Finding New Cell Wall Regulatory Genes in Populus trichocarpa Using Multiple Lines of Evidence.

Understanding the regulatory network controlling cell wall biosynthesis is of great interest in Populus trichocarpa, both because of its status as a model woody perennial and its importance for lignocellulosic products. We searched for genes with putatively unknown roles in regulating cell wall biosynthesis using an extended network-based Lines of Evidence (LOE) pipeline to combine multiple omics data sets in P. trichocarpa, including gene coexpression, gene comethylation, population level pairwise SNP correlations, and two distinct SNP-metabolite Genome Wide Association Study (GWAS) layers. By incorporating validation, ranking, and filtering approaches we produced a list of nine high priority gene candidates for involvement in the regulation of cell wall biosynthesis. We subsequently performed a detailed investigation of candidate gene GROWTH-REGULATING FACTOR 9 (PtGRF9). To investigate the role of PtGRF9 in regulating cell wall biosynthesis, we assessed the genome-wide connections of PtGRF9 and a paralog across data layers with functional enrichment analyses, predictive transcription factor binding site analysis, and an independent comparison to eQTN data. Our findings indicate that PtGRF9 likely affects the cell wall by directly repressing genes involved in cell wall biosynthesis, such as PtCCoAOMT and PtMYB.41, and indirectly by regulating homeobox genes. Furthermore, evidence suggests that PtGRF9 paralogs may act as transcriptional co-regulators that direct the global energy usage of the plant. Using our extended pipeline, we show multiple lines of evidence implicating the involvement of these genes in cell wall regulatory functions and demonstrate the value of this method for prioritizing candidate genes for experimental validation

A Survey of Processing Systems for Phylogenetics and Population Genetics

The COVID-19 pandemic brought Bioinformatics into the spotlight, revealing that several existing methods, algorithms, and tools were not well prepared to handle large amounts of genomic data efficiently. This led to prohibitively long execution times and the need to reduce the extent of analyses to obtain results in a reasonable amount of time. In this survey, we review available high-performance computing and hardware-accelerated systems based on FPGA and GPU technology. Optimized and hardware-accelerated systems can conduct more thorough analyses considerably faster than pure software implementations, allowing to reach important conclusions in a timely manner to drive scientific discoveries. We discuss the reasons that are currently hindering high-performance solutions from being widely deployed in real-world biological analyses and describe a research direction that can pave the way to enable this

Wavelet-Based Genomic Signal Processing for Centromere Identification and Hypothesis Generation

Various ‘omics data types have been generated for Populus trichocarpa, each providing a layer of information which can be represented as a density signal across a chromosome. We make use of genome sequence data, variants data across a population as well as methylation data across 10 different tissues, combined with wavelet-based signal processing to perform a comprehensive analysis of the signature of the centromere in these different data signals, and successfully identify putative centromeric regions in P. trichocarpa from these signals. Furthermore, using SNP (single nucleotide polymorphism) correlations across a natural population of P. trichocarpa, we find evidence for the co-evolution of the centromeric histone CENH3 with the sequence of the newly identified centromeric regions, and identify a new CENH3 candidate in P. trichocarpa

Bioinformatics

This book is divided into different research areas relevant in Bioinformatics such as biological networks, next generation sequencing, high performance computing, molecular modeling, structural bioinformatics, molecular modeling and intelligent data analysis. Each book section introduces the basic concepts and then explains its application to problems of great relevance, so both novice and expert readers can benefit from the information and research works presented here

