G3: Genes|Genomes|Genetics Early Online, published on September 15, 2016 as doi:10.1534/g3.116.033308
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Genomic, transcriptomic and proteomic analysis provide insights into the cold
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adaptation mechanism of the obligate psychrophilic fungus Mrakia psychrophila
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Yao Su*, Xianzhi Jiang†, Wenping Wu†, Manman Wang*, M. Imran Hamid*, Meichun
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Xiang* and Xingzhong Liu*
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*
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Sciences, No 3 Park 1, Beichen West Rd., Chaoyang District, Beijing 100101, China
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and † Novozymes (China) Investment Co. Ltd., China Headquarters, 14 Xinxi Road,
State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of
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Shangdi Zone, Haidian District, Beijing 100085, China
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Corresponding aurthor: State Key Laboratory of Mycology, Institute of Microbiology,
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Chinese Academy of Sciences, No 3 Park 1, Beichen West Rd., Chaoyang District,
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Beijing 100101, China. Email: [email protected]
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Reference numbers for data available in public repositories:
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Genome: Bioproject PID PRJNA304674 (NCBI)
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Transcriptome: GSE76769 (GEO)
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Proteome: PXD004881 (PRIDE Archive)
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© The Author(s) 2013. Published by the Genetics Society of America.
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Running Title: Cold adaptation of fungi
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Key words: Comparative genomics, Transcriptomics, Proteomics, Temperature
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adaptation and Basidiomycetous yeast.
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Corresponding aurthor:
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Name: Xingzhong Liu
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Office mailing address: State Key Laboratory of Mycology, Institute of Microbiology,
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Chinese Academy of Sciences, No 3 Park 1, Beichen West Rd., Chaoyang District,
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Beijing 100101, China.
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Phone number: 0086-10-64807512
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Email: [email protected]
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ABSTRACT
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Mrakia psychrophila is an obligate psychrophilic fungus. The cold adaptation
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mechanism of psychrophilic fungi remains unknown. Comparative genomics analysis
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indicated that M. psychrophila had a specific codon usage preference, especially for
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codons of Gly and Arg and its major facilitator superfamily (MFS) transporter gene
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family was expanded. Transcriptomic analysis revealed that genes involved in
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ribosome and energy metabolism were upregulated at 4 C, while genes involved in
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unfolded protein binding, protein processing in the endoplasmic reticulum,
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proteasome, spliceosome and mRNA surveillance were upregulated at 20 C. In
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addition, genes related to unfolded protein binding were alternatively spliced.
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Consistent
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dehydrogenase which are involved in biosynthesis of unsaturated fatty acid and
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glycerol respectively were upregulated at 4 C. Cold adaptation of M. psychrophila is
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mediated by synthesizing unsaturated fatty acids to maintain membrane fluidity and
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accumulating glycerol as a cryoprotectant. The proteomic analysis indicated that the
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correlations between the dynamic patterns between transcript level changes and
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protein level changes for some pathways were positive at 4 C, but negative at 20 C.
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The death of M. psychrophila above 20 C might be caused by an unfolded protein
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response.
with
other
psychrophiles,
desaturase
and
glycerol
3-phophate
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INTRODUCTION
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Fungi are found in all kinds of cold habitats, including permafrost, glaciers and
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Polar Regions. The cold habitats (≤5 C) occupy about 75% of the Earth‟s biosphere.
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Fungi are better adapted to cold habitats than bacteria in solid media (Panikov and
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Sizova 2007). Psychrophilic microorganisms (psychrophiles) exhibit an optimal
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growth temperature of about 15 C, a minimal growth temperature of ≤0 C and
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cannot grow above 20 C (Arthur and Watson 1976; Morita 1975). Some
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psychrophilic fungi are animal or plant pathogens, such as Pseudogymnoascus
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destructans, which causes white-nose syndrome of bats (Zhang et al. 2013). Although
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many psychrophilic fungi have been isolated, little is known about their cold
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adaptation mechanisms.
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The majority studies of microbiological cold adaptation mechanism have focused
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on the cold stress response of mesophilic model organisms, such as Escherichia coli,
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Bacillus subtilis and Saccharomyces cerevisiae. E. coli and B. subtilis respond to cold
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stress by inhibiting general protein synthesis and inducing cold shock proteins after
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growth has stopped for several hours (Goldstein et al. 1990; Willimsky et al. 1992;
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Jones et al. 1987). Synthesis of unsaturated fatty acid, accumulation of compatible
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solutes and an antioxidant response are considered important responses for cold
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adaptation (Zhang et al. 2003; Chattopadhyay 2006; Borges et al. 2002; Casanueva et
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al. 2010). Whether psychrophilic fungi possess these cold adaptation mechanisms is
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unknown.
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Cold shock and cold adaptation are two different processes. Cold shock means
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microorganism transferred from a higher temperature (e.g., 37 C) to a lower
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temperature (e.g., 10 C) in a short time, while cold adaptation refers to
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microorganism that exists under a steady-state for a long time at low temperatures.
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Transcriptome profiles vary significantly at different time points after cold shock
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(Langin et al. 1995). As eukaryotes, fungi are quite different from bacteria in terms of
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their cold adaptation mechanism. A more moderate cold shock response is induced in
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yeast than in bacteria, while a strong cold shock response was observed in yeast after
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transfer to a near-freezing temperature (Kandror et al. 2004; Al-Fageeh Mb Fau -
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Smales and Smales 2006). Condition-specific alternative splicing has been
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documented to play an important role in adaptation to environmental stresses (Linde
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et al. 2015). However, most studies have focused on how psychrophilic
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microorganisms survive and grow under low temperatures; little attention has been
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paid to why psychrophilic microorganism cannot survive above 20 C.
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Mrakia psychrophila is an obligate psychrophilic fungus and a basidiomycetous
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yeast (Cystofilobasidiales, Tremellomycetes, Basidiomycota) with an optimal growth
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temperature range of 12 to 15 C, and cannot grow above 20 C (Supplemental
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Material, Figure S1). M. psychrophila has been isolated from diverse cold habitats,
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including Alpine glaciers and Antarctic soil (Xin and Zhou 2007; Turchetti et al.
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2013).
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In this study, the genome of M. psychrophila was analyzed and compared with
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other psychrophilic, thermophilic and mesophilic fungi (Supplemental Material, Table
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S1). An integrative analysis of transcriptomic and proteomic data of M. psychrophila
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at 4,12 and 20 C was performed. This is the first integrated study providing insights
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into the cold adaptation mechanism of psychrophilic fungi from genomic,
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transcriptomic and proteomic perspectives.
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MATERIALS AND METHODS
M. psychrophila strains and growth condition
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M. psychrophila NN053900 was isolated from permafrost on the Qinghai-Tibet
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Plateau. M. psychrophila was cultured on potato dextrose agar (PDA) and maintained
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at 4, 12 and 20C on PDA for one month, respectively. For cold shock treatments, M.
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psychrophila cultured at 12 C were transferred to 4 C.
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Genome sequencing and annotation
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The genome of M. psychrophila was sequenced using Illumina HiSeq 2000
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apparatus. The data were assembled using release v0.19 of Idba (Peng et al. 2010). We
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used homology and ab-initio prediction to identify protein-coding genes. For the
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homology-based gene prediction, we aligned the NCBI nr protein database to the M.
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psychrophila genome using TBLASTN and Genewise (Birney et al. 2004). We used
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FGENESH (Solovyev et al. 2006), GENEID (Blanco et al. 2002), GeneMark
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(Ter-Hovhannisyan et al. 2008) and SNAP (Korf 2004) for the ab-initio prediction.
