1
Genome-wide characterization of light-regulated genes in Neurospora crassa
2
Cheng Wu1, Fei Yang1, Kristina M. Smith2, Matthew Peterson3, Rigzin Dekhang1, Ying
3
Zhang1, Jeremy Zucker4, Erin L. Bredeweg2, Chandrashekara Mallappa5, Xiaoying Zhou5,
4
Anna Lyubetskaya6, Jeffrey P. Townsend7,8, James E. Galagan3,4,6,9, Michael Freitag2, Jay C.
5
Dunlap5, Deborah Bell-Pedersen1, Matthew S. Sachs1*
6
1
7
2
8
97331-7305.
9
3
10
4
11
5
12
03755-3844
13
6
14
7
15
CT 06520
16
8
17
9
Department of Biology, Texas A&M University, College Station, Texas 77843-3258.
Department of Biochemistry and Biophysics, Oregon State University, Corvallis, OR
Department of Biomedical Engineering, Boston University, Boston, MA 02215
The Eli and Edy L. Broad Institute of Harvard and MIT, Cambridge, MA 02142
Department of Genetics, Geisel School of Medicine, Dartmouth College, Hanover, NH
Bioinformatics Program, Boston University, Boston, MA 02215
Department of Ecology and Evolutionary Biology, Yale University, New Haven,
Department of Biostatistics, Yale School of Public Health, New Haven, CT 06520
Department of Microbiology, Boston University, Boston, MA 02215
18
19
* To whom correspondence should be addressed; E-mail: [email protected]
1
20
ABSTRACT
21
The filamentous fungus Neurospora crassa responds to light in complex ways. To
22
thoroughly study the transcriptional response of this organism to light, RNA-seq was used to
23
analyze capped and polyadenylated mRNA prepared from mycelium grown for 24 hr in the
24
dark and then exposed to light for 0 (control) 15, 60, 120 and 240 min. More than three
25
quarters of all defined protein coding genes (79%) were expressed in these cells. The
26
increased sensitivity of RNA-seq compared to previous microarray studies revealed that the
27
RNA levels for 31% of expressed genes were affected 2-fold or more by exposure to light.
28
Additionally, a large class of mRNAs, enriched for transcripts specifying products involved in
29
rRNA metabolism, showed decreased expression in response to light, indicating a heretofore
30
undocumented effect of light on this pathway. Based on measured changes in mRNA levels,
31
light generally increases cellular metabolism, and at the same time causes significant
32
oxidative stress to the organism. To deal with this stress, protective photopigments are made,
33
antioxidants are produced and genes involved in ribosome biogenesis are transiently
34
repressed.
35
2
36
INTRODUCTION
37
The ability to sense and respond to light is critical for the survival of most organisms. In
38
Neurospora crassa, one of the best studied model systems for light responses, blue light
39
controls many physiological processes including the synthesis of protective photopigments
40
(carotenoids), asexual and sexual spore formation, the direction of sexual spore release, and
41
entrainment and resetting of the circadian clock (BAHN et al. 2007; BALLARIO and MACINO
42
1997; CHEN et al. 2010; CORROCHANO 2007; CORROCHANO 2011; HERRERA-ESTRELLA and
43
HORWITZ 2007; LINDEN and MACINO 1997; PURSCHWITZ et al. 2006). Underlying these
44
light-regulated physiological processes is the transcriptional control of gene expression.
45
Neurospora perceives blue light through the photoreceptor and GATA zinc finger
46
transcription factor encoded by white collar-1 (wc-1, NCU02356); the chromophore flavin
47
adenine dinucleotide (FAD) is bound by WC-1 and undergoes a transient covalent addition to
48
the protein upon illumination (BALLARIO et al. 1996; CHEN and LOROS 2009; FROEHLICH et
49
al. 2002; HE et al. 2002; LINDEN et al. 1997b; SARGENT and BRIGGS 1967). WC-1 interacts
50
with the zinc-finger protein WC-2 (encoded by NCU00902) through its Per-Arnt-Sim (PAS)
51
domain to form a heterodimeric transcription factor, the White Collar Complex (WCC)
52
(BALLARIO et al. 1996; CHENG et al. 2002; CROSTHWAITE et al. 1997; DENAULT et al. 2001).
53
Upon light exposure, the WCC can bind to light-responsive elements (LREs) in the promoters
54
of many light-responsive genes to activate their transcription (CHENG et al. 2003; FROEHLICH
3
55
et al. 2002; HE and LIU 2005; OLMEDO et al. 2010a; SMITH et al. 2010). In addition to WC-1,
56
the blue light photoreceptor VVD, encoded by vivid (vvd, NCU03967), which is strongly
57
light-induced under the control of the WCC, plays a key role in photoadaptation by
58
desensitizing the WCC-mediated light response, and thereby reducing the transcription of
59
WCC target genes (CHEN et al. 2010; GIN et al. 2013; HEINTZEN et al. 2001; HUNT et al.
60
2010; MALZAHN et al. 2010; SCHWERDTFEGER and LINDEN 2000; SCHWERDTFEGER and
61
LINDEN 2003; SHRODE et al. 2001). The Neurospora genome sequence revealed several
62
additional putative photoreceptors, including a cryptochrome (cry, NCU00582), two
63
phytochrome homologs (NCU04834 and NCU05790), and an opsin (nop-1, NCU10055)
64
(BIESZKE et al. 1999b; GALAGAN et al. 2003). However, the effects of deletion of these
65
candidate photoreceptors on physiology and light-controlled gene expression are subtle
66
(CHEN et al. 2009; FROEHLICH et al. 2010; FROEHLICH et al. 2005; OLMEDO et al. 2010b),
67
consistent with a primary role for the WCC in Neurospora light signaling cascades (CHEN et
68
al. 2009).
69
To better understand gene regulation in N. crassa in response to light, several studies
70
have identified light-controlled genes (CHEN et al. 2009; DONG et al. 2008; LEWIS et al. 2002;
71
SMITH et al. 2010). Estimates of the number of light-responsive genes based on microarray
72
analyses have varied widely, ranging from 3-14 % of the genome (CHEN et al. 2009; DONG et
73
al. 2008; LEWIS et al. 2002), reflecting the use of different microarray platforms, strains,
4
74
culture conditions and statistical cut-offs. Light-induced genes can be roughly classified as
75
early-response (with peak mRNA levels between 15-45 min of light treatment), and
76
late-response (with peak mRNA levels between 45-90 min of light treatment), consistent with
77
earlier patterns detected from analyses of individual genes (LINDEN et al. 1997a).
78
More recently ChIP-seq was used to identify ~400 direct targets of light-activated WCC
79
(SMITH et al. 2010); genes encoding transcription factors (TFs) were overrepresented. This
80
was consistent with expression studies that uncovered a hierarchical network in which the
81
light-activated WCC directly controls expression of early light-induced genes, including some
82
of the TF genes identified as direct WCC targets (Chen et al., 2009). Early light-induced
83
proteins in turn control the expression of late light-induced genes. Among the early
84
light-induced TFs, SUB-1 (submerged protoperithecia-1, NCU01154), are necessary for
85
light-induction of a large set of the late light-inducible genes (CHEN et al. 2009), and CSP-1
86
(conidial separation-1, NCU02713) acted at a similar place as sub-1 in the hierarchy, just
87
below WC-1 (CHEN and LOROS 2009; SANCAR et al. 2011).
88
To better understand the organism’s response to light and to comprehensively describe
89
the light-controlled gene regulatory network, we used RNA-seq to identify N. crassa
90
transcripts whose levels are responsive to light. We compared RNA-seq data from dark-grown
91
cells to that from cells exposed to light for between 15 and 240 min, and identified both
92
known and novel light-induced genes. We also discovered many transcripts whose levels
5
93
decreased in response to light. This latter class of transcripts is enriched for genes whose
94
products function in ribosome biogenesis; this response to light has not been described
95
previously.
96
RESULTS
97
RNA-seq to identify light-regulated transcripts
98
We grew N. crassa in liquid cultures in the dark for 24 hr, and then exposed the cultures
99
to light for 15, 60, 120, or 240 min. Capped and polyadenylated mRNA was purified from
100
harvested cells, hexanucleotide-primed cDNA was produced and sequenced, and results of
101
two independent biological replicates are reported here. The reproducibility between
102
biological replicates was excellent for cultures grown in the dark or exposed to light for 15,
103
60 and 120 min (R2>0.95); there was more divergence between the replicate cultures exposed
104
to light for 240 min (R2=0.75) (Figure 1). For determining expression levels of individual
105
genes, and for statistical analyses, the data from the biological replicates were pooled and
106
analyzed with CuffDiff 2.0 (TRAPNELL et al. 2013). The analyses of the combined data are
107
given in Table S1; the analyses of each independent experiment are given in Table S2 and
108
Table S3. Based on the analyses of the combined data, 79% of predicted protein coding genes
109
(7660 of 9728) were expressed with FPKM>1 (FPKM, fragments per kilobase per million
110
reads) at one or more time points analyzed, and these were considered “expressed genes”
111
under these growth conditions. Most expressed genes (55%) specified proteins that have
6
112
known functions in N. crassa or other organisms or whose sequences are conserved in the
113
fungi or other organisms. In contrast, only 16% (341 of 2068) of the poorly or non-expressed
114
genes (FPKM<1 at all time points analyzed) specified known or conserved proteins.
115
Importantly, among the poorly expressed genes that specified proteins with known functions
116
were many that had roles in secondary metabolism or were associated with the sexual cycle
117
(Table S4), consistent with their low expression under the vegetative culture conditions used
118
here.
119
Our observations of genes abundantly expressed in the dark (and also in the light) were
120
generally consistent with prior work using microarrays (KASUGA et al. 2005). The most
121
abundant transcripts in the cell were those implicated in thiamine biosynthesis (NCU06110
122
and NCU09345) (CHEAH et al. 2007; FAOU and TROPSCHUG 2003; FAOU and TROPSCHUG
123
2004; MCCOLL et al. 2003). Also present at high levels in these cultures (FPKM>400 or
124
FPKM>1000) were transcripts encoding proteins involved in translation, including those
125
specifying ribosomal proteins and translation factors, and those with roles in energy
126
metabolism (Figure 2A and Table S5).
127
Light has a major effect on the physiology of Neurospora and this is reflected in
128
light-driven changes in the levels of many transcripts. Transcript levels changed at least
129
twofold for at least one time point with respect to the dark-grown sample in 24% of the
130
predicted protein coding genes (2353 of 9728), or 31% of the expressed genes (2353/7660)
7
131
(Table S6). Among the transcripts whose levels increased in response to light, the major
132
fraction has unclassified functions in the FunCat scheme (RUEPP et al. 2004); genes with roles
133
in carbon metabolism and in stress responses are also among those that are significantly
134
over-represented (Figure 2B and Table S7). Among the transcripts whose levels decreased in
135
response to light, genes with roles in metabolism and biogenenesis were significantly
136
over-represented (Figure 2C and Table S8).
