Transcriptome characterization and sequencing-based identification of salt-responsive genes in Millettia pinnata, a semi-mangrove plant

Abstract

Semi-mangroves form a group of transitional species between glycophytes and halophytes, and hold unique potential for learning molecular mechanisms underlying plant salt tolerance. Millettia pinnata is a semi-mangrove plant that can survive a wide range of saline conditions in the absence of specialized morphological and physiological traits. By employing the Illumina sequencing platform, we generated ~192 million short reads from four cDNA libraries of M. pinnata and processed them into 108,598 unisequences with a high depth of coverage. The mean length and total length of these unisequences were 606 bp and 65.8 Mb, respectively. A total of 54,596 (50.3%) unisequences were assigned Nr annotations. Functional classification revealed the involvement of unisequences in various biological processes related to metabolism and environmental adaptation. We identified 23,815 candidate salt-responsive genes with significantly differential expression under seawater and freshwater treatments. Based on the reverse transcription-polymerase chain reaction (RT-PCR) and real-time PCR analyses, we verified the changes in expression levels for a number of candidate genes. The functional enrichment analyses for the candidate genes showed tissue-specific patterns of transcriptome remodelling upon salt stress in the roots and the leaves. The transcriptome of M. pinnata will provide valuable gene resources for future application in crop improvement. In addition, this study sets a good example for large-scale identification of salt-responsive genes in non-model organisms using the sequencing-based approach.

Figure 1.

Flowcharts of the transcriptome analyses for M. pinnata. The steps include sequence assembly and clustering, Nr annotation, GO annotation, KEGG analysis, and identification of DEGs as candidate salt-responsive genes.

Figure 2.

Length distribution of the all-unigenes with Nr annotations. In this study, only 33% of the all-unigenes shorter than 500 bp had BLAST hits in the Nr database, whereas more than 80% of the all-unigenes over 500 bp did.

Figure 3.

GO classification of M. pinnata transcriptome. The results are summarized in three main categories as follows: biological process, cellular component, and molecular function. In total, 11 974 all-unigenes have been assigned GO terms. In some cases, one all-unigene has multiple terms.

Figure 4.

Number of all-unigenes in each clade of the KEGG pathway maps. The all-unigenes were assigned 124 KEGG pathways within 20 clades under five major categories: Metabolism (I), Genetic information processing (II), Environmental information processing (III), Cellular processes (IV), and Organismal systems (V). In each category, the clades are listed according to their abundancies of all-unigenes.

Figure 5.

Number of DEGs in the root and the leaf of M. pinnata. The numbers of DEGs that were exclusively up- or down-regulated in one tissue are shown in each circle. The numbers of DEGs with a common or opposite tendency of expression changes between the two tissues are shown in the overlapping regions. The total numbers of up- or down-regulated genes in each tissue are shown outside the circles.

Figure 6.

Relative expression levels of 20 DEGs at a series of time points following the seawater treatments. The relative gene expression levels as expressed by 2^−ΔΔCT were determined separately for each tissue and were presented as the mean ± SD. Significant differences (P < 0.01, LSD-t test) between the expression levels at 1, 2, 4, and 8 h time points and those at 0 h are indicated by asterisks.