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Protein alignments and ab-initio gene predictions were combined to build a consensus
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gene set using EvidenceModeler (Haas et al. 2008). Repeat sequences were identified
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using RepeatMasker (http://www.repeatmasker.org). Protein domains were identified
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with InterProScan (Consortium: et al. 2000). The final gene set was mapped to KEGG
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pathways using KAAS (Moriya et al. 2007). GO annotations were retrieved from the
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results of InterProScan and Blast2GO (Conesa et al. 2005). Homology-independent
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GO annotations were also predicted using FFPred (Minneci et al. 2013). Transfer
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RNAs (tRNAs) were predicted using tRNAScan-SE (Lowe and Eddy 1997). Other
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genome sequences and annotations used in comparative genomic analysis were
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downloaded from JGI (http://genome.jgi.doe.gov).
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Synonymous codon usage
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We analyzed the patterns of synonymous codon usage in 15 completely
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sequenced fungal genomes, including four psychrophiles, three thermophiles and
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eight mesophiles. We combined all the genes of each fungal genome, and calculated
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the relative synonymous codon usage (Vogel et al. 2010) for each fungus. We then
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used correspondence analysis to characterize the pattern of codon usage and map the
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pattern on to the distribution of codons and species (Lynn et al. 2002).
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Correspondence analysis was carried out using the „ca‟ package of R.
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Identification of optimal codon
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For each gene of M. psychrophila, we calculated Nc (effective number of codons)
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and Nc‟ (Nc corrected for nucleotide content) using ENCprime (Novembre 2002). We
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then calculated the correlation between the each codon and the overall codon bias (Nc
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and Nc‟) of each gene. The codon in each codon family showing the strongest and
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significantly negative correlation with the Nc or Nc‟ was defined as the optimal codon
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(Hershberg and Petrov 2009). A correlation was considered significant at a P value ≤
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0.05/n, where n is the number of codons in the codon family. Spearman correlations
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were calculated using the R statistical package.
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Orthology, phylogenetic, and protein family evolutionary analyses
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We used OrthoMCL (Li et al. 2003) to analyze the orthogroups of the selected 15
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selected fungal genomes. A total of 16325 orthogroups were identified, in which 296
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orthogroups were single-copy orthologous genes. Based on the single-copy
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orthologous genes, a phylogenetic tree was constructed using RAxML 7.2.8 with the
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PROTGAMMAILGF model and 100 rapid bootstrap replications (Stamatakis 2006).
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The divergence time was estimated with the program r8s v1.7 (Sanderson 2003) and
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the origin of the Ascomycota at 500–650 million years ago (Lücking et al. 2009) as
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the calibration point. Each orthogroup from OrthoMCL was defined as a protein
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family. Protein family expansions and contractions were analyzed using CAFE (De
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Bie et al. 2006).
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Identification of orphan genes
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Protein sequences were aligned against the NCBI nr database and SwissProt
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databases. All proteins with a BLAST hit with an E value ≤ 10-3 were eliminated. The
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remaining proteins were defined as encoded by orphan genes (Wissler et al. 2013).
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RNA extraction and sequencing
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RNA was isolated using a RNeasy® Plant Mini Kit (QIAGEN) from M.
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psychrophila cultured at three temperatures: 4, 12 and 20 oC, with three replications
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per temperature. Sequencing libraries were generated using a NEBNext®Ultra™
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RNA Library Prep Kit for Illumina®(NEB, USA) following the manufacturer‟s
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recommendations. The prepared libraries were sequenced on an Illumina HiSeq 2000
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platform and 100bp paired-end reads were generated.
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Reads alignment and differential gene expression
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TopHat v2.1.0 (Kim et al. 2013) was used to align the reads against the M.
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psychrophila genome sequences. The expression levels of transcripts were measured
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by fragments per kilobase per million mapped fragments using the Cufflinks software
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v2.2.1 (Trapnell et al. 2010). Differential expression was estimated and tested with the
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MA-plot-based method with random sampling model in the DEGseq package of R
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(Wang et al. 2010) between M. psychrophila cultured at 4 C and 12 C, as well as 20
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C and 12 C, cutoff of P value was 0.001. P value and FDR of each gene are listed in
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Supplemental Material, Table S2.
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Annotation of alternative splicing events
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SpliceGrapher (Rogers et al. 2012) was used to annotate and visualize all AS
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events, including intron retention, skipped exons, alternative 5SSs and alternative
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3SSs. Only AS events detected in more than two replicates were identified as true AS
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events.
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Real-time quantitative RT-PCR
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RNA was isolated from M. psychrophila at 0 min, 10 min 30 min, 1h, 2h, 4h, 6h
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and 8h after cold shock. The reverse transcription reactions were performed with a
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Fast Quant kit (TIANGEN) in a 20 µL reaction system. The RT-solution was diluted
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10 times, and 1µL of the solution was used as the template in the 20 µL reaction
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system with 2×THUNDERBIRD SYBR qPCR Mix (TOYOBO). The quantitative
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PCRs were performed in technical triplicate using the BioRad CFX96 TouchTM
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Read-Time PCR detection system. The primers used in quantitative qPCR are listed in
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Supplemental Material, Table S3.
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Protein extraction, Digestion and iTRAQ labeling
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M. psychrophila cultured at 4,12 and 20 C were harvested and lysed in a buffer
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containing 8M urea, 30mM 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid,
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1mM phenylmethanesulfonylfluoride, 2mM ethylenediaminetetraacetic acid, and
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10mM dithiothreitol. After centrifugation at 20,000×g for 30 min, the supernatants
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were reduced and alkylated by 10mM DTT and 55mM Iodoacetamide. The treated
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proteins were precipitated in 80% acetone at -20 C for 3h. After centrifugation at
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20,000×g for 30 min, the precipitants were resuspended in 50% tetraethylammonium
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bromide and 0.1% sodium dodecyl sulfate and again centrifuged at 20,000×g for
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30min. The protein concentrations were determined using the Bradford method. The
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proteins were digested with trypsin at 37 C for 12h. The tryptic peptides were labeled
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using an iTRAQ® reagents 8-plex multiplex kit (Applied Biosystems) following the
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manufacturer‟s protocol.
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NanoLC-MS/MS analysis and protein identification
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The iTRAQ labeled peptide mixtures were separated on a Luna SCX strong
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cation exchange high performance liquid chromatography column (Phenomenex) and
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desalted with strata-X C18 column (Phenomenex). The mobile phase A was 0.1%
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formic acid in water, while mobile phase B was 0.1% formic acid in acetonitrile.
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Peptides were eluted in a linear gradient of 5–80% mobile phase B over 65 min. The
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elutes were directly entered into a Thermo Fisher Q Exactive mass spectrometer,
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setting in positive ion mode and data-dependent manner with full MS scan from
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350–2000 m/z, resolution at 70,000. The MS/MS data were searched using Mascot
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2.3.01 (Matrix Science, Boston, MA, USA) against the database with all predicted
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proteins in M. psychrophila. Only proteins identified below the 1% global FDR were
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qualified for further quantitative data analysis. The fold changes in protein abundance
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were defined as the median ratio of all significantly matched spectra with tag signals.
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DEPs were identified with fold changes >1.5. When analyzing correlation between
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the transcriptome and the proteome, transcript level is qualified with FPKM,
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transcript level change and protein level change are qualified with fold change of
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DEG and DEP, respectively.
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Data availability
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The genome sequence of M. psychrophila was submitted to NCBI (Bioproject
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PID PRJNA304674). The transcriptome data have been deposited in the NCBI Gene
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Expression Omnibus and are accessible through GEO Series accession number
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GSE76769. The proteomics data were deposited at PRIDE Archive under accession
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number PXD004881.
