Eric K. Wafula

Bio: Eric K. Wafula is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Parasitic plant & Genome. The author has an hindex of 25, co-authored 35 publications receiving 3990 citations.

Phylotranscriptomic analysis of the origin and early diversification of land plants

Abstract: Reconstructing the origin and evolution of land plants and their algal relatives is a fundamental problem in plant phylogenetics, and is essential for understanding how critical adaptations arose, including the embryo, vascular tissue, seeds, and flowers. Despite advances in molecular systematics, some hypotheses of relationships remain weakly resolved. Inferring deep phylogenies with bouts of rapid diversification can be problematic; however, genome-scale data should significantly increase the number of informative characters for analyses. Recent phylogenomic reconstructions focused on the major divergences of plants have resulted in promising but inconsistent results. One limitation is sparse taxon sampling, likely resulting from the difficulty and cost of data generation. To address this limitation, transcriptome data for 92 streptophyte taxa were generated and analyzed along with 11 published plant genome sequences. Phylogenetic reconstructions were conducted using up to 852 nuclear genes and 1,701,170 aligned sites. Sixty-nine analyses were performed to test the robustness of phylogenetic inferences to permutations of the data matrix or to phylogenetic method, including supermatrix, supertree, and coalescent-based approaches, maximum-likelihood and Bayesian methods, partitioned and unpartitioned analyses, and amino acid versus DNA alignments. Among other results, we find robust support for a sister-group relationship between land plants and one group of streptophyte green algae, the Zygnematophyceae. Strong and robust support for a clade comprising liverworts and mosses is inconsistent with a widely accepted view of early land plant evolution, and suggests that phylogenetic hypotheses used to understand the evolution of fundamental plant traits should be reevaluated.

Data access for the 1,000 Plants (1KP) project.

Abstract: The 1,000 plants (1KP) project is an international multi-disciplinary consortium that has generated transcriptome data from over 1,000 plant species, with exemplars for all of the major lineages across the Viridiplantae (green plants) clade. Here, we describe how to access the data used in a phylogenomics analysis of the first 85 species, and how to visualize our gene and species trees. Users can develop computational pipelines to analyse these data, in conjunction with data of their own that they can upload. Computationally estimated protein-protein interactions and biochemical pathways can be visualized at another site. Finally, we comment on our future plans and how they fit within this scalable system for the dissemination, visualization, and analysis of large multi-species data sets.

The butterfly plant arms-race escalated by gene and genome duplications.

Abstract: Coevolutionary interactions are thought to have spurred the evolution of key innovations and driven the diversification of much of life on Earth. However, the genetic and evolutionary basis of the innovations that facilitate such interactions remains poorly understood. We examined the coevolutionary interactions between plants (Brassicales) and butterflies (Pieridae), and uncovered evidence for an escalating evolutionary arms-race. Although gradual changes in trait complexity appear to have been facilitated by allelic turnover, key innovations are associated with gene and genome duplications. Furthermore, we show that the origins of both chemical defenses and of molecular counter adaptations were associated with shifts in diversification rates during the arms-race. These findings provide an important connection between the origins of biodiversity, coevolution, and the role of gene and genome duplications as a substrate for novel traits.

A genome triplication associated with early diversification of the core eudicots

Abstract: Background Although it is agreed that a major polyploidy event, gamma, occurred within the eudicots, the phylogenetic placement of the event remains unclear.

Genome of the long-living sacred lotus ( Nelumbo nucifera Gaertn.)

Abstract: Background: Sacred lotus is a basal eudicot with agricultural, medicinal, cultural and religious importance. It was domesticated in Asia about 7,000 years ago, and cultivated for its rhizomes and seeds as a food crop. It is particularly noted for its 1,300-year seed longevity and exceptional water repellency, known as the lotus effect. The latter property is due to the nanoscopic closely packed protuberances of its self-cleaning leaf surface, which have been adapted for the manufacture of a self-cleaning industrial paint, Lotusan. Results: The genome of the China Antique variety of the sacred lotus was sequenced with Illumina and 454 technologies, at respective depths of 101× and 5.2×. The final assembly has a contig N50 of 38.8 kbp and a scaffold N50 of 3.4 Mbp, and covers 86.5% of the estimated 929 Mbp total genome size. The genome notably lacks the paleo-triplication observed in other eudicots, but reveals a lineage-specific duplication. The genome has evidence of slow evolution, with a 30% slower nucleotide mutation rate than observed in grape. Comparisons of the available sequenced genomes suggest a minimum gene set for vascular plants of 4,223 genes. Strikingly, the sacred lotus has 16 COG2132 multi-copper oxidase family proteins with root-specific expression; these are involved in root meristem phosphate starvation, reflecting adaptation to limited nutrient availability in an aquatic environment. Conclusions: The slow nucleotide substitution rate makes the sacred lotus a better resource than the current standard, grape, for reconstructing the pan-eudicot genome, and should therefore accelerate comparative analysis between eudicots and monocots.

