pH-dependent CLE peptide perception permits phloem differentiation in Arabidopsis roots.

The plant vasculature delivers phloem sap to the growth apices of sink organs, the meristems, via the interconnected sieve elements of the protophloem. In the A. thaliana root meristem, the stem cells form two files of protophloem sieve elements (PPSEs), whose timely differentiation requires a set of positive genetic regulators.

Mapping and engineering of auxin-induced plasma membrane dissociation in BRX family proteins.

Angiosperms have evolved the phloem for the long-distance transport of metabolites. The complex process of phloem development involves genes that only occur in vascular plant lineages. For example, in Arabidopsis thaliana, the BREVIS RADIX (BRX) gene is required for continuous root protophloem differentiation, together with PROTEIN KINASE ASSOCIATED WITH BRX (PAX).

Local auxin competition explains fragmented differentiation patterns.

Trajectories of cellular ontogeny are tightly controlled and often involve feedback-regulated molecular antagonism. For example, sieve element differentiation along developing protophloem cell files of Arabidopsis roots requires two antagonistic regulators of auxin efflux. Paradoxically, loss-of-function in either regulator triggers similar, seemingly stochastic differentiation failures of individual sieve element precursors.

Local and Systemic Effects of Brassinosteroid Perception in Developing Phloem.

The plant vasculature is an essential adaptation to terrestrial growth. Its phloem component permits efficient transfer of photosynthates between source and sink organs but also transports signals that systemically coordinate physiology and development. Here, we provide evidence that developing phloem orchestrates cellular behavior of adjacent tissues in the growth apices of plants, the meristems.

Sequence-Based Synteny Analysis of Multiple Large Genomes.

Current methods for synteny analysis provide only limited support to study large genomes at the sequence level. In this chapter, we describe a pipeline based on existing tools that, applied in a suitable fashion, enables synteny analysis of large genomic datasets. We give a hands-on description of each step of the pipeline using four avian genomes for data.

New Genome Similarity Measures based on Conserved Gene Adjacencies.

Many important questions in molecular biology, evolution, and biomedicine can be addressed by comparative genomic approaches. One of the basic tasks when comparing genomes is the definition of measures of similarity (or dissimilarity) between two genomes, for example, to elucidate the phylogenetic relationships between species. The power of different genome comparison methods varies with the underlying formal model of a genome.

NEMo: An Evolutionary Model With Modularity for PPI Networks.

Modeling the evolution of biological networks is a major challenge. Biological networks are usually represented as graphs; evolutionary events not only include addition and removal of vertices and edges but also duplication of vertices and their associated edges. Since duplication is viewed as a primary driver of genomic evolution, recent work has focused on duplication-based models.

On Computing Breakpoint Distances for Genomes with Duplicate Genes.

A fundamental problem in comparative genomics is to compute the distance between two genomes in terms of its higher level organization (given by genes or syntenic blocks). For two genomes without duplicate genes, we can easily define (and almost always efficiently compute) a variety of distance measures, but the problem is NP-hard under most models when genomes contain duplicate genes. To tackle duplicate genes, three formulations (exemplar, maximum matching, and any matching) have been proposed, all of which aim to build a matching between homologous genes so as to minimize some distance measure.

A Fast and Exact Algorithm for the Exemplar Breakpoint Distance.

A fundamental problem in comparative genomics is to compute the distance between two genomes. For two genomes without duplicate genes, we can easily compute a variety of distance measures in linear time, but the problem is NP-hard under most models when genomes contain duplicate genes. Sankoff proposed the use of exemplars to tackle the problem of duplicate genes and gene families: each gene family is represented by a single gene (the exemplar for that family), chosen so as to optimize some metric.

Comparing genomes with rearrangements and segmental duplications.

Motivation: Large-scale evolutionary events such as genomic rearrange.ments and segmental duplications form an important part of the evolution of genomes and are widely studied from both biological and computational perspectives. A basic computational problem is to infer these events in the evolutionary history for given modern genomes, a task for which many algorithms have been proposed under various constraints.

An Exact Algorithm to Compute the Double-Cut-and-Join Distance for Genomes with Duplicate Genes.

Computing the edit distance between two genomes is a basic problem in the study of genome evolution. The double-cut-and-join (DCJ) model has formed the basis for most algorithmic research on rearrangements over the last few years. The edit distance under the DCJ model can be computed in linear time for genomes without duplicate genes, while the problem becomes NP-hard in the presence of duplicate genes.

Study of cell differentiation by phylogenetic analysis using histone modification data.

Background: In cell differentiation, a cell of a less specialized type becomes one of a more specialized type, even though all cells have the same genome. Transcription factors and epigenetic marks like histone modifications can play a significant role in the differentiation process.

Results: In this paper, we present a simple analysis of cell types and differentiation paths using phylogenetic inference based on ChIP-Seq histone modification data.

Evaluating synteny for improved comparative studies.