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RESULTS
Genome sequencing and annotation
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The draft sequence of Mrakia psychrophila‟s genome was obtained using the
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whole genome shotgun Sanger sequencing approach to ~400×coverage. The genome
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was assembled into 1975 contigs, with a total size of 27.8 Mb (Table 1). Comparison
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with two phylogenetically related basidiomycetous yeasts showed that its genome size
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is larger than Cryptococcus neoformans (19.1 Mb), but smaller than Dioszegia
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cryoxerica (39.5 Mb). The overall GC content is 53.8%, which is higher than C.
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neoformans (48.5%), but lower than D. cryoxerica (56.1%). 76.4% of the predicted
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gene models (4579) in M. psychrophila had matches in the GenBank non-redundant
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protein database (BLASTP; E-value<1e-5) and about 21.3% of the predicted gene
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models (1276) were identified as orphan genes. The GC contents of the coding
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sequences in the psychrophilic fungi M. psychrophila (56.5%) and D. cryoxerica
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(58.6%) are higher than that in the mesophilic fungus C. neoformans (51.2%). GC
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contents in the third codon position (GC3) are even higher in M. psychrophila (63.3%)
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and D. cryoxerica (68.3%) than that in C. neoformans (52.1%). The average number
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of exons in M. psychrophila is 8.0, which is higher than that of C. neoformans (6.5)
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and D. cryoxerica (5.4).
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Synonymous codon usage bias
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The genes of each genome were combined for correspondence analysis of
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relative synonymous codon usage. Codons were separated along the horizontal axis
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by their GC3 values. All the psychrophiles and thermophiles showed a preference for
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codons ending in G and C, while some mesophiles prefer to use codons ending in A
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and U, such as C. neoformans and S. cerevisiae. M. psychrophila is separated from
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other fungi along the vertical axis because of its preferential usage of codons GGA
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and CGA for Gly and Arg, respectively (Figure 1), which was also supported from the
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optimal codons analysis (Supplemental Material, Table S4). Gly and Arg account for
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7.6% and 6.0% of the amino acid composition in M. psychrophila, respectively. The
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copy numbers of tRNAs corresponding to GGA or CGA in M. psychrophila are higher
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than those in other basidiomycetous yeasts, which are in turn higher than the copy
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numbers of tRNAs corresponding to other synonymous codons of Gly or Arg in M.
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psychrophila (Supplemental Material, Table S5).
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Lineage specific expansion and contraction of gene families
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Annotated genes were organized into 16325 families based on orthoMCL, in
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which 3221 families contain genes from M. psychrophila. We identified eight gene
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families that are expanded in M. psychrophila compared with other fungi, while one
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gene family has been lost in M. psychrophila. Two gene families are significantly
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expanded that do not have orthologs in other fungi and are predicted to be homologs
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encoding receptor binding, ATP binding and regulation of gene expression. Other
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expanded gene families are related to “glucosidase activity” (GO:0015926),
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“peptidase activity” (GO:0008233) and “transmembrane transport” (GO:0055085).
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The gene family lost from M. psychrophila is an orphan gene family of D. cryoxerica.
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Tremellomycetes clade (Figure 2) comprising two psychrophilic fungi (M.
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psychrophila and D. cryoxerica) and C. neoformans, while the genus Cryptococcus is
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also frequently isolated from cold habitats (Thomas-Hall and Watson 2002). There are
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10 expanded gene families and two contracted gene families in the Tremellomycetes
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clade. The expanded gene families in the Tremellomycetes clade are related to
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transport
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two-component
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GO:0000155, “two-component sensor activity”; GO:0000156, “two-component
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response regulator activity”). One expanded gene family in M. psychrophila and three
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expanded gene families in Tremellomycetes clade all belong to the major facilitator
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superfamily (MFS). There are 83 gene belong to MFS in M. psychrophila. The MFS
(GO:0022857,
system
“transmembrane
(GO:0004673,
transporter
“protein
activity”)
histidine
kinase
and
the
activity”;
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is a large and ancient family of secondary transporters that are energized by
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electrochemical proton motive force (Sá-Correia et al. 2009). MFS proteins are
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involved in anti-fungal resistance and nutrition transport (Gaur et al. 2008).The gene
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family related to glycoside hydrolase has been expanded in two psychrophilic fungi,
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M. psychrophila and D. cryoxerica, while the gene family containing an oligopeptide
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transporter (OPT) domain have been expanded in two psychrophilic fungi M.
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psychrophila and Ophiocordyceps sinensis (Xiao et al. 2013). Genes with an OPT
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domain are responsible for transporting of oligopeptides (Perlin et al. 2014).
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Differentially expressed genes (DEGs) at 4 C and 20 C
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Compared with the optimal temperature for growth at 12 C, 684 genes were
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upregulated and 844 genes were downregulated at 4 C, while 1202 genes were
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upregulated and 1078 genes were downregulated at 20 C. Significant differences in
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transcriptome profiles were observed between M. psychrophila cultured at 4 C and
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20 C. For DEGs at 4 C, GO terms related to the ribosome, translation and
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transporter are enriched, suggesting that translation may play an important role at
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near-freezing temperatures (Table 2). For DEGs at 20 C, GO terms related to
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ribosomes are also enriched, which implied that translation is also important for
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survival at 20 C (Table 3). By performing KEGG pathway analyses, DEGs at 4 C
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were identified as being involved in the ribosome, glycolysis/gluconeogenesis,
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pentose phosphate, TCA cycle and fatty acid metabolism pathways. For DEGs at 20
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C, the ribosome, spliceosome and oxidative phosphorylation pathways were
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significantly enriched. Ribosomal genes were upregulated at 4 C and down-regulated
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at 20 C. Proteins involved in the proteasome, spliceosome, unfolded protein binding,
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and mRNA surveillance were upregulated at 20 C (Figure 3A). Energy metabolism
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was upregulated at near-freezing temperature (Figure 3B). Desaturase DesC
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(MPSY2164), which is involved in the biosynthesis of unsaturated fatty acids was
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only up-regulated at 4 C, while another desaturase Fad2 (MPSY3203) was
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upregulated at 4 C and 20 C. Nine genes of the steroid biosynthesis pathway were
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upregulated at 4 C, but none of them were upregulated at 20 C (Supplemental
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Material, Figure S2). Glycerol 3-phosphate dehydrogenase (Gpd, MPSY651), the
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rate-controlling enzyme of glycerol formation, was upregulated at 4 C, which
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indicated that glycerol serves as compatible solute in M. psychrophila.
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Trehalose-6-phophate synthase (Tps, MPSY304), the enzyme for trehalose synthesis,
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was not upregulated at 4 C or 20 C, which suggested that there is no trehalose
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accumulation in M. psychrophila. Although reactive oxygen species (ROS) is a threat
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at low temperatures, superoxide dismutase (Sod, MPSY659), which is involved in
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catalase involving antioxidant defense were not upregulated at 4 C or 20 C. Ire1
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(MPSY2892) and Kar2 (MPSY3525), which are involved in the unfolded protein
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response (UPR), were both upregulated at 20 C. In the 133 MFS genes of M.
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psychrophila, 39 genes were upregulated and 13 genes were downregulated at 4 C,
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while nine genes were upregulated and 48 genes were downregulated at 20 C. Of
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1276 orphan genes of M. psychrophila, 469 orphan genes (36.8%) were differentially
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expressed.
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Alternative splicing at different temperatures
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Alternative splicing (AS) is prevalent in M. psychrophila. We identified 14481
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AS events including 8910 intron retention, 663 exon skipping, 1756 alternative 5
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splice sites (SSs), and 2968 alternative 3 SSs. All the predicted splicing sites were
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restricted to the canonical GT-AG or GC-AG pattern. Intron retention (IR) was the
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most prevalent AS event at 4, 12, 20 C, alternative 3 SSs were the second most
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common AS events (Table 4). About one third of all the genes in M. psychrophila had
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undergone AS and three quarters of the alternatively spliced genes contained retained
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introns (Table 5). IR in most genes leads to premature termination of translation.