Coevolution between nuclear and plastid genomes in Geraniaceae

Plastid genomes of angiosperms are highly conserved in both genome organization and nucleotide substitution rates. Geraniaceae have highly rearranged genomes and elevated nucleotide substitution rates, which provides an attractive system to study nuclear-plastid genome coevolution. My dissertation research has focused on two areas of nuclear-plastid genome coevolution in Geraniaceae. First, I have investigated the correlation of nucleotide substitution rates between nuclear and plastid genes that encode interacting subunits that form the multi-subunit complex of Plastid Encoded RNA Polymerase (PEP). Second, the hypothesis that the unusual changes of plastid genome organization and elevated nucleotide substitution rates of plastid encoded genes is the result of alterations in nuclear encoded DNA replication, recombination and repair (DNA RRR) genes is tested. The second chapter investigates the optimal methods for transcriptome sequencing/assembly. My findings supported the use of transcriptome assemblers optimized for Illumina sequencing platform (Trinity and SOAPdenovo-trans). The third chapter investigated coevolution of nucleotide substitution rates between plastid encoded RNAP (rpoA, rpoB, rpoC1, rpoC2) and nuclear encoded SIG (sig1-6) genes that are part of the multi-subunit complex PEP. Using the transcriptomes of 27 Geraniales species I extracted the PEP genes and performed a systematic correlation test. I detected strong correlations of dN (nonsynonymous substitutions) but not dS (synonymous substitutions) between RNAP and SIG but no correlations were detected for the control genes, which provides a plausible explanation for the cause of plastome-genome incompatibility in Geraniaceae. The fourth chapter investigated the effect of DNA RRR system on the aberrant evolutionary phenomena in Geraniaceae plastid genomes. I extracted DNA RRR and nuclear control genes with different subcellular locations from 27 Geraniales transcriptomes and estimated genome complexity with various measures from plastid genomes of the same species. I detected significant correlations for dN but not dS for three DNA RRR genes, 10 nuclear encoded plastid targeted (NUCP) and three nuclear encoded mitochondrial targeted (NUMT) genes. The findings of a correlation between dN of DNA RRR genes and genome complexity support the hypothesis that changes of plastid genome complexity in Geraniaceae may be caused by dysfunction of DNA RRR systems.Plant Biolog

Faster inference from state space models via GPU computing

Funding: C.F.-J. is funded via a doctoral scholarship from the University of St Andrews, School of Mathematics and Statistics.Inexpensive Graphics Processing Units (GPUs) offer the potential to greatly speed up computation by employing their massively parallel architecture to perform arithmetic operations more efficiently. Population dynamics models are important tools in ecology and conservation. Modern Bayesian approaches allow biologically realistic models to be constructed and fitted to multiple data sources in an integrated modelling framework based on a class of statistical models called state space models. However, model fitting is often slow, requiring hours to weeks of computation. We demonstrate the benefits of GPU computing using a model for the population dynamics of British grey seals, fitted with a particle Markov chain Monte Carlo algorithm. Speed-ups of two orders of magnitude were obtained for estimations of the log-likelihood, compared to a traditional ‘CPU-only’ implementation, allowing for an accurate method of inference to be used where this was previously too computationally expensive to be viable. GPU computing has enormous potential, but one barrier to further adoption is a steep learning curve, due to GPUs' unique hardware architecture. We provide a detailed description of hardware and software setup, and our case study provides a template for other similar applications. We also provide a detailed tutorial-style description of GPU hardware architectures, and examples of important GPU-specific programming practices.Publisher PDFPeer reviewe

The role of zinc in the adaptive evolution of polar phytoplankton

Zinc is an essential trace metal for oceanic primary producers with the highest concentrations in polar oceans. However, its role in the biological functioning and adaptive evolution of polar phytoplankton remains enigmatic. Here, we have applied a combination of evolutionary genomics, quantitative proteomics, co-expression analyses and cellular physiology to suggest that model polar phytoplankton species have a higher demand for zinc because of elevated cellular levels of zinc-binding proteins. We propose that adaptive expansion of regulatory zinc-finger protein families, co-expanded and co-expressed zinc-binding proteins families involved in photosynthesis and growth in these microalgal species and their natural communities were identified to be responsible for the higher zinc demand. The expression of their encoding genes in eukaryotic phytoplankton metatranscriptomes from pole-to-pole was identified to correlate not only with dissolved zinc concentrations in the upper ocean but also with temperature, suggesting that environmental conditions of polar oceans are responsible for an increased demand of zinc. These results suggest that zinc plays an important role in supporting photosynthetic growth in eukaryotic polar phytoplankton and that this has been critical for algal colonization of low-temperature polar oceans.</p