BackgroundRestriction site associated DNA sequencing (RAD-seq), a next-generation sequencing technology, has greatly facilitated genetic linkage mapping studies in outbred species. RAD-seq is capable of discovering thousands of genetic markers for linkage mapping across many individuals, and can be applied in species with or without a reference genome. Although several analytical tools are available for RAD-seq data, alternative strategies are necessary for improving the marker quality and hence the genetic mapping accuracy.ResultsWe demonstrate a strategy for constructing dense genetic linkage maps in hybrid forest trees by combining RAD-seq and whole-genome sequencing technologies. We performed RAD-seq of 150 progeny and whole-genome sequencing of the two parents in an F1 hybrid population of Populus deltoides × P. simonii. Two rough references were assembled from the whole-genome sequencing reads of the two parents separately. Based on the parental reference sequences, 3442 high-quality single nucleotide polymorphisms (SNPs) were identified that segregate in the ratio of 1:1. The maternal linkage map of P. deltoides was constructed with 2012 SNPs, containing 19 linkage groups and spanning 4067.16 cM of the genome with an average distance of 2.04 cM between adjacent markers, while the male map of P. simonii consisted of 1430 SNPs and the same number of linkage groups with a total length of 4356.04 cM and an average interval distance of 3.09 cM. Collinearity between the parental linkage maps and the reference genome of P. trichocarpa was also investigated. Compared with the result on the basis of the existing reference genome, our strategy identified more high-quality SNPs and generated parental linkage groups that nicely match the karyotype of Populus.ConclusionsThe strategy of simultaneously using RAD and whole-genome sequencing technologies can be applied to constructing high-density genetic maps in forest trees regardless of whether a reference genome exists. The two parental linkage maps constructed here provide more accurate genetic resources for unraveling quantitative trait loci and accelerating molecular breeding programs, as well as for comparative genomics in Populus.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3003-9) contains supplementary material, which is available to authorized users.
Populus trees meet continuous difficulties from the environment through their life cycle. To warrant their durability and generation, Populus trees exhibit various types of defenses, including the production of secondary metabolites. Syntheses derived from the shikimate-phenylpropanoid pathway are a varied and plentiful class of secondary metabolites manufactured in Populus. Amongst other main classes of secondary metabolites in Populus are fatty acid and terpenoid-derivatives. Many of the secondary metabolites made by Populus trees have been functionally described. Any others have been associated with particular ecological or biological processes, such as resistance against pests and microbial pathogens or acclimatization to abiotic stresses. Still, the functions of many Populus secondary metabolites are incompletely understood. Furthermore, many secondary metabolites have therapeutic effects, leading to more studies of secondary metabolites and their biosynthesis. This paper reviews the biosynthetic pathways and therapeutic impacts of secondary metabolites in Populus using a genomics approach. Compared with bacteria, fewer known pathways produce secondary metabolites in Populus despite P. trichocarpa having had its genome sequenced.
Constructing a sensibly functional gene interaction network is highly appealing for better understanding system-level biological processes governing various Populus traits. Bayesian Network (BN) learning provides an elegant and compact statistical approach for modeling causal gene-gene relationships in microarray data. Therefore, it could come with the illumination of functional molecular playing in Biology Systems. In the present study, different forms of gene Bayesian networks were detected on Populus cellular transcriptome data. Markov blankets would likely be emerging at every possible gene regulatory Bayesian network level. Results showed that PtpAffx.1257.4.S1_a_at,1.0 hypothetical protein is the most important in its possible regulatory program. This paper illustrates that the gene network regulatory inference is possible to encapsulate within a single BN model. Therefore, such a BN model can serve as a promising training tool for Populus gene expression data for better future experimental scenarios. Bangladesh J. Bot. 50(4): 1077-1086, 2021 (December)
Populus is not only important for wood-based products, such as paper and timber, but also for metabolic-based production, for instance, bioethanol and biofuels. Constructing a sensibly functional gene interaction network is highly appealing to better understand system-level biological processes governing various Populus traits. Bayesian network learning provides an elegant and compact statistical approach for modeling causal gene-gene relationships in microarray data. Therefore, it could come with the illumination of functional molecular playing in Biology Systems. In this study, different forms of gene Bayesian networks were learned on Populus cellular transcriptome data. We addressed that Markov blankets, separating genes external to a regulatory Bayesian network from its internal genes, would likely be emerging at every possible gene regulatory Bayesian network level. The results have also shown that PtpAffx.1257.4.S1_a_at,1.0 hypothetical protein is the most important in its possible regulatory program. This paper illustrates that the gene network regulatory inference is possible to encapsulate within a single BN model. Therefore, such a BN model can serve as a promising training tool for Populus gene expression data to better prepare future experimental scenarios.
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