Kona Typica variants
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB93727 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Anisakis typica Genome sequencing and assembly
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Project description:Anisakis typica Genome sequencing and assembly
| PRJNA997597 | ENA
Project description:The closely related Coffea arabica cultivars ‘Tall Mokka’ and ‘Typica’, with excellent flavor, but differing distinctively in the size of aerial organs, branching pattern and branch numbers. Differential gene expression analysis of shoot tips of arabica coffee cultivars 'Tall Mokka' and 'Typica' were done using Potato cDNA microarray as cross-species platform. Using cross-species microarray hybridization, we identified a prolyl oligopeptidase (CaPOP) gene as differentially expressed between the shoot tips of ‘Tall Mokka’ and ‘Typica’. Isolation and sequencing of POP genes from coffee identified three paralogs, CaPOP1, CaPOP2 and CaPOP3. All three genes were present in both cultivars, which suggest that differences in the expression of CaPOP are caused by factor(s) regulating the transcription of CaPOPs. CaPOP1 differs in sequence from CaPOP2 primarily in having two large deletions in the promoter region. CaPOP genes are homologous to arabidopsis At1g20380, encoding a post-proline cleaving enzyme that acts on substrates shorter than 30 amino acids. Ectopic expression of CaPOP1 under its native promoter in transgenic arabidopsis resulted in more secondary branches than in the wild type. This is the first study to successfully isolate CaPOP genes and characterize their expression in the developing tissues of coffee. This study also identified a novel role for prolyl oligopeptidase in control of branching.
2011-08-04 | GSE31179 | GEO
Project description:The closely related Coffea arabica cultivars ‘Tall Mokka’ and ‘Typica’, with excellent flavor, but differing distinctively in the size of aerial organs, branching pattern and branch numbers. Differential gene expression analysis of shoot tips of arabica coffee cultivars 'Tall Mokka' and 'Typica' were done using Potato cDNA microarray as cross-species platform. Using cross-species microarray hybridization, we identified a prolyl oligopeptidase (CaPOP) gene as differentially expressed between the shoot tips of ‘Tall Mokka’ and ‘Typica’. Isolation and sequencing of POP genes from coffee identified three paralogs, CaPOP1, CaPOP2 and CaPOP3. All three genes were present in both cultivars, which suggest that differences in the expression of CaPOP are caused by factor(s) regulating the transcription of CaPOPs. CaPOP1 differs in sequence from CaPOP2 primarily in having two large deletions in the