From: Michel Salomon Date: Tue, 19 Nov 2013 10:24:06 +0000 (+0100) Subject: Modifications made in the two first sections X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/chloroplast13.git/commitdiff_plain/0f2f8faba6ce0dbfd8f3e8df9d31f67756cff6c1 Modifications made in the two first sections --- diff --git a/abstract.tex b/abstract.tex index 9b3c438..3c789e3 100644 --- a/abstract.tex +++ b/abstract.tex @@ -1,20 +1,20 @@ \begin{abstract} -DNA analysis techniques have received a lot of attention these last -years, because they play an important role in understanding -genomes evolution over time, and in phylogenetic and genetic analyses. Various models -of genomes evolution are based on the analysis of DNA sequences, SNPs, -mutations, and so on. We have recently investigated the use of -core (\emph{i.e.}, common genes) and pan genomes to infer evolutionary information -on a collection of 107 chloroplasts. In particular, -we have regarded methods to build a genes content evolutionary tree using -distances to core genome. However, -the production of reliable core and pan genomes is not an easy task, -due to error annotations of the NCBI. The presentation will then -consist in various compared approaches to construct such a tree using -fully annotated genomes by NCBI and Dogma, followed by a gene quality -control among the common genes. We will finally explain how, by comparing -sequences from Dogma with NCBI contents, we achieved to identify the -genes that play a key role in the dynamics of genomes evolution. \\ +DNA analysis techniques have received a lot of attention these last +years, because they play an important role in understanding genomes +evolution over time, and in phylogenetic and genetic analyses. Various +models of genomes evolution are based on the analysis of DNA +sequences, SNPs, mutations, and so on. We have recently investigated +the use of core (\emph{i.e.}, common genes) and pan genomes to infer +evolutionary information on a collection of 107 chloroplasts. In +particular, we have regarded methods to build a genes content +evolutionary tree using distances to core genome. However, the +production of reliable core and pan genomes is not an easy task, due +to error annotations. We will first compare different approaches to +construct such a tree using fully annoted genomes provided by NCBI and +Dogma, followed by a gene quality control among the common genes. Then +we will explain how, by comparing sequences from Dogma with NCBI +contents, we achieved to identify the genes that play a key role in +the dynamics of genomes evolution. \textbf{Keywords:} genome evolution, phylogenetic tree, core genes, evolution tree, genome annotation -\end{abstract} \ No newline at end of file +\end{abstract} diff --git a/annotated.tex b/annotated.tex index 762d50c..3a7fbd1 100644 --- a/annotated.tex +++ b/annotated.tex @@ -1,4 +1,26 @@ -The field of genome annotation pays a lot of attentions where the ability to collect and analysis genomical data can provide strong indicators for the study of life\cite{Eisen2007}. Four of genome annotation centers (such as, \textit{NCBI\cite{Sayers01012011}, Dogma \cite{RDogma}, cpBase \cite{de2002comparative}, CpGAVAS \cite{liu2012cpgavas}, and CEGMA\cite{parra2007cegma}}) present various types of annotation tools (\emph{i.e.} cost-effective sequencing methods\cite{Bakke2009}) on different annotation levels. Generally, previous studies used one of three methods for gene finding in annotated genome using these centers: \textit{alignment-based, composition based, or combination of both\cite{parra2007cegma}}. The alignment-based method is used when we try to predict a coding gene (\emph{i.e.}. genes that produce proteins) by aligning DNA sequence of gene to the protein of cDNA sequence of homology\cite{parra2007cegma}. This approach also is used in GeneWise\cite{birney2004genewise}. Composition-based method (known as \textit{ab initio}) is based on a probabilistic model of gene structure to find genes according to the gene value probability (GeneID\cite{parra2000geneid}). In this section, we consider a new method of finding core genes from large amount of chloroplast genomes, as a solution of the problem resulting from the method stated in section two. This method is based on extracting gene features. A general overview of the system is illustrated in Figure \ref{Fig1}.\\ +The field of genome annotation pays a lot of attentions where the +ability to collect and analysis genomical data can provide strong +indicators for the study of life\cite{Eisen2007}. Four of genome +annotation centers (such as, \textit{NCBI\cite{Sayers01012011}, +Dogma \cite{RDogma}, cpBase \cite{de2002comparative}, +CpGAVAS \cite{liu2012cpgavas}, and CEGMA\cite{parra2007cegma}}) +present various types of annotation tools (\emph{i.e.