Integrative Genomics Viewer

Abstract: Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference.

Abstract: MOTIVATION Phylogenies are important for fundamental biological research, but also have numerous applications in biotechnology, agriculture and medicine. Finding the optimal tree under the popular maximum likelihood (ML) criterion is known to be NP-hard. Thus, highly optimized and scalable codes are needed to analyze constantly growing empirical datasets. RESULTS We present RAxML-NG, a from-scratch re-implementation of the established greedy tree search algorithm of RAxML/ExaML. RAxML-NG offers improved accuracy, flexibility, speed, scalability, and usability compared with RAxML/ExaML. On taxon-rich datasets, RAxML-NG typically finds higher-scoring trees than IQTree, an increasingly popular recent tool for ML-based phylogenetic inference (although IQ-Tree shows better stability). Finally, RAxML-NG introduces several new features, such as the detection of terraces in tree space and the recently introduced transfer bootstrap support metric. AVAILABILITY AND IMPLEMENTATION The code is available under GNU GPL at https://github.com/amkozlov/raxml-ng. RAxML-NG web service (maintained by Vital-IT) is available at https://raxml-ng.vital-it.ch/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

ASTRAL-III: polynomial time species tree reconstruction from partially resolved gene trees.

Abstract: Evolutionary histories can be discordant across the genome, and such discordances need to be considered in reconstructing the species phylogeny. ASTRAL is one of the leading methods for inferring species trees from gene trees while accounting for gene tree discordance. ASTRAL uses dynamic programming to search for the tree that shares the maximum number of quartet topologies with input gene trees, restricting itself to a predefined set of bipartitions. We introduce ASTRAL-III, which substantially improves the running time of ASTRAL-II and guarantees polynomial running time as a function of both the number of species (n) and the number of genes (k). ASTRAL-III limits the bipartition constraint set (X) to grow at most linearly with n and k. Moreover, it handles polytomies more efficiently than ASTRAL-II, exploits similarities between gene trees better, and uses several techniques to avoid searching parts of the search space that are mathematically guaranteed not to include the optimal tree. The asymptotic running time of ASTRAL-III in the presence of polytomies is $O\left ((nk)^{1.726} D \right)$ where D=O(nk) is the sum of degrees of all unique nodes in input trees. The running time improvements enable us to test whether contracting low support branches in gene trees improves the accuracy by reducing noise. In extensive simulations, we show that removing branches with very low support (e.g., below 10%) improves accuracy while overly aggressive filtering is harmful. We observe on a biological avian phylogenomic dataset of 14K genes that contracting low support branches greatly improve results. ASTRAL-III is a faster version of the ASTRAL method for phylogenetic reconstruction and can scale up to 10,000 species. With ASTRAL-III, low support branches can be removed, resulting in improved accuracy.

GetOrganelle: a fast and versatile toolkit for accurate de novo assembly of organelle genomes

Abstract: GetOrganelle is a state-of-the-art toolkit to accurately assemble organelle genomes from whole genome sequencing data. It recruits organelle-associated reads using a modified “baiting and iterative mapping” approach, conducts de novo assembly, filters and disentangles the assembly graph, and produces all possible configurations of circular organelle genomes. For 50 published plant datasets, we are able to reassemble the circular plastomes from 47 datasets using GetOrganelle. GetOrganelle assemblies are more accurate than published and/or NOVOPlasty-reassembled plastomes as assessed by mapping. We also assemble complete mitochondrial genomes using GetOrganelle. GetOrganelle is freely released under a GPL-3 license ( https://github.com/Kinggerm/GetOrganelle ).