137
Cluster analysis of light-regulated transcripts
138
As noted above, a characteristic of the light response is that subsets of genes are
139
regulated with different kinetics, and this suggested that cellular functions might be
140
temporally coordinated. To set the stage for hierarchical clustering of genes by regulation, we
141
identified a subset of transcripts (5%, 532 of 9728 genes) that demonstrated a change in level
142
with a q-value of 0.2 or less in the combined analysis of the two independent experiments
143
(Table S9). The q value provides a measure of the false discovery rate, and 532 genes had
144
q≤0.2, 392 genes had q≤0.1 and 300 genes had q≤0.05 for at least one time point (Table S9).
145
In the aggregate this subset of 532 genes with q≤0.2 generally reflected the same functional
146
categories as the larger set of 2352 genes with a 2-fold change in levels in response to light
147
(compare Figure 2B with Figure 2D and Cluster 5 in Figure 3C), except that unclassified
148
genes are not a major enriched category among the genes whose expression level changes
149
were significant at q0.2. Comparisons of genes based on gene ontology (GO) to examine
8
150
enrichments in the two datasets (all genes that were 2-fold regulated by light and all genes
151
whose light regulation met the q0.2 stringency requirement) showed overall similar
152
correspondences in GO terms for the top classes (Table S10), with unclassified genes missing
153
in the q0.2 set.
154
Hierarchical clustering based on changes in expression of the 532 gene set relative to the
155
dark sample (Figure 3A) revealed 310 transcripts up-regulated and, surprisingly, 222
156
transcripts down-regulated in response to light, the latter representing a class not heretofore
157
described in N. crassa. We demarcated genes with common expression profiles into five main
158
clusters based on analyses of overall differences in expression patterns in the tree-structure
159
(Figure 3A and Figure 3B). The average transcript level of all genes in each cluster at each
160
time point in the light relative to the average transcript level in the dark are given in Figure
161
3B. FunCat (RUEPP et al. 2004) and GO analyses of the genes in each cluster identified
162
significantly enriched functional gene categories (Figure 3C and Table S11).
163
Cluster 1 includes transcripts with rapid, high level, sustained light responses. This
164
cluster was significantly enriched for genes involved in carotenoid biosynthesis, such as
165
albino-1 (al-1) (NCU00552) and al-2 (NCU00585), and blue light photoresponses, including
166
the photoreceptor genes vvd and cry, both of which attenuate WCC light responses
167
(HEINTZEN et al. 2001; OLMEDO et al. 2010b). The observation that vvd mRNA levels are
168
induced >100 fold, while the transcripts for its activator WC-1 (LEE et al. 2003) are rising and
9
169
peak later in the light, suggests that basal levels of WC-1 are sufficient to maintain
170
photoresponses. The conidiation (con)-related genes con-10 (NCU07325) and con-6
171
(NCU08769) (BERLIN and YANOFSKY 1985), originally identified by their induction during
172
conidiation, and previously shown to be light-responsive (CORROCHANO et al. 1995; LAUTER
173
and RUSSO 1991) are also included in this group.
174
Cluster 2 represents genes that were typically induced by light within 15 min, but
175
returned to dark levels by 60 or 120 min. This response is typical of the light adaptation
176
response of Neurospora that is mediated through feedback inhibition of the WCC by the
177
photoreceptor VVD present in cluster 1 (CHEN et al. 2010; HEINTZEN et al. 2001; MALZAHN
178
et al. 2010; SCHWERDTFEGER and LINDEN 2001; SCHWERDTFEGER and LINDEN 2003;
179
SHRODE et al. 2001). Cluster 2 includes WC-1 (NCU02356), and several of the TFs known to
180
be direct targets of WCC:
181
(csp-2, NCU06095), vos-1 (NCU05964), sub-1 (NCU01154), and siderophore regulation (sre,
182
NCU07728) (CHEN and LOROS 2009; SMITH et al. 2010). Also included in this group of TFs
183
was the fluffy (fl) gene (NCU08726) encoding a major regulator of conidiation in N. crassa
184
(BAILEY and EBBOLE 1998; RERNGSAMRAN et al. 2005). Although fl was not observed in
185
general microarray studies to be light-regulated, its behavior in RNA-seq was similar to that
186
observed in directed studies of fl expression (BELDEN et al. 2007; OLMEDO et al. 2010a). Also
187
included in this cluster were genes involved in metal ion homeostasis (mig-12,NCU09830; sre,
conidial separation-1 (csp-1, NCU02713), conidial separation-2,
10
188
NCU07728; and cax, NCU07075), uncovering a previously not discerned need for the fungus
189
to control metal ion homeostasis during exposure to light.
190
Cluster 3 includes genes that typically peaked in expression between 60 and 120 min in
191
the light, the so-called late light-induced genes. Cluster 3 was visually subdivided into
192
clusters 3a, 3b and 3c based on differences in expression patterns within the tree-structure of
193
this cluster (Figure 3A and Figure S1). Each of the subclusters showed higher levels of RNA
194
at 120 min than at 15 min, as did the main cluster. FunCat analyses showed differences in
195
functional enrichment categories for these subclusters (Table S11). Cluster 3a is highly
196
enriched for genes involved in metabolism and responses to oxidative stress, including the
197
genes for the well-described detoxification enzymes glutathione-S transferase (NCU05706),
198
glutamate decarboxylase (NCU00678), and NADH cytochrome B5 reductase (NCU03112).
199
This cluster also includes a large number of genes encoding hypothetical proteins (75 genes),
200
suggesting that at least some of these genes function in metabolism or cellular stress
201
responses. Cluster 3b is enriched for genes involved in sugar metabolism. This cluster also
202
included catalase-1 (cat-1, NCU08791), which is important in hydrogen peroxide
203
detoxification following light-triggered production of reactive oxygen species (WANG et al.
204
2007a; WANG et al. 2007b). Interestingly, cluster 3b includes clock-controlled gene-1
205
(ccg-1/grg-1, NCU03753), a gene of unknown function that is regulated by the circadian
206
clock as well as by light, oxidative stress and glucose starvation (LOROS et al. 1989;
11
207
MCNALLY and FREE 1988). Both cat-1 and ccg-1 were previously shown to be regulated by
208
the TF ATF-1 (also called ASL-1; NCU01346) which functions downstream of the
209
osmosensing MAPK pathway in N. crassa (LAMB et al. 2012; YAMASHITA et al. 2008). The
210
atf-1/asl-1 gene displayed a >2-fold light induction, peaking at 15 min (Table S6); however, it
211
did not make our stringent cutoff of q≤0.2. Cluster 3c is enriched for genes primarily involved
212
in responses to environmental stress, including heat shock and cell wall integrity stress
213
response pathways. These data are consistent with previous studies demonstrating regulation
214
of these pathways by the WCC complex and the clock (BENNETT et al. 2013; SMITH et al.
215
2010).
216
Cluster 4 genes were rapidly and highly induced by light, and generally stayed induced
217
over the course of light-treatment; this pattern of induction resembles that of Cluster 1. This
218
cluster includes the core circadian oscillator gene frequency (frq, NCU02265), previously
219
shown to be insulated from photoadaptation (CROSTHWAITE et al. 1995). Also included in this
220
cluster are several oxidoreductases (mig-3, NCU04452; NCU01861; and NCU08291)
221
important in redox reactions.
222
Genes in Cluster 5 are repressed by light, with repression being the strongest 60-120 min
223
after light treatment. Although some light-repressed genes were noted in earlier work (DONG
224
et al. 2008) a large cluster of such genes has not been previously described in detail. Because
225
of the novelty of this observation we confirmed light-repression on a subset of transcripts by
12
226
RT-qPCR (Figure 4). The repression is observed when mRNA levels are normalized either to
227
25S rRNA levels or to levels of cox-5, a transcript whose levels did not respond to light.
228
Genes implicated in ribosome biogenesis were highly enriched in this cluster, suggesting that
229
light triggers a temporary reduction in the production of new ribosomes, which in turn would
230
likely limit protein synthesis. As light is a stress to the organism (reflected here by the
231
induction of numerous stress response genes in response to light), these data are consistent
232
with previous studies demonstrating global protein synthesis repression following
233
environmental stress (HOLCIK and SONENBERG 2005; LINDQUIST 1981; SHALGI et al. 2013;
234
SPRIGGS et al. 2010).
235
Taken together, functional analyses of the clusters revealed that light generally increases
236
cellular metabolism (Clusters 3a and 3b), and at the same time causes significant oxidative
237
stress to the organism. To deal with this stress, protective photopigments are made (Cluster 1),
238
antioxidants are produced (Clusters 2, 3a, 3b, 3c, and 4), genes involved in ribosome
239
biogenesis are transiently repressed (Cluster 5), and the overarching regulatory pattern driven
240
by the circadian system is reset to subjective morning (Cluster 4) in anticipation of a long
241
period of continued light.
242
243
244
Global regulation by light
Nearly 25% of the genome showed a >2-fold change in gene expression in response to
light under our growth conditions. As previous studies have implicated a hierarchical network
13
245
of TFs controlling light induction (CHEN et al. 2009; SMITH et al. 2010), it was not surprising
246
to find that TFs are overrepresented in several of the light-induced clusters. Overall, 58 of 252
247
identified TFs are regulated by light (Figure 5). Among these, 12 TFs were significantly
248
regulated at a q-value ≤ 0.2 (indicated by asterisks in Figure 5) and are represented in clusters
249
2, 3a, and 5. Furthermore, of the 27 TFs identified as direct targets of the WCC (SMITH et al.
250
2010), 14 showed a >2-fold change in response to light for at least one time point, and 7 with
251
a q-value ≤ 0.2 (Table S12). Of these 14 genes, 3 TF genes, adv-1, NCU07846, and
252
NCU05994, showed decreased levels for at least one time point. Together, these data
253
demonstrate that, with the growth conditions used here, not all steady state mRNAs from
254
genes that are direct targets of the WCC show significant light responses, and that some direct
255
targets of the WCC are repressed by light.
256
A relatively large number of transcripts showed sizeable increases in expression upon
257
light exposure; 27 mRNAs had 16-fold or greater increases at one or more time points (Table
258
1). FunCat analysis indicated enrichment for functions similar to those identified for Cluster 1
259
genes (compare Table S13). Plots of the numbers of genes showing increased or decreased
260
responses to light at different q-value thresholds are shown in Figure 6A. In general,
261
reductions in response to light were smaller than induction in response to light, with no
262
reduction more than 8-fold. The greatest reductions were seen 60-120 min after lights on, in
263
contrast to induction, which peaked 15-60 min after lights on. Global analyses of the
14
264
distribution of light-regulated transcripts across N. crassa chromosomes did not reveal
265
obvious regions where expression patterns of genes clustered (Figure 6B and Figure S2).