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Multiple occurrences of AS events were observed in more than four hundred genes in
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M. psychrophila, so the total AS events (Table 4) are higher than those detected in
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genes (Table 5). There was a significant difference in AS between M. psychrophila at
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different temperatures. Some genes only underwent AS at a certain temperature; for
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example, IR in 418 genes only occurred at 4 C (Figure 4). IR was the most prevalent
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form of AS in M. psychrophila; therefore, we analyzed the functional categories of
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genes that underwent IR only at 4 C or 20 C. Genes that underwent IR at 4 C are
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related to “transporter activity” (GO:0005215), “ribonucleoprotein complex
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biogenesis” (GO:0022613), “metal ion binding” (GO:0046872) and “hydrolase
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activity” (GO:0016787). Genes that underwent IR only at 20 C are related to
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“unfolded protein binding” (GO:0051082), “helicase activity” (GO:0004386) and
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“L-serine metabolic process” (GO:0006563) (Figure 5). Pathway analysis also
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indicated that IR tends to occur in specific pathways at 4 C or 20 C. For example,
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seven genes involved in the spliceosome undergo IR at 20 C, while only one gene
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underwent IR at 4 C in that pathway.
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Cold stress response at near-freeze temperature
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To analyze the transcriptome profile in response to cold stress, we monitored the
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expression levels of seven genes at 0 min, 10 min, 30 min, 1h, 2h, 4h, 6h, 8h after
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cold shock (from 12 C to 4 C) via quantitative real-time PCR (qPCR) (Figure 6A).
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The desaturase gene DesC (MPSY2164), which was upregulated at 4 C, was
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downregulated at 10 min and upregulated at 30 min, after which it was expressed at a
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low level from 1h to 8h. Gpd (MPSY651), a core gene for the biosynthesis of glycerol,
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was downregulated immediately after cold shock, but upregulated from 1h. Sod
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(MPSY659) was also downregulated immediately after cold shock and up-regulated
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from 1h, which indicated that Sod (MPSY659) is important for ROS reduction after
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cold shock. Catalase (Cat,MPSY4125), which degrades hydrogen peroxide, was
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expressed at low level after cold shock. The gene encoding small nuclear
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ribonucleoprotein-associated protein 1 (Snu13, MPSY2409), which is involved in the
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spliceosome, was upregulated before 4h and down-regulated after 4h. Ribosomal
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genes were upregulated at 4 C, the expression levels of ribosomal genes L13Ae
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(MPSY369) and S19 (MPSY3084) were examined and shown to increase gradually
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after cold shock. The qPCR result showed that gene expression levels fluctuate after
396
cold shock. Comparing with RNA-seq analysis of cold adaptation (Figure 6B),
18
397
ribosomal genes L13Ae (MPSY369) and S19 (MPSY3084) shown the same tendency.
398
399
Differentially expressed proteins (DEPs) at different temperature
400
Isobaric tag for relative and absolute quantitation (iTRAQ)-based proteomics
401
analysis was performed to obtain the protein expression profiles in M. psychrophila
402
cultured at 4, 12 and 20 C. Overall, 12107 unique peptides, corresponding to 1673
403
proteins were identified. Considering FDR < 0.01 and unique peptide numbers ≥ 2,
404
1345 non-redundant proteins were obtained, of which 41 are encoded by orphan genes.
405
Compared with M. psychrophila cultured at 12 C, there were 54 differentially
406
expressed proteins (DEPs) (27 upregulated and 27 downregulated) and 75 DEPs (28
407
DEPs upregulated and 47 downregulated) at 4 and 20 C respectively. Comparing the
408
DEPs at 4 C and 20 C, eight DEPs were upregulated, while 10 DEPs were
409
downregulated at both temperatures. At 4 C, two proteins of tricarboxylic acid (TCA)
410
cycle (citrate synthase MPSY4093 and LSC2, MPSY4552), one protein of glycolysis
411
(PDC, MPSY2287), and one ribosomal protein (RPSB, MPSY5379) were
412
downregulated, while one protein of amino acid metabolism (GLNA, MPSY123) and
413
one MFS transporter (MPSY2821) were up-regulated. At 20 C, 4 proteins of the TCA
414
cycle
415
DLST(MPSY3759)
416
phosphorylation (MTCP1, MPSY4350), and one protein of glycerophospholipid
417
metabolism (CLD1, MPSY5022) were downregulated, while one heat shock protein
418
(DNAJ, MPSY1312) and two MFS transporters (MPSY4181 and MPSY2821) were
including
tow
and
citrate
LSC2
synthase
(MPSY4127
(MPSY4552),
one
and
protein
MPSY4093),
of
oxidative
19
419
upregulated. The results indicated that energy metabolism is involved in the
420
adaptation of M. psychrophila at 4 C and 20 C, and the heat shock response might be
421
induced at 20 oC.
422
423
Correlation between the transcriptome and the proteome
424
Transcriptome and proteome of M. psychrophila were compared, 12 and 8 genes
425
are upregulated at both mRNA and protein levels at 4 oC and 20 oC, while 19 and 21
426
genes are downregulated at both mRNA and protein levels at 4 oC and 20 oC. The
427
mRNA abundance and the expression change of proteins in M. psychrophila were
428
compared between 4 oC and 20 oC. The relationship between the transcript level and
429
the protein level change was positive (ρ=0.09, P=1.7×10-3, Supplemental Material,
430
Figure S3A) at 4 oC, but significantly negative (ρ=-0.11,P=8.3×10-5, Supplemental
431
Material, Figure S3B) at 20 oC. This indicated that proteins encoded by highly
432
expressed transcripts tend to be upregulated at 4 oC, but downregulated at 20 oC.
433
Protein level changes and corresponding transcript level changes at 4 oC and 20 oC
434
were compared and the overall correlation coefficients were 0.25 and 0.09 at 4 oC and
435
20 oC respectively. Furthermore, the correlation of dynamic patterns between protein
436
level changes and transcript level changes by each pathway were highly variable
437
between the two temperatures (Supplemental Material, Table S6), for example, the
438
change of transcript and protein levels in glycerophospholipid metabolism were
439
significantly positively correlated at 4 oC (ρ=0.68,P=1.84×10-3), but not correlated
440
(ρ=-0.29,P=0.24) at 20 oC (Figure 7). Glycerophospholipid metabolism is important
20
441
for membrane fluidity. The same tendencies have been observed for fatty acid
442
metabolism, Glycolysis/Gluconeogenesis
and RNA degradation.
443
DISCUSSION
444
445
Comparative genomic, transcriptomic and proteomic analyses have revealed the
446
cold adaptation mechanisms in M. psychrophila. Although, some strategies for cold
447
adaptation by M. psychrophila are shared with other psychrophilies, some new
448
findings that are different from other psychrophiles were observed. Codon usage bias
449
and AS might contribute to the cold adaptation of M. psychrophila. In addition, no
450
growth above 20 oC could be caused, at least partially by accumulation of unfolded
451
proteins in the ER.
452
453
The transcriptome profile fluctuated after cold stress; therefore, cold adaptation
454
of psychrophilies cannot be simply explained by the cold stress response of
455
mesophilic model organisms. Cold adaptation and cold shock are distinct processes.
