Project description:Background: Evolutionary engineering is a powerful approach to isolate suppressor mutants and industrially relevant genotypes. Until recently, DNA microarray analysis was the only affordable genome-wide approach to identify the responsible mutations. This situation has changed due to the rapidly decreasing costs of whole genome (re)sequencing. DNA microarray-based mRNA expression analysis and whole genome resequencing were combined in a study on lactate transport in Saccharomyces cerevisiae. Jen1p is the only S. cerevisiae lactate transporter reported in literature. To identify alternative lactate transporters, a jen1Δ strain was evolved for growth on lactate. Results: Two independent evolution experiments yielded Jen1p-independent growth on lactate (μmax 0.14 and 0.18 h-1 for single-cell lines IMW004 and IMW005, respectively). Whereas mRNA expression analysis did not provide leads, whole-genome resequencing showed different single nucleotide changes (C755G/Leu219Val and C655G/Ala252Gly) in the acetate transporter gene ADY2. Analysis of mRNA levels and depth of coverage of DNA sequencing combined with karyotyping, gene deletions and diagnostic PCR showed that in IMW004 an isochromosome III (~475 kb), which contains two additional copies of ADY2C755G, was formed via crossover between YCLWΔ15 and YCRCΔ6. Introduction of the ADY2 alleles in a jen1 ady2 strain resulted in growth on lactate (μmax 0.14 h-1 for Ady2pLeu219Val and 0.12 h-1 for Ady2pAla252Gly). Conclusions: Whole-genome resequencing of yeast strains obtained from independent evolution experiments enabled rapid identification of a key gene that was not identified by mRNA expression analysis of the same strains. Reverse metabolic engineering showed that mutated alleles of ADY2 (C655G and C755G) encode efficient lactate transporters.
Project description:Whole-genome resequencing of eight transcription factor mutants and one wild-type, in order to verify the T-DNA insertion site and its uniqueness.
Project description:We carried out a comparative genomic analysis of 48 avian species to identify avian-specific highly conserved elements (ASHCEs). We performed genome-wide chromatin immunoprecipitation sequencing (ChIP-seq) for three enhancer-associated histone modifications (H3K4me1, H3K27ac, H3K27me3), to investigate dynamic regulatory roles of ASHCEs in chicken development. We found that all three enhancer-associated histone marks are enriched in ASHCEs compared to the whole genome background.
Project description:A major effort is underway to study the natural variation within the model plant species, Arabidopsis thaliana. Much of this effort is focused on genome resequencing, however the translation of genotype to phenotype will be largely effected through variations within the transcriptomes at the sequence and expression levels. To examine the cross-talk between natural variation in genomes and transcriptomes, we have examined the transcriptomes of three divergent A. thaliana accessions using tiling arrays. Combined with genome resequencing efforts, we were able to adjust the tiling array datasets to account for polymorphisms between the accessions and therefore gain a more accurate comparison of the transcriptomes. The corrected results for the transcriptomes allowed us to correlate higher gene polymorphism with greater variation in transcript level among the accessions. Our results demonstrate the utility of combining genomic data with tiling arrays to assay non-reference accession transcriptomes.
Project description:A major effort is underway to study the natural variation within the model plant species, Arabidopsis thaliana. Much of this effort is focused on genome resequencing, however the translation of genotype to phenotype will be largely effected through variations within the transcriptomes at the sequence and expression levels. To examine the cross-talk between natural variation in genomes and transcriptomes, we have examined the transcriptomes of three divergent A. thaliana accessions using tiling arrays. Combined with genome resequencing efforts, we were able to adjust the tiling array datasets to account for polymorphisms between the accessions and therefore gain a more accurate comparison of the transcriptomes. The corrected results for the transcriptomes allowed us to correlate higher gene polymorphism with greater variation in transcript level among the accessions. Our results demonstrate the utility of combining genomic data with tiling arrays to assay non-reference accession transcriptomes.
Project description:A major effort is underway to study the natural variation within the model plant species, Arabidopsis thaliana. Much of this effort is focused on genome resequencing, however the translation of genotype to phenotype will be largely effected through variations within the transcriptomes at the sequence and expression levels. To examine the cross-talk between natural variation in genomes and transcriptomes, we have examined the transcriptomes of three divergent A. thaliana accessions using tiling arrays. Combined with genome resequencing efforts, we were able to adjust the tiling array datasets to account for polymorphisms between the accessions and therefore gain a more accurate comparison of the transcriptomes. The corrected results for the transcriptomes allowed us to correlate higher gene polymorphism with greater variation in transcript level among the accessions. Our results demonstrate the utility of combining genomic data with tiling arrays to assay non-reference accession transcriptomes. Wild type accessions Col-0, Bur-0 and C24 were grown on soil at 23M-BM-0C with a 16 hour light period. Inflorescence tissue up to floral stage 14 was used for RNA extraction. Samples were collected 7-8 hours into the light period, with tissue from five plants pooled for each sample. RNA samples were converted into double stranded and hybridized to whole genome tiling arrays (Affymetrix Arabidopis Tiling1.0RM-BM-.). Three biological replicates were performed for each accession.
Project description:A major effort is underway to study the natural variation within the model plant species, Arabidopsis thaliana. Much of this effort is focused on genome resequencing, however the translation of genotype to phenotype will be largely effected through variations within the transcriptomes at the sequence and expression levels. To examine the cross-talk between natural variation in genomes and transcriptomes, we have examined the transcriptomes of three divergent A. thaliana accessions using tiling arrays. Combined with genome resequencing efforts, we were able to adjust the tiling array datasets to account for polymorphisms between the accessions and therefore gain a more accurate comparison of the transcriptomes. The corrected results for the transcriptomes allowed us to correlate higher gene polymorphism with greater variation in transcript level among the accessions. Our results demonstrate the utility of combining genomic data with tiling arrays to assay non-reference accession transcriptomes. Wild type accessions Col-0 were grown on soil at 16M-BM-0C with a 16 hour light period. Inflorescence tissue up to floral stage 14 was used for RNA extraction. Samples were collected 7-8 hours into the light period, with tissue from five plants pooled for each sample. RNA samples were converted into double stranded and hybridized to whole genome tiling arrays (Affymetrix Arabidopis Tiling1.0RM-BM-.). Three biological replicates were performed for each accession.