Project description:Subsequently, using a combination of BSA-seq, transcriptomic sequencing (RNA-seq), and proteomic sequencing approaches, we identified the candidate gene Nitab4.5_0008674g0010 that encodes dihydroneopterin aldolase as a factor associated with tobacco leaf yellowing.
Project description:ATAC-seq analysis of wild type C. albicans and a HIR1 gene deletion mutant during nutrient rich growth (YPD) and upon the shift to nitrogen starvation in yeast carbon base medium supplemented with BSA (YCB-BSA medium).
Project description:DDA analysis of samples of commercial tryptic peptides of BSA which had been either untreated ("original"), conjugated with the Harnimarta et al sequencing reagent ("conj") or conjugated and exposed to alkaline cleavage conditions ("seq"). Data was searched in Proteome Discoverer 2.5 using a 58.017 Da for the sequencing reagent dynamic modification. The associated BSA2 fasta includes a synthetic sequence to generate in silico tryptic peptides representing the original BSA tryptic peptides lacking a single N-terminal amino acid.
Project description:Targeted genomic enrichment followed by next-generation sequencing dramatically increased the efficiency of mutation discovery in human genomes. Here we demonstrate that these techniques also revolutionize traditional genetic approaches in model systems. We developed a two-step protocol utilizing a traditional bulk-segregant analysis (BSA) approach for positional cloning mutants in phenotype-driven forward genetic screens. First, BSA pools are 'light' sequenced for rough mapping, followed by targeted enrichment and deep-sequencing of the mutant BSA pool for the linked genomic region to fine-map and discover candidate mutations. We applied this method successfully to three Arabidopsis mutants and show that it can be scaled by multiplexing. Similarly, we applied these techniques to a gene-driven reverse genetics method (chemical driven target-selected mutagenesis or TILLING) that is used for generating gene knockouts in a wide range of organisms, including plants, invertebrates and vertebrates. We developed an efficient multiplexed genomic enrichment protocol for pre-barcoded samples. As a proof-of-principle, 770 genes were screened for induced mutations in 30 rats, which identified all but one known variants (30) as well as a large series of novel knockout and missense alleles. Mutations were retrieved at the expected frequency with a the false-positive rate of less than 1 in 6 million basepairs, which is much lower as compared to traditional mutation discovery approaches. Both methods are largely independent of the genome size due to the targeted enrichment and can thus be applied to any genetic model system of interest. Targeted genomic enrichment followed by next-generation sequencing dramatically increased the efficiency of mutation discovery in human genomes. Here we demonstrate that these techniques also revolutionize traditional genetic approaches in model systems. We developed a two-step protocol utilizing a traditional bulk-segregant analysis (BSA) approach for positional cloning mutants in phenotype-driven forward genetic screens. First, BSA pools are 'light' sequenced for rough mapping, followed by targeted enrichment and deep-sequencing of the mutant BSA pool for the linked genomic region to fine-map and discover candidate mutations. We applied this method successfully to three Arabidopsis mutants and show that it can be scaled by multiplexing. Similarly, we applied these techniques to a gene-driven reverse genetics method (chemical driven target-selected mutagenesis or TILLING) that is used for generating gene knockouts in a wide range of organisms, including plants, invertebrates and vertebrates. We developed an efficient multiplexed genomic enrichment protocol for pre-barcoded samples. As a proof-of-principle, 770 genes were screened for induced mutations in 30 rats, which identified all but one known variants (30) as well as a large series of novel knockout and missense alleles. Mutations were retrieved at the expected frequency with a the false-positive rate of less than 1 in 6 million basepairs, which is much lower as compared to traditional mutation discovery approaches. Both methods are largely independent of the genome size due to the targeted enrichment and can thus be applied to any genetic model system of interest.