456
Cold adaptation means that microorganisms are cultured in a steady state at a low
457
temperature for a long time, whereas in cold shock, the culture temperature is
458
downshifted suddenly. Energy metabolism is repressed during the cold stress response
459
of bacteria Pseudomonas putida (Frank et al. 2011), but it is upregulated in cold
460
adapted M. psychrophila. Cold shock induces accumulation of glycogen and trehalose,
461
as well as upregulation of Sod and Cat, in psychrotolerant fungi Penicillium olsonii
462
(Gocheva et al. 2009). Although glycerol is thought to be accumulated, activation of
21
463
the antioxidant response was not observed in M. psychrophila cultured at near-freeze
464
temperature. Similarly, in S. cerevisiae, trehalose did not serve as compatible solute in
465
the steady state at low temperature (Tai et al. 2007) , but accumulation of trehalose
466
was observed in response to cold shock at near-freezing temperatures (temperature
467
downshift to near freeze temperature) (Kandror et al. 2004). Genes involved in RNA
468
polymerase and rRNA processing, cytosolic ribosomal proteins, and the general stress
469
response were upregulated at the early, middle and late phases of cold stress response
470
of S. cerevisiae respectively (Sahara et al. 2002). The time-dependent transcriptomic
471
variation may reflect the transition from cold shock to cold adaption.
472
473
M. psychrophila produces unsaturated fatty acids (UFAs) to maintain membrane
474
fluidity and accumulates glycerol as a compatible solute at 4 oC, indicating by
475
upregulation of DesC (P value = 4.17E-9) and Gpd (P value = 2.21E-6).
476
transporter and energy metabolism are also important for cold adaptation. Membrane
477
fluidity is essential for organisms to survive in psychrophilic habitats and the
478
desaturase DesC, is generally upregulated to produce unsaturated fatty acid as
479
observed in B. subtilis after cold shock (Aguilar et al. 1998). Desaturase is a key
480
enzyme for biosynthesis of UFAs, which are beneficial for keeping membrane fluidity
481
at low temperatures. M. psychrophila is predicted to accumulate glycerol as a
482
compatible solute by upregulation of Gpd at 4
483
of glycerol. S. cerevisiae also accumulates glycerol for freeze protection in a
484
HOG-dependent manner (Butler et al. 2009). Ribosomes serve as sensors of heat and
The MFS
C, which is responsible for synthesis
22
485
cold shock in E. coli (VanBogelen and Neidhardt 1990). Ribosomal genes or
486
ribosome-biogenesis genes are upregulated in M. psychrophila and S. cerevisiae
487
respectively (Tai et al. 2007). The translation process may slow down at low
488
temperature, and more ribosomes might be needed for translation.
489
490
Specific codon usage bias might be also benefit for the cold adaptation of M.
491
psychrophila, especially GGA for Gly and CGA for Arg. There are several reasons for
492
the codon usage bias in M. psychrophila. First, codon usage bias might influence
493
mRNA folding structure (Trotta 2013) and special codon usage may faciliate
494
translation at low temperatures. Second, codon usage bias may have coevoluted with
495
the copy number of the corresponding tRNAs. The speed and accuracy of translation
496
might be influenced by tRNA abundance (Higgs and Ran 2008; Shah and Gilchrist
497
2010). In fact, copy numbers of tRNA corresponding to GGA and CGA are the
498
highest among those corresponding to other codons encoding Gly and Arg. Thus, the
499
specific codon usage bias in M. psychrophila might be beneficial for the speed and
500
accuracy of translation at low temperatures. Third, codon usage bias might be caused
501
by genetic code ambiguity. In Candida albicans, Leu codon CUG can be translated to
502
Ser (97%) or Leu (3%) (Zhou et al. 2013). There may be such genetic code ambiguity
503
in M. psychrophila; theirfore, it must use rare codons as optimal codons to avoid
504
nonsynonymous mutations. The MFS gene family is expanded in M. psychrophila and
505
other species in the Tremellomycetes clade, which may contribute to the accumulation
506
of nutrients from the environments (Perlin et al. 2014). MFS transporters are also
23
507
important for acid tolerance of Penicillium funiculosum (Xu et al. 2014). Energy
508
metabolism is upregulated in M. psychrophila at 4 C, as well as in Candida glabrata
509
under acidic stress (Zhou et al. 2011). M. psychrophila may need more ATP for
510
transport, biosynthesis of UFAs and glycerol at 4 C.
511
512
The nonsurvival of M. psychrophila above 20 C might be owing to the induction
513
of UPR. Genes involved in unfolded protein binding, protein processing in the
514
endoplasmic reticulum (ER), proteasome, spliceosome and mRNA surveillance are
515
upregulated at 20 C. Upregulation of genes related to unfolded protein binding and
516
genes involved in UPR indicated that there was an accumulation of unfolded proteins
517
at 20 C . Unfolded proteins accumulating in the ER has been named as ER stress
518
(Gardner et al. 2013). UPR is triggered to maintain protein-folding homeostasis of the
519
ER and induce expression of genes involved in protein folding, vesicle trafficking and
520
protein degradation (Labunskyy et al. 2014; Hou et al. 2014). The protein processing
521
in endoplasmic reticulum pathway is upregulated to enhance the protein-folding
522
capacity of the ER. Upregulation of the proteasome indicated that unfolded proteins
523
are degraded in a ubiquitin-mediated way. In addition to post-translational regulation,
524
mRNA expression may be downregulated by spliceosome-mediated decay (SMD)
525
given that the spliceosome pathway is upregulated at 20 C. In SMD, splicing mutants
526
are produced by the spliceosome and degraded by mRNA surveillance systems
527
(Volanakis et al. 2013). The negative correlation between protein level change and
528
transcript level change might reflect ubiquitin mediated protein degradation and SMD.
24
529
If a cell cannot rebuild homeostasis, UPR will become cytotoxic and lead to apoptosis
530
(Gardner et al. 2013). AS also plays an important role in the cold adaptation of M.
531
psychrophila. Genes related to unfolded protein binding are especially alternatively
532
spliced and upregulated at 20 C. IR, the most frequent form of alternative splicing, is
533
observed in plants, fungi and mammals (Ner-Gaon et al. 2004; Braunschweig et al.
534
2014; Sebé-Pedrós et al. 2013).AS could enhance proteome diversity, most IR events
535
produce premature termination codon (PTC) transcripts (Kwon et al. 2014), which are
536
turned over by nonsense-mediated decay (NMD) (de Lima Morais and Harrison 2010).
537
Cold-induced AS is also observed in the alga Chlamydomonas reinhardtii (Valledor et
538
al. 2013); thus AS might be an important adaptive mechanism for eukaryotic
539
microorganisms.
540
This study provided a comprehensive analysis of the cold adaptation mechanism
541
in the obligate psychrophilic fungus M. psychrophila using omics approaches. M.
542
psychrophila shares some cold adaptive strategies with other microorganisms,
543
including desaturation of fatty acids, accumulation of the compatible solute glycerol,
544
upregulation of ribosome-associated proteins and energy metabolism. There are
545
special traits of M. psychrophila, which are not observed in other psychrophiles. The
546
codon usage bias of M. psychrophila is very different from other psychrophilic,
547
mesophilic and thermophilic fungi. Thousands of genes are alternatively spliced in M.
548
psychrophila and IR is the most common form. Codon usage bias and AS may
549
contribute to the cold adaptation of M. psychrophila. In addition to adaptation at low
550
temperatures, we also tried to explain the upper temperature limit for growth. Above
25
551
20 C , unfolded proteins accumulate in the ER. The overloaded ER triggers the UPR,
552
which upregulates genes related to protein folding and protein degradation. If the
553
UPR cannot rescue ER homeostasis, apoptosis is induced. Although the results of the
554
cold stress response in model organism are heuristic, cold adaptation in the steady
555
state is different from cold shock, and psychrophiles adopt more flexible strategies to
556
cope with cold. Our results provide a global view of the cold adaptation mechanism of
557
psychrophilic fungi (Figure 8).
