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1.
Genome Biol Evol ; 9(4): 1013-1029, 2017 Apr 01.
Artigo em Inglês | MEDLINE | ID: mdl-28444194

RESUMO

Plant 3R-MYB transcription factors are an important subgroup of the MYB super family in plants; however, their evolutionary history and functions remain poorly understood. We identified 225 3R-MYB proteins from 65 plant species, including algae and all major lineages of land plants. Two segmental duplication events preceding the common ancestor of angiosperms have given rise to three subgroups of the 3R-MYB proteins. Five conserved introns in the domain region of the 3R-MYB genes were identified, which arose through a step-wise pattern of intron gain during plant evolution. Alternative splicing (AS) analysis of selected species revealed that transcripts from more than 60% of 3R-MYB genes undergo AS. AS could regulate transcriptional activity for some of the plant 3R-MYBs by generating different regulatory motifs. The 3R-MYB genes of all subgroups appear to be enriched for Mitosis-Specific Activator element core sequences within their upstream promoter region, which suggests a functional involvement in cell cycle. Notably, expression of 3R-MYB genes from different species exhibits differential regulation under various abiotic stresses. These data suggest that the plant 3R-MYBs function in both cell cycle regulation and abiotic stress response, which may contribute to the adaptation of plants to a sessile lifestyle.

2.
Bioinformatics ; 31(3): 432-3, 2015 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-25273112

RESUMO

SUMMARY: MulRF is a platform-independent software package for phylogenetic analysis using multi-copy gene trees. It seeks the species tree that minimizes the Robinson-Foulds (RF) distance to the input trees using a generalization of the RF distance to multi-labeled trees. The underlying generic tree distance measure and fast running time make MulRF useful for inferring phylogenies from large collections of gene trees, in which multiple evolutionary processes as well as phylogenetic error may contribute to gene tree discord. MulRF implements several features for customizing the species tree search and assessing the results, and it provides a user-friendly graphical user interface (GUI) with tree visualization. The species tree search is implemented in C++ and the GUI in Java Swing. AVAILABILITY: MulRF's executable as well as sample datasets and manual are available at http://genome.cs.iastate.edu/CBL/MulRF/, and the source code is available at https://github.com/ruchiherself/MulRFRepo. CONTACT: ruchic@ufl.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Assuntos
Dosagem de Genes/genética , Filogenia , Análise de Sequência de DNA/métodos , Software , Algoritmos , Simulação por Computador , Evolução Molecular , Humanos , Linguagens de Programação
3.
Algorithms Mol Biol ; 8(1): 28, 2013 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-24180377

RESUMO

BACKGROUND: Constructing species trees from multi-copy gene trees remains a challenging problem in phylogenetics. One difficulty is that the underlying genes can be incongruent due to evolutionary processes such as gene duplication and loss, deep coalescence, or lateral gene transfer. Gene tree estimation errors may further exacerbate the difficulties of species tree estimation. RESULTS: We present a new approach for inferring species trees from incongruent multi-copy gene trees that is based on a generalization of the Robinson-Foulds (RF) distance measure to multi-labeled trees (mul-trees). We prove that it is NP-hard to compute the RF distance between two mul-trees; however, it is easy to calculate this distance between a mul-tree and a singly-labeled species tree. Motivated by this, we formulate the RF problem for mul-trees (MulRF) as follows: Given a collection of multi-copy gene trees, find a singly-labeled species tree that minimizes the total RF distance from the input mul-trees. We develop and implement a fast SPR-based heuristic algorithm for the NP-hard MulRF problem.We compare the performance of the MulRF method (available at http://genome.cs.iastate.edu/CBL/MulRF/) with several gene tree parsimony approaches using gene tree simulations that incorporate gene tree error, gene duplications and losses, and/or lateral transfer. The MulRF method produces more accurate species trees than gene tree parsimony approaches. We also demonstrate that the MulRF method infers in minutes a credible plant species tree from a collection of nearly 2,000 gene trees. CONCLUSIONS: Our new phylogenetic inference method, based on a generalized RF distance, makes it possible to quickly estimate species trees from large genomic data sets. Since the MulRF method, unlike gene tree parsimony, is based on a generic tree distance measure, it is appealing for analyses of genomic data sets, in which many processes such as deep coalescence, recombination, gene duplication and losses as well as phylogenetic error may contribute to gene tree discord. In experiments, the MulRF method estimated species trees accurately and quickly, demonstrating MulRF as an efficient alternative approach for phylogenetic inference from large-scale genomic data sets.

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