X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/chloroplast13.git/blobdiff_plain/b6d9122987057b1c8c45d6ca3ff752ea12ec9484..181fe86127b57e8c7df3e97082134e7a5b7b8618:/annotated.tex?ds=sidebyside diff --git a/annotated.tex b/annotated.tex index 6bd0d55..b43666b 100644 --- a/annotated.tex +++ b/annotated.tex @@ -295,11 +295,7 @@ names\_Accession number)}. While an edge is labelled with the number of lost genes from a leaf genome or an intermediate core gene. Such numbers are very interesting because they give an information about the evolution: how many genes were lost between two species whether -they belong to the same family or not. By the principle of -classification, a small number of genes lost among species indicates -that those species are close to each other and belong to same family, -while a large lost means that we have an evolutionary relationship -between species from different families. To depict the links between +they belong to the same lineage or not. Phylogenetic relationships are mainly built by comparison of sets of coding and non-coding sequences. Phylogenies of photosynthetic plants are important to assess the origin of chloroplasts (REF) and the modalities of gene loss among lineages. These phylogenies are usually done using less than ten chloroplastic genes (REF), and some of them may not be conserved by evolution process for every taxa. As phylogenetic relationships inferred from data matrices complete for each species included and with the same evolution history are better assumptions, we selected core genomes for a new investivation of photosynthetic plants phylogeny. To depict the links between species clearly, we built a phylogenetic tree showing the relationships based on the distances among genes sequences. Many tools are available to obtain a such tree, for example: @@ -345,9 +341,9 @@ for each method}\label{Etime} Method & \multicolumn{2}{c}{Annotation} & \multicolumn{2}{c}{Features} & \multicolumn{2}{c}{Exec. time (min.)} & \multicolumn{2}{c}{Core genes} & \multicolumn{2}{c}{Bad genomes} \\ ~ & N & D & Name & Seq & N & D & N & D & N & D \\ \hline -Gene prediction & $\surd$ & - & - & $\surd$ & ? & - & ? & - & 0 & -\\[0.5ex] -Gene features & $\surd$ & $\surd$ & $\surd$ & - & 4.98 & 1.52 & 28 & 10 & 1 & 0\\[0.5ex] -Gene quality & $\surd$ & $\surd$ & $\surd$ & $\surd$ & \multicolumn{2}{c}{$\simeq$3 days + 1.29} & \multicolumn{2}{c}{4} & \multicolumn{2}{c}{1}\\[1ex] +Gene prediction & $\surd$ & - & - & $\surd$ & 1.7 & - & ? & - & 0 & -\\[0.5ex] +Gene Features & $\surd$ & $\surd$ & $\surd$ & - & 4.98 & 1.52 & 28 & 10 & 1 & 0\\[0.5ex] +Gene Quality & $\surd$ & $\surd$ & $\surd$ & $\surd$ & \multicolumn{2}{c}{$\simeq$3 days + 1.29} & \multicolumn{2}{c}{4} & \multicolumn{2}{c}{1}\\[1ex] \hline \end{tabular} } @@ -407,7 +403,7 @@ depends on the size of each genome. \hline\hline Method& & Load Gen. & Conv. gV & Read gV & ICM & Core tree & Core Seq. \\ \hline -Gene prediction & ~ & ~ & ~ & ~ & ~ & ~ & ~\\ +Gene prediction & NCBI & 108 & - & - & - & - & -\\ \multirow{2}{*}{Gene Features} & NCBI & 15.4 & 18.9 & 17.5 & 18 & 18 & 28.1\\ & DOGMA& 15.3 & 15.3 & 16.8 & 17.8 & 17.9 & 31.2\\ Gene Quality & ~ & 15.3 & $\le$3G & 16.1 & 17 & 17.1 & 24.4\\