266
We examined the phenotypes of a subset of genes whose transcripts were altered 2-fold
267
or more in response to light with a q≤0.2 with both known and unknown functions. The
268
phenotypes of knockouts of these selected genes are shown in Figure 7. Many of these genes
269
showed obvious phenotypes affecting vegetative growth or sexual development. Interestingly,
270
the frq deletion strain, in an otherwise WT background, showed slower linear growth in race
271
tubes, and a phenotype on plates that differed from the wild type. This result was surprising
272
given growth differences between frq-null mutations in the ras-1bd background (commonly
273
used for clock studies) and control ras-1bd strains, have not been observed or reported
274
(ARONSON et al. 1994; LOROS and FELDMAN 1986). We confirmed that an independent
275
disruption of frq with the Barr marker in the wild-type background also showed slower linear
276
growth at 25C, but in the (already slower-growing) ras-1bd strain, disruption of frq with the
277
Barr marker did not further reduce the linear growth rate (data not shown). The fluffy deletion
278
strain showed a morphological phenotype when yeast extract was included in the growth
279
medium. While the functions of many of these gene products are hypothetical, the results of
280
phenotyping illustrate that light affects the expression of many genes whose functions are
281
important for the growth of the organism. Additional phenotypic analyses of strains
282
containing deletions of these light-regulated genes should provide clues to the functions of the
15
283
hypothetical genes and reveal broader connections among the functions of genes with similar
284
expression profiles.
285
Discussion
286
The goal of this work was to achieve a comprehensive understanding of how gene
287
expression in N. crassa changes in response to light through the use of RNA-seq. We
288
therefore purified capped and polyadenylated mRNA from vegetatively growing N. crassa
289
mycelium grown in the dark or grown in the dark and exposed to light for 15, 60, 120 or 240
290
minutes. We sequenced cDNA obtained from this mRNA by using Illumina short-read
291
methodology, and analyzed gene expression by measuring the relative abundance of mRNA
292
for known or predicted N. crassa protein coding genes (based on assembly Nc10 and
293
annotation 10.6). The abundance of transcripts for approximately 25% of all predicted N.
294
crassa genes changed 2-fold or more based on these data. Transcript abundance levels for 532
295
genes (5% of all predicted genes) were light-regulated using a false discovery rate cutoff of
296
q0.2 for the data from two independent experiments. The increased power of the RNA-seq
297
approach compared to previous microarray-based approaches enabled the identification of
298
genes which were not highly expressed, but which were regulated in response to light. For
299
example, we obtained evidence for a major class of genes predicted to have roles in rRNA
300
processing that were down-regulated in response to light.
301
Estimates of the fraction of N. crassa genes induced by light have ranged from 3-14 %
16
302
of the predicted protein-coding genes in the genome (CHEN et al. 2009; DONG et al. 2008;
303
LEWIS et al. 2002). A conservative estimate based on the data obtained here (using a cutoff of
304
q≤0.2) is 5% of the genome, while a more liberal estimate is 25% since this is the fraction of
305
genes whose expression changed 2-fold in response to light. A major category of genes whose
306
predicted functions are significantly enriched in response to light in the larger group of genes
307
(2-fold regulated) are those with uncategorized or unknown functions. Among these are genes
308
that are fungal-specific. For example, within this category of genes for which there is strong
309
statistical support for light induction is NCU07923 (4-fold induction with q<0.02, Table S9), a
310
hypothetical protein that appears strongly conserved within the ascomycetes but not outside
311
of them: deletion of this gene has an obvious vegetative growth phenotype (Figure 7).
312
While a substantial fraction of predicted N. crassa protein-coding genes are regulated at
313
the transcript level in response to light, there were no obvious large chromosomal clusters of
314
genes that showed common regulation. This indicates that the action of light to increase or
315
decrease transcript levels is not generally operating on clustered genes, and further that these
316
mechanisms are not affecting large contiguous domains of chromatin.
317
The functions of genes that respond early to light appear different than those that
318
respond later. Light induces the expression of many genes associated with stress responses
319
60-120 min after exposure, and this can be rationalized because light can generate reactive
320
oxygen species (WANG et al. 2007b). Consistent with the damaging effects of light, direct
17
321
targets of the WCC are enriched for DNA repair enzymes (SMITH et al. 2010). Thus, it is not
322
surprising that we found genes involved in DNA repair mechanisms, and encoding light
323
absorbing photopigments, are rapidly light-induced. The kinetics of the responses of
324
stress-response genes are similar to those of a subset of genes with roles in C-compound and
325
carbohydrate metabolism whose expression is also induced by light (Cluster 3, Figure 3C and
326
Table S11). FunCat functional enrichment for this category of genes among late light response
327
genes has been observed previously in microarray studies using the same growth medium
328
(CHEN et al. 2009). The expression of a large set of genes is also reduced 60-120 min after
329
light exposure. While the mRNAs for the protein components of the ribosome are not reduced
330
by light exposure, many of the mRNAs specifying factors involved in rRNA processing and
331
ribosome assembly are reduced. Thus, it may be more efficient for cells to control ribosome
332
assembly, as opposed to adjusting the levels of abundantly expressed mRNAs encoding
333
ribosome proteins, in response to environmental signals.
334
Among the early light-induced genes that are associated with DNA repair are
335
NCU08850 (mus-18) and NCU08626 (phr). Mutations in mus-18 were originally identified
336
because they were UV-sensitive (ISHII et al. 1991), and mutant strains are deficient in
337
excision-repair. This light response is deeply conserved because UVE1, the homolog of this
338
gene in the basidiomycete Cryptococcus neoformans, is also strongly light induced through
339
the WCC (VERMA and IDNURM 2013). UV-irradiation can result in the formation of
18
340
cyclobutane pyrimidine dimers, and N. crassa phr specifies a cyclobutane pyrimidine dimer
341
photolyase that reduces this DNA damage through light-dependent photoreactivation
342
(SHIMURA et al. 1999).
343
The value of RNA-seq in discovery for a better understanding of the behavior of
344
relatively well-characterized genes is illustrated by the results obtained here with nop-1 (new
345
eukaryotic opsin 1). nop-1 (NCU10055) encodes a retinal binding protein that affects the
346
expression of genes that are themselves light-regulated, and thus would be anticipated to have
347
light-specific functions (BIESZKE et al. 1999a; BIESZKE et al. 2007). In previous studies, the
348
nop-1 mRNA level was not observed to increase in response to light (BIESZKE et al. 2007;
349
CHEN et al. 2009). However, in each of our two independent experiments, and in analyses of
350
the pooled experimental data, nop-1 mRNA increased at 60 min and 120 min (and came down
351
at 240 in one while remaining up at 240 in the other). This increase in nop-1 was significant at
352
a q-value <0.2 in each case. The RNA-seq data thus demonstrate that the expression of nop-1
353
is light-regulated, and provides the basis for further experiments to identify how its increased
354
expression relatively late in the light-response impacts the biology of the organism.
355
The transcripts for con-6 (NCU08769) and con-10 (NCU07325) are strongly induced in
356
response to light as shown here and elsewhere (CHEN et al. 2009; CORROCHANO et al. 1995;
357
LAUTER and RUSSO 1991; LAUTER and YANOFSKY 1993; OLMEDO et al. 2010b). The role of
358
these genes in N. crassa has remained elusive since single mutants do not display significant
19
359
phenotypes. However, a phenotype for the equivalent double mutant of the A. nidulans
360
homologs conF and conJ has been described (SUZUKI et al. 2013). The double knockout
361
strain resulted in significant increases in the amount of cellular glycerol and erythritol, which
362
delayed conidial germination and provided an increase in resistance of the cells to desiccation.
363
As is the case for N. crassa, both conF and conJ are rapidly light-induced, and the single
364
knockouts displayed no obvious phenotypes. These data suggest the likelihood that con-6 and
365
con-10 have redundant functions in spore germination in response to light.
366
Light plays a key role in synchronizing the N. crassa circadian clock to local time, and
367
therefore, it is not surprising to find that light affects the levels and activities of core clock
368
components. We found that wc-1 (NCU02356) is transiently light induced, consistent with
369
previous work (BALLARIO et al. 1996; LINDEN and MACINO 1997). However, while wc-2
370
(NCU00902) is reported to be weakly light induced (BALLARIO et al. 1996; LINDEN and
371
MACINO 1997), no increase in wc-2 transcripts was observed following light treatment in our
372
experiments. In agreement with these data, light induces a transient increase in WC-1 protein
373
levels, but little or no change in the WC-2 (SCHWERDTFEGER and LINDEN 2000; TALORA et
374
al. 1999), whose levels, unlike WC-1, are not limiting in cells (CHENG et al. 2001; DENAULT
375
et al. 2001). Light-activated WCC binds to light-responsive elements (LRE’s) in the frq
376
promoter, leading to subsequent activation of frq transcription (FROEHLICH et al. 2002; HE
377
and LIU 2005). This change in frq mRNA and protein levels is responsible for resetting the
20
378
phase of the clock to the appropriate time of the day (CROSTHWAITE et al. 1995). Interestingly,
379
none of the other clock components and modifiers of the components, including FRH
380
(FRQ-Interacting RNA Helicase), a binding partner of FRQ necessary for negative feedback
381
(GUO et al. 2010), and several kinases (CK1, CK2, PKA, and CAMK-1) and phosphatases
382
(PP1, PP2A, and PP4) that modify the activities of the clock components, met our stringent
383
criteria for light-regulation. Three genes, camk-1 (NCU09123), ppp-1 (NCU00043 encoding
384
the catalytic subunit of protein phosphatase 1),and rgb-1 (NCU09377 encoding the regulatory
385
subunit of protein phosphatase 2A) had a greater than 2X change in expression following
386
light treatment, but the q value was >0.2. These data suggest that circadian light responses are
387
mediated by the absolute changes in frq mRNA levels through the activity of the WCC.
388
RNA expression analyses of 27 TF genes shown to be direct targets of the WCC has
389
been accomplished using RT-qPCR to compare RNA levels in dark-grown cells and cells
390
given a 15-min light pulse (SMITH et al. 2010). These data are similar to the RNA-seq data we
391
obtained (Table S12) with the exception of adv-1 discussed below. First, in both studies, not
392
all of the genes that are direct targets of the WCC were light-regulated. Second, while not
393
noted before (SMITH et al. 2010), the steady-state mRNA levels of some of the TF genes are
394
reduced in response to light (e.g. NCU05994). These data suggest that the WCC has
395
repressive, as well as activating functions for specific targets, or that other TFs participate in
396
the regulation of the light-repressed genes. Identification of the direct targets of the TFs will
21
397
help to resolve this question. The gene encoding the ADV-1 TF was the only case where
398
differences were observed between the two data sets. In our experiments, the levels of adv-1
399
mRNA stayed fairly constant in DD and L15, but then decreased more than 2-fold at L60 and
400
L120. In contrast, in previous RT-PCR assays, adv-1 mRNA levels were induced more than
401
2-fold following a 15 min light treatment (SMITH et al. 2010). The basis for this difference is
402
not understood. It may reflect the use of different media in the two studies, or differences in
403
the culture conditions. Specifically, the amount of time the cultures were in the dark before
404
the light treatment varied in the two data sets, 12 h (SMITH et al. 2010) versus 24 h in our
405
experiments, which for a rhythmic gene, such as adv-1, would result in time-of-day
406
differences in the dark mRNA levels.
407
Together, the identification of light-responsive genes will provide the foundation for our
408
ongoing efforts to decipher the specific roles of TFs that respond to light and the clock in the
409
regulation of the global photo-responses and circadian rhythmicity. These studies include
410
determining the direct and indirect targets of the light-controlled TFs, and the interplay of TFs
411
in orchestrating the light and circadian response. With a substantial fraction of the genome
412
showing altered gene expression in response to light, and with different patterns of expression,
413
we anticipate a complex light-controlled and circadian-regulated TF network.
