De novo characterization of the Chinese fir (Cunninghamia lanceolata) transcriptome and analysis of candidate genes involved in cellulose and lignin biosynthesis.

BACKGROUND: Chinese fir (Cunninghamia lanceolata) is an important timber species that accounts for 20-30% of the total commercial timber production in China. However, the available genomic information of Chinese fir is limited, and this severely encumbers functional genomic analysis and molecular breeding in Chinese fir. Recently, major advances in transcriptome sequencing have provided fast and cost-effective approaches to generate large expression datasets that have proven to be powerful tools to profile the transcriptomes of non-model organisms with undetermined genomes. RESULTS: In this study, the transcriptomes of nine tissues from Chinese fir were analyzed using the Illumina HiSeq™ 2000 sequencing platform. Approximately 40 million paired-end reads were obtained, generating 3.62 gigabase pairs of sequencing data. These reads were assembled into 83,248 unique sequences (i.e. Unigenes) with an average length of 449 bp, amounting to 37.40 Mb. A total of 73,779 Unigenes were supported by more than 5 reads, 42,663 (57.83%) had homologs in the NCBI non-redundant and Swiss-Prot protein databases, corresponding to 27,224 unique protein entries. Of these Unigenes, 16,750 were assigned to Gene Ontology classes, and 14,877 were clustered into orthologous groups. A total of 21,689 (29.40%) were mapped to 119 pathways by BLAST comparison against the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The majority of the genes encoding the enzymes in the biosynthetic pathways of cellulose and lignin were identified in the Unigene dataset by targeted searches of their annotations. And a number of candidate Chinese fir genes in the two metabolic pathways were discovered firstly. Eighteen genes related to cellulose and lignin biosynthesis were cloned for experimental validating of transcriptome data. Overall 49 Unigenes, covering different regions of these selected genes, were found by alignment. Their expression patterns in different tissues were analyzed by qRT-PCR to explore their putative functions. CONCLUSIONS: A substantial fraction of transcript sequences was obtained from the deep sequencing of Chinese fir. The assembled Unigene dataset was used to discover candidate genes of cellulose and lignin biosynthesis. This transcriptome dataset will provide a comprehensive sequence resource for molecular genetics research of C. lanceolata.

[Studies on furmaric acid and isofraxidin content in Sarcandra glabra of different provenances].

OBJECTIVE: To study the content variation of furmarid acid and isofraxidin in Sarcandra glabra from 21 different provenances and provide the basis for resource utilization and quality optimization of S. glabra. METHOD: HPLC method was developed to determine the contents of furmarid acid and isofraxidin in 330 samples of S. glabra which were collected respectively from 21 different provenances. RESULT: There were significant differences in the contents of isofraxidin and furmarid acid in S. glabra from different provenances. The contents of isofraxidin and furmarid acid dropped off from low altitude to high altitude, which were also close with longitude and latitude. The content of isofraxidin in S. glabra at central area of natural distribution was the highest. The different parts of the plant had different results, the influence on the contents of the acitive components in stem were more obvious than the leaf. CONCLUSION: This simple, accurate and reproducible method could be use to determine the contents of furmarid acid and isofraxidin in S. glabra. The results represented the status of medicines quality and difference of Chinese S. glabra. These agreed with the traditional views that the medicines quality of Sarcandra glabra in Jiangxi, Fujian, Zhejiang was better. These provenances were considered as important areas of medicines breeding and bases building on S. glabra in future.

Molecular Characterization of SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) Gene Family in Betula luminifera.

As a major family of plant-specific transcription factors, SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) genes play vital regulatory roles in plant growth, development and stress responses. In this study, 18 SPL genes were identified and cloned from Betula luminifera. Two zinc finger-like structures and a nuclear location signal (NLS) segments were existed in the SBP domains of all BlSPLs. Phylogenetic analysis showed that these genes were clustered into nine groups (group I-IX). The intron/exon structure and motif composition were highly conserved within the same group. 12 of the 18 BlSPLs were experimentally verified as the targets of miR156, and two cleavage sites were detected in these miR156-targeted BlSPL genes. Many putative cis-elements, associated with light, stresses and phytohormones response, were identified in the promoter regions of BlSPLs, suggesting that BlSPL genes are probably involved in important physiological processes and developmental events. Tissue-specific expression analysis showed that miR156-targeted BlSPLs exhibited a more differential expression pattern, while most miR156-nontargeted BlSPLs tended to be constitutively expressed, suggesting the distinct roles of miR156-targeted and nontargeted BlSPLs in development and growth of B. luminifera. Further expression analysis revealed that miR156-targeted BlSPLs were dramatically up-regulated with age, whereas mature BlmiR156 level was apparently declined with age, indicating that miR156/SPL module plays important roles in vegetative phase change of B. luminifera. Moreover, yeast two-hybrid assay indicated that several miR156-targeted and nontargeted BlSPLs could interact with two DELLA proteins (BlRGA and BlRGL), which suggests that certain BlSPLs take part in the GA regulated processes through protein interaction with DELLA proteins. All these results provide an important basis for further exploring the biological functions of BlSPLs in B. luminifera.

Application of near-infrared spectroscopy to predict sweetpotato starch thermal properties and noodle quality.

Sweetpotato starch thermal properties and its noodle quality were analyzed using a rapid predictive method based on near-infrared spectroscopy (NIRS). This method was established based on a total of 93 sweetpotato genotypes with diverse genetic background. Starch samples were scanned by NIRS and analyzed for quality properties by reference methods. Results of statistical modelling indicated that NIRS was reasonably accurate in predicting gelatinization onset temperature (T(o)) (standard error of prediction SEP=2.014 degrees C, coefficient of determination RSQ=0.85), gelatinization peak temperature (T(p)) (SEP=1.371 degrees C, RSQ=0.89), gelatinization temperature range (T(r)) (SEP=2.234 degrees C, RSQ=0.86), and cooling resistance (CR) (SEP=0.528, RSQ=0.89). Gelatinization completion temperature (T(c)), enthalpy of gelatinization (DeltaH), cooling loss (CL) and swelling degree (SWD), were modelled less well with RSQ between 0.63 and 0.84. The present results suggested that the NIRS based method was sufficiently accurate and practical for routine analysis of sweetpotato starch and its noodle quality.