558
559
ACKNOWLEDGEMENTS
560
The authors thank Novozymes (China) Investment Co. Ltd for providing the genome
561
sequences, the Beijing Institute of Genomics, Chinese Academyof Sciences, for
562
iTRAQ-based proteomics analysis, and Edanz for language editing.
563
564
565
566
567
568
569
570
571
572
26
573
574
Figure 1 Correspondence analysis of the relative synonymous codon usage from 15 fungal genomes.
575
(A) The distribution of synonymous codons along the first and second axes of the correspondence
576
analysis. Codons ending in A or U are shown in green and codons ending in G or C are shown in red. (B)
577
The distribution of species along the first and second axes of the correspondence analysis.
578
Psychrophiles are shown in blue, mesophiles are shown in green and thermophiles are shown in red.
579
580
581
582
583
584
585
586
587
588
27
589
590
Figure 2 Gene family expansion and contraction in fungal genomes. The gene families that have
591
undergone expansion and contraction are shown in red and green, respectively. The psychrophilic
592
fungi branches are shown in blue; the thermophilic fungi branches are shown in red; the
593
Tremellomycetes branch is shown in purple; and
Chaetomiaceae branch is shown in orange.
594
595
596
597
598
599
600
601
602
603
604
605
28
606
607
Figure 3 (A) Heatmap of differentially expressed genes (DEGs) involved in transcription,
608
post-transcriptional regulation, translation and post-translational regulation. (B) Heatmap of DEGs
609
involved in energy metabolism.
610
611
612
613
614
615
616
617
618
619
29
620
621
Figure 4 Venn diagram showing unique and shared genes that undergo alternative splicing between
622
and among M. psychrophila at 4 C, 12 C and 20 C.
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
30
639
640
Figure 5 Enrichment of GO terms in genes that undergo intron retention at 4 C and 20 C.
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
31
656
657
Figure 6 (A) Gene expressions analyzed by qPCR of selected genes at eight time points after cold shock
658
in M. psychrophila. (B) Gene expressions analyzed by RNA-seq of selected genes at three temperature
659
after cold adaptation in M. psychrophila. The bars represent the standard deviations calculated from
660
three technical replicates of each experiment.
661
662
663
664
665
666
667
668
669
670
671
672
32
673
674
Figure 7 Correlation ρ between protein level change and transcript level change for genes involved in
675
glycerophospholipid metabolism. N: gene number in the pathway.
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
33
692
693
Figure 8 Global view of the adaptation mechanism of M. psychrophila at 4 and 20 C.
694
695
696
697
698
699
700
701
702
703
704
705
706
34
707
708
Table 1 Genomic features of M. psychrophila
Characteristic
M．psychrophila
Total Contigs Length (Mb)
27.8
Number of Contigs
1976
Contig N50 (kb)
33.7
Repeat sequences (%)
5
Percentage of CDS (%)
36.6
GC (%) genome
53.8
GC (%) CDS
56.5
GC3 (%)
63.3
Protein coding gene number
5994
Mean exon number per gene
8
Mean gene length (bp)
1697.6
Mean protein length (amino acid)
564.9
CDS, coding sequence; GC3, GC content at the third codon position.
709
710
711
712
713
714
715
35
Table 2 GO enrichment analysis of DEGs at 4 C in M. psychrophila
GO ID
GO Term
GO
P value
Class
Adjusted
P value
GO:0010467
Gene expression
BP
5.42E-15
3.78E-12
GO:0016491
Oxidoreductase activity
MF
6.71E-14
4.67E-11
GO:0008152
Metabolic process
BP
1.48E-12
1.03E-09
GO:0030529
Ribonucleoprotein complex
CC
6.52E-11
4.53E-08
GO:0055114
Oxidation-reduction process
BP
9.71E-11
6.73E-08
GO:0003735
Structural constituent of
MF
2.90E-10
2.01E-07
ribosome
GO:0005840
Ribosome
CC
2.39E-09
1.65E-06
GO:0006412
Translation
BP
8.86E-06
6.11E-03
GO:0005975
Carbohydrate metabolic
BP
9.39E-06
6.47E-03
MF
2.00E-05
1.37E-02
process
GO:0022857
Transmembrane transporter
activity
GO:0043169
Cation binding
MF
2.80E-05
1.93E-02
GO:0006007
Glucose catabolic process
BP
4.43E-05
3.04E-02
The significance of the enrichment was calculated using Fisher‟s exact test following
a conservative correction for multiple tests (false discovery rate <0.05, Holm‟s
correction). BP, biological process; CC, component; DEGs, differentially expressed
genes; MF, molecular function.
36
Table 3 GO enrichment analysis of DEGs at 20 C in M. psychrophila
GO ID
GO Term
GO
P value
Class
GO:0003735
Structural constituent of
MF
ribosome
GO:0005840
Ribosome
Adjusted
P value
3.88E-1
3.56E-07
0
CC
7.05E-0
6.45E-06
9
GO:0010467
Gene expression
BP
6.43E-0
5.87E-05
8
GO:0016491
Oxidoreductase activity
MF
4.16E-0
3.79E-04
7
GO:0008152
Metabolic process
BP
4.38E-0
3.99E-03
6
GO:0030529
Ribonucleoprotein complex
CC
6.83E-0
6.22E-03
6
The significance of the enrichment was calculated using Fisher‟s exact test following
a conservative correction for multiple tests (false discovery rate <0.05, Holm‟s
correction). BP, biological process; CC, component; DEGs, differentially expressed
genes; MF, molecular function.
37
Table 4 Alternative splicing events at different temperatures
Temperature
Intron
Exon
Alternative
Alternative
(C)
Retention
skipping
5SS
3SS
4
1581
168
733
1150 (31.8%) 3613
(43.8%)
(4.6%)
(20.3%)
1431
180
749
(40.0%)
(5.0%)
(20.9%)
1319
221
703
(38.2%)
(6.4%)
(20.3%)
12
20
Total
1242 (34.7%) 3576
1234 (35.7%) 3455
SS:Splice site.
38
Table 5 Genes that undergo alternative splicing at different temperatures
Temperature
Intron
Exon
(C)
Retention
skipping
5SS
3SS
4
1636 (77.8%)
123
343
534
(5.8%)
(16.3%)
(25.4%)
130
342
579
(6.2%)
(16.3%)
(27.7%)
169
333
576
(8.2%)
(16.2%)
(28.0%)
12
20
1587 (75.9%)
1538 (74.8%)
Alternative
Alternative
Total
2104
2092
2056
SS:Splice site.
39
LITERATURE CITED
Aguilar, P.S., J.E. Cronan, and D. de Mendoza, 1998 A Bacillus subtilis Gene
Induced by Cold Shock Encodes a Membrane Phospholipid Desaturase. J
Bacteriol. 180 (8):2194-2200.
Al-Fageeh Mb Fau - Smales, C.M., and C.M. Smales, 2006 Control and regulation of
the cellular responses to cold shock: the responses in. Biochem J. 397
(2):247-259.
Arthur, H., and K. Watson, 1976 Thermal adaptation in yeast: growth temperatures,
membrane lipid, and cytochrome composition of psychrophilic, mesophilic,
and thermophilic yeasts. J Bacteriol. 128 (1):56-68.
Birney, E., M. Clamp, and R. Durbin, 2004 GeneWise and Genomewise. Genome Res
14 (5):988-995.
Blanco, E., G. Parra, and R. Guigó, 2002 Using geneid to Identify Genes in Current
Protocols in Bioinformatics, edited by Baxevanis A.D. John Wiley & Sons,
Inc.