22
414
MATERIALS AND METHODS
415
Strains
416
Wild-type strains 74-OR23-IVA (FGSC 2489; mat A) and ORS-SL6a (FGSC 4200; mat
417
a), and single gene deletion strains (COLOT et al. 2006) NCU00250 (FGSC12215; mat a),
418
NCU01862 (FGSC19012; mat a), NCU01870 (FGSC13270; mat a), NCU02209
419
(FGSC16054; mat a), NCU02265 (FGSC11554; mat a), NCU05770 (FGSC11532; mat A),
420
NCU07923 (FGSC19046; mat A), NCU08726 (FGSC11044; mat a) were obtained from
421
the Fungal Genetics Stock Center (Kansas City, MO).
422
Light Treatment
423
Macroconidia were obtained from flask cultures containing 1X Vogel’s medium with 2%
424
sucrose and 2% agar (SACHS and YANOFSKY 1991). Conidia were harvested with water,
425
filtered through cheesecloth, and counted with a hemacytometer. For each time-point, 200-ml
426
of Bird’s Medium (METZENBERG 2004) was inoculated to a final concentration of 107
427
conidia/ml, and grown in the dark for 24 h at 25oC with orbital shaking (150 rpm). Some of
428
the cultures were exposed to white-light using cool white fluorescent bulbs (1200 lux), and
429
cells were harvested in a darkroom at time 0 (dark), 15, 60, 120 and 240 min after light
430
exposure. The cells were harvested by centrifugation (1000 xg for 1 min) using an IEC
431
clinical centrifuge and washed once with ice-cold sterile water (50 ml). The mycelia pad was
432
cut into small pieces (approximately 100 mg/piece) with a razor. Individual pieces were
23
433
placed into 15ml screw-cap tubes and snap-frozen in liquid nitrogen. Mycelia were stored
434
frozen at –80°C.
435
436
Total RNA and poly(A) RNA Isolation
Total RNA was isolated from frozen mycelia (approximately 100 mg) using 1 g of
437
autoclaved Zirconia/Silica Beads (Biospec Products, Inc, Bartlesville OK, product number
438
11079105Z) and a Mini-BeadBeater-8 (Biospec Products, Inc, Bartlesville OK) with ice-cold
439
580 µl extraction buffer (100 mM Tris-HCl, pH 7.5; 100 mM LiCl; 20 mM DTT), 420 µL
440
phenol, 420 µL chloroform, and 84 µL 10% SDS (SACHS and YANOFSKY 1991). Immediately
441
after removal from -80 °C storage, mycelia were homogenized in the bead beater for 1 min.
442
After a 4 min end-over-end rotation, the homogenate was centrifuged at 12000 xg at 4 °C for
443
1 min to separate phases. The aqueous phase was extracted with phenol/chloroform and
444
chloroform, and precipitated in 0.3 M sodium acetate and ethanol. The pellet was washed
445
twice with 70% ethanol that was prepared with diethylpyrocarbonate (DEPC)-treated water,
446
briefly air-dried, and then dissolved in 100 l filter-sterilized DEPC-treated water. RNA
447
concentration was determined using a Nanodrop spectrophotometer, and quality was assessed
448
by denaturing gel electrophoresis in formaldehyde gels and northern analyses. Poly(A)
449
mRNA was purified from total RNA using oligo-dT cellulose (SACHS and YANOFSKY 1991)
450
for replicate 1, or using the Poly(A)Purist MAG kit (replicate 2) (Ambion, Grand Island, NY).
451
Residual DNA was removed from poly(A) mRNA using Ambion Turbo DNase and intact
24
452
mRNA was selectively enriched using Epicentre mRNA-Only. (Illumina, San Diego, CA) to
453
degrade mRNA species lacking a cap. Poly(A) mRNA concentration was determined by
454
RiboGreen fluorometric assay (Life Technologies, Grand Island, NY).
455
cDNA Preparation
456
The procedure for preparing cDNA was modified from a previously described procedure
457
(CARNINCI et al. 2002) as follows. To synthesize the first-strand cDNA, 1 µg poly(A) mRNA
458
was mixed with 1.2 µl of 10 mM dNTPs, 1 µg of random hexamer, heated at 65 °C for 5 min,
459
and then placed on ice for 3 min to remove any secondary structure. 10 µl of 5X first strand
460
buffer (250 mM Tris-HCl, pH 8.3; 375 mM KCl; 15 mM MgCl2), 4.55 µl of 0.1 M DTT, 5.6
461
µl of 80% glycerol, 2.88 µl of 1 µg/µl BSA, 20 units RNasin (Promega, Madison WI), and
462
300 units SuperScript III reverse transcriptase (Life Technologies, Grand Island, NY) were
463
then added to the reaction tube and the reaction was incubated at 25 °C for 5 min, 50 °C for
464
50 min, and 70 °C for 15 min in a thermocycler. The reaction mix was precipitated with 0.3 M
465
sodium acetate and ethanol, and the pellet was washed twice with 70% ethanol, briefly
466
air-dried, and dissolved in 22 µl of DEPC-treated water. The RNA-DNA hybrid was treated
467
with 2.5 units of E. coli RNaseH (New England Biolabs, Ipswich, MA) at 37 °C for 20 min.
468
Then 10 µl of 10X second strand buffer (200 mM Tris-HCl, pH 8.93; 350 mM KCl; 50 mM
469
(NH4)2SO4; 10 mM MgSO4; 10 mM MgCl2; 0.5% Triton X-100), 3 µl of 10 mM dNTPs, 6
470
units RNaseH, and 50 units E. coli DNA polymerase I (New England Biolabs, Ipswich, MA)
25
471
were added to the reaction tube. The reaction was incubated at 16 °C for 2.5 h and then
472
stopped by freezing.
473
Sequencing Library Preparation
474
cDNA was resuspended in 300 µl TE in a 1.5 ml TPX micro tube (Diagenode, Denville,
475
NJ) and sheared using the low energy cycle for 15 min (15 sec on/15 sec off) in a Diagenode
476
Bioruptor, whose water bath was maintained at 4C with a recirculating chiller. Sheared
477
cDNA was transferred to a 1.7 ml polypropylene microcentrifuge tube and precipitated with
478
0.3 M sodium acetate and ethanol. The pellet was washed once with 70% ethanol, air-dried,
479
and dissolved in 15 µl sterile water and stored at -20C. The yield of recovered DNA was
480
determined by PicoGreen fluorimetric assay with  DNA (New England Biolabs, Ipswich,
481
MA) as the standard using a Victor3V 1420 multilabel counter (Perkin Elmer, Waltham, MA).
482
An aliquot of sheared DNA (1.5 µl) was examined on a 1% TAE agarose gel to verify sizes
483
ranging between 100-800-bp.
484
RNA-seq libraries were prepared from 1 µg of sheared DNA using an Illumina (San
485
Diego, CA) TruSeq Sample Prep kit according to the manufacturer’s instructions. Each
486
sample was ligated to an indexing adapter and selectively enriched through a 10-cycle
487
amplification. The library was then separated on a 1% TAE agarose gel, and DNA ranging
488
between 200-500 bp was excised and purified using QIAEX II gel purification kit (Qiagen,
489
Germantown, MD). The yield of amplified DNA was determined using the PicoGreen assay.
26
490
An aliquot (3 µl) was examined on a 1% TAE agarose gel to monitor amplification. The DNA
491
was diluted in water to a final concentration of (10 nM in 30 µl) for Illumina sequencing.
492
High throughput sequencing
493
cDNA libraries were sequenced on an Illumina HiSeq 2000 for 57 cycles, and processed
494
with Illumina pipeline RTA 1.13.48 and CASAVA v1.8.2. Trimming the 6-mer adapter
495
generated 51-mer reads. The yield for each sample is shown in Table S14. Raw and processed
496
data were submitted to the NCBI GEO database with accession number GSE53534.
497
Data Analysis
498
Illumina reads were mapped to N. crassa assembly 10 with TopHat v2.0.5 (options -i 30
499
-I 2000). FPKM and fold-changes were calculated using the cuffdiff command from version 2
500
of the Cufflinks suite. Version 10.6 of the N. crassa annotation was used, and fragment bias
501
(the "-b" option) and multiple-read correction (the "-u" option) options were enabled.
502
Quantitation and statistical tests were performed both separately for each time course, as
503
well as for the combined set of replicates. FPKM values across the light time course were
504
hierarchically clustered and visualized as heat maps with Cytoscape 2.8.3 and the
505
clusterMaker plugin (MORRIS et al. 2011). Functional enrichments for each cluster were
506
calculated using the FunCat database (FunCatDb) (RUEPP et al. 2004). Gene identifiers in
507
FunCatDb were mapped to the identifiers in the current annotation using the mapping
508
information available at the Broad Institute Neurospora Database
27
509
(http://www.broadinstitute.org/annotation/genome/neurospora/MultiDownloads.html). Gene
510
identifiers in the Gene Ontology were mapped using the GO Term Finder tool
511
(http://go.princeton.edu/cgi-bin/GOTermFinder) with a Neurospora GO gene association file
512
(go_for_nc12.tsv downloaded from
513
http://www.broadinstitute.org/annotation/genome/neurospora/Downloads.html.
514
Quantitative RT-PCR
515
Eight ng of cDNA (0.125 ng for quantification of 25S cDNA) was used as qPCR
516
template in a reaction containing: 1X Platinum® Taq PCR Buffer (200 mM Tris-HCl pH 8.4,
517
500mM KCl) (Life Technologies, Grand Island, NY), 2.5 mM MgCl2, 0.2 mM dNTPs, 1X
518
ROX Reference Dye (Life Technologies, Grand Island, NY) 1X SYBR® Green I (Life
519
Technologies, Grand Island, NY), 500 nM each primer and 5 U/µl Platinum® Taq DNA
520
Polymerase (Life Technologies, Grand Island, NY) or 5 U/µl TaKaRaTaq™ DNA Polymerase
521
(Clontech, Mountain View, CA) in a 20μl reaction with filtered sterile DEPC-treated water.
522
Amplification was as follows: 50 °C for 2 min, 95 °C for 10 min followed by 40 cycles at 95
523
°C for 15s, and 60 °C 1 min. 25S rRNA was used as an internal control for normalization.
524
Phenotype analyses
525
Phenotyping of N. crassa single gene deletion strains, including strains containing
526
deletions of genes whose expression was affected by light, was accomplished in an
527
undergraduate research course at Texas A&M University (BIOL452, Fungal Functional
28
528
Genomics) taught by MSS, DBP, YZ and RD. Phenotyping was performed as described
529
(COLOT et al. 2006) with minor modifications. Vogel's minimal medium (VM)/1.5%
530
sucrose/2% agar was used for vegetative growth and synthetic crossing medium (SCM)/1%
531
sucrose/2% agar for development of female sexual structures (Davis, R. H., & de Serres, F. J.
