BackgroundIn diphyodont mammals, the additional molars (permanent molars) bud off from the posterior-free end of the primary dental lamina compared with successional teeth (replacement teeth) budding off from the secondary dental lamina. The diphyodont miniature pig has proved to be a valuable model for studying human molar morphogenesis. The additional molars show a sequential initiation pattern related to the specific tooth development stage of additional molars in miniature pigs during the morphogenesis of additional molars. However, the molecular mechanisms of the regulatory network of mRNAs and long non-coding RNAs during sequential formation of additional molars remain poorly characterized in diphyodont mammals. Here, we performed RNA-seq and microarray on miniature pigs at three key molar developmental stages to examine their differential gene expression profiles and potential regulatory networks during additional molar morphogenesis.ResultsWe have profiled the differential transcript expression and functional networks during morphogenesis of additional molars in miniature pigs. We also have identified the coding and long non-coding transcripts using Coding-Non-Coding Index (CNCI) and annotated transcripts through mapping to the porcine, Wuzhishan miniature pig, mice, cow and human genomes. Many new unannotated genes plus 450 putative long intergenic non-coding RNAs (lincRNAs) were identified. Detailed regulatory network analyses reveal that WNT and TGF-β pathways are critical in regulating sequential morphogenesis of additional molars.ConclusionsThis is the first study to comprehensively analyze the spatiotemporal dynamics of coding and long non-coding transcripts during morphogenesis of additional molars in diphyodont mammals. The miniature pig serves as a large model animal to elucidate the relationship between morphogenesis and transcript level during the cascade initiation of additional molars. Our data provide fundamental knowledge and a basis for understanding the molecular mechanisms governing cascade initiation of additional molars, but also provide an important resource for developmental biology research.

BackgroundIn diphyodont mammals, the additional molars (permanent molars) bud off from the posterior-free end of the primary dental lamina compared with successional teeth (replacement teeth) budding off from the secondary dental lamina. The diphyodont miniature pig has proved to be a valuable model for studying human molar morphogenesis. The additional molars show a sequential initiation pattern related to the specific tooth development stage of additional molars in miniature pigs during the morphogenesis of additional molars. However, the molecular mechanisms of the regulatory network of mRNAs and long non-coding RNAs during sequential formation of additional molars remain poorly characterized in diphyodont mammals. Here, we performed RNA-seq and microarray on miniature pigs at three key molar developmental stages to examine their differential gene expression profiles and potential regulatory networks during additional molar morphogenesis.ResultsWe have profiled the differential transcript expression and functional networks during morphogenesis of additional molars in miniature pigs. We also have identified the coding and long non-coding transcripts using Coding-Non-Coding Index (CNCI) and annotated transcripts through mapping to the porcine, Wuzhishan miniature pig, mice, cow and human genomes. Many new unannotated genes plus 450 putative long intergenic non-coding RNAs (lincRNAs) were identified. Detailed regulatory network analyses reveal that WNT and TGF-β pathways are critical in regulating sequential morphogenesis of additional molars.ConclusionsThis is the first study to comprehensively analyze the spatiotemporal dynamics of coding and long non-coding transcripts during morphogenesis of additional molars in diphyodont mammals. The miniature pig serves as a large model animal to elucidate the relationship between morphogenesis and transcript level during the cascade initiation of additional molars. Our data provide fundamental knowledge and a basis for understanding the molecular mechanisms governing cascade initiation of additional molars, but also provide an important resource for developmental biology research.

BackgroundDNA methylation has been found to associate with disease, aging and environmental exposure, but it is unknown how genome, environment and disease influence DNA methylation dynamics in childhood.ResultsBy analysing 538 paired DNA blood samples from children at birth and at 4–5 years old and 726 paired samples from children at 4 and 8 years old from four European birth cohorts using the Illumina Infinium Human Methylation 450 k chip, we have identified 14,150 consistent age-differential methylation sites (a-DMSs) at epigenome-wide significance of p < 1.14 × 10−7. Genes with an increase in age-differential methylation were enriched in pathways related to ‘development’, and were more often located in bivalent transcription start site (TSS) regions, which can silence or activate expression of developmental genes. Genes with a decrease in age-differential methylation were involved in cell signalling, and enriched on H3K27ac, which can predict developmental state. Maternal smoking tended to decrease methylation levels at the identified da-DMSs. We also found 101 a-DMSs (0.71%) that were regulated by genetic variants using cis-differential Methylation Quantitative Trait Locus (cis-dMeQTL) mapping. Moreover, a-DMS-associated genes during early development were significantly more likely to be linked with disease.ConclusionOur study provides new insights into the dynamic epigenetic landscape of the first 8 years of life.