Motivation: Comparative genomics aims to understand the structure and function of genomes by translating knowledge gained about some genomes to the object of study. Early approaches used pairwise comparisons, but today researchers are attempting to leverage the larger potential of multi-way comparisons. Comparative genomics relies on the structuring of genomes into syntenic blocks: blocks of sequence that exhibit conserved features across the genomes.

Probabilistic partitioning methods to find significant patterns in ChIP-Seq data.

Motivation: We have witnessed an enormous increase in ChIP-Seq data for histone modifications in the past few years. Discovering significant patterns in these data is an important problem for understanding biological mechanisms.

Results: We propose probabilistic partitioning methods to discover significant patterns in ChIP-Seq data.

Sorting genomes with rearrangements and segmental duplications through trajectory graphs.

We study the problem of sorting genomes under an evolutionary model that includes genomic rearrangements and segmental duplications. We propose an iterative algorithm to improve any initial evolutionary trajectory between two genomes in terms of parsimony. Our algorithm is based on a new graphical model, the trajectory graph, which models not only the final states of two genomes but also an existing evolutionary trajectory between them.

A transcript perspective on evolution.

Alternative splicing is now recognized as a major mechanism for transcriptome and proteome diversity in higher eukaryotes, yet its evolution is poorly understood. Most studies focus on the evolution of exons and introns at the gene level, while only few consider the evolution of transcripts. In this paper, we present a framework for transcript phylogenies where ancestral transcripts evolve along the gene tree by gains, losses, and mutation.

Maximum likelihood phylogenetic reconstruction from high-resolution whole-genome data and a tree of 68 eukaryotes.

The rapid accumulation of whole-genome data has renewed interest in the study of the evolution of genomic architecture, under such events as rearrangements, duplications, losses. Comparative genomics, evolutionary biology, and cancer research all require tools to elucidate the mechanisms, history, and consequences of those evolutionary events, while phylogenetics could use whole-genome data to enhance its picture of the Tree of Life. Current approaches in the area of phylogenetic analysis are limited to very small collections of closely related genomes using low-resolution data (typically a few hundred syntenic blocks); moreover, these approaches typically do not include duplication and loss events.

TIBA: a tool for phylogeny inference from rearrangement data with bootstrap analysis.

TIBA is a tool to reconstruct phylogenetic trees from rearrangement data that consist of ordered lists of synteny blocks (or genes), where each synteny block is shared with all of its homologues in the input genomes. The evolution of these synteny blocks, through rearrangement operations, is modelled by the uniform Double-Cut-and-Join model. Using a true distance estimate under this model and simple distance-based methods, TIBA reconstructs a phylogeny of the input genomes.

Bootstrapping phylogenies inferred from rearrangement data.

Background: Large-scale sequencing of genomes has enabled the inference of phylogenies based on the evolution of genomic architecture, under such events as rearrangements, duplications, and losses. Many evolutionary models and associated algorithms have been designed over the last few years and have found use in comparative genomics and phylogenetic inference. However, the assessment of phylogenies built from such data has not been properly addressed to date.

ChIPnorm: a statistical method for normalizing and identifying differential regions in histone modification ChIP-seq libraries.

The advent of high-throughput technologies such as ChIP-seq has made possible the study of histone modifications. A problem of particular interest is the identification of regions of the genome where different cell types from the same organism exhibit different patterns of histone enrichment. This problem turns out to be surprisingly difficult, even in simple pairwise comparisons, because of the significant level of noise in ChIP-seq data.

Inferring transcript phylogenies.

Alternative splicing, an unknown mechanism 20 years ago, is now recognized as a major mechanism for proteome and transcriptome diversity, particularly in mammals–some researchers conjecture that up to 90% of human genes are alternatively spliced. Despite much research on exon and intron evolution, little is known about the evolution of transcripts. In this paper, we present a model of transcript evolution and an associated algorithm to reconstruct transcript phylogenies.

Refining regulatory networks through phylogenetic transfer of information.

The experimental determination of transcriptional regulatory networks in the laboratory remains difficult and timeconsuming, while computational methods to infer these networks provide only modest accuracy. The latter can be attributed partly to the limitations of a single-organism approach. Computational biology has long used comparative and evolutionary approaches to extend the reach and accuracy of its analyses.

A metric for phylogenetic trees based on matching.

Comparing two or more phylogenetic trees is a fundamental task in computational biology. The simplest outcome of such a comparison is a pairwise measure of similarity, dissimilarity, or distance. A large number of such measures have been proposed, but so far all suffer from problems varying from computational cost to lack of robustness; many can be shown to behave unexpectedly under certain plausible inputs.

FluReF, an automated flu virus reassortment finder based on phylogenetic trees.

Background: Reassortments are events in the evolution of the genome of influenza (flu), whereby segments of the genome are exchanged between different strains. As reassortments have been implicated in major human pandemics of the last century, their identification has become a health priority. While such identification can be done "by hand" on a small dataset, researchers and health authorities are building up enormous databases of genomic sequences for every flu strain, so that it is imperative to develop automated identification methods.