Identifying marker-trait associations for Fiber Components in Sugarcane with Simple Sequence Repeat Markers
Poster Jan 09, 2015
Karine Kettener; Natalia Spagnol Stabellini, Marcia Moreno, Karine Miranda Oliveira, Itaraju Brum, Francisco Claudio da Conceicao Lopes, Thiago Benatti, Alessandro Pellegrineschi; Jorge A. da Silva; Celso Luis Marino.
Modern sugarcane varieties are derived from interspecific hybridization between Saccharum officinarum and Saccharum spontaneum, resulting in highly polyploid and aneuploid plants with chromosome number ranging from 80 to 140. The identification of marker-trait associations can expedite breeding programs by reducing the cycle of selection through the indirect identification of plants with desirable traits. Here we describe 26 marker-trait associations to lignin and cellulose content in 250 individuals derived from a bi-parental cross between two elite clones from the CTC’s (Centro de Tecnologia Canavieira) breeding program (Brazil). Lignin and cellulose content analyses were performed at the plant cane and first ratoon stages by Near Infrared. Seventy Expressed Sequence Tags Single Sequence Repeats (EST-SSR), obtained from the lignin and cellulose biochemical pathways, and 15 genomic Single Sequence Repeats (gSSR) were screened in the population, producing 157 polymorphic markers. Only single dose markers were considered, in a total of 64. A Single-Marker Analysis for both lignin and cellulose content was performed by maximum likelihood tests in models considering one marker at a time. Overall, 26 marker-trait associations were found at P<0.05 (13 markers with cellulose and 13 with lignin). Ten markers (38%) were aligned to the sorghum genome and mapped in the chromosomes 1, 2, 4 and 7. There are evidences that, in sorghum, chromosome 1 is related to cellulose and chromosomes 2, 4 and 7 to hemicellulose content, thus confirming that SSRs, conserved in sugarcane and sorghum, would be informative for mapping quantitative trait loci in sugarcane. Multiple linear regression determined the ratio of phenotypic variance explained by the association between SSR markers and traits (R2). These SSRs are explaining 18% in Lignin content and 27% in Cellulose content. These markers can be useful if applied in marker-assisted selection and genomic studies.
Characterization of a Type 2 diabetes-associated islet-specific enhancer cluster in STARD10 by genome editing of EndoC-βH1 cellsPoster
Genome-wide association studies (GWAS) have identified more than 100 genetic loci associated with type 2 diabetes. The majority of these are located in the intergenic or intragenic regions suggesting that the implicated variants may alter chromatin conformation. This, in turn, is likely to influence the expression of nearby or more remotely located genes to alter beta cell function. At present, however, detailed molecular and functional analyses are still lacking for most of these variants. We recently analysed one of these loci and mapped five causal variants in an islet-specific enhancer cluster within the STARD10 gene locus. Here, we aimed to understand how these causal variants influence b-cell function by alteration of the chromatin structure of enhancer clusterREAD MORE
Psychiatric Risk Gene Cacna1c and Early Life Stress: Potential Gene-Environment interactions?Poster
Early life stress (ELS) is highly associated with development of psychopathology
and mood disorders in adulthood. Genetic studies have identified variation in the gene calcium voltage-gated channel subunit alpha1C (CACNA1C) to increase risk for several psychiatric disorders. This poster assessed the expression of Cacna1c following prepubertal stress.
The Role of K13 in Artemisinin ResistancePoster
Plasmodium falciparum is evolving resistance to Artemisinin Combination Therapy. The gene with the strongest association with resistance is K13. K13 is an ortholog of the well characterized transcriptional regulator Keap1. In this work we transcriptionally characterized a mutant with a transposon inserted in the K13 promoter region which results in dysregulation of K13 at 2 points of the intraerythrocytic cycle of the life-cycle to identify the processes regulated by K13.READ MORE