Liying Cui

Methods for Obtaining and Analyzing Whole Chloroplast Genome Sequences

During the past decade, there has been a rapid increase in our understanding of plastid genome organization and evolution due to the availability of many new completely sequenced genomes. There are 45 complete genomes published and ongoing projects are likely to increase this sampling to nearly 200 genomes during the next 5 years. Several groups of researchers including ours have been developing new techniques for gathering and analyzing entire plastid genome sequences and details of these developments are summarized in this chapter. The most important developments that enhance our ability to generate whole chloroplast genome sequences involve the generation of pure fractions of chloroplast genomes by whole genome amplification using rolling circle amplification, cloning genomes into Fosmid or bacterial artificial chromosome (BAC) vectors, and the development of an organellar annotation program (Dual Organellar GenoMe Annotator [DOGMA]). In addition to providing details of these methods, we provide an overview of methods for analyzing complete plastid genome sequences for repeats and gene content, as well as approaches for using gene order and sequence data for phylogeny reconstruction. This explosive increase in the number of sequenced plastid genomes and improved computational tools will provide many insights into the evolution of these genomes and much new data for assessing relationships at deep nodes in plants and other photosynthetic organisms.

ChloroplastDB: the Chloroplast Genome Database

The Chloroplast Genome Database (ChloroplastDB) is an interactive, web-based database for fully sequenced plastid genomes, containing genomic, protein, DNA and RNA sequences, gene locations, RNA-editing sites, putative protein families and alignments (). With recent technical advances, the rate of generating new organelle genomes has increased dramatically. However, the established ontology for chloroplast genes and gene features has not been uniformly applied to all chloroplast genomes available in the sequence databases. For example, annotations for some published genome sequences have not evolved with gene naming conventions. ChloroplastDB provides unified annotations, gene name search, BLAST and download functions for chloroplast encoded genes and genomic sequences. A user can retrieve all orthologous sequences with one search regardless of gene names in GenBank. This feature alone greatly facilitates comparative research on sequence evolution including changes in gene content, codon usage, gene structure and post-transcriptional modifications such as RNA editing. Orthologous protein sets are classified by TribeMCL and each set is assigned a standard gene name. Over the next few years, as the number of sequenced chloroplast genomes increases rapidly, the tools available in ChloroplastDB will allow researchers to easily identify and compile target data for comparative analysis of chloroplast genes and genomes.

EST clustering error evaluation and correction

MOTIVATIONnThe gene expression intensity information conveyed by (EST) Expressed Sequence Tag data can be used to infer important cDNA library properties, such as gene number and expression patterns. However, EST clustering errors, which often lead to greatly inflated estimates of obtained unique genes, have become a major obstacle in the analyses. The EST clustering error structure, the relationship between clustering error and clustering criteria, and possible error correction methods need to be systematically investigated.nnnRESULTSnWe identify and quantify two types of EST clustering error, namely, Type I and II in EST clustering using CAP3 assembling program. A Type I error occurs when ESTs from the same gene do not form a cluster whereas a Type II error occurs when ESTs from distinct genes are falsely clustered together. While the Type II error rate is <1.5% for both 5 and 3 EST clustering, the Type I error in the 5 EST case is approximately 10 times higher than the 3 EST case (30% versus 3%). An over-stringent identity rule, e.g., P >/= 95%, may even inflate the Type I error in both cases. We demonstrate that approximately 80% of the Type I error is due to insufficient overlap among sibling ESTs (ISO error) in 5 EST clustering. A novel statistical approach is proposed to correct ISO error to provide more accurate estimates of the true gene cluster profile.

Adaptive evolution of chloroplast genome structure inferred using a parametric bootstrap approach