532
(1970). VM was supplemented with 2% yeast extract (YE) where indicated. All strains were
533
analyzed in at least triplicate for each phenotype. All strains were incubated at either 25C or
534
37C in Percival chambers with a 12-hr light/12-hr dark cycle. Images of hyphae were
535
obtained using Olympus SZX16 microscopes with IDEA 5 cameras and IDEA SPOT software.
536
Plate photos were obtained using Canon APS-C sensor cameras. Tests for female fertility
537
were accomplished using 3 ml SCM in Falcon T12.5 Tissue Flask (353108) with the arrow on
538
the flask’s cap pointed to the top of the flask to ensure sufficient airflow.
539
29
540
541
ACKNOWLEDGMENTS
542
This work was supported by P01 GM068087 “Functional Analysis of a Model
543
Filamentous Fungus” and the Texas Institute for Advanced Study at Texas A&M University.
544
Strains were obtained from the Fungal Genetics Stock Center (Kansas City, MO). We thank
545
Katherine Borkovich and Luis Larrondo for advice identifying N. crassa transcription factors
546
and Ulrich Gueldener and Jason Stajich for advice on FunCat and GO analyses, respectively.
547
30
548
REFERENCES
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
ARONSON, B. D., K. A. JOHNSON, J. J. LOROS and J. C. DUNLAP, 1994 Negative feedback
defining a circadian clock: autoregulation of the clock gene frequency. Science 263:
1578-1584.
BAHN, Y. S., C. XUE, A. IDNURM, J. C. RUTHERFORD, J. HEITMAN et al., 2007 Sensing the
environment: lessons from fungi. Nat Rev Microbiol 5: 57-69.
BAILEY, L. A., and D. J. EBBOLE, 1998 The fluffy gene of Neurospora crassa encodes a
Gal4p-type C6 zinc cluster protein required for conidial development. Genetics 148:
1813-1820.
BALLARIO, P., and G. MACINO, 1997 White collar proteins: PASsing the light signal in
Neurospora crassa. Trends Microbiol. 5: 458-462.
BALLARIO, P., P. VITTORIOSO, A. MAGRELLI, C. TALORA, A. CABIBBO et al., 1996 White
collar-1, a central regulator of blue light responses in Neurospora, is a zinc finger
protein. EMBO J. 15: 1650-1657.
BELDEN, W. J., L. F. LARRONDO, A. C. FROEHLICH, M. SHI, C. H. CHEN et al., 2007 The
564
band mutation in Neurospora crassa is a dominant allele of ras-1 implicating RAS
565
566
567
signaling in circadian output. Genes Dev. 21: 1494-1505.
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
BENNETT, L. D., P. BEREMAND, T. L. THOMAS and D. BELL-PEDERSEN, 2013 Circadian
activation of the mitogen-activated protein kinase MAK-1 facilitates rhythms in
clock-controlled genes in Neurospora crassa. Eukaryot Cell 12: 59-69.
BERLIN, V., and C. YANOFSKY, 1985 Isolation and characterization of genes differentially
expressed during conidiation of Neurospora crassa. Mol. Cell. Biol. 5: 849-855.
BIESZKE, J. A., E. L. BRAUN, L. E. BEAN, S. KANG, D. O. NATVIG et al., 1999a The nop-1
gene of Neurospora crassa encodes a seven transmembrane helix retinal-binding
protein homologous to archaeal rhodopsins. Proc. Natl. Acad. Sci. USA 96:
8034-8039.
BIESZKE, J. A., L. LI and K. A. BORKOVICH, 2007 The fungal opsin gene nop-1 is
negatively-regulated by a component of the blue light sensing pathway and influences
conidiation-specific gene expression in Neurospora crassa. Curr Genet 52: 149-157.
BIESZKE, J. A., E. N. SPUDICH, K. L. SCOTT, K. A. BORKOVICH and J. L. SPUDICH, 1999b A
eukaryotic protein, NOP-1, binds retinal to form an archaeal rhodopsin-like
photochemically reactive pigment. Biochemistry 38: 14138-14145.
CARNINCI, P., T. SHIRAKI, Y. MIZUNO, M. MURAMATSU and Y. HAYASHIZAKI, 2002
Extra-long first-strand cDNA synthesis. Biotechniques 32: 984-985.
CHEAH, M. T., A. WACHTER, N. SUDARSAN and R. R. BREAKER, 2007 Control of alternative
31
584
585
586
587
588
589
590
591
592
RNA splicing and gene expression by eukaryotic riboswitches. Nature 447: 497-500.
CHEN, C. H., J. C. DUNLAP and J. J. LOROS, 2010 Neurospora illuminates fungal
photoreception. Fungal Genet Biol 47: 922-929.
CHEN, C. H., and J. J. LOROS, 2009 Neurospora sees the light: light signaling components in a
model system. Commun Integr Biol 2: 448-451.
CHEN, C. H., C. S. RINGELBERG, R. H. GROSS, J. C. DUNLAP and J. J. LOROS, 2009
Genome-wide analysis of light-inducible responses reveals hierarchical light
signalling in Neurospora. EMBO J. 28: 1029-1042.
CHENG, P., Y. YANG, K. H. GARDNER and Y. LIU, 2002 PAS domain-mediated WC-1/WC-2
593
594
interaction is essential for maintaining the steady-state level of WC-1 and the function
595
596
22: 517-524.
597
598
599
600
601
of both proteins in circadian clock and light responses of Neurospora. Mol Cell Biol
CHENG, P., Y. YANG and Y. LIU, 2001 Interlocked feedback loops contribute to the robustness
of the Neurospora circadian clock. Proc Natl Acad Sci U S A 98: 7408-7413.
CHENG, P., Y. YANG, L. WANG, Q. HE and Y. LIU, 2003 WHITE COLLAR-1, a
multifunctional neurospora protein involved in the circadian feedback loops, light
sensing, and transcription repression of wc-2. J Biol Chem 278: 3801-3808.
COLOT, H. V., G. PARK, G. E. TURNER, C. RINGELBERG, C. M. CREW et al., 2006 A
602
high-throughput gene knockout procedure for Neurospora reveals functions for
603
604
multiple transcription factors. Proc. Natl. Acad. Sci. USA 103: 10352-10357.
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
CORROCHANO, L. M., 2007 Fungal photoreceptors: sensory molecules for fungal
development and behaviour. Photochem Photobiol Sci 6: 725-736.
CORROCHANO, L. M., 2011 Fungal photobiology: a synopsis. IMA Fungus 2: 25-28.
CORROCHANO, L. M., F. R. LAUTER, D. J. EBBOLE and C. YANOFSKY, 1995 Light and
developmental regulation of the gene con-10 of Neurospora crassa. Dev Biol 167:
190-200.
CROSTHWAITE, S. K., J. C. DUNLAP and J. J. LOROS, 1997 Neurospora wc-1 and wc-2:
transcription, photoresponses, and the origins of circadian rhythmicity. Science 276:
763-769.
CROSTHWAITE, S. K., J. J. LOROS and J. C. DUNLAP, 1995 Light-induced resetting of a
circadian clock is mediated by a rapid increase in frequency transcript. Cell 81:
1003-1012.
DENAULT, D. L., J. J. LOROS and J. C. DUNLAP, 2001 WC-2 mediates WC-1-FRQ interaction
within the PAS protein-linked circadian feedback loop of Neurospora. EMBO J. 20:
109-117.
DONG, W., X. TANG, Y. YU, R. NILSEN, R. KIM et al., 2008 Systems biology of the clock in
Neurospora crassa. PLoS One 3: e3105.
FAOU, P., and M. TROPSCHUG, 2003 A novel binding protein for a member of CyP40-type
32
622
Cyclophilins: N.crassa CyPBP37, a growth and thiamine regulated protein homolog
623
624
625
to yeast Thi4p. J Mol Biol 333: 831-844.
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
FAOU, P., and M. TROPSCHUG, 2004 Neurospora crassa CyPBP37: a cytosolic stress protein
that is able to replace yeast Thi4p function in the synthesis of vitamin B1. J Mol Biol
344: 1147-1157.
FROEHLICH, A. C., C. H. CHEN, W. J. BELDEN, C. MADETI, T. ROENNEBERG et al., 2010
Genetic and molecular characterization of a cryptochrome from the filamentous
fungus Neurospora crassa. Eukaryot Cell 9: 738-750.
FROEHLICH, A. C., Y. LIU, J. J. LOROS and J. C. DUNLAP, 2002 White Collar-1, a circadian
blue light photoreceptor, binding to the frequency promoter. Science 297: 815-819.
FROEHLICH, A. C., B. NOH, R. D. VIERSTRA, J. LOROS and J. C. DUNLAP, 2005 Genetic and
molecular analysis of phytochromes from the filamentous fungus Neurospora crassa.
Eukaryot Cell 4: 2140-2152.
GALAGAN, J. E., S. E. CALVO, K. A. BORKOVICH, E. U. SELKER, N. D. READ et al., 2003 The
genome sequence of the filamentous fungus Neurospora crassa. Nature 422:
859-868.
GIN, E., A. C. DIERNFELLNER, M. BRUNNER and T. HOFER, 2013 The Neurospora
photoreceptor VIVID exerts negative and positive control on light sensing to achieve
adaptation. Mol Syst Biol 9: 667.
GUO, J., P. CHENG and Y. LIU, 2010 Functional significance of FRH in regulating the
phosphorylation and stability of Neurospora circadian clock protein FRQ. J Biol
Chem 285: 11508-11515.
HE, Q., P. CHENG, Y. YANG, L. WANG, K. H. GARDNER et al., 2002 White collar-1, a DNA
binding transcription factor and a light sensor. Science 297: 840-843.
HE, Q., and Y. LIU, 2005 Molecular mechanism of light responses in Neurospora: from
light-induced transcription to photoadaptation. Genes Dev 19: 2888-2899.
HEINTZEN, C., J. J. LOROS and J. C. DUNLAP, 2001 The PAS protein VIVID defines a
649
clock-associated feedback loop that represses light input, modulates gating, and
650
651
regulates clock resetting. Cell 104: 453-464.
652
653
654
655
656
657
658
659
HERRERA-ESTRELLA, A., and B. A. HORWITZ, 2007 Looking through the eyes of fungi:
molecular genetics of photoreception. Mol Microbiol 64: 5-15.
HOLCIK, M., and N. SONENBERG, 2005 Translational control in stress and apoptosis. Nat Rev
Mol Cell Biol 6: 318-327.
HUNT, S. M., S. THOMPSON, M. ELVIN and C. HEINTZEN, 2010 VIVID interacts with the
WHITE COLLAR complex and FREQUENCY-interacting RNA helicase to alter
light and clock responses in Neurospora. Proc Natl Acad Sci U S A 107:
16709-16714.
ISHII, C., K. NAKAMURA and H. INOUE, 1991 A novel phenotype of an excision-repair mutant
33
660
in Neurospora crassa: mutagen sensitivity of the mus-18 mutant is specific to UV.
661
662
663
664
Mol. Gen. Genet. 228: 33-39.
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
KASUGA, T., J. P. TOWNSEND, C. TIAN, L. B. GILBERT, G. MANNHAUPT et al., 2005
Long-oligomer microarray profiling in Neurospora crassa reveals the transcriptional
program underlying biochemical and physiological events of conidial germination.