} cost-effective +sequencing methods\cite{Bakke2009}) on different annotation +levels. Generally, previous studies used one of three methods for gene +finding in annotated genome using these +centers: \textit{alignment-based, composition based, or combination of +both\cite{parra2007cegma}}. The alignment-based method is used when we +try to predict a coding gene (\emph{i.e.}. genes that produce +proteins) by aligning DNA sequence of gene to the protein of cDNA +sequence of homology\cite{parra2007cegma}. This approach also is used +in GeneWise\cite{birney2004genewise}. Composition-based method (known +as \textit{ab initio}) is based on a probabilistic model of gene +structure to find genes according to the gene value probability +(GeneID\cite{parra2000geneid}). In this section, we consider a new +method of finding core genes from large amount of chloroplast genomes, +as a solution of the problem resulting from the method stated in +section two. This method is based on extracting gene features. A +general overview of the system is illustrated in Figure \ref{Fig1}.\\ \begin{figure}[H] \centering diff --git a/classEquiv.tex b/classEquiv.tex index 41abda4..00b227d 100644 --- a/classEquiv.tex +++ b/classEquiv.tex @@ -1,28 +1,50 @@ -Identifying core genes is important to understand evolutionary and -functional phylogenies. Therefore, in this work we present two methods -to build a genes content evolutionary tree. More precisely, we focus -on the following questions considering a collection of -99~chloroplasts annotated from NCBI \cite{Sayers01012011} and Dogma -\cite{RDogma} : how can we identify the best core genome and what -is the evolutionary scenario of these chloroplasts. -Two methods are considered here. The first one is based on NCBI annotation, it is explained below. -We start by the following definition. + +The first method, described below, considers NCBI annotations and uses +a distance-based similarity measure. We start with the following +preliminary Definition: + \begin{definition} \label{def1} -Let $A=\{A,T,C,G\}$ be the nucleotides alphabet, and $A^\ast$ be the set of finite words on $A$ (\emph{i.e.}, of DNA sequences). Let $d:A^{\ast}\times A^{\ast}\rightarrow[0,1]$ be a distance on $A^{\ast}$. Consider a given value $T\in[0,1]$ called a threshold. For all $x,y\in A^{\ast}$, we will say that $x\sim_{d,T}y$ if $d(x,y)\leqslant T$. +Let $A=\{A,T,C,G\}$ be the nucleotides alphabet, and $A^\ast$ be the +set of finite words on $A$ (\emph{i.e.}, of DNA sequences). Let +$d:A^{\ast}\times A^{\ast}\rightarrow[0,1]$ be a distance on +$A^{\ast}$. Consider a given value $T\in[0,1]$ called a threshold. For +all $x,y\in A^{\ast}$, we will say that $x\sim_{d,T}y$ if +$d(x,y)\leqslant T$. \end{definition} -\noindent$\sim_{d,T}$ is obviously an equivalence relation. When $d=1-\Delta$, where $\Delta$ is the similarity scoring function embedded into the emboss package (Needleman-Wunch released by EMBL), we will simply denote $\sim_{d,0.1}$ by $\sim$. The method starts by building an undirected graph based on -the similarity rates $r_{ij}$ between sequences $g_{i}$ and $g_{j}$ (\emph{i.e.}, $r_{ij}=\Delta(g_{i},g_{j})$). -In this latter, nodes are constituted by all the coding sequences of the set of genomes under consideration, and there is an edge between $g_{i}$ and $g_{j}$ if the -similarity rate $r_{ij}$ is -greater than the given similarity threshold. The Connected Components -(CC) of the ``similarity'' graph are thus computed. -This produces an equivalence -relation between sequences in the same CC based on Definition~\ref{def1}. -Any class for this relation is called ``gene'' here, where its representatives (DNA sequences) are the ``alleles'' of this gene. Thus this first method produces for each genome $G$, which is a set $\{g_{1}^G,...,g_{m_G}^G\}$ of $m_{G}$ DNA coding sequences, the projection of each sequence according to $\pi$, where $\pi$ maps each sequence -into its gene (class) according to $\sim$. In other words, $G$ is mapped into $\{\pi(g_{1}^G),...,\pi(g_{m_G}^G)\}$. -Remark that a projected genome has no duplicated gene, as it is a set. The core genome (resp. the pan genome) of $G_{1}$ and $G_{2}$ is defined thus as the intersection (resp. as the union) of these projected genomes.\\ -We then consider the intersection of all the projected genomes, which is the set of all the genes $\dot{x}$ -such that each genome has at least one allele in $\dot{x}$. The pan genome is computed similarly as the union of all the projected genomes. However such approach suffers from producing too small core genomes, -for any chosen similarity threshold, compared to what is usually waited by biologists regarding these chloroplasts. We are then left with the following questions: how can we improve the confidence put in the produced core? Can we thus guess the evolution scenario of these genomes? \ No newline at end of file +\noindent $\sim_{d,T}$ is obviously an equivalence relation and when $d=1-\Delta$, where $\Delta$ is the similarity scoring function embedded into the emboss package (Needleman-Wunch released by EMBL), we will simply denote $\sim_{d,0.1}$ by $\sim$. + +The method begins by building an undirected graph based on similarity +rates $r_{ij}$ between DNA~sequences $g_{i}$ and $g_{j}$ (\emph{i.e.}, +$r_{ij}=\Delta\left(g_{i},g_{j}\right)$). In this latter graph, nodes +are constituted by all the coding sequences of the set of genomes +under consideration, and there is an edge between $g_{i}$ and $g_{j}$ +if the similarity rate $r_{ij}$ is greater than a given similarity +threshold. The Connected Components (CC) of the ``similarity'' graph +are thus computed. + +This process also results in an equivalence relation between sequences +in the same CC based on Definition~\ref{def1}. Any class for this +relation is called ``gene'' here, where its representatives +(DNA~sequences) are the ``alleles'' of this gene. Thus this first +method produces for each genome $G$, which is a set +$\left\{g_{1}^G,...,g_{m_G}^G\right\}$ of $m_{G}$ DNA coding +sequences, the projection of each sequence according to $\pi$, where +$\pi$ maps each sequence into its gene (class) according to $\sim$. In +other words, a genome $G$ is mapped into +$\left\{\pi(g_{1}^G),...,\pi(g_{m_G}^G)\right\}$. Note that a +projected genome has no duplicated gene since it is a set. + +Consequently, the core genome (resp. the pan genome) of two genomes +$G_{1}$ and $G_{2}$ is defined as the intersection (resp. as the +union) of their projected genomes. We then consider the intersection +of all the projected genomes, which is the set of all the genes +$\dot{x}$ such that each genome has at least one allele in +$\dot{x}$. The pan genome is computed similarly as the union of all +the projected genomes. However such approach suffers from producing +too small core genomes, for any chosen similarity threshold, compared +to what is usually expected by biologists regarding these +chloroplasts. We are then left with the following questions: how can +we improve the confidence put in the produced core? Can we thus guess +the evolution scenario of these genomes? diff --git a/intro.tex b/intro.tex index e69de29..84c9ed8 100644 --- a/intro.tex +++ b/intro.tex @@ -0,0 +1,7 @@ +Identifying core genes is important to understand evolutionary and +functional phylogenies. Therefore, in this work we present methods to +build a genes content evolutionary tree. More precisely, we focus on +the following questions considering a collection of 107~chloroplasts +annotated from NCBI \cite{Sayers01012011} and Dogma \cite{RDogma}: how +can we identify the best core genome and what is the evolutionary +scenario of these chloroplasts. diff --git a/main.tex b/main.tex index 921954b..65e70d4 100755 --- a/main.tex +++ b/main.tex @@ -16,30 +16,23 @@ \usepackage{tikz} \usetikzlibrary{shapes,arrows} - % correct bad hyphenation here \hyphenation{op-tical net-works semi-conduc-tor} - \begin{document} \title{Finding the core-genes of Chloroplast Species} - - \author{ -Bassam AlKindy, -Jean-Fran\c{c}ois Couchot, -Christophe Guyeux, -and Michel Salomon*\\ -FEMTO-ST Institute, UMR 6174 CNRS\\ -Computer Science Laboratory DISC, -University of Franche-Comt\'{e}, -Besan\c con, France.\\ -$*:$ Authors in alphabetic order.\\ +Bassam AlKindy\footnote{email: balkindy@femto-st.fr} \and Jean-Fran\c{c}ois Couchot +\and Christophe Guyeux \and Michel Salomon \and\\ +FEMTO-ST Institute, UMR 6174 CNRS, \\ +Computer Science Department DISC, \\ +University of Franche-Comt\'{e}, France \\ +{\small \it Authors in alphabetic order} } + \newcommand{\JFC}[1]{\begin{color}{green}\textit{}\end{color}} -\newcommand{\CG}[1]{\begin{color} -{blue}\textit{}\end{color}} +\newcommand{\CG}[1]{\begin{color}{blue}\textit{}\end{color}} % make the title area \maketitle @@ -49,22 +42,17 @@ $*:$ Authors in alphabetic order.\\ \section{Introduction}\label{sec:intro} \input{intro.tex} - -\section{Similarity-based Approach} -%input +\section{Similarity-based approach} % Main author : jfc \input{classEquiv} - - -\section{Annotated-based Approaches} +\section{Annotations-based approaches} % Main author : bassam \input{annotated} % \section{Second Stage: to Find Closed Genomes} % \input{closedgenomes} - \section{Conclusion}\label{sec:concl}