Borges, N., A. Ramos, N. Raven, R. Sharp, and H. Santos, 2002 Comparative study of
the thermostabilizing properties of mannosylglycerate and other compatible
solutes on model enzymes. Extremophiles 6 (3):209-216.
Braunschweig, U., N.L. Barbosa-Morais, Q. Pan, E.N. Nachman, B. Alipanahi et al.,
2014
Widespread
intron
retention
in
mammals
functionally
tunes
transcriptomes. Genome Res. 24 (11):1774-1786.
Butler, G., M.D. Rasmussen, M.F. Lin, M.A.S. Santos, S. Sakthikumar et al., 2009
40
Evolution of pathogenicity and sexual reproduction in eight Candida genomes.
Nature 459 (7247):657-662.
Casanueva, A., M. Tuffin, C. Cary, and D.A. Cowan, 2010 Molecular adaptations to
psychrophily: the impact of „omic‟ technologies. Trends Microbiol .18
(8):374-381.
Chattopadhyay, M.K., 2006 Mechanism of bacterial adaptation to low temperature. J
Biosciences. 31 (1):157-165.
Conesa, A., S. Götz, J.M. García-Gómez, J. Terol, M. Talón et al., 2005 Blast2GO: a
universal tool for annotation, visualization and analysis in functional genomics
research. Bioinformatics 21 (18):3674-3676.
Consortium:, T.I., R. Apweiler, T.K. Attwood, A. Bairoch, A. Bateman et al., 2000
InterPro-an integrated documentation resource for protein families, domains
and functional sites. Bioinformatics 16 (12):1145-1150.
De Bie, T., N. Cristianini, J.P. Demuth, and M.W. Hahn, 2006 CAFE: a
computational tool for the study of gene family evolution. Bioinformatics 22
(10):1269-1271.
de Lima Morais, D.A., and P.M. Harrison, 2010 Large-Scale Evidence for
Conservation of NMD Candidature Across Mammals. PLoS ONE 5
(7):e11695.
Frank, S., F. Schmidt, J. Klockgether, C.F. Davenport, M. Gesell Salazar et al., 2011
Functional genomics of the initial phase of cold adaptation of Pseudomonas
putida KT2440. FEMS Microbiol Lett. 318 (1):47-54.
41
Gardner, B.M., D. Pincus, K. Gotthardt, C.M. Gallagher, and P. Walter, 2013
Endoplasmic Reticulum Stress Sensing in the Unfolded Protein Response.
CSH Perspect Biol. 5 (3).
Gaur, M., N. Puri, R. Manoharlal, V. Rai, G. Mukhopadhayay et al., 2008 MFS
transportome of the human pathogenic yeast Candida albicans. BMC
Genomics 9 (1):579.
Gocheva, Y., S. Tosi, E. Krumova, L. Slokoska, J. Miteva et al., 2009 Temperature
downshift induces antioxidant response in fungi isolated from Antarctica.
Extremophiles 13 (2):273-281.
Goldstein, J., N.S. Pollitt, and M. Inouye, 1990 Major cold shock protein of
Escherichia coli. Proc.Natl. Acad. Sci. USA 87 (1):283-287.
Haas, B., S. Salzberg, W. Zhu, M. Pertea, J. Allen et al., 2008 Automated eukaryotic
gene structure annotation using EVidenceModeler and the Program to
Assemble Spliced Alignments. Genome Biol. 9 (1):R7.
Hershberg, R., and D.A. Petrov, 2009 General Rules for Optimal Codon Choice.
PLoS Genet. 5 (7):e1000556.
Higgs, P.G., and W. Ran, 2008 Coevolution of Codon Usage and tRNA Genes Leads
to Alternative Stable States of Biased Codon Usage. Mol. Biol. Evol. 25
(11):2279-2291.
Hou, J., H. Tang, Z. Liu, T. Osterlund, J. Nielsen et al., 2014 Management of the
endoplasmic reticulum stress by activation of the heat shock response in yeast.
FEMS Yeast Res. 14 (3):481-494.
42
Jones, P.G., R.A. VanBogelen, and F.C. Neidhardt, 1987 Induction of proteins in
response to low temperature in Escherichia coli. J Bacteriol. 169
(5):2092-2095.
Kandror, O., N. Bretschneider, E. Kreydin, D. Cavalieri, and A.L. Goldberg, 2004
Yeast Adapt to Near-Freezing Temperatures by STRE/Msn2,4-Dependent
Induction of Trehalose Synthesis and Certain Molecular Chaperones. Mol Cell.
13 (6):771-781.
Kim, D., G. Pertea, C. Trapnell, H. Pimentel, R. Kelley et al., 2013 TopHat2: accurate
alignment of transcriptomes in the presence of insertions, deletions and gene
fusions. Genome Biol. 14 (4):R36.
Korf, I., 2004 Gene finding in novel genomes. BMC Bioinformatics 5 (1):59.
Kwon, Y.-J., M.-J. Park, S.-G. Kim, I. Baldwin, and C.-M. Park, 2014 Alternative
splicing and nonsense-mediated decay of circadian clock genes under
environmental stress conditions in Arabidopsis. BMC Plant Biol. 14 (1):136.
Lücking, R., S. Huhndorf, D.H. Pfister, E.R. Plata, and H.T. Lumbsch, 2009 Fungi
evolved right on track. Mycologia 101 (6):810-822.
Labunskyy, V.M., M.V. Gerashchenko, J.R. Delaney, A. Kaya, B.K. Kennedy et al.,
2014 Lifespan Extension Conferred by Endoplasmic Reticulum Secretory
Pathway Deficiency Requires Induction of the Unfolded Protein Response.
PLoS Genet. 10 (1):e1004019.
Langin, T., P. Capy, and M.-J. Daboussi, 1995 The transposable element impala, a
fungal member of the Tc1-mariner superfamily. Mol Gen Genet. 246
43
(1):19-28.
Li, L., C.J. Stoeckert, and D.S. Roos, 2003 OrthoMCL: Identification of Ortholog
Groups for Eukaryotic Genomes. Genome Res. 13 (9):2178-2189.
Linde, J., S. Duggan, M. Weber, F. Horn, P. Sieber et al., 2015 Defining the
transcriptomic landscape of Candida glabrata by RNA-Seq. Nucleic Acids Res.
43 (3):1392-1406.
Lowe, T.M., and S.R. Eddy, 1997 tRNAscan-SE: A Program for Improved Detection
of Transfer RNA Genes in Genomic Sequence. Nucleic Acids Res. 25
(5):0955-0964.
Lynn, D.J., G.A.C. Singer, and D.A. Hickey, 2002 Synonymous codon usage is
subject to selection in thermophilic bacteria. Nucleic Acids Res. 30
(19):4272-4277.
Minneci, F., D. Piovesan, D. Cozzetto, and D.T. Jones, 2013 FFPred 2.0: Improved
Homology-Independent Prediction of Gene Ontology Terms for Eukaryotic
Protein Sequences. PLoS ONE 8 (5):e63754.
Morita, R.Y., 1975 Psychrophilic bacteria. Bacteriological Reviews 39 (2):144-167.
Moriya, Y., M. Itoh, S. Okuda, A.C. Yoshizawa, and M. Kanehisa, 2007 KAAS: an
automatic genome annotation and pathway reconstruction server. Nucleic
Acids Res. 35 (suppl 2):W182-W185.
Ner-Gaon, H., R. Halachmi, S. Savaldi-Goldstein, E. Rubin, R. Ophir et al., 2004
Intron retention is a major phenomenon in alternative splicing in Arabidopsis.
Plant J. 39 (6):877-885.