Nucleic Acids Res. 33: 6469-6485.
LAMB, T. M., K. E. FINCH and D. BELL-PEDERSEN, 2012 The Neurospora crassa OS MAPK
pathway-activated transcription factor ASL-1 contributes to circadian rhythms in
pathway responsive clock-controlled genes. Fungal Genet Biol 49: 180-188.
LAUTER, F. R., and V. E. RUSSO, 1991 Blue light induction of conidiation-specific genes in
Neurospora crassa. Nucleic Acids Res 19: 6883-6886.
LAUTER, F. R., and C. YANOFSKY, 1993 Day/night and circadian rhythm control of con gene
expression in Neurospora. Proc. Natl. Acad. Sci. USA 90: 8249-8253.
LEE, K., J. C. DUNLAP and J. J. LOROS, 2003 Roles for WHITE COLLAR-1 in circadian and
general photoperception in Neurospora crassa. Genetics 163: 103-114.
LEWIS, Z. A., A. CORREA, C. SCHWERDTFEGER, K. L. LINK, X. XIE et al., 2002
Overexpression of White Collar-1 (WC-1) activates circadian clock-associated genes,
but is not sufficient to induce most light-regulated gene expression in Neurospora
crassa. Mol Microbiol 45: 917-931.
LINDEN, H., P. BALLARIO and G. MACINO, 1997a Blue light regulation in Neurospora crassa.
Fungal Genet. Biol. 22: 141-150.
LINDEN, H., and G. MACINO, 1997 White collar 2, a partner in blue-light signal transduction,
controlling expression of light-regulated genes in Neurospora crassa. EMBO J. 16:
98-109.
LINDEN, H., M. RODRIGUEZ-FRANCO and G. MACINO, 1997b Mutants of Neurospora crassa
defective in regulation of blue light perception. Mol. Gen. Genet. 254: 111-118.
LINDQUIST, S., 1981 Regulation of protein synthesis during heat shock. Nature 293: 311-314.
LOROS, J. J., S. A. DENOME and J. C. DUNLAP, 1989 Molecular cloning of genes under
control of the circadian clock in Neurospora. Science 243: 385-388.
LOROS, J. J., and J. F. FELDMAN, 1986 Loss of temperature compensation of circadian period
length in the frq-9 mutant of Neurospora crassa. J. Biol. Rhythms 1: 187-198.
MALZAHN, E., S. CIPRIANIDIS, K. KALDI, T. SCHAFMEIER and M. BRUNNER, 2010
Photoadaptation in Neurospora by competitive interaction of activating and inhibitory
LOV domains. Cell 142: 762-772.
MCCOLL, D., C. A. VALENCIA and P. J. VIERULA, 2003 Characterization and expression of the
Neurospora crassa nmt-1 gene. Curr. Genet. 44: 216-223.
MCNALLY, M. T., and S. J. FREE, 1988 Isolation and characterization of a Neurospora
glucose-repressible gene. Curr. Genet. 14: 545-551.
34
698
699
700
701
702
703
704
705
706
METZENBERG, R. L., 2004 Bird Medium: an alternative to Vogel Medium. Fungal Genet.
Newsl. 51: 19-20.
MORRIS, J. H., L. APELTSIN, A. M. NEWMAN, J. BAUMBACH, T. WITTKOP et al., 2011
clusterMaker: a multi-algorithm clustering plugin for Cytoscape. BMC
Bioinformatics 12: 436.
OLMEDO, M., C. RUGER-HERREROS and L. M. CORROCHANO, 2010a Regulation by blue light
of the fluffy gene encoding a major regulator of conidiation in Neurospora crassa.
Genetics 184: 651-658.
OLMEDO, M., C. RUGER-HERREROS, E. M. LUQUE and L. M. CORROCHANO, 2010b A
707
complex photoreceptor system mediates the regulation by light of the conidiation
708
709
genes con-10 and con-6 in Neurospora crassa. Fungal Genet Biol 47: 352-363.
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
PURSCHWITZ, J., S. MULLER, C. KASTNER and R. FISCHER, 2006 Seeing the rainbow: light
sensing in fungi. Curr Opin Microbiol 9: 566-571.
RERNGSAMRAN, P., M. B. MURPHY, S. A. DOYLE and D. J. EBBOLE, 2005 Fluffy, the major
regulator of conidiation in Neurospora crassa, directly activates a developmentally
regulated hydrophobin gene. Mol. Microbiol. 56: 282-297.
RUEPP, A., A. ZOLLNER, D. MAIER, K. ALBERMANN, J. HANI et al., 2004 The FunCat, a
functional annotation scheme for systematic classification of proteins from whole
genomes. Nucleic Acids Res 32: 5539-5545.
SACHS, M. S., and C. YANOFSKY, 1991 Developmental expression of genes involved in
conidiation and amino acid biosynthesis in Neurospora crassa. Dev. Biol. 148:
117-128.
SANCAR, G., C. SANCAR, B. BRUGGER, N. HA, T. SACHSENHEIMER et al., 2011 A global
circadian repressor controls antiphasic expression of metabolic genes in Neurospora.
Mol. Cell 44: 687-697.
SARGENT, M. L., and W. R. BRIGGS, 1967 The effects of light on a circadian rhythm of
conidiation in Neurospora. Plant Physiol. 42: 1504-1510.
SCHWERDTFEGER, C., and H. LINDEN, 2000 Localization and light-dependent
phosphorylation of white collar 1 and 2, the two central components of blue light
signaling in Neurospora crassa. Eur. J. Biochem. 267: 414-422.
SCHWERDTFEGER, C., and H. LINDEN, 2001 Blue light adaptation and desensitization of light
signal transduction in Neurospora crassa. Mol. Microbiol. 39: 1080-1087.
SCHWERDTFEGER, C., and H. LINDEN, 2003 VIVID is a flavoprotein and serves as a fungal
blue light photoreceptor for photoadaptation. EMBO J 22: 4846-4855.
SHALGI, R., J. A. HURT, I. KRYKBAEVA, M. TAIPALE, S. LINDQUIST et al., 2013 Widespread
regulation of translation by elongation pausing in heat shock. Mol Cell 49: 439-452.
SHIMURA, M., Y. ITO, C. ISHII, H. YAJIMA, H. LINDEN et al., 1999 Characterization of a
Neurospora crassa photolyase-deficient mutant generated by repeat induced point
35
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
mutation of the phr gene. Fungal Genet Biol 28: 12-20.
SHRODE, L. B., Z. A. LEWIS, L. D. WHITE, D. BELL-PEDERSEN and D. J. EBBOLE, 2001 vvd
is required for light adaptation of conidiation-specific genes of Neurospora crassa, but
not circadian conidiation. Fungal Genet Biol 32: 169-181.
SMITH, K. M., G. SANCAR, R. DEKHANG, C. M. SULLIVAN, S. LI et al., 2010 Transcription
factors in light and circadian clock signaling networks revealed by genomewide
mapping of direct targets for neurospora white collar complex. Eukaryot Cell 9:
1549-1556.
SPRIGGS, K. A., M. BUSHELL and A. E. WILLIS, 2010 Translational regulation of gene
expression during conditions of cell stress. Mol Cell 40: 228-237.
SUZUKI, S., O. SARIKAYA BAYRAM, O. BAYRAM and G. H. BRAUS, 2013 conF and conJ
contribute to conidia germination and stress response in the filamentous fungus
Aspergillus nidulans. Fungal Genet Biol.
TALORA, C., L. FRANCHI, H. LINDEN, P. BALLARIO and G. MACINO, 1999 Role of a white
collar-1-white collar-2 complex in blue-light signal transduction. EMBO J. 18:
4961-4968.
TRAPNELL, C., D. G. HENDRICKSON, M. SAUVAGEAU, L. GOFF, J. L. RINN et al., 2013
Differential analysis of gene regulation at transcript resolution with RNA-seq. Nat
Biotechnol 31: 46-53.
VERMA, S., and A. IDNURM, 2013 The Uve1 endonuclease is regulated by the white collar
complex to protect cryptococcus neoformans from UV damage. PLoS Genet 9:
e1003769.
WANG, N., Y. YOSHIDA and K. HASUNUMA, 2007a Catalase-1 (CAT-1) and nucleoside
diphosphate kinase-1 (NDK-1) play an important role in protecting conidial viability
under light stress in Neurospora crassa. Mol Genet Genomics 278: 235-242.
WANG, N., Y. YOSHIDA and K. HASUNUMA, 2007b Loss of Catalase-1 (Cat-1) results in
decreased conidial viability enhanced by exposure to light in Neurospora crassa. Mol.
Genet. Genomics 277: 13-22.
YAMASHITA, K., A. SHIOZAWA, S. WATANABE, F. FUKUMORI, M. KIMURA et al., 2008 ATF-1
transcription factor regulates the expression of ccg-1 and cat-1 genes in response to
fludioxonil under OS-2 MAP kinase in Neurospora crassa. Fungal Genet Biol 45:
1562-1569.
769
36
770
771
Figure Legends
Figure 1. Comparison of RNA-seq replicate experiments. The FPKM for biological
772
replicate 1 is plotted against biological replicate 2 for each gene, demonstrating strong
773
correlation between replicate experiments at each time point. The correlation coefficient, R, is
774
shown for each time point.
775
776
Figure 2. (A) FunCat Analyses of genes with FPKM>400. The complete analyses are
777
given in Table S5. (B, C) FunCat analysis of the most up-regulated (B) and most
778
down-regulated (C) subsets of the 2353 genes regulated 2-fold or more in response to light.
779
The top 999 genes in each category were analyzed. The complete analyses are given in Table
780
S7 and Table S8. (D) FunCat analyses of the up-regulated genes whose levels changed with a
781
q value of 0.2 or less. The complete analyses are given in Table S9.
782
783
Figure 3. Light responses of selected transcripts. (A) Unsupervised hierarchical
784
clustering of light-inducible responses identifies early and late light-responsive genes for
785
genes whose transcript levels are different with q≤ 0.2 between cells grown in the dark and
786
exposed to light for 15, 60, 120 or 240 min. Yellow: up-regulated; blue: down-regulated. Five
787
major clusters determined by visual analysis of the tree-structure are indicated; cluster 3 was
37
788
further divided into three sub-clusters based on similarities in expression-patterns within this
789
relatively large cluster. (B) Expression-changes for transcripts in each of the five major
790
clusters. Values for each time-point (L15, L60, L120 and L240) are normalized to expression
791
in the dark. The horizontal black bar is the median, the box top and bottom are the 75% and
792
25% quantiles, and the whiskers extend to the maximum and minimum values. (C) FunCat
793
enrichment analyses of genes in the five major clusters shown in panel A. The charts show
794
major enriched classes; the complete data are given in Table S11.
795
796
Figure 4. Validation by RT-qPCR of selected down-regulated transcripts in Cluster 5.
797
FPKM at each time point (white bars) are compared to RT-qPCR values for each transcript
798
that were normalized to either 25S rRNA (dark gray bars) or to cox-5 (light gray bars); the
799
cox-5 transcript does not show a light-response in the RNA-seq data. Error bars show the
800
standard error obtained from triplicate technical replicates of each of the two RNA
801
preparations used for RNA-seq.