BackgroundGenome rearrangements influence gene order and configuration of gene clusters in all genomes. Most land plant chloroplast DNAs (cpDNAs) share a highly conserved gene content and with notable exceptions, a largely co-linear gene order. Conserved gene orders may reflect a slow intrinsic rate of neutral chromosomal rearrangements, or selective constraint. It is unknown to what extent observed changes in gene order are random or adaptive. We investigate the influence of natural selection on gene order in association with increased rate of chromosomal rearrangement. We use a novel parametric bootstrap approach to test if directional selection is responsible for the clustering of functionally related genes observed in the highly rearranged chloroplast genome of the unicellular green alga Chlamydomonas reinhardtii, relative to ancestral chloroplast genomes.ResultsAncestral gene orders were inferred and then subjected to simulated rearrangement events under the random breakage model with varying ratios of inversions and transpositions. We found that adjacent chloroplast genes in C. reinhardtii were located on the same strand much more frequently than in simulated genomes that were generated under a random rearrangement processes (increased sidedness; p < 0.0001). In addition, functionally related genes were found to be more clustered than those evolved under random rearrangements (p < 0.0001). We report evidence of co-transcription of neighboring genes, which may be responsible for the observed gene clusters in C. reinhardtii cpDNA.ConclusionSimulations and experimental evidence suggest that both selective maintenance and directional selection for gene clusters are determinants of chloroplast gene order.

Phylogenetic reconstruction from arbitrary gene-order data

Phylogenetic reconstruction from gene-order data has attracted attention from both biologists and computer scientists over the last few years. So far, our software suite GRAPPA is the most accurate approach, but it requires that all genomes have identical gene content, with each gene appearing exactly once in each genome. Some progress has been made in handling genomes with unequal gene content, both in terms of computing pair-wise genomic distances and in terms of reconstruction. In this paper, we present a new approach for computing the median of three arbitrary genomes and apply it to the reconstruction of phylogenies from arbitrary gene-order data. We implemented these methods within GRAPPA and tested them on simulated datasets under various conditions as well as on a real dataset of chloroplast genomes; we report the results of our simulations and our analysis of the real dataset and compare them to reconstructions made by using neighbor-joining and using the original GRAPPA on the same genomes with equalized gene contents. Our new approach is remarkably accurate both in simulations and on the real dataset, in contrast to the distance-based approaches and to reconstructions using the original GRAPPA applied to equalized gene contents.

Gene capture prediction and overlap estimation in EST sequencing from one or multiple libraries

BackgroundIn expressed sequence tag (EST) sequencing, we are often interested in how many genes we can capture in an EST sample of a targeted size. This information provides insights to sequencing efficiency in experimental design, as well as clues to the diversity of expressed genes in the tissue from which the library was constructed.ResultsWe propose a compound Poisson process model that can accurately predict the gene capture in a future EST sample based on an initial EST sample. It also allows estimation of the number of expressed genes in one cDNA library or co-expressed in two cDNA libraries. The superior performance of the new prediction method over an existing approach is established by a simulation study. Our analysis of four Arabidopsis thaliana EST sets suggests that the number of expressed genes present in four different cDNA libraries of Arabidopsis thaliana varies from 9155 (root) to 12005 (silique). An observed fraction of co-expressed genes in two different EST sets as low as 25% can correspond to an actual overlap fraction greater than 65%.ConclusionThe proposed method provides a convenient tool for gene capture prediction and cDNA library property diagnosis in EST sequencing.

Gene rearrangement analysis and ancestral order inference from chloroplast genomes with inverted repeat

BackgroundGenome evolution is shaped not only by nucleotide substitutions, but also by structural changes including gene and genome duplications, insertions, deletions and gene order rearrangements. The most popular methods for reconstructing phylogeny from genome rearrangements include GRAPPA and MGR. However these methods are limited to cases where equal gene content or few deletions can be assumed. Since conserved duplicated regions are present in many chloroplast genomes, the inference of inverted repeats is needed in chloroplast phylogeny analysis and ancestral genome reconstruction.ResultsWe extend GRAPPA and develop a new method GRAPPA-IR to handle chloroplast genomes. A test of GRAPPA-IR using divergent chloroplast genomes from land plants and green algae recovers the phylogeny congruent with prior studies, while analysis that do not consider IR structure fail to obtain the accepted topology. Our extensive simulation study also confirms that GRAPPA has better accuracy then the existing methods.ConclusionsTests on a biological and simulated dataset show GRAPPA-IR can accurately recover the genome phylogeny as well as ancestral gene orders. Close analysis of the ancestral genome structure suggests that genome rearrangement in chloroplasts is probably limited by inverted repeats with a conserved core region. In addition, the boundaries of inverted repeats are hot spots for gene duplications or deletions. The new GRAPPA-IR is available from http://phylo.cse.sc.edu.