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author:("Dong, hubei")
1.  The aging biological clock in Neurospora crassa 
Ecology and Evolution  2014;4(17):3494-3507.
The biological clock affects aging through ras-1 (bd) and lag-1, and these two longevity genes together affect a clock phenotype and the clock oscillator in Neurospora crassa. Using an automated cell-counting technique for measuring conidial longevity, we show that the clock-associated genes lag-1 and ras-1 (bd) are true chronological longevity genes. For example, wild type (WT) has an estimated median life span of 24 days, while the double mutant lag-1, ras-1 (bd) has an estimated median life span of 120 days for macroconidia. We establish the biochemical function of lag-1 by complementing LAG1 and LAC1 in Saccharomyces cerevisiae with lag-1 in N. crassa. Longevity genes can affect the clock as well in that, the double mutant lag-1, ras-1 (bd) can stop the circadian rhythm in asexual reproduction (i.e., banding in race tubes) and lengthen the period of the frequency oscillator to 41 h. In contrast to the ras-1 (bd), lag-1 effects on chronological longevity, we find that this double mutant undergoes replicative senescence (i.e., the loss of replication function with time), unlike WT or the single mutants, lag-1 and ras-1 (bd). These results support the hypothesis that sphingolipid metabolism links aging and the biological clock through a common stress response
PMCID: PMC4228622  PMID: 25535564
Aging; bd; biological clock; lag-1; Neurospora crassa; ras-1
2.  Removing PCR for the elimination of undesired DNA fragments cycle by cycle 
Scientific Reports  2013;3:2303.
A novel removing polymerase chain reaction (R-PCR) technique was developed, which can eliminate undesired genes, cycle by cycle, with efficiencies of 60.9% (cDNAs), 73.6% (genomic DNAs), and ~ 100% (four DNA fragments were tested). Major components of the R-PCR include drivers, a thermostable restriction enzyme - ApeKI, and a poly(dA) adapter with mismatched restriction enzyme recognition sites. Drivers were generated from the undesired genes. In each cycle of R-PCR, drivers anneal to complementary sequences and allow extension by Taq DNA polymerase. Thus, ApeKI restriction sites in the undesired genes are recovered, and adapters of these undesired DNA fragments are removed. Using R-PCR, we isolated maize upregulated defense-responsive genes and Blumeria graminis specialized genes, including key pathogenesis-related effectors. Our results show that after the R-PCR reaction, most undesired genes, including very abundant genes, became undetectable. The R-PCR is an easy and cost-efficient method to eliminate undesired genes and clone desired genes.
PMCID: PMC3725479  PMID: 23892515
3.  Complete genome sequence of a putative novel victorivirus from Ustilaginoidea virens 
Archives of Virology  2013;158(6):1403-1406.
Ustilaginoidea virens is the causal agent of a serious disease of rice. Here, we report the presence of five dsRNA bands ranging from about 1.2, 1.5, 1.7, and 1.8 to 5.6 kb in an isolate of this fungus from China and the complete sequence of the largest dsRNA segment, putatively representing the genome of a novel virus, designated as Ustilaginoidea virens RNA virus 1 (UvRV1), UvRV1, which has a genome length of 5567 bp and has two consecutive open reading frames (ORFs) with a five-nucleotide overlap. Phylogenetic analysis showed that UvRV1 belongs to the genus of Victorivirus in the family Totiviridae.
Electronic supplementary material
The online version of this article (doi:10.1007/s00705-013-1615-9) contains supplementary material, which is available to authorized users.
PMCID: PMC3668124  PMID: 23385326
4.  Systems Biology of the qa Gene Cluster in Neurospora crassa 
PLoS ONE  2011;6(6):e20671.
