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De novo shoot regeneration is one of the important manifestations of cell totipotency in organogenesis, which reflects a survival strategy organism evolved when facing natural selection. Compared with tissue regeneration, and somatic embryogenesis, de novo shoot regeneration denotes a shoot regeneration process directly from detatched or injured tissues of plant. Studies on plant shoot regeneration had identified key genes mediating shoot regeneration. However, knowledge was derived from Arabidopsis; the regeneration capacity is hugely distinct among species. To achieve a comprehensive understanding of the shoot regeneration mechanism from tree species, we select four genetic lines of Populus euphratica from a natural population to be sequenced at transcriptome level. On the basis of the large difference of differentiation capacity, between the highly differentiated (HD) and low differentiated (LD) groups, the analysis of differential expression identified 4920 differentially expressed genes (DEGs), which were revealed in five groups of expression patterns by clustering analysis. Enrichment showed crucial pathways involved in regulation of regeneration difference, including “plant hormone signal transduction”, “cell differentiation”, "cellular response to auxin stimulus", and “auxin-activated signaling pathway”. The expression of nine genes reported to be associated with shoot regeneration was validated using quantitative real-time PCR (qRT-PCR). For the specificity of regeneration mechanism with P. euphratica, large amount of DEGs involved in "plant-pathogen interaction", ubiquitin-26S proteosome mediated proteolysis pathway, stress-responsive DEGs, and senescence-associated DEGs were summarized to possibly account for the differentiation difference with distinct genotypes of P. euphratica. The result in this study helps screening of key regulators in mediating the shoot differentiation. The transcriptomic characteristic in P. euphratica further enhances our understanding of key processes affecting the regeneration capacity of de novo shoots among distinct species.

De novo shoot regeneration is one of the important manifestations of cell totipotency in organogenesis, which reflects a survival strategy organism evolved when facing natural selection. Compared with tissue regeneration, and somatic embryogenesis, de novo shoot regeneration denotes a shoot regeneration process directly from detatched or injured tissues of plant. Studies on plant shoot regeneration had identified key genes mediating shoot regeneration. However, knowledge was derived from Arabidopsis, the regeneration capacity is hugely distinct among species. To achieve a comprehensive understanding of the shoot regeneration mechanism from tree species, we select four genetic lines of Populus euphratica from a natural population to be sequenced at transcriptome level. On the basis of the large difference of differentiation capacity, between the highly differentiated (HD) and low differentiated (LD) groups, the analysis of differential expression identified 4920 differentially expressed genes (DEGs), which were revealed in five groups of expression patterns by clustering analysis. Enrichment showed crucial pathways involved in regulation of regeneration difference, including &ldquo, plant hormone signal transduction&rdquo, &ldquo, cell differentiation&rdquo, "cellular response to auxin stimulus", and &ldquo, auxin-activated signaling pathway&rdquo, The expression of nine genes reported to be associated with shoot regeneration was validated using quantitative real-time PCR (qRT-PCR). For the specificity of regeneration mechanism with P. euphratica, large amount of DEGs involved in "plant-pathogen interaction", ubiquitin-26S proteosome mediated proteolysis pathway, stress-responsive DEGs, and senescence-associated DEGs were summarized to possibly account for the differentiation difference with distinct genotypes of P. euphratica. The result in this study helps screening of key regulators in mediating the shoot differentiation. The transcriptomic characteristic in P. euphratica further enhances our understanding of key processes affecting the regeneration capacity of de novo shoots among distinct species.

Many higher plants of economic and biological importance undergo apomixis in which the maternal tissue of the ovule forms a seed, without experiencing meiosis and fertilization. This feature of apomixis has made it difficult to perform linkage mapping which relies on meiotic recombination. Here, we describe a computational model for mapping quantitative trait loci (QTLs) that control complex traits in apomictic plants. The model is founded on the mixture model-based likelihood in which maternal genotypes are dissolved into two possible components generated by meiotic and apomictic processes, respectively. The EM algorithm was implemented to discern meiotic and apomictic genotypes and, therefore, allow the marker-QTL linkage relationship to be estimated. By capitalizing on reciprocal crosses, the model is renovated to estimate and test imprinting effects of QTLs, providing a better gateway to characterize the genetic architecture of complex traits. The model was validated through computer simulation and further demonstrated for its usefulness by analyzing a real data for an apomictic woody plant. The model has for the first time provided a unique tool for genetic mapping in apomictic plants.

As a group of economically important species, linkage mapping of polysomic autotetraploids, including potato, sugarcane and rose, is difficult to conduct due to their unique meiotic property of double reduction that allows sister chromatids to enter into the same gamete. We describe and assess a statistical model for mapping quantitative trait loci (QTLs) in polysomic autotetraploids. The model incorporates double reduction, built in the mixture model-based framework and implemented with the expectation-maximization algorithm. It allows the simultaneous estimation of QTL positions, QTL effects and the degree of double reduction as well as the assessment of the estimation precision of these parameters. We performed computer simulation to examine the statistical properties of the method and validate its use through analyzing real data in tetraploid switchgrass.

Cells with the same genotype growing under the same conditions can show different phenotypes, which is known as “population heterogeneity”. The heterogeneity of hematopoietic progenitor cells has an effect on their differentiation potential and lineage choices. However, the genetic mechanisms governing population heterogeneity remain unclear. Here, we present a statistical model for mapping the quantitative trait locus (QTL) that affects hematopoietic cell heterogeneity. This strategy, termed systems mapping, integrates a system of differential equations into the framework for systems mapping, allowing hypotheses regarding the interplay between genetic actions and cell heterogeneity to be tested. A simulation approach based on cell heterogeneity dynamics has been designed to test the statistical properties of the model. This model not only considers the traditional QTLs, but also indicates the methylated QTLs that can illustrate non-genetic individual differences. It has significant implications for probing the molecular, genetic and epigenetic mechanisms of hematopoietic progenitor cell heterogeneity.