802
803
Figure 5. Hierarchical clustering of transcription factors whose mRNA levels are
804
light-regulated. Factors whose mRNA levels were regulated at q0.2 are indicated with
805
asterisks.
38
806
807
Figure 6. Genome wide view of light responses. (A) A plot of the number of
808
light-induced genes as a function of time after lights on at each of the time points. These plots
809
show the number of genes for a given level of expression-change (FC, fold-change) in
810
response to light (up- or down-regulated) at q0.2, 0.1, or 0.05 (the primary data are in Table
811
S9). (B) A plot of the number of light-repressed genes as a function of time after lights on
812
with all of time points. (C) Pattern of light-regulation of genes on Linkage Group I
813
(Chromosome 1). The log2 of the fold-change in expression in the light versus the dark is
814
given on the Y-axis for each time-point (15, 60, 120 and 240 min). Several examples of
815
strongly light-induced genes mentioned in the text are marked by arrows.
816
817
Figure 7. Phenotypes of selected light-regulated genes. A sampling of mutants
818
containing disruptions of genes showing light regulation with q0.2 were analyzed for
819
vegetative-growth phenotypes. The strain name indicates the gene that was disrupted (74A is
820
the wild-type strain). The indicated gene’s expression in the wild-type strain as determined by
821
RNA-seq is shown for reference. VM: Vogel’s Minimal medium; YE, VM supplemented
822
with yeast extract; 25 and 37, 25C and 37C, respectively. Analyses of sexual growth
823
phenotypes showed that each strain was female-fertile, except for NCU01870, which was
824
female-sterile.
39
825
40
826
Tables
827
Table 1. Transcripts with 16-fold or more induction by light. The log2 change in
828
expression in the light versus the dark is given for each time-point in the light (15, 60, 120
829
and 240 min).
Locus
Symbol Name
L15/D L60/D L120/D L240/D
NCU00552 al-1
albino-1
8.3
6.9
4.1
2.4
NCU08699 bli-4
bli-4 protein
7.5
7.8
4.8
3.5
NCU02190
oxysterol binding protein
7.3
5.6
2.5
1.5
NCU03967 vvd
vivid
6.6
5.1
4.0
3.1
NCU08770
hypothetical protein
6.4
7.6
2.3
0.7
NCU00582 cry
cryptochrome DASH
6.3
4.9
4.4
4.1
NCU10063
sugar isomerase
6.2
4.3
2.8
2.1
NCU08769 con-6
conidiation-6
6.0
8.5
7.5
2.4
NCU08626 phr
photoreactivation-deficient
5.3
4.0
1.9
1.2
NCU00585 al-2
albino-2
5.2
5.3
3.9
2.5
NCU07325 con-10
conidiation-10
4.8
7.1
4.3
1.5
NCU11424
carotenoid oxygenase-2
4.8
4.1
2.8
2.1
NCU07434
short-chain dehydrogenase/reductase SDR
4.6
3.8
1.5
1.7
NCU07267 bli-3
blue light-induced-3
4.6
6.8
4.6
2.4
NCU11395
S-(hydroxymethyl)glutathione dehydrogenase
4.0
6.1
4.4
2.7
NCU06420
hypothetical protein
3.8
4.1
2.7
1.3
NCU01060
hypothetical protein
3.5
4.9
3.9
2.8
NCU09049
hypothetical protein
3.4
6.1
4.3
1.3
NCU03506
hypothetical protein
3.1
4.3
3.0
1.5
NCU05844
hypothetical protein
2.7
4.5
2.6
-0.5
NCU01861
short chain dehydrogenase/reductase family
2.2
5.6
4.5
1.1
NCU06597
hypothetical protein
2.0
5.4
3.3
0.6
NCU04823
NADP-dependent alcohol dehydrogenase C
1.6
4.5
3.5
1.0
NCU05652
hypothetical protein
1.4
4.6
3.5
0.7
NCU07345
hypothetical protein
1.2
4.3
3.2
0.4
NCU07337
hypothetical protein
1.2
4.2
4.1
2.1
NCU00716 ncw-5
non-anchored cell wall protein-5
-0.3
2.8
4.1
4.3
cao-2
41
830
831
832
833
834
835
836
837
838
SUPPLEMENTARY DATA
Figure S1. Expression-changes for transcripts in Cluster 3 subclusters A, B, and C
demarcated in (Figure 3). Values for each time-point (L15, L60, L120 and L240) are
normalized to expression in the dark and plotted as described in Figure 3B.
Figure S2. Pattern of light-regulation of genes on Linkage Groups II-VII (Chromosomes
2-7). The log2 change in expression in the light versus the dark is given on the Y-axis for each
time-point in the light (15, 60, 120 and 240 min).
839
840
Table S1. CuffDiff analyses of FPKM (fragments per kilobase per million reads) for the
841
combined RNA-seq datasets from two biological replicates. The ratio values given are the
842
log2 ratio values. The q-value represents an adjusted p-value that is calculated with a
843
consideration of the false discovery rate of 0.05.
844
845
846
Table S2. CuffDiff analyses of FPKM for biological replicate 1. The ratio values given
are the log2 ratio values.
847
848
849
Table S3. CuffDiff analyses of FPKM for biological replicate 2. The ratio values given
are the log2 ratio values.
850
42
851
852
Table S4. Predicted genes that are not expressed in the combined biological replicates
(FPKM<1) that are not designated as hypothetical proteins.
853
854
855
Table S5. FunCat analyses for predicted genes that are highly expressed in the dark in
the combined biological replicates (FPKM>400 and FPKM>1000).
856
857
858
Table S6. CuffDiff analyses for the subset of transcripts determined to be regulated
2-fold in response to light. The ratio values given are the log2 ratio values.
859
860
Table S7. FunCat analysis of the 999 mRNAs most up-regulated in response to light.
861
862
Table S8. FunCat analysis of the 999 mRNAs most down-regulated in response to light.
863
864
865
Table S9. CuffDiff analyses for the subsets of transcripts determined to respond to light
with q≤0.2, 0.1 or 0.05. The ratio values given are the log2 ratio values.
866
867
868
Table S10. Gene Ontology (GO) analyses of genes that were 2-fold regulated by light and
genes whose light-regulation met the q0.2 stringency requirement.
869
43
870
871
872
873
874
Table S11. Funcat and GO enrichment analyses of the 5 major clusters delineated in
Figure 3A.
Table S12. RNA-seq data (extracted from Table S1) for the 27 TFs analyzed as WCC
targets in (SMITH et al. 2010). The ratio values given are the log2 ratio values.
875
876
877
Table S13. FunCat analysis of mRNAs whose levels change more than 16-fold in
response to light (Table 1).
878
879
Table S14. Summary of read-depth from Illumina RNA-seq.
44
Fig 1
A
B
Regulation of
metabolism and
protein function
Cell type
differentiation
Biogenesis
Cell fate
of cellular
components
C-compound and
carbohydrate
metabolism
Other
Stress
response
Protein with
binding function
or cofactor
requirement
Cell cycle and
DNA processing
Cell rescue,
defense and
virulence
Secondary
metabolism Complex
cofactor/cosubstrate
/vitamine binding
Detoxification
Protein synthesis
Interaction with
the environment
Modification by
ubiquitination,
deubiquitination
Unclassified
Other
Cellular transport
Energy
Metabolism
2-fold up
FPKM>400
C
D
Interaction with
the environment
Energy
Cell rescue,
defense and
virulence
Biogenesis
of cellular
components
Cell fate
Other
Kinase inhibitor
Protein with
binding function
or cofactor
requirement
Protein fate
Metabolism
Protein synthesis
Cell cycle and
DNA processing
Metabolism
of hormones
Alcohol
fermentation
Rhythm
Other
Glycolysis and
gluconeogenesis
Homeostasis
of metal ions
C-compound and
carbohydrate
metabolism
Biosynthesis of
vitamins,
cofactors, and
prothetic groups
Secondary
metabolism
Detoxification
Cellular
transport
2-fold down
Transcription
Complex
cofactor/cosubstrate
/vitamine binding
Stress
response
up, q≤0.2
Fig 2
240
120
60
15
-3.27 log2-fold change 8.50
NCU00582
NCU03967
NCU00552
NCU08699
NCU02190
NCU08770
NCU00585
NCU01060
NCU07325
NCU07267
NCU11395
NCU09049
NCU08769
NCU00607
NCU01112
NCU04266
NCU00584
NCU01124
NCU01957
NCU08824
NCU00360
NCU04805
NCU05964
NCU08557
NCU00999
NCU05568
NCU06306
NCU05594
NCU00244
NCU01154
NCU09841
NCU02713
NCU06125
NCU00236
NCU00761
NCU01810
NCU02074
NCU07075
NCU06231
NCU08413
NCU02356
NCU00203
NCU01997
NCU05683
NCU01188
NCU05770
NCU07074
NCU04416
NCU01862
NCU08727
NCU07837
NCU00276
NCU02282
NCU02651
NCU06095
NCU02790
NCU02636
NCU07728
NCU05721
NCU08726
NCU00281
NCU08606
NCU08402
NCU09830
NCU04430
NCU05005
NCU01697
NCU03949
NCU07149
NCU09559
NCU03107
NCU09421
NCU02122
NCU07073
NCU00451
NCU05154
NCU03273
NCU00332
NCU00748
NCU06265
NCU02099
NCU08298
NCU11367
NCU04295
NCU01510
