Xiao-Ming Song

Prof. Dr. Xiao-Ming Song


Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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23 August 2013 in BMC Genomics
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Journal Article
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XSXiao-Ming Song
Xiao-Ming Song
YLYing Li
Ying Li
Xilin HouXilin Hou
Xilin Hou
Background: Chinese cabbage (Brassica rapassp.pekinensis) is a member of one of the most important leaf vegetables grown worldwide, which has experienced thousands of years in cultivation and artificial selection. The entire Chinese cabbage genome sequence, and more than forty thousand proteins have been obtained to date. The genome has undergone triplication events since its divergence fromArabidopsis thaliana(13 to 17 Mya), however a high degree of sequence similarity and conserved genome structure remain between the two species.Arabidopsisis therefore a viable reference species for comparative genomics studies. Variation in the number of members in gene families due to genome triplication may contribute to the broad range of phenotypic plasticity, and increased tolerance to environmental extremes observed inBrassicaspecies. Transcription factors are important regulators involved in plant developmental and physiological processes. The AP2/ERF proteins, one of the most important families of transcriptional regulators, play a crucial role in plant growth, and in response to biotic and abiotic stressors. Our analysis will provide resources for understanding the tolerance mechanisms inBrassica rapassp.pekinensis.Results: In the present study, 291 putative AP2/ERF transcription factor proteins were identified from the Chinese cabbage genome database, and compared with proteins from 15 additional species. The Chinese cabbage AP2/ERF superfamily was classified into four families, including AP2, ERF, RAV, and Soloist. The ERF family was further divided into DREB and ERF subfamilies. The AP2/ERF superfamily was subsequently divided into 15 groups. The identification, classification, phylogenetic reconstruction, conserved motifs, chromosome distribution, functional annotation, expression patterns, and interaction networks of the AP2/ERF transcription factor superfamily were predicted and analyzed. Distribution mapping results showed AP2/ERF superfamily genes were localized on the 10 Chinese cabbage chromosomes. AP2/ERF transcription factor expression levels exhibited differences among six tissue types based on expressed sequence tags (ESTs). In the AP2/ERF superfamily, 214 orthologous genes were identified between Chinese cabbage andArabidopsis. Orthologous gene interaction networks were constructed, and included seven CBF and four AP2 genes, primarily involved in cold regulatory pathways and ovule development, respectively.Conclusions: The evolution of the AP2/ERF transcription factor superfamily in Chinese cabbage resulted from genome triplication and tandem duplications. A comprehensive analysis of the physiological functions and biological roles of AP2/ERF superfamily genes in Chinese cabbage is required to fully elucidate AP2/ERF, which provides us with rich resources and opportunities to understand crop stress tolerance mechanisms.

20 April 2015 in BMC Genomics
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Journal Article
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XSXiao-Ming Song
Xiao-Ming Song
TGTingting Ge
Tingting Ge
YLYing Li
Ying Li
Xilin HouXilin Hou
Xilin Hou
Non-heading Chinese cabbage (NHCC), belonging to Brassica, is an important leaf vegetable in Asia. Although genetic analyses have been performed through conventional selection and breeding efforts, the domestication history of NHCC and the genetics underlying its morphological diversity remain unclear. Thus, the reliable molecular markers representative of the whole genome are required for molecular-assisted selection in NHCC. A total of 20,836 simple sequence repeats (SSRs) were detected in NHCC, containing repeat types from mononucleotide to nonanucleotide. The average density was 62.93 SSRs/Mb. In gene regions, 5,435 SSRs were identified in 4,569 genes. A total of 5,008 primer pairs were designed, and 74 were randomly selected for validation. Among these, 60 (81.08%) were polymorphic in 18 Cruciferae. The number of polymorphic bands ranged from two to five, with an average of 2.70 for each primer. The average values of the polymorphism information content, observed heterozygosity, Hardy-Weinberg equilibrium, and Shannon’s information index were 0.2970, 0.4136, 0.5706, and 0.5885, respectively. Four clusters were classified according to the unweighted pair-group method with arithmetic average cluster analysis of 18 genotypes. In addition, a total of 1,228,979 single nucleotide polymorphisms (SNPs) were identified in the NHCC through a comparison with the genome of Chinese cabbage, and the average SNP density in the whole genome was 4.33/Kb. The number of SNPs ranged from 341,939 to 591,586 in the 10 accessions, and the average heterozygous SNPs ratio was ~42.53%. All analyses showed these markers were high quality and reliable. Therefore, they could be used in the construction of a linkage map and for genetic diversity studies for NHCC in future. This is the first systematic and comprehensive analysis and identification of SSRs in NHCC and 17 species. The development of a large number of SNP and SSR markers was successfully achieved for NHCC. These novel markers are valuable for constructing genetic linkage maps, comparative genome analysis, quantitative trait locus (QTL) mapping, genome-wide association studies, and marker-assisted selection in NHCC breeding system research.

1 April 2020 in Horticulture Research
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Journal Article
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XSXiao-Ming Song
Xiao-Ming Song
FNFulei Nie
Fulei Nie
WCWei Chen
Wei Chen
XMXiao Ma
Xiao Ma
KGKe Gong
Ke Gong
XWXiyin Wang
Xiyin Wang
Coriander (Coriandrum sativum L.), also known as cilantro, is a globally important vegetable and spice crop. Its genome and that of carrot are models for studying the evolution of the Apiaceae family. Here, we developed the Coriander Genomics Database (CGDB, http://cgdb.bio2db.com/) to collect, store, and integrate the genomic, transcriptomic, metabolic, functional annotation, and repeat sequence data of coriander and carrot to serve as a central online platform for Apiaceae and other related plants. Using these data sets in the CGDB, we intriguingly found that seven transcription factor (TF) families showed significantly greater numbers of members in the coriander genome than in the carrot genome. The highest ratio of the numbers of MADS TFs between coriander and carrot reached 3.15, followed by those for tubby protein (TUB) and heat shock factors. As a demonstration of CGDB applications, we identified 17 TUB family genes and conducted systematic comparative and evolutionary analyses. RNA-seq data deposited in the CGDB also suggest dose compensation effects of gene expression in coriander. CGDB allows bulk downloading, significance searches, genome browser analyses, and BLAST searches for comparisons between coriander and other plants regarding genomics, gene families, gene collinearity, gene expression, and the metabolome. A detailed user manual and contact information are also available to provide support to the scientific research community and address scientific questions. CGDB will be continuously updated, and new data will be integrated for comparative and functional genomic analysis in Apiaceae and other related plants.

12 April 2016 in Plant Growth Regulation
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Journal Article
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PWPeng Wu
Peng Wu
XSXiao-Ming Song
Xiao-Ming Song
ZWZhen Wang
Zhen Wang
WDWeiKe Duan
WeiKe Duan
RHRong Hu
Rong Hu
Xilin HouXilin Hou
Xilin Hou

22 March 2014 in BMC Plant Biology
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Journal Article
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XSXiao-Ming Song
Xiao-Ming Song
YLYing Li
Ying Li
TLTongkun Liu
Tongkun Liu
WDWeike Duan
Weike Duan
ZHZhinan Huang
Zhinan Huang
Xilin HouXilin Hou
Xilin Hou
The genomes of non-heading Chinese cabbage (Brassica rapa ssp. chinensis), heading Chinese cabbage (Brassica rapa ssp. pekinensis) and their close relative Arabidopsis thaliana have provided important resources for studying the evolution and genetic improvement of cruciferous plants. Natural growing conditions present these plants with a variety of physiological challenges for which they have a repertoire of genes that ensure adaptability and normal growth. We investigated the differential expressions of genes that control adaptability and development in plants growing in the natural environment to study underlying mechanisms of their expression. Using digital gene expression tag profiling, we constructed an expression profile to identify genes related to important agronomic traits under natural growing conditions. Among three non-heading Chinese cabbage cultivars, we found thousands of genes that exhibited significant differences in expression levels at five developmental stages. Through comparative analysis and previous reports, we identified several candidate genes associated with late flowering, cold tolerance, self-incompatibility, and leaf color. Two genes related to cold tolerance were verified using quantitative real-time PCR. We identified a large number of genes associated with important agronomic traits of non-heading Chinese cabbage. This analysis will provide a wealth of resources for molecular-assisted breeding of cabbage. The raw data and detailed results of this analysis are available at the website http://nhccdata.njau.edu.cn .

1 January 2021 in Mathematical Biosciences and Engineering
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Journal Article
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HZHasan Zulfiqar
Hasan Zulfiqar
RKRida Sarwar Khan
Rida Sarwar Khan
FHFarwa Hassan
Farwa Hassan
KHKyle Hippe
Kyle Hippe
CHCassandra Hunt
Cassandra Hunt
RCRenzhi Cao
Renzhi Cao
<![CDATA[N4-methylcytosine (4mC) is a kind of DNA modification which could regulate multiple biological processes. Correctly identifying 4mC sites in genomic sequences can provide precise knowledge about their genetic roles. This study aimed to develop an ensemble model to predict 4mC sites in the mouse genome. In the proposed model, DNA sequences were encoded by k-mer, enhanced nucleic acid composition and composition of k-spaced nucleic acid pairs. Subsequently, these features were optimized by using minimum redundancy maximum relevance (mRMR) with incremental feature selection (IFS) and five-fold cross-validation. The obtained optimal features were inputted into random forest classifier for discriminating 4mC from non-4mC sites in mouse. On the independent dataset, our model could yield the overall accuracy of 85.41%, which was approximately 3.8% -6.3% higher than the two existing models, i4mC-Mouse and 4mCpred-EL respectively. The data and source code of the model can be freely download from https://github.com/linDing-groups/model_4mc.]]>