An ensemble of genetic networks that describe how the model fungal system, Neurospora crassa, utilizes quinic acid (QA) as a sole carbon source has been identified previously. A genetic network for QA metabolism involves the genes, qa-1F and qa-1S, that encode a transcriptional activator and repressor, respectively and structural genes, qa-2, qa-3, qa-4, qa-x, and qa-y. By a series of 4 separate and independent, model-guided, microarray experiments a total of 50 genes are identified as QA-responsive and hypothesized to be under QA-1F control and/or the control of a second QA-responsive transcription factor (NCU03643) both in the fungal binuclear Zn(II)2Cys6 cluster family. QA-1F regulation is not sufficient to explain the quantitative variation in expression profiles of the 50 QA-responsive genes. QA-responsive genes include genes with products in 8 mutually connected metabolic pathways with 7 of them one step removed from the tricarboxylic (TCA) Cycle and with 7 of them one step removed from glycolysis: (1) starch and sucrose metabolism; (2) glycolysis/glucanogenesis; (3) TCA Cycle; (4) butanoate metabolism; (5) pyruvate metabolism; (6) aromatic amino acid and QA metabolism; (7) valine, leucine, and isoleucine degradation; and (8) transport of sugars and amino acids. Gene products both in aromatic amino acid and QA metabolism and transport show an immediate response to shift to QA, while genes with products in the remaining 7 metabolic modules generally show a delayed response to shift to QA. The additional QA-responsive cutinase transcription factor-1β (NCU03643) is found to have a delayed response to shift to QA. The series of microarray experiments are used to expand the previously identified genetic network describing the qa gene cluster to include all 50 QA-responsive genes including the second transcription factor (NCU03643). These studies illustrate new methodologies from systems biology to guide model-driven discoveries about a core metabolic network involving carbon and amino acid metabolism in N. crassa.
PMCID: PMC3114802  PMID: 21695121
5.  Systems Biology of the Clock in Neurospora crassa 
PLoS ONE  2008;3(8):e3105.
A model-driven discovery process, Computing Life, is used to identify an ensemble of genetic networks that describe the biological clock. A clock mechanism involving the genes white-collar-1 and white-collar-2 (wc-1 and wc-2) that encode a transcriptional activator (as well as a blue-light receptor) and an oscillator frequency (frq) that encodes a cyclin that deactivates the activator is used to guide this discovery process through three cycles of microarray experiments. Central to this discovery process is a new methodology for the rational design of a Maximally Informative Next Experiment (MINE), based on the genetic network ensemble. In each experimentation cycle, the MINE approach is used to select the most informative new experiment in order to mine for clock-controlled genes, the outputs of the clock. As much as 25% of the N. crassa transcriptome appears to be under clock-control. Clock outputs include genes with products in DNA metabolism, ribosome biogenesis in RNA metabolism, cell cycle, protein metabolism, transport, carbon metabolism, isoprenoid (including carotenoid) biosynthesis, development, and varied signaling processes. Genes under the transcription factor complex WCC ( = WC-1/WC-2) control were resolved into four classes, circadian only (612 genes), light-responsive only (396), both circadian and light-responsive (328), and neither circadian nor light-responsive (987). In each of three cycles of microarray experiments data support that wc-1 and wc-2 are auto-regulated by WCC. Among 11,000 N. crassa genes a total of 295 genes, including a large fraction of phosphatases/kinases, appear to be under the immediate control of the FRQ oscillator as validated by 4 independent microarray experiments. Ribosomal RNA processing and assembly rather than its transcription appears to be under clock control, suggesting a new mechanism for the post-transcriptional control of clock-controlled genes.
PMCID: PMC2518617  PMID: 18769678
6.  Genome-wide expression analysis of genetic networks in Neurospora crassa 
Bioinformation  2007;1(10):390-395.
The products of five structural genes and two regulatory genes of the qa gene cluster of Neurospora crassa control the metabolism of quinic acid (QA) as a carbon source. A detailed genetic network model of this metabolic process has been reported. This investigation is designed to expand the current model of the QA reaction network. The ensemble method of network identification was used to model RNA profiling data on the qa gene cluster. Through microarray and cluster analysis, genome-wide identification of RNA transcripts associated with quinic acid metabolism in N. crassa is described and suggests a connection to other metabolic circuits. More than 100 genes whose products include carbon metabolism, protein degradation and modification, amino acid metabolism and ribosome synthesis appear to be connected to quinic acid metabolism. The core of the qa gene cluster network is validated with respect to RNA profiling data obtained from microarrays.
PMCID: PMC1896053  PMID: 17597928
genetic networks; quinic acid; qa gene cluster; genome; microarray

Results 1-6 (6)