NCU02321
NCU04016
NCU07923
NCU11050
NCU09451
NCU05202
NCU05706
NCU05165
NCU07608
NCU04267
NCU11309
NCU01059
NCU01088
NCU09713
NCU04538
NCU01181
NCU08425
NCU11356
NCU03893
NCU06460
NCU09604
NCU04415
NCU06506
NCU08155
NCU05142
NCU07349
NCU09914
NCU09674
NCU04720
NCU00755
NCU03641
NCU09526
NCU10470
NCU00247
NCU01735
NCU02765
NCU04605
NCU01080
NCU09040
NCU07806
NCU00766
NCU04466
NCU03780
NCU00701
NCU07474
NCU04237
NCU07915
NCU10129
NCU00175
NCU04667
NCU11989
NCU05490
NCU01555
NCU09714
NCU11687
NCU00397
NCU06603
NCU05387
NCU01064
NCU01065
NCU02395
NCU00985
NCU04816
NCU00069
NCU05522
NCU02690
NCU01233
NCU11507
NCU05313
NCU04256
NCU09692
NCU04539
NCU00678
NCU08873
NCU01870
NCU09195
NCU07156
NCU02396
NCU09683
NCU05143
NCU02466
NCU06370
NCU11724
NCU03430
NCU03908
NCU11365
NCU05069
NCU09116
NCU04246
NCU08057
NCU02397
NCU10055
NCU07273
NCU07395
NCU07422
NCU00322
NCU09075
NCU06977
NCU02771
NCU05819
NCU04360
NCU04950
NCU01058
NCU04238
NCU06616
NCU08409
NCU06558
NCU09615
NCU11540
NCU02629
NCU02798
NCU01070
NCU07082
NCU01107
NCU05525
NCU03112
NCU07233
NCU06751
NCU04914
NCU07495
NCU09041
NCU11860
NCU05524
NCU08390
NCU08457
NCU10852
NCU09141
NCU09305
NCU11300
NCU00667
NCU01922
NCU08747
NCU08167
NCU06549
NCU05881
NCU06020
NCU11870
NCU05089
NCU07661
NCU09676
NCU11201
NCU08695
NCU06803
NCU05148
NCU12074
NCU08549
NCU03682
NCU02596
NCU08949
NCU04823
NCU05652
NCU07345
NCU03205
NCU00838
NCU07061
NCU04635
NCU09821
NCU01127
NCU08791
NCU02322
NCU05291
NCU09513
NCU05395
NCU07962
NCU01056
NCU05619
NCU04583
NCU09057
NCU11876
NCU02540
NCU07439
NCU05341
NCU03753
NCU06890
NCU07143
NCU05768
NCU07927
NCU11264
NCU04908
NCU09403
NCU12134
NCU00868
NCU07232
NCU00250
NCU01063
NCU07441
NCU07337
NCU00716
NCU01011
NCU09775
NCU10641
NCU04528
NCU05534
NCU07067
NCU09420
NCU05384
NCU07569
NCU08907
NCU07787
NCU09508
NCU01861
NCU06597
NCU05844
NCU01089
NCU04452
NCU02801
NCU07585
NCU06420
NCU03506
NCU00586
NCU09235
NCU07921
NCU08291
NCU02265
NCU08850
NCU01108
NCU04639
NCU12116
NCU07540
NCU07541
NCU07434
NCU08626
NCU11424
NCU10063
NCU02344
NCU03092
NCU09764
NCU00202
NCU04923
NCU07846
NCU06187
NCU06912
NCU03813
NCU01245
NCU06341
NCU07974
NCU02916
NCU06054
NCU02546
NCU00337
NCU03396
NCU07166
NCU07430
NCU02511
NCU03555
NCU03241
NCU05287
NCU04041
NCU03380
NCU08295
NCU06090
NCU09832
NCU09894
NCU04334
NCU01589
NCU06055
NCU05835
NCU05789
NCU11699
NCU06607
NCU04433
NCU03608
NCU05289
NCU01638
NCU04826
NCU00193
NCU03006
NCU01824
NCU03702
NCU06783
NCU07696
NCU09497
NCU02209
NCU06327
NCU03748
NCU09659
NCU01485
NCU02333
NCU03814
NCU03561
NCU10893
NCU08898
NCU10053
NCU04698
NCU08120
NCU10895
NCU07386
NCU08352
NCU02898
NCU05803
NCU05238
NCU04924
NCU02762
NCU02494
NCU00273
NCU07658
NCU04548
NCU06468
NCU00406
NCU07688
NCU00372
NCU03808
NCU04348
NCU00712
NCU06308
NCU08951
NCU00301
NCU06409
NCU07041
NCU04439
NCU03018
NCU07871
NCU01524
NCU06366
NCU09437
NCU11714
NCU03986
NCU04534
NCU08487
NCU02284
NCU08135
NCU05936
NCU08551
NCU09595
NCU03768
NCU05132
NCU06342
NCU02002
NCU08840
NCU08616
NCU05826
NCU05680
NCU05301
NCU09858
NCU08468
NCU02066
NCU00925
NCU07528
NCU02385
NCU01894
NCU01257
NCU08003
NCU08421
NCU06043
NCU03560
NCU06217
NCU08518
NCU06340
NCU09206
NCU09380
NCU02236
NCU04273
NCU05830
NCU01675
NCU04327
NCU03321
NCU02729
NCU09499
NCU06272
NCU08595
NCU03669
NCU08869
NCU01612
NCU03051
NCU09349
NCU09488
NCU10687
NCU03066
NCU08968
NCU06780
NCU07654
NCU02528
NCU04485
NCU08287
NCU07070
NCU11175
NCU03488
NCU03606
NCU04646
NCU07736
NCU00457
NCU06578
NCU05822
NCU06348
NCU05627
NCU00336
NCU04609
NCU07670
NCU04463
NCU06338
NCU07246
NCU07870
NCU08923
NCU00350
NCU08661
NCU05832
NCU02477
NCU02533
NCU01240
NCU11321
NCU08931
NCU07262
NCU07380
NCU09783
NCU08816
NCU10021
NCU07802
NCU08325
NCU01121
NCU05650
NCU01083
NCU07459
NCU02480
NCU12021
NCU12022
NCU01195
NCU04385
NCU03076
NCU05712
NCU05788
NCU00790
NCU02369
NCU04910
NCU09505
NCU11405
NCU08976
NCU09504
NCU06785
NCU08535
NCU03963
NCU07375
NCU09823
NCU02482
NCU05828
NCU06417
NCU00821
NCU09909
NCU10038
NCU04909
NCU04963
NCU05126
NCU07307
NCU07308
NCU09506
NCU09873
NCU10040
1
2
3
4
5
Fig 3A
Cluster 1
Cluster 2
10
[FPKM]/[FPKM]D
[FPKM]/[FPKM]D
400
300
200
100
0
L15
L60
L120
4
0
L240
L15
[FPKM]/[FPKM]D
20
15
10
5
L60
L120
L240
Cluster 4
60
25
[FPKM]/[FPKM]D
6
2
Cluster 3
0
8
50
40
30
20
10
L15
L60
L120
L240
0
L15
L60
L120
L240
Cluster 5
[FPKM]/[FPKM]D
1.5
1.0
0.5
0
L15
L60
L120
L240
Fig 3B
Fruit body
development
Catalase reaction
Antibiotic
resistance
Proton driven
antiporter
Development
of conidia
Rhythm
Lipid, fatty acid
and isoprenoid
metabolism
Photoperception
and response
Other
DNA processing
Modification by
ubiquitination,
deubiquitination
Alcohol
fermentation
Transcriptional
control
Homeostasis of
metal ions
DNA
binding
Disease, virulence
and defense
Cluster 1
Growth
Metabolism of factors
intercellular
mediators
Metabolism of
the D-alanine
amino acid
Kinase inhibitor
group
Extracellular
metabolism
Cluster 2
C-compound
binding
Other
C-compound and
carbohydrate
metabolism
Glycolysis and
gluconeogenesis
Rhythm
Metabolism
of porphyrins
Metabolism of
alkaloids
Detoxification
Complex
cofactor/substrate
/vitamine binding
Biosynthesis
of vitamins,
cofactors, and
prosthetic
groups
Secondary
metabolsim
Complex
cofactor/cosubstrate
/vitamine binding
Regulation of
nitrogen, sulfur
and selenium
metabolism
Stress response
Cluster 4
Cluster 3
Other
DNA repair
Nucleic
acid
binding
RNA
processing
C-compound and
carbohydrate
metabolism
Nucleotide/nucleo
side/nucleobase
metabolism
RNA synthesis
Metal binding
Cell cycle
Amino acid
metabolism
Ribosome
biogenesis
Lipid, fatty acid
Nucleotide/nucleo
and isoprenoid Transport
side/nucleobase
routes DNA processing
metabolism
binding
Cluster 5
Fig 3C
NCU03396/25S
NCU03396/cox-5
NCU03396 FPKM
1.2
100
0.8
60
0.6
40
0.4
20
0.2
0
0
D
L15
NCU03702/25S
L60
L120
NCU03702/cox-5
L240
NCU03702 FPKM
1.2
100
80
0.8
60
0.6
40
0.4
FPKM
mRNA (RU)
1
20
0.2
0
0
D
L15
NCU08951/25S
mRNA (RU)
FPKM
80
L60
L120
NCU08951/cox-5
L240
NCU08951 FPKM
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
250
200
150
100
FPKM
mRNA (RU)
1
50
0
D
L15
L60
L120
L240
Fig 4
240
120
15
60
NCU02356*
NCU01734
NCU02819
NCU04179
NCU01345
NCU01856
NCU02203
NCU00097
NCU01312
NCU08159
NCU04022
NCU06744
NCU02432
NCU04770
NCU07945
NCU02182
NCU08307
NCU08184
NCU01640
NCU09615*
NCU06551
NCU03273*
NCU04295*
NCU02713*
NCU01924
NCU01154*
NCU06095*
NCU06407
NCU07728*
NCU08726*
NCU00285
NCU01958
NCU04058
NCU03126
NCU02315
NCU03352
NCU05061
NCU05242
NCU05994
NCU07246*
NCU03043
NCU00155
NCU01414
NCU07863
NCU07669
NCU08289
NCU00100
NCU03892
NCU07587
NCU09549
NCU07392
NCU03073
NCU08003*
NCU07430*
NCU01871
NCU11295
NCU02307
NCU08807
wc-1
sah-1
asl-1
bek-1
rca-1
tah-4
rpn-4
csp-1
sub-1
csp-2
vad-3
sre
fl
matA-1
aod-2
div-11
acon-4
Asm-1
fid-21
pco-1
dmm-2
div-16
adv-1
pole-4
mad-11
cre-1
Fig 5
-1.84
log2-fold change
3.10
A
B
200
180
160
140
141
140
84
q 0.2
72
16
20
0
52521
19
11
L15/D
FC>1
FC≥2
5431
FC≥8
FC≥32
FC≥64
20
20000
L240/D
q 0.1
51
36
5252
0
12
11
L15/D
FC>1
FC≥2
543
10
1
L60/D
FC≥4
FC≥8
8
0010
L120/D
FC≥16
FC≥32
FC≥64
60
L240/D
0
L15/D
FC>1
FC≥2
11
543
L15/D
0
7
L60/D
FC>1
8
1
L120/D
FC≥2
FC≥4
0
L240/D
FC≥8
92
90
66
FC≥8
22
60
0010
L120/D
FC≥16
FC≥32
FC≥64
q 0.05
37
40
20
10
1
L60/D
FC≥4
4
0
33
q 0.05
21
7
2
60
36
1
40
29
26
FC≥128 FC≥256
44
26
5252
q 0.1
78
50
15
99
80
85
20
110
0
67
40
137
20
20000
100
53
FC≥8
80
102
80
FC≥4
0
L240/D
133
40
20
120
100
FC≥2
60
33
22
1
L120/D
100
68
16
L60/D
120
68
10
1
160
140
60
20
22
0
FC>1
111
29
L15/D
FC≥128 FC≥256
8790
40
12
0
47
42
31
3
0
133
100
34
40
8
0010
140
103
q 0.2
100
80
23
L120/D
FC≥16
120
60
22
10
L60/D
FC≥4
62
44
36
33
40
80
161
160
95
60
80
195
179
180
136
80
120
206
200
157
120
100
220
185
20
7
20000
L240/D
29
2
0
25
19
3
0
L15/D
0
3
L60/D
FC≥128 FC≥256
FC>1
1
L120/D
FC≥2
FC≥4
8
0
L240/D
FC≥8
C
chromosome 1
gene density
7.5 15/dark
-2.5
7.5 60/dark
-2.5
7.5 120/dark
-2.5
7.5 240/dark
-2.5
NCU07434
NCU01861
NCU07345
ncw-5
cry
al-2
ncw-6
al-1
con-8
phr
Fig 6
Fig 7