44
Novembre, J.A., 2002 Accounting for Background Nucleotide Composition When
Measuring Codon Usage Bias. Mol. Biol. Evol. 19 (8):1390-1394.
Panikov, N.S., and M.V. Sizova, 2007 Growth kinetics of microorganisms isolated
from Alaskan soil and permafrost in solid media frozen down to −35°C. FEMS
Microbiol Ecol. 59 (2):500-512.
Peng, Y., H.M. Leung, S.M. Yiu, and F.L. Chin, 2010 IDBA – A Practical Iterative de
Bruijn Graph De Novo Assembler, pp. 426-440 in Research in Computational
Molecular Biology, edited by B. Berger. Springer Berlin Heidelberg.
Perlin, M.H., J. Andrews, and S. San Toh, 2014 Chapter Four - Essential Letters in
the Fungal Alphabet: ABC and MFS Transporters and Their Roles in Survival
and Pathogenicity, pp. 201-253 in Advances in Genetics, edited by J.C.D.
Theodore Friedmann and F.G. Stephen. Academic Press.
Rogers, M., J. Thomas, A. Reddy, and A. Ben-Hur, 2012 SpliceGrapher: detecting
patterns of alternative splicing from RNA-Seq data in the context of gene
models and EST data. Genome Biol. 13 (1):R4.
Sá-Correia, I., S.C. dos Santos, M.C. Teixeira, T.R. Cabrito, and N.P. Mira, 2009
Drug:H+ antiporters in chemical stress response in yeast. Trends Microbiol.
17 (1):22-31.
Sahara, T., T. Goda, and S. Ohgiya, 2002 Comprehensive Expression Analysis of
Time-dependent Genetic Responses in Yeast Cells to Low Temperature. J.
Biol. Chem. 277 (51):50015-50021.
Sanderson, M.J., 2003 r8s: inferring absolute rates of molecular evolution and
45
divergence times in the absence of a molecular clock. Bioinformatics 19
(2):301-302.
Sebé-Pedrós, A., M. Irimia, J. del Campo, H. Parra-Acero, C. Russ et al., 2013
Regulated aggregative multicellularity in a close unicellular relative of
metazoa. Elife 2.
Shah, P., and M.A. Gilchrist, 2010 Effect of Correlated tRNA Abundances on
Translation Errors and Evolution of Codon Usage Bias. PLoS Genet. 6
(9):e1001128.
Solovyev, V., P. Kosarev, I. Seledsov, and D. Vorobyev, 2006 Automatic annotation
of eukaryotic genes, pseudogenes and promoters. Genome Biol. 7 (Suppl
1):S10.
Stamatakis, A., 2006 RAxML-VI-HPC: maximum likelihood-based phylogenetic
analyses with thousands of taxa and mixed models. Bioinformatics 22
(21):2688-2690.
Tai, S.L., P. Daran-Lapujade, M.C. Walsh, J.T. Pronk, and J.-M. Daran, 2007
Acclimation of Saccharomyces cerevisiae to Low Temperature:
A
Chemostat-based Transcriptome Analysis. Mol. Biol. Cell 18 (12):5100-5112.
Ter-Hovhannisyan, V., A. Lomsadze, Y.O. Chernoff, and M. Borodovsky, 2008 Gene
prediction in novel fungal genomes using an ab initio algorithm with
unsupervised training. Genome Res. 18 (12):1979-1990.
Thomas-Hall, S., and K. Watson, 2002 Cryptococcus nyarrowii sp. nov., a
basidiomycetous yeast from Antarctica. Int. J. Syst. Evol. Micr. 52
46
(3):1033-1038.
Trapnell, C., B.A. Williams, G. Pertea, A. Mortazavi, G. Kwan et al., 2010 Transcript
assembly and quantification by RNA-Seq reveals unannotated transcripts and
isoform switching during cell differentiation. Nat. Biotech. 28 (5):511-515.
Trotta, E., 2013 Selection on codon bias in yeast: a transcriptional hypothesis. Nucleic
Acids Res. 41 (20):9382-9395.
Turchetti, B., M. Goretti, E. Branda, G. Diolaiuti, C. D'Agata et al., 2013 Influence of
abiotic variables on culturable yeast diversity in two distinct Alpine glaciers.
FEMS Microbiol. Ecol. 86 (2):327-340.
Valledor, L., T. Furuhashi, A.-M. Hanak, and W. Weckwerth, 2013 Systemic cold
stress adaptation of Chlamydomonas reinhardtii. Mol. Cell. Proteomics.
VanBogelen, R.A., and F.C. Neidhardt, 1990 Ribosomes as sensors of heat and cold
shock in Escherichia coli. Proc.Natl. Acad. Sci. USA 87 (15):5589-5593.
Vogel, C., R. de Sousa Abreu, D. Ko, S.-Y. Le, B.A. Shapiro et al., 2010 Sequence
signatures and mRNA concentration can explain two-thirds of protein
abundance variation in a human cell line. Mol Syst Biol 6 (1):400.
Volanakis, A., M. Passoni, R.D. Hector, S. Shah, C. Kilchert et al., 2013
Spliceosome-mediated decay (SMD) regulates expression of nonintronic
genes in budding yeast. Gene. Dev. 27 (18):2025-2038.
Wang, L., Z. Feng, X. Wang, X. Wang, and X. Zhang, 2010 DEGseq: an R package
for identifying differentially expressed genes
from
RNA-seq data.
Bioinformatics 26 (1):136-138.
47
Willimsky, G., H. Bang, G. Fischer, and M.A. Marahiel, 1992 Characterization of
cspB, a Bacillus subtilis inducible cold shock gene affecting cell viability at
low temperatures. J. Bacteriol. 174 (20):6326-6335.
Wissler, L., J. Gadau, D.F. Simola, M. Helmkampf, and E. Bornberg-Bauer, 2013
Mechanisms and Dynamics of Orphan Gene Emergence in Insect Genomes.
Genome Biol. Evol. 5 (2):439-455.
Xiao, H., Z. YongJie, X. GuoHua, Z. Peng, X. YongLiang et al., 2013 Genome
survey uncovers the secrets of sex and lifestyle in caterpillar fungus. Chinese
Science Bulletin (23):2846-2854.
Xin, M.X., and P.J. Zhou, 2007 Mrakia psychrophila sp. nov., a new species isolated
from Antarctic soil. J. Zhejiang Univ. Sci. B 8 (4):260-265.
Xu, X., J. Chen, H. Xu, and D. Li, 2014 Role of a major facilitator superfamily
transporter in adaptation capacity of Penicillium funiculosum under extreme
acidic stress. Fungal Genet. Biol. 69 (0):75-83.
Zhang, G., C. Cowled, Z. Shi, Z. Huang, K.A. Bishop-Lilly et al., 2013 Comparative
Analysis of Bat Genomes Provides Insight into the Evolution of Flight and
Immunity. Science 339 (6118):456-460.
Zhang, L., K. Onda, R. Imai, R. Fukuda, H. Horiuchi et al., 2003 Growth temperature
downshift induces antioxidant response in Saccharomyces cerevisiae. Biochem.
Bioph. Res. Co. 307 (2):308-314.
Zhou, J., L. Liu, and J. Chen, 2011 Improved ATP supply enhances acid tolerance of
Candida glabrata during pyruvic acid production. J. Appl. Microbiol. 110
48
(1):44-53.
Zhou, X.-L., Z.-P. Fang, Z.-R. Ruan, M. Wang, R.-J. Liu et al., 2013 Aminoacylation
and translational quality control strategy employed by leucyl-tRNA synthetase
from a human pathogen with genetic code ambiguity. Nucleic Acids Res. 41
(21):9825-9838.
49