Biology subjects

Tuskan, G.

Publications and source records attributed to Tuskan, G..

3 recordsLinked to original sources

bioRxiv2021

Integrative genomics reveals paths to sex dimorphism in Salix purpurea L.

Sex dimorphism and gene expression were studied in developing catkins in 159 F2 individuals from the bioenergy crop Salix purpurea, and potential mechanisms and pathways for regulating sex development were explored. Differential expression, eQTL, bisulfite sequencing, and network analysis were used to characterize sex dimorphism, detect candidate master regulator genes, and identify pathways through which the sex determination region (SDR) may mediate sex dimorphism. Eleven genes are presented as candidates for master regulators of sex, supported by gene expression and network analyses. These include genes putatively involved in hormone signaling, epigenetic modification, and regulation of transcription. eQTL analysis revealed a suite of transcription factors and genes involved in secondary metabolism and floral development that were predicted to be under direct control of the sex determination region. Furthermore, data from bisulfite sequencing and small RNA sequencing revealed strong differences in expression between males and females that would implicate both of these processes in sex dimorphism pathways. These data indicate that the mechanism of sex determination in Salix purpurea is likely different from that observed in the related genus Populus. This further demonstrates the dynamic nature of SDRs in plants, which involves a multitude of mechanisms of sex determination and a high rate of turnover.

genomics↗

bioRxiv2019

AlphaBeta: Computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants

IntroductionHeritable changes in cytosine methylation can arise stochastically in plant genomes independently of DNA sequence alterations. These so-called spontaneous epimutations appear to be a byproduct of imperfect DNA methylation maintenance during mitotic or meitotic cell divisions. Accurate estimates of the rate and spectrum of these stochastic events are necessary to be able to quantify how epimutational processes shape methylome diversity in the context of plant evolution, development and aging. MethodHere we describe AlphaBeta, a computational method for estimating epimutation rates and spectra from pedigree-based high-throughput DNA methylation data. The approach requires that the topology of the pedigree is known, which is typically the case in the experimental construction of mutation accumulation lines (MA-lines) in sexually or clonally reproducing species. However, this method also works for inferring somatic epimutation rates in long-lived perennials, such as trees, using leaf methylomes and coring data as input. In this case, we treat the tree branching structure as an intra-organismal phylogeny of somatic lineages and leverage information about the epimutational history of each branch. ResultsTo illustrate the method, we applied AlphaBeta to multi-generational data from selfing- and asexually-derived MA-lines in Arabidopsis and dandelion, as well as to intra-generational leaf methylome data of a single poplar tree. Our results show that the epimutation landscape in plants is deeply conserved across angiosperm species, and that heritable epimutations originate mainly during somatic development, rather than from DNA methylation reinforcement errors during sexual reproduction. Finally, we also provide the first evidence that DNA methylation data, in conjunction with statistical epimutation models, can be used as a molecular clock for age-dating trees. ConclusionAlphaBeta faciliates unprecedented quantitative insights into epimutational processes in a wide range of plant systems. Software implementing our method is available as a Bioconductor R package at http://bioconductor.org/packages/3.10/bioc/html/AlphaBeta.html

genomics↗

bioRxiv2018

Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery

Biological organisms are complex systems that are composed of functional networks of interacting molecules and macromolecules. Complex phenotypes are the result of orchestrated, hierarchical, heterogeneous collections of expressed genomic variants. However, the effects of these variants are the result of historic selective pressure and current environmental and epigenetic signals, and, as such, their co-occurrence can be seen as genome-wide correlations in a number of different manners. Biomass recalcitrance (i.e., the resistance of plants to degradation or deconstruction, which ultimately enables access to a plants sugars) is a complex polygenic phenotype of high importance to biofuels initiatives. This study makes use of data derived from the re-sequenced genomes from over 800 different Populus trichocarpa genotypes in combination with metabolomic and pyMBMS data across this population, as well as co-expression and co-methylation networks in order to better understand the molecular interactions involved in recalcitrance, and identify target genes involved in lignin biosynthesis/degradation. A Lines Of Evidence (LOE) scoring system is developed to integrate the information in the different layers and quantify the number of lines of evidence linking genes to lignin-related lignin-phenotypes across the network layers. The resulting Genome Wide Association Study networks, integrated with Single Nucleotide Polymorphism (SNP) correlation, co-methylation and co-expression networks through the LOE scores are proving to be a powerful approach to determine the pleiotropic and epistatic relationships underlying cellular functions and, as such, the molecular basis for complex phenotypes, such as recalcitrance.

bioinformatics↗