BackgroundAldehyde dehydrogenases (ALDHs) represent a group of enzymes that detoxify aldehydes by facilitating their oxidation to carboxylic acids, and have been shown to play roles in plant response to abiotic stresses. However, the comprehensive analysis of ALDH superfamily in soybean (Glycine max) has been limited.ResultsIn present study, a total of 53 GmALDHs were identified in soybean, and grouped into 10 ALDH families according to the ALDH Gene Nomenclature Committee and phylogenetic analysis. These groupings were supported by their gene structures and conserved motifs. Soybean ALDH superfamily expanded mainly by whole genome duplication/segmental duplications. Gene network analysis identified 1146 putative co-functional genes of 51 GmALDHs. Gene Ontology (GO) enrichment analysis suggested the co-functional genes of these 51 GmALDHs were enriched (FDR < 1e-3) in the process of lipid metabolism, photosynthesis, proline catabolism, and small molecule catabolism. In addition, 22 co-functional genes of GmALDHs are related to plant response to water deprivation/water transport. GmALDHs exhibited various expression patterns in different soybean tissues. The expression levels of 13 GmALDHs were significantly up-regulated and 14 down-regulated in response to water deficit. The occurrence frequencies of three drought-responsive cis-elements (ABRE, CRT/DRE, and GTGCnTGC/G) were compared in GmALDH genes that were up-, down-, or non-regulated by water deficit. Higher frequency of these three cis-elements was observed for the group of up-regulated GmALDH genes as compared to the group of down- or non- regulated GmALDHs by drought stress, implying their potential roles in the regulation of soybean response to drought stress.ConclusionsA total of 53 ALDH genes were identified in soybean genome and their phylogenetic relationships and duplication patterns were analyzed. The potential functions of GmALDHs were predicted by analyses of their co-functional gene networks, gene expression profiles, and cis-regulatory elements. Three GmALDH genes, including GmALDH3H2, GmALDH12A2 and GmALDH18B3, were highly induced by drought stress in soybean leaves. Our study provides a foundation for future investigations of GmALDH gene function in soybean.

BackgroundAldehyde dehydrogenases (ALDHs) represent a group of enzymes that detoxify aldehydes by facilitating their oxidation to carboxylic acids, and have been shown to play roles in plant response to abiotic stresses. However, the comprehensive analysis of ALDH superfamily in soybean (Glycine max) has been limited.ResultsIn present study, a total of 53 GmALDHs were identified in soybean, and grouped into 10 ALDH families according to the ALDH Gene Nomenclature Committee and phylogenetic analysis. These groupings were supported by their gene structures and conserved motifs. Soybean ALDH superfamily expanded mainly by whole genome duplication/segmental duplications. Gene network analysis identified 1146 putative co-functional genes of 51 GmALDHs. Gene Ontology (GO) enrichment analysis suggested the co-functional genes of these 51 GmALDHs were enriched (FDR < 1e-3) in the process of lipid metabolism, photosynthesis, proline catabolism, and small molecule catabolism. In addition, 22 co-functional genes of GmALDHs are related to plant response to water deprivation/water transport. GmALDHs exhibited various expression patterns in different soybean tissues. The expression levels of 13 GmALDHs were significantly up-regulated and 14 down-regulated in response to water deficit. The occurrence frequencies of three drought-responsive cis-elements (ABRE, CRT/DRE, and GTGCnTGC/G) were compared in GmALDH genes that were up-, down-, or non-regulated by water deficit. Higher frequency of these three cis-elements was observed for the group of up-regulated GmALDH genes as compared to the group of down- or non- regulated GmALDHs by drought stress, implying their potential roles in the regulation of soybean response to drought stress.ConclusionsA total of 53 ALDH genes were identified in soybean genome and their phylogenetic relationships and duplication patterns were analyzed. The potential functions of GmALDHs were predicted by analyses of their co-functional gene networks, gene expression profiles, and cis-regulatory elements. Three GmALDH genes, including GmALDH3H2, GmALDH12A2 and GmALDH18B3, were highly induced by drought stress in soybean leaves. Our study provides a foundation for future investigations of GmALDH gene function in soybean.