RESUMO
BACKGROUND: Cassava, Manihot esculenta Crantz, is one of the most important crops world-wide representing the staple security for more than one billion of people. The development of dense genetic and physical maps, as the basis for implementing genetic and molecular approaches to accelerate the rate of genetic gains in breeding program represents a significant challenge. A reference genome sequence for cassava has been made recently available and community efforts are underway for improving its quality. Cassava is threatened by several pathogens, but the mechanisms of defense are far from being understood. Besides, there has been a lack of information about the number of genes related to immunity as well as their distribution and genomic organization in the cassava genome. RESULTS: A high dense genetic map of cassava containing 2,141 SNPs has been constructed. Eighteen linkage groups were resolved with an overall size of 2,571 cM and an average distance of 1.26 cM between markers. More than half of mapped SNPs (57.4%) are located in coding sequences. Physical mapping of scaffolds of cassava whole genome sequence draft using the mapped markers as anchors resulted in the orientation of 687 scaffolds covering 45.6% of the genome. One hundred eighty nine new scaffolds are anchored to the genetic cassava map leading to an extension of the present cassava physical map with 30.7 Mb. Comparative analysis using anchor markers showed strong co-linearity to previously reported cassava genetic and physical maps. In silico based searching for conserved domains allowed the annotation of a repertory of 1,061 cassava genes coding for immunity-related proteins (IRPs). Based on physical map of the corresponding sequencing scaffolds, unambiguous genetic localization was possible for 569 IRPs. CONCLUSIONS: This is the first study reported so far of an integrated high density genetic map using SNPs with integrated genetic and physical localization of newly annotated immunity related genes in cassava. These data build a solid basis for future studies to map and associate markers with single loci or quantitative trait loci for agronomical important traits. The enrichment of the physical map with novel scaffolds is in line with the efforts of the cassava genome sequencing consortium.
Assuntos
Mapeamento Cromossômico , Genoma de Planta , Manihot/genética , Imunidade Vegetal/genética , Análise por Conglomerados , Ligação Genética , Marcadores Genéticos , Genótipo , Proteínas de Plantas/genética , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas , Análise de Sequência de DNARESUMO
La secuenciación de transcritos con RNA-Seq es hoy en día una de las técnicas más populares en los estudios transcriptómicos. Relativamente reciente, esta técnica ha permitido la secuenciación de transcritos de RNA en una escala y profundidad no alcanzada por otras técnicas anteriores. Sin embargo, el alcance de las conclusiones que se pueden sacar depende estrictamente de un proceso adecuado, desde el diseño experimental hasta el análisis bioinformático de los datos. Dadas las diferencias en el proceso transcripcional de las células eucariotas y procariotas, el análisis de RNA-Seq deberá tener ciertas consideraciones dependiendo del tipo de organismo estudiado. En esta revisión se exponen los principales factores a tener en cuenta para lograr un análisis de RNA-Seq consistente, replicable y concluyente, enfocándose específicamente en organismos procariotas.
RNA-Seq is nowadays the method of choice for the sequencing of transcripts and transcriptomes in the field of molecular biology and gene expression assays. Until recently, this technique has allowed for the sequencing of RNA transcripts in an unprecedented scale and depth never reached in previous years; nevertheless, the reach and validity of the conclusions generated will depend strictly on an adequate experimental design and a robust analysis of the data. Given the inherent differences between prokaryotes and eukaryotes, the RNA-Seq analysis should take into account the type of organism studied. In this review we present the main factors to take into consideration when designing a consistent analysis for this type of data in prokaryotes, from the experimental design to the in silico analysis of the generated data.