 (A. fumigatus WT) and 2.6 × 10−11 ± 4.7 × 10−12 (A. nidulans WT) per base per mitosis, which is one to two orders of magnitude lower than in ascomycete and basidiomycete yeasts [42, 43, 46, 47, 49]. The base-substitution rate for the ∆ku70 mutants was slightly higher: 4.3 × 10−11 ± 3.5 × 10−12 (A. flavus ∆ku70), 1.5 × 10−11 ± 3.3 × 10−12 (A. fumigatus ∆ku70) and 3.5 × 10−11 ± 7.9 × 10−12 (A. nidulans ∆ku70) per base per mitosis, but still lower than in the yeasts (Fig. 3).
We found the spectrum of base-substitution mutations varied enormously between the species. The transition/transversion (ts/tv) ratio was extremely low in A. flavus (0.3) and higher in A. fumigatus (2.3) and A. nidulans (1.9). However, the number of base-substitution mutations in A. fumigatus was very low. The number of transitions and transversions and the ts/tv ratio did not change significantly between the wild-type and the ∆ku70 mutant strains (Fig. 4a). The major changes found in the ∆ku70 mutants with respect to the wild-type strains were that the difference between the number of transitions and transversions was statistically significant in A. fumigatus ∆ku70 (two-tailed t test; P = 0.027) but not in the wild type (two-tailed t test; P = 0.36). In A. nidulans, the number of transversions (22) increased to reach nearly the number of transitions (21) in the ∆ku70, and consequently, the ts/tv ratio was close to 1.
Considering the very low ts/tv ratio in A. flavus, we note that this species produces the toxic and mutagenic secondary metabolite aflatoxin, well known for its induction of G→T and C→A transversions in human p53 gene [50, 51]. Following this fact, it was interesting to observe a strong G/C to A/T bias in A. flavus (Fig. 5a). Specifically, there were 5.8 times more G/C to A/T mutations than A/T to G/C mutations. This strong bias was not observed in A. fumigatus (1.0×) or A. nidulans (2.4×). This mutation bias towards A/T seemed to have been observed previously in many other species (). However, it is only found in A. flavus and not in the other two Aspergillus species, which do not produce aflatoxin, although A. nidulans produces the aflatoxin precursor sterigmatocystin. In A. flavus MA lines, the GC→TA transversions are particularly enriched (χ2; P < 0.001; df = 5), while in A. nidulans MA lines the GC→AT transitions are the most frequent substitutions (χ2; P < 0.001; df = 5). The most frequent SNPs were 31 times C→A and 27 times G→T in A. flavus, 6 times A→G, 5 times G→A and T→C in A. fumigatus and 22 times C→T and 17 times G→A in A. nidulans (Fig. 5b). According to these estimates, the genomes of A. flavus and A. nidulans have not reached a nucleotide-content equilibrium. The expected G + C% would be 15% in A. flavus and 29% in A. nidulans based solely on the base-substitution mutation rate. However, the G + C% content is 50.5% and 52.2% in the genic regions and 45.1% and 47.4% in the intergenic regions of A. flavus and A. nidulans, respectively. Since the differences between the expected and the observed G + C were very different, we further looked at the frequency of G + C in the third position in the triplet of the fourfold degenerate codons. A plot of the G + C% of each gene vs the G + C% of the synonymous sites revealed that the genome of A. flavus shows a higher dispersion of the data with a lower coefficient of determination (Additional file 3: Figure S3). The regression coefficient (slope) in A. flavus is also the lowest of the three, suggesting that A. flavus has the lowest bias towards G + C of the three species, which is in agreement with the observed data.
The analysis of the trinucleotide context can provide information about the causes of the mutations. Therefore, we also analysed the trinucleotide context of the base-substitution mutations, considering the nucleotides adjacent immediately before and after to the mutated nucleotide. This gives 64 possible combinations that can be reduced to 32 possibilities combining strand orientation nucleotides . The mutated nucleotide together with the neighbouring positions can be assigned to one of these 32 trinucleotides. From this, it was clear that G/C were mutated on average 6.6 and 2.4 times more than A/T in A. flavus and A. nidulans, respectively (Fig. 6). Although in A. flavus the trinucleotide that was most frequently mutated was ACA, the CpG environment accounted for 28% of the base-substitution mutations, while NCA accounted for 25%. In A. nidulans however, the most frequent trinucleotide was TCT, and NCT accounted for 24%, which was far higher than the 14% of mutations observed in CpG.
Most of the mutations in all the species were either non-synonymous (missense) or intergenic (Fig. 7, Additional file 4: Figure S4). In Additional file 5: Table S1, Additional file 6: Table S2 and Additional file 7: Table S3, there is a list with the genes found to contain mutations in our MA experiment. When we compared the total number of mutations in the wild-type strains with the ∆ku70 strains for each species, we found only a clear trend in the intergenic mutations (23 in the wild type vs 29 in the ∆ku70, 2 vs 10 and 22 vs 29 in A. flavus, A. fumigatus and A. nidulans, respectively). The ratio of synonymous to non-synonymous mutations was 0.21, 0.29 and 0.14 in the wild-type strains of A. flavus, A. fumigatus and A. nidulans, respectively, and 0.28, 0.09 and 0.41 in the ∆ku70 mutants of A. flavus, A. fumigatus and A. nidulans, respectively.
Out of the 280 total number of mutations, 56 indel mutations were identified in the six strains of Aspergillus, 19 were deletions and 37 were insertions, which on average accounts for 1.9 times more insertions than deletions (Fig. 4b). The distribution varied between species, being A. nidulans the species accumulating more indel mutations (7 deletions and 11 insertions in the wild-type strain). This is 1.8 times lower than the number of base-substitution mutations. The low proportion of indel mutations found in aspergilli (ranging from 0.08 to 0.36) is consistent with other organisms. In general, indels were observed to be increased in ∆ku70 mutants compared to the corresponding wild-type strain. However, insertions in the ∆ku70 were only significantly increased in A. flavus (one-tailed t test; P = 0.038) and deletions in A. fumigatus (one-tailed t test; P = 0.033). In A. nidulans, the number of indel mutations was even higher in the wild type (18 indel mutations) than in the ∆ku70 mutant (11 indel mutations), with a particular but not significant increase in the number of deletions (7 in the wild type vs 2 in the ∆ku70 mutant strain) (one-tailed t test; P = 0.09). Based on these data, we estimated an indel mutation rate of 3.4 × 10−12 ± 1.5 × 10−13 (A. flavus), 1.8 × 10−12 ± 1.2 × 10−13 (A. fumigatus) and 1.5 × 10−11 ± 4.4 × 10−13 (A. nidulans) per base per mitosis for the wild-type strains and 8.1 × 10−12 ± 2.2 × 10−13 (A. flavus), 7.1 × 10−12 ± 2.2 × 10−13 (A. fumigatus) and 9.1 × 10−12 ± 1.5 × 10−13 (A. nidulans) per base per mitosis for the ∆ku70 mutant strains.
Cessation of cleistothecia development in the sexual MA lines of the A. nidulans NHEJ mutants
A. nidulans is the only homothallic species of these three. Self-crossing provides a framework in which any mutations or changes in genome sequence or structure that arise during the meiotic divisions are not due to the genetic heterogeneity of two parental strains. Taking advantage of this characteristic, a similar procedure was carried out with A. nidulans during sexual reproduction. We employed the same 10 independent MA lines established for the asexual passages. This scenario combined mitotic with meiotic divisions. As it can be observed in Fig. 8, all the ∆ku70 MA lines stopped producing cleistothecia after 5–9 passages. On the other hand, most of the wild-type MA lines (7 out of 10) still produced cleistothecia after 10 passages. We can assume that the cessation of cleistothecia production was not a consequence of the accumulation of mutations, as only 15 mutations were identified in 9 populations of the ∆ku70 strain after 5 passages and 5 mutations were found in the wild-type MA lines, and none of them seem to play an essential role (Additional file 8: Table S4). Therefore, the causes of cessation in the production of cleistothecia could be either epigenetics, or big chromosomal re-arrangements, or shortening of the telomeres. Although null mutations in histone modification genes associated with defects in reproduction also show vegetative growth defects and mutants in the DNA methyltransferase still produce cleistothecia , hypomorphic mutations could be responsible for this inhibition (see the “Discussion” section for other explanations). Although it is easy to argue how either chromosomal re-arrangements or telomere shortening could result in sterile cleistothecia (empty cleistothecia, without ascospores), it is not obvious how they could inhibit cleistothecial formation.
After the 5 meiotic rounds and the subsequent WGS, we found a total of 20 mutations, 5 in the wild-type strain and 15 in the ∆ku70 mutant strain (Fig. 9). Even though the total number of mutations is higher in the ∆ku70, this is not statistically significant (one-tailed t test; P = 0.052). We identified a total of 2 indels, which were all accumulated in the wild-type strain. The number of base-substitution mutations was significantly higher in the ∆ku70 mutant strain (one-tailed t test; P = 0.028) with 15 mutations vs 3 mutations in the wild-type strain. The differences are mainly due to an increase number in transitions (1 in the wild-type vs 11 in the ∆ku70 strain). However, only one of the MA lines is the major contributor with 5 base-substitution mutations. This is the MA line number 5, which was capable of reaching the maximum number of sexual passages of all MA lines. Despite that the MA line 5 accumulated a higher number of mutations, the distribution of mutations across the MA lines was consistent with a uniform distribution (K-S test), P = 0.08 and 0.93 for the wild-type and the ∆ku70 strains, respectively.
Filamentous fungal species are excellent cell factories for the production of biotech goods such as organic acids, recombinant enzymes and pharmaceuticals. This makes them worth billions of euros every year. This is the first report that estimates the mutation rate based on WGS in filamentous fungi. We allowed 10 independent MA lines of each strain to accumulate mutations for over ~ 4000 mitoses with 60 growth passages. Under these conditions, we assumed that the nuclei with deleterious mutations were lost during the experiment, and only nuclei with mutations that can grow in complete media will progress. For this reason, we chose complete media rather than minimal media, which would have resulted in a lower accumulation of mutations due to the loss of many auxotrophic mutants. Globally, our experiment considered a total of ~ 242,000 mitoses and we sequenced the whole genomes with a 100× depth on average. After the analysis of ~ 1.9 × 1011-bp sequences, we have estimated that the total mutation rate is 3.1 × 10−11 ± 5.4 × 10−12 per base per mitosis on average for the three Aspergillus strains with small differences between the different species (4.2 × 10−11 ± 5.6 × 10−12 per base per mitosis in A. flavus, 1.1 × 10−11 ± 4.1 × 10−12 per base per mitosis in A. fumigatus and 4.1 × 10−11 ± 6.4 × 10−12 per base per mitosis in A. nidulans). Only the mutation rate of A. fumigatus seems to be statistically different from the other two Aspergillus species (two-way ANOVA, Tukey’s post hoc test P = 2.9 × 10−5 and 2.5 10−3 with A. flavus and A. nidulans, respectively). We considered two possible scenarios for these differences. First, the genome of A. fumigatus is more robust. However, it is hard to argue that this is due to its pathogenic capabilities, as it is an opportunistic pathogen and A. flavus is also a pathogenic species. The second and more likely possibility is that many calls in regions of poor/spurious read alignments in A. fumigatus were filtered out, resulting in a lower number. This second possibility is supported by the coverage depth of 97% in A. nidulans and only 90% in A. fumigatus.
The rate of non-homologous integrations of recombinant constructs during transformation is usually very high in filamentous fungi, which can make the construction of knock-out mutants, for example, a very laborious work. For this reason, most laboratories across the world have established the use of NHEJ mutants to increase the rate of the homologous integration [25, 28, 32, 53,54,55,56,57,58,59,60,61]. However, the genomic stability of these strains has not been tested up to date and raised concerns of the appropriateness of using these mutants in industry or to assess virulence in pathogenic fungi. Here, we found that the ∆ku70 deletion mutants accumulated an average of 1.2 times higher number of mutations: 76, 25 and 54 in all the MA lines. We estimated a total mutation rate of 5.1 × 10−11 ± 4.7 × 10−12 (A. flavus), 2.2 × 10−11 ± 3.8 × 10−12 (A. fumigatus) and 4.5 × 10−11 ± 8.1 × 10−12 (A. nidulans) per base per mitosis. The average mutation rate for all three species is 3.9 × 10−11 ± 5.5 × 10−12 per base per mitosis. This number, although statistically significant, did not increase drastically for mutations accumulated in ∆ku70 strains compared to the wild-type strains. Bruggeman et al. estimated a base-substitution mutation rate of 2.26 × 10−10 per base per mitosis for asexual passages of A. nidulans based solely on fitness assays . Our estimate using WGS is 10× lower (2.5 × 10−11 ± 4.2 × 10−12 per base per mitosis). When we compared the Aspergillus average base-substitution mutation rate with unicellular fungi (Fig. 3), we found that it is one order of magnitude lower than the reported mutation rates for yeasts: 1.70 ± 0.13 × 10−10 or 2.00 ± 0.10 × 10−10 per base per generation in Schizosaccharomyces pombe [42, 43], 1.67 × 10−10 per base per generation in Saccharomyces cerevisiae  and 1.90 × 10−10 per base per generation in the basidiomycete yeast Rhodotorula toruloides . Even more important, the base-substitution mutation rate in the ∆ku70 mutants is still 5.3–6.4 times lower than in the yeasts. S. cerevisiae is frequently employed as cell factory and also is very important in fermentation processes to make bread, beer or wine. Another cell factory bacterium Escherichia coli has a base-substitution mutation rate of 2.6 × 10−10 per base per generation based on reporter constructs , the same range as yeasts but an order of magnitude higher than the wild-type Aspergillus and 8.3 times higher than the ∆ku70 mutants. Taking altogether, this suggests that Aspergillus genomes are the most robust genomes of the cell factories analysed so far and that the ∆ku70 mutants have genomes that are robust enough for use directly in industrial fermentation processes.
The fact that the number of mutations is slightly higher in the ∆ku70 than in the wild-type strains raises some questions about alternative roles of the KU70/KU80 dimer in genome stability. After a DNA double-strand break, two possible repair mechanisms can act: the NHEJ and the HR [63, 64]. Many filamentous fungi are haploids during most of their life cycles, although diploids can be constructed and maintained in the lab. Therefore, in the absence of a sister chromatid and a homologous chromosome, the NHEJ is responsible for the repair of DSBs during the G1 and early S phases [63, 64]. However, in the absence of KU, cells are still capable of DNA resection in G1 at DSBs prior to repair by homologous recombination, which activates the checkpoints. Bergen and Morris  estimated that the G1 phase lasts 15 out of 75 min of the complete nuclear cycle of A. nidulans. Therefore, Aspergillus species spend most of their time in S or G2 phases (55 min) where sister chromatids are present and HR is possible. Indeed, the number of base-substitution mutations was on average 24% higher in the ∆ku70 than in the wild-type strain (ranging from 10 to 70%). This is in agreement with the time that Aspergillus spends in G1, which is approximately 20% of the total nuclear cycle. Furthermore, it has been shown in yeasts that the replication fork is stalled at fragile sites containing CCG and CAG trinucleotides that lead to DSBs . However, when we analysed the trinucleotide context of the mutations found in our MA lines, we found that only in the case of A. flavus mutations in the CCG trinucleotides are statistically significant (χ2; P = 0.001; df = 1). Actually in A. flavus MA lines, mutations in the CpG context are particularly enriched (χ2; P = 0.00; df = 1). In most of the reports describing the spontaneous mutation rates in eukaryotic organisms, mutations in this context are associated mainly to the oxidation of guanine to give 8-oxo-guanidine, which produces a GC→AT transition. These mutations are significantly increased in A. fumigatus and A. nidulans accounting for 32% and 39% of all the base-substitution mutations (χ2; P = 0.028 and 0.000; df = 1, respectively), but not in A. flavus (χ2; P = 0.517; df = 5). This can be easily explained because the strains were cultivated on the surface of solid media and continuously exposed to an air interphase for 8–9 months. Methylation of cytosines results in the spontaneous deamination of cytosines provoking a GC→AT transition. However, the oxidation of guanine is probably more parsimonious taking into account that 5-methylated cytosines (5-mC) have not been detected in neither A. nidulans nor A. flavus yet [52, 66,67,68], despite the existence of DNA methyltransferases in the aspergilli genomes.
The type of mutation that most called our attention was the high number of GC→TA transversions found in A. flavus MA lines, which accounts for nearly half of all the base-substitution mutations (χ2; P = 0.000; df = 1). As mentioned earlier, A. flavus produces the carcinogenic secondary metabolite aflatoxin, the most potent natural environmental mutagen known. Aflatoxin is infamous for causing human hepatocarcinomas by inducing mutations in the p53 oncogene [50, 51]. Specifically, an epoxide derivative of aflatoxin intercalates into DNA and the epoxide moiety reacts with the guanine residue to produce GC→TA transversions . A. fumigatus, which is unable to produce aflatoxin, accumulated only 11% of GC→TA transversions. On the other hand, A. nidulans produces an intermediate in the aflatoxin pathway, sterigmatocystin, which is also a carcinogen and shows demonstrable mutagenic properties in vitro . Yet evidence does not support a mutational role for sterigmatocystin in nature, likely due to the non-pathogenic nature of A. nidulans as well as the low levels of sterigmatocystin synthesized by this species in comparison to aflatoxin output in many A. flavus strains (including the strain used in this study which produces aflatoxin in the medium used to grow the strains, ). Indeed, in A. nidulans, the number of GC→TA transversions accumulated is not significantly increased (χ2; P = 0.500; df = 1). Considering the A. flavus data, this raises interesting questions about the consequences and advantages of producing mutagenic secondary metabolites for endogenous producers.
During this study, it was shown that the absence of KU70 lead to an early cessation of cleistothecia development after repetitive selfing crosses in A. nidulans. This observation was not reported in a previous article that employed 40 generations of MA lines . However, their setup was slightly different from our setup and this observation could have been overlooked. They observed a reduction in fitness after the 40 generations, which they argued was due to the accumulation of mutations . Another study in which Xu employed the heterothallic mushroom Agaricus bisporus  reported an inbreeding depression, as observed with the percentage of heterokaryons forming primordia, density of fruiting bodies and other parameters. Because A. bisporus is heterothallic, the inbreeding coefficient was 0.5 and yet they observed a significant decreased in the percentage of heterokaryons forming primordia . In our setup, because A. nidulans is homothallic, the inbreeding coefficient was 1.0. We observed that 30% of the wild-type MA lines ceased to form cleistothecia suggesting an inbreeding depression. In case of the ∆ku70 MA lines, all ceased to form cleistothecia before the 10 passages. The reason is unclear. Both strains are veA1, which made us to consider that this allele could not be responsible for the phenomenon. However, we cannot exclude possible genetic interactions between veA1 and ∆ku70 leading to the cessation of cleistothecia formation. Theoretically, chromosomal re-arrangements are more likely to be the cause than telomere shortening, because it appears to be specific to meiosis, and therefore the more drastic depression could be due to increased genomic instability in the absence of KU heterodimer in the ∆ku70 strain during meiosis. However, this does not explain why cleistothecia development was halted. The phenomenon resembles epigenetic regulation. Several studies have reported aberrancies in sexual development in A. nidulans (or A. flavus) chromatin modifying mutants including DmtA (a cytosine methyltransferase, ), SntB (a histone reader, ), Set3 (a chromatin-associated PHD domain protein, ) and HosA (a histone deacetylase, ).
Aspergilli are widely used in the biotechnology industry and are emerging as the best model systems for fungal genetics and comparative genomics with species that are pathogens of plants and/or animals. The increasing capacity of DNA sequencing has allowed us to evaluate the consequences of evolution in a control experiment in the laboratory for the first time in a multicellular eukaryote under standard non-selective conditions. The widespread use of the NHEJ strains has impelled this work. We have found that the genomes of the Aspergillus ∆ku70 strains are very robust, more than other cell factories employed in the biotech industry, and therefore they can be considered safe enough for production purposes. A stable genome is especially important for biotechnology applications, where much time and money is spent to optimize processes and a small change in yield can have large financial consequences. Therefore, as shown in this work, Aspergillus and their corresponding NHEJ mutants also offer robustness in addition to the other previously known advantages for industrial applications. The comparative studies on Aspergillus genome evolution and stability observed in this work can be extrapolated to other Aspergilli, and maybe also applicable to other fungi, where the use of NHEJ mutants is growing.
Materials and methods
Strains and media used in this study
There are several genes involved in the NHEJ DNA repair mechanism; for this work, only mutants in the homologues of human KU70 were employed to allow for comparisons between species. All the strains used in this study are listed in Additional file 9: Table S5. Strains were grown in Aspergillus complete media .
Establishment of MA lines and growth passages
The MA experiment was performed as previously described [19, 76] with small modifications as depicted in Fig. 1b. Appropriate dilutions of one single stock of spores of each strain were plated on 10 plates per strain containing complete solid media to give single isolated colonies. Ten independent colonies of each strain were point inoculated in the centre of individual plates (one plate per colony). Then, the 10 independent MA lines of each strain were established. Plates were incubated for 3 days at 37 °C (30 °C for A. flavus), and the spores were harvested and were kept frozen as controls.
Plugs were taken from the conidiating edge of each single colony, i.e. from the farthest point from the colony centre that was conidiating, just before there was only vegetative mycelium. Plugs were placed in a microcentrifuge tube with 1000 μl of tween 0.05% (0.02% for A. fumigatus) to resuspend the spores. For the next growth passage (generation), 2 μl of the suspension was inoculated in the centre of the plate and the plates were incubated at 37 °C (30 °C for A. flavus). Two passages were made per week, which accounted for bottlenecks every ~ 58 and ~ 77 nuclear mitosis (3 and 4 days, respectively).
In the case of A. nidulans, sexual passages were also performed. The procedure was the same, with the difference that one cleistothecium from each plate was picked, cleaned of spores and Hülle cells, and ascospores were resuspended in 200 μl of tween 0.05% and 0.02% respectively.
After all passaging was completed, gDNA of populations at passage 0 and after 60 passages was isolated using standard techniques. For standard fragment Illumina libraries, 500 ng–1 μg of genomic DNA was sheared using the Covaris E210 (Covaris) and sized selected for 475 bp using Agencourt Ampure Beads (Beckman Coulter). The DNA fragments were treated with end repair, A-tailing and adapter ligation using the TruSeq DNA Sample Prep Kit (Illumina) and purified using Agencourt Ampure Beads (Beckman Coulter). These were sequenced on HiSeq to produce 2 × 150 bp reads. These reads were aligned to the reference genome using BWA , and on average, 100× coverage was sequenced for each population. SNPs and small indels were called using bbtools callVariants.sh (https://sourceforge.net/projects/bbmap/) and allele frequencies estimated. The SRA accession numbers for the genome sequences are listed in Additional file 10: Table S6.
Filtering of mutations
To remove false-positive calls and identify the point mutations that appeared during the growth passages, we removed all calls that had less than 3 supporting reads. We found that in some areas, the sequenced strain was highly divergent from the reference genome deposited in the database. In these cases, only a small percentage of the reads from these regions were able to align, and none of the calls in these regions were reliable. To filter out these unreliable calls, they were also removed if they occurred in regions with less than 10% of the average depth to avoid false positives in highly diverged regions. Finally, since point mutations will be unique to only a single strain, all calls that were shared by multiple strains were removed.
Putative single nucleotide variants and small indels were identified using callVariants (from the bbmap package v37.06) with default parameters and adding “rarity = 0.05 minallelefraction = 0.05”. A series of filters were then applied, only calls unique to a single strain were retained, calls with less than 10% of the average depth were discarded after noting an excess of these calls in regions of poor/spurious read alignment especially in A. fumigatus and calls with less than 3 reads supporting the alternate allele were also discarded. The remaining calls were then manually reviewed using the Integrative Genomics Viewer (IGV)  genome browser to remove calls that were obviously bad, typically due to sequencing errors. Allele frequency counts were also manually adjusted during the review due to some issues with allele frequency estimates in that version of callVariants. No variants of higher complexity than SNVs and small indels were attempted.
The statistical tests described in the text for the analysis of the data were performed using Excel, PAST or STATGRAPHICS software.
Availability of data and materials
Strains used in this study are listed in Additional file 9: Table S5 and available at the Fungal Genetics Stock Center (http://www.fgsc.net/asperg.html). The last passage of the mutation accumulating lines is available on request to the laboratories (A. flavus from Keller lab, A. fumigatus from Braus lab and A. nidulans from Cánovas lab). The SRA accession numbers for the genome sequences are listed in Additional file 10: Table S6).
Pel HJ, de Winde JH, Archer DB, Dyer PS, Hofmann G, Schaap PJ, Turner G, de Vries RP, Albang R, Albermann K, et al. Genome sequencing and analysis of the versatile cell factory Aspergillus niger CBS 513.88. Nat Biotechnol. 2007;25(2):221–31.
Berka RM, Grigoriev IV, Otillar R, Salamov A, Grimwood J, Reid I, Ishmael N, John T, Darmond C, Moisan MC, et al. Comparative genomic analysis of the thermophilic biomass-degrading fungi Myceliophthora thermophila and Thielavia terrestris. Nat Biotechnol. 2011;29(10):922–7.
Yue Q, Chen L, Zhang X, Li K, Sun J, Liu X, An Z, Bills GF. Evolution of chemical diversity in echinocandin lipopeptide antifungal metabolites. Eukaryot Cell. 2015;14(7):698–718.
Stricker AR, Mach RL, de Graaff LH. Regulation of transcription of cellulases- and hemicellulases-encoding genes in Aspergillus niger and Hypocrea jecorina (Trichoderma reesei). Appl Microbiol Biotechnol. 2008;78(2):211–20.
Wang D, Sun J, Yu HL, Li CX, Bao J, Xu JH. Maximum saccharification of cellulose complex by an enzyme cocktail supplemented with cellulase from newly isolated Aspergillus fumigatus ECU0811. Appl Biochem Biotechnol. 2012;166(1):176–86.
Grigorevski-Lima AL, Da Vinha FN, Souza DT, Bispo AS, Bon EP, Coelho RR, Nascimento RP. Aspergillus fumigatus thermophilic and acidophilic endoglucanases. Appl Biochem Biotechnol. 2009;155(1–3):321–9.
Yamakawa Y, Endo Y, Li N, Yoshizawa M, Aoyama M, Watanabe A, Kanamaru K, Kato M, Kobayashi T. Regulation of cellulolytic genes by McmA, the SRF-MADS box protein in Aspergillus nidulans. Biochem Biophys Res Commun. 2013;431(4):777–82.
Clevenger KD, Bok JW, Ye R, Miley GP, Verdan MH, Velk T, Chen C, Yang K, Robey MT, Gao P, et al. A scalable platform to identify fungal secondary metabolites and their gene clusters. Nat Chem Biol. 2017;13(8):895–901.
Hendrickson L, Davis CR, Roach C, Nguyen DK, Aldrich T, McAda PC, Reeves CD. Lovastatin biosynthesis in Aspergillus terreus: characterization of blocked mutants, enzyme activities and a multifunctional polyketide synthase gene. Chem Biol. 1999;6(7):429–39.
Andersen MR, Salazar MP, Schaap PJ, van de Vondervoort PJ, Culley D, Thykaer J, Frisvad JC, Nielsen KF, Albang R, Albermann K, et al. Comparative genomics of citric-acid-producing Aspergillus niger ATCC 1015 versus enzyme-producing CBS 513.88. Genome Res. 2011;21(6):885–97.
Galagan JE, Calvo SE, Cuomo C, Ma LJ, Wortman JR, Batzoglou S, Lee SI, Basturkmen M, Spevak CC, Clutterbuck J, et al. Sequencing of Aspergillus nidulans and comparative analysis with A. fumigatus and A. oryzae. Nature. 2005;438(7071):1105–15.
Gibbons JG, Rokas A. The function and evolution of the Aspergillus genome. Trends Microbiol. 2013;21(1):14–22.
Bayram O, Braus GH. Coordination of secondary metabolism and development in fungi: the velvet family of regulatory proteins. FEMS Microbiol Rev. 2012;36(1):1–24.
Bok JW, Hoffmeister D, Maggio-Hall LA, Murillo R, Glasner JD, Keller NP. Genomic mining for Aspergillus natural products. Chem Biol. 2006;13(1):31–7.
Keller NP, Turner G, Bennett JW. Fungal secondary metabolism - from biochemistry to genomics. Nat Rev Microbiol. 2005;3(12):937–47.
Palmer JM, Keller NP. Secondary metabolism in fungi: does chromosomal location matter? Curr Opin Microbiol. 2010;13(4):431–6.
Pringle A, Taylor J. The fitness of filamentous fungi. Trends Microbiol. 2002;10(10):474–81.
Xu J. Analysis of inbreeding depression in Agaricus bisporus. Genetics. 1995;141(1):137–45.
Schoustra SE, Debets AJ, Slakhorst M, Hoekstra RF. Reducing the cost of resistance; experimental evolution in the filamentous fungus Aspergillus nidulans. J Evol Biol. 2006;19(4):1115–27.
Schoustra SE, Slakhorst M, Debets AJ, Hoekstra RF. Comparing artificial and natural selection in rate of adaptation to genetic stress in Aspergillus nidulans. J Evol Biol. 2005;18(4):771–8.
Bruggeman J, Debets AJ, Wijngaarden PJ, deVisser JA, Hoekstra RF. Sex slows down the accumulation of deleterious mutations in the homothallic fungus Aspergillus nidulans. Genetics. 2003;164(2):479–85.
Davis AJ, Chen DJ. DNA double strand break repair via non-homologous end-joining. Transl Cancer Res. 2013;2(3):130–43.
Dudasova Z, Dudas A, Chovanec M. Non-homologous end-joining factors of Saccharomyces cerevisiae. FEMS Microbiol Rev. 2004;28(5):581–601.
Walker JR, Corpina RA, Goldberg J. Structure of the Ku heterodimer bound to DNA and its implications for double-strand break repair. Nature. 2001;412(6847):607–14.
Ninomiya Y, Suzuki K, Ishii C, Inoue H. Highly efficient gene replacements in Neurospora strains deficient for nonhomologous end-joining. Proc Natl Acad Sci U S A. 2004;101(33):12248–53.
El-Khoury R, Sellem CH, Coppin E, Boivin A, Maas MF, Debuchy R, Sainsard-Chanet A. Gene deletion and allelic replacement in the filamentous fungus Podospora anserina. Curr Genet. 2008;53(4):249–58.
Nakazawa T, Honda Y. Absence of a gene encoding cytosine deaminase in the genome of the agaricomycete Coprinopsis cinerea enables simple marker recycling through 5-fluorocytosine counterselection. FEMS Microbiol Lett. 2015;362(15):fnv123.
Gandia M, Xu S, Font C, Marcos JF. Disruption of ku70 involved in non-homologous end-joining facilitates homologous recombination but increases temperature sensitivity in the phytopathogenic fungus Penicillium digitatum. Fungal biology. 2016;120(3):317–23.
Verbeke J, Beopoulos A, Nicaud JM. Efficient homologous recombination with short length flanking fragments in Ku70 deficient Yarrowia lipolytica strains. Biotechnol Lett. 2013;35(4):571–6.
Choquer M, Robin G, Le Pecheur P, Giraud C, Levis C, Viaud M. Ku70 or Ku80 deficiencies in the fungus Botrytis cinerea facilitate targeting of genes that are hard to knock out in a wild-type context. FEMS Microbiol Lett. 2008;289(2):225–32.
Guangtao Z, Hartl L, Schuster A, Polak S, Schmoll M, Wang T, Seidl V, Seiboth B. Gene targeting in a nonhomologous end joining deficient Hypocrea jecorina. J Biotechnol. 2009;139(2):146–51.
Nayak T, Szewczyk E, Oakley CE, Osmani A, Ukil L, Murray SL, Hynes MJ, Osmani SA, Oakley BR. A versatile and efficient gene targeting system for Aspergillus nidulans. Genetics. 2006;172(3):1557–66.
da Silva Ferreira ME, Kress MR, Savoldi M, Goldman MH, Hartl A, Heinekamp T, Brakhage AA, Goldman GH. The akuB(KU80) mutant deficient for nonhomologous end joining is a powerful tool for analyzing pathogenicity in Aspergillus fumigatus. Eukaryot Cell. 2006;5(1):207–11.
Nayak T, Edgerton-Morgan H, Horio T, Xiong Y, De Souza CP, Osmani SA, Oakley BR. Gamma-tubulin regulates the anaphase-promoting complex/cyclosome during interphase. J Cell Biol. 2010;190(3):317–30.
Nandakumar J, Cech TR. Finding the end: recruitment of telomerase to telomeres. Nat Rev Mol Cell Biol. 2013;14(2):69–82.
Palmer JM, Mallaredy S, Perry DW, Sanchez JF, Theisen JM, Szewczyk E, Oakley BR, Wang CC, Keller NP, Mirabito PM. Telomere position effect is regulated by heterochromatin-associated proteins and NkuA in Aspergillus nidulans. Microbiology. 2010;156(Pt 12):3522–31.
Canovas D, Marcos AT, Gacek A, Ramos MS, Gutierrez G, Reyes-Dominguez Y, Strauss J. The histone acetyltransferase GcnE (GCN5) plays a central role in the regulation of Aspergillus asexual development. Genetics. 2014;197(4):1175–89.
Catalano V, Vergara M, Hauzenberger JR, Seiboth B, Sarrocco S, Vannacci G, Kubicek CP, Seidl-Seiboth V. Use of a non-homologous end-joining-deficient strain (delta-ku70) of the biocontrol fungus Trichoderma virens to investigate the function of the laccase gene lcc1 in sclerotia degradation. Curr Genet. 2011;57(1):13–23.
Liu H, Wang G, Li W, Liu X, Li E, Yin WB. A highly efficient genetic system for the identification of a harzianum B biosynthetic gene cluster in Trichoderma hypoxylon. Microbiology. 2018;164:769–78.
Nierman WC, Yu J, Fedorova-Abrams ND, Losada L, Cleveland TE, Bhatnagar D, Bennett JW, Dean R, Payne GA. Genome sequence of Aspergillus flavus NRRL 3357, a strain that causes aflatoxin contamination of food and feed. Genome announcements. 2015;3(2):e00168–15.
Bergen LG, Morris NR. Kinetics of the nuclear division cycle of Aspergillus nidulans. J Bacteriol. 1983;156(1):155–60.
Farlow A, Long H, Arnoux S, Sung W, Doak TG, Nordborg M, Lynch M. The spontaneous mutation rate in the fission yeast Schizosaccharomyces pombe. Genetics. 2015;201(2):737–44.
Behringer MG, Hall DW. Genome-wide estimates of mutation rates and spectrum in Schizosaccharomyces pombe indicate CpG sites are highly mutagenic despite the absence of DNA methylation. G3. 2015;6(1):149–60.
Sung W, Tucker AE, Doak TG, Choi E, Thomas WK, Lynch M. Extraordinary genome stability in the ciliate Paramecium tetraurelia. Proc Natl Acad Sci U S A. 2012;109(47):19339–44.
Long H, Winter DJ, Chang AY, Sung W, Wu SH, Balboa M, Azevedo RBR, Cartwright RA, Lynch M, Zufall RA. Low base-substitution mutation rate in the germline genome of the ciliate Tetrahymena thermophil. Genome Biol Evol. 2016;8(12):3629–39.
Zhu YO, Siegal ML, Hall DW, Petrov DA. Precise estimates of mutation rate and spectrum in yeast. Proc Natl Acad Sci U S A. 2014;111(22):E2310–8.
Long H, Behringer MG, Williams E, Te R, Lynch M. Similar mutation rates but highly diverse mutation spectra in ascomycete and basidiomycete yeasts. Genome Biol Evol. 2016;8(12):3815–21.
Kaminskyj SG, Hamer JE. hyp loci control cell pattern formation in the vegetative mycelium of Aspergillus nidulans. Genetics. 1998;148(2):669–80.
Lynch M, Sung W, Morris K, Coffey N, Landry CR, Dopman EB, Dickinson WJ, Okamoto K, Kulkarni S, Hartl DL, et al. A genome-wide view of the spectrum of spontaneous mutations in yeast. Proc Natl Acad Sci U S A. 2008;105(27):9272–7.
Lasky T, Magder L. Hepatocellular carcinoma p53 G > T transversions at codon 249: the fingerprint of aflatoxin exposure? Environ Health Perspect. 1997;105(4):392–7.
Zhang W, He H, Zang M, Wu Q, Zhao H, Lu LL, Ma P, Zheng H, Wang N, Zhang Y, et al. Genetic features of aflatoxin-associated hepatocellular carcinoma. Gastroenterology. 2017;153(1):249–62 e242.
Lee DW, Freitag M, Selker EU, Aramayo R. A cytosine methyltransferase homologue is essential for sexual development in Aspergillus nidulans. PLoS One. 2008;3(6):e2531.
Carvalho ND, Arentshorst M, Jin Kwon M, Meyer V, Ram AF. Expanding the ku70 toolbox for filamentous fungi: establishment of complementation vectors and recipient strains for advanced gene analyses. Appl Microbiol Biotechnol. 2010;87(4):1463–73.
Chang PK, Scharfenstein LL, Wei Q, Bhatnagar D. Development and refinement of a high-efficiency gene-targeting system for Aspergillus flavus. J Microbiol Methods. 2010;81(3):240–6.
Krappmann S, Sasse C, Braus GH. Gene targeting in Aspergillus fumigatus by homologous recombination is facilitated in a nonhomologous end- joining-deficient genetic background. Eukaryot Cell. 2006;5(1):212–5.
Meyer V, Arentshorst M, El-Ghezal A, Drews AC, Kooistra R, van den Hondel CA, Ram AF. Highly efficient gene targeting in the Aspergillus niger kusA mutant. J Biotechnol. 2007;128(4):770–5.
Nakazawa T, Ando Y, Kitaaki K, Nakahori K, Kamada T. Efficient gene targeting in ∆Cc.ku70 or ∆Cc.lig4 mutants of the agaricomycete Coprinopsis cinerea. Fungal Genet Biol. 2011;48(10):939–46.
Zhang J, Mao Z, Xue W, Li Y, Tang G, Wang A, Zhang Y, Wang H. Ku80 gene is related to non-homologous end-joining and genome stability in Aspergillus niger. Curr Microbiol. 2011;62(4):1342–6.
de Boer P, Bastiaans J, Touw H, Kerkman R, Bronkhof J, van den Berg M, Offringa R. Highly efficient gene targeting in Penicillium chrysogenum using the bi-partite approach in ∆lig4 or ∆ku70 mutants. Fungal Genet Biol. 2010;47(10):839–46.
Bugeja HE, Boyce KJ, Weerasinghe H, Beard S, Jeziorowski A, Pasricha S, Payne M, Schreider L, Andrianopoulos A. Tools for high efficiency genetic manipulation of the human pathogen Penicillium marneffei. Fungal Genet Biol. 2012;49(10):772–8.
Villalba F, Collemare J, Landraud P, Lambou K, Brozek V, Cirer B, Morin D, Bruel C, Beffa R, Lebrun MH. Improved gene targeting in Magnaporthe grisea by inactivation of MgKU80 required for non-homologous end joining. Fungal Genet Biol. 2008;45(1):68–75.
Lynch M. Evolution of the mutation rate. Trends Genet. 2010;26(8):345–52.
Huertas P. DNA resection in eukaryotes: deciding how to fix the break. Nat Struct Mol Biol. 2010;17(1):11–6.
Hopfner KP, Putnam CD, Tainer JA. DNA double-strand break repair from head to tail. Curr Opin Struct Biol. 2002;12(1):115–22.
Aguilera A, Gomez-Gonzalez B. Genome instability: a mechanistic view of its causes and consequences. Nat Rev Genet. 2008;9(3):204–17.
Antequera F, Tamame M, Villanueva JR, Santos T. DNA methylation in the fungi. J Biol Chem. 1984;259(13):8033–6.
Liu SY, Lin JQ, Wu HL, Wang CC, Huang SJ, Luo YF, Sun JH, Zhou JX, Yan SJ, He JG, et al. Bisulfite sequencing reveals that Aspergillus flavus holds a hollow in DNA methylation. PLoS One. 2012;7(1):e30349.
Tamame M, Antequera F, Villanueva JR, Santos T. High-frequency conversion to a “fluffy” developmental phenotype in Aspergillus spp. by 5-azacytidine treatment: evidence for involvement of a single nuclear gene. Mol Cell Biol. 1983;3(12):2287–97.
Smela ME, Currier SS, Bailey EA, Essigmann JM. The chemistry and biology of aflatoxin B(1): from mutational spectrometry to carcinogenesis. Carcinogenesis. 2001;22(4):535–45.
Kuczuk MH, Benson PM, Heath H, Hayes AW. Evaluation of the mutagenic potential of mycotoxins using Salmonella typhimurium and Saccharomyces cerevisiae. Mutat Res. 1978;53(1):11–20.
Kale SP, Milde L, Trapp MK, Frisvad JC, Keller NP, Bok JW. Requirement of LaeA for secondary metabolism and sclerotial production in Aspergillus flavus. Fungal Genet Biol. 2008;45(10):1422–9.
Pfannenstiel BT, Greco C, Sukowaty AT, Keller NP. The epigenetic reader SntB regulates secondary metabolism, development and global histone modifications in Aspergillus flavus. Fungal Genet Biol. 2018;120:9–18.
Lan H, Wu L, Fan K, Sun R, Yang G, Zhang F, Yang K, Lin X, Chen Y, Tian J, et al. Set3 is required for asexual development, aflatoxin biosynthesis, and fungal virulence in Aspergillus flavus. Front Microbiol. 2019;10:530.
Lan H, Wu L, Sun R, Keller NP, Yang K, Ye L, He S, Zhang F, Wang S. The HosA histone deacetylase regulates aflatoxin biosynthesis through direct regulation of aflatoxin cluster genes. Mol Plant Microbe Interact. 2019;32(9):1210–28.
Cove DJ. The induction and repression of nitrate reductase in the fungus Aspergillus nidulans. Biochim Biophys Acta. 1966;113(1):51–6.
Schoustra SE, Bataillon T, Gifford DR, Kassen R. The properties of adaptive walks in evolving populations of fungus. PLoS Biol. 2009;7(11):e1000250.
Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25(14):1754–60.
Robinson JT, Thorvaldsdottir H, Winckler W, Guttman M, Lander ES, Getz G, Mesirov JP. Integrative genomics viewer. Nat Biotechnol. 2011;29(1):24–6.
Denver DR, Wilhelm LJ, Howe DK, Gafner K, Dolan PC, Baer CF. Variation in base-substitution mutation in experimental and natural lineages of Caenorhabditis nematodes. Genome Biol Evol. 2012;4(4):513–22.
Drost JB, Lee WR. Biological basis of germline mutation: comparisons of spontaneous germline mutation rates among drosophila, mouse, and human. Environ Mol Mutagen. 1995;25(Suppl 26):48–64.
Ness RW, Morgan AD, Vasanthakrishnan RB, Colegrave N, Keightley PD. Extensive de novo mutation rate variation between individuals and across the genome of Chlamydomonas reinhardtii. Genome Res. 2015;25(11):1739–49.
Ossowski S, Schneeberger K, Lucas-Lledo JI, Warthmann N, Clark RM, Shaw RG, Weigel D, Lynch M. The rate and molecular spectrum of spontaneous mutations in Arabidopsis thaliana. Science. 2010;327(5961):92–4.
Saxer G, Havlak P, Fox SA, Quance MA, Gupta S, Fofanov Y, Strassmann JE, Queller DC. Whole genome sequencing of mutation accumulation lines reveals a low mutation rate in the social amoeba Dictyostelium discoideum. PLoS One. 2012;7(10):e46759.
D.C. would like to thank Pablo Huertas for comments on the manuscript, Berl Oakley for the helpful discussions on nuclear division timing and Luka Pavageau for the help with the DNA isolation.
The work conducted by the U.S. Department of Energy Joint Genome Institute, a DOE Office of Science User Facility, was supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. The work was supported by the Spanish Ministry of Economy and Competitiveness (MINECO, grant number BIO2015-67148-R) to DC, NIH R01AI065728 to N.P.K., NIH SBIR R44AI118086 to J.W.B. and by the Deutsche Forschungsgemeinschaft (DFG: BR1502/11-2 and SFB860) to GHB.
Ethics approval and consent to participate
Consent for publication
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Additional file 1: Figure S1. Boxplot showing the frequency of each mutation identified in all the MA lines of each strain. MA lines consist of populations of nuclei. The boxplot represents the frequency of each mutation found in each population of nuclei in each MA line. Mutations were called when they were present in more than 10% of nuclei.
Additional file 2: Figure S2. The distribution of mutations per chromosome in the Aspergillus species. Total number of mutations per chromosome in all MA lines of both wild type and ∆ku70 mutant strains are shown for each species. Black bars represent the chromosomes in which the ku70 and ku80 genes are located in each species.
Additional file 3: Figure S3. The plot depict the GC (G + C %) in the y-axis vs the GC4fold (G + C% in the third position of the four fold degenerate triplets) for each coding region of the genes in the three species. Formulas represent the linear fit of the data and the coefficient of determination of the fit.
About this article
Cite this article
Álvarez-Escribano, I., Sasse, C., Bok, J.W. et al. Genome sequencing of evolved aspergilli populations reveals robust genomes, transversions in A. flavus, and sexual aberrancy in non-homologous end-joining mutants. BMC Biol 17, 88 (2019) doi:10.1186/s12915-019-0702-0
- Mutation accumulating lines
- Genome stability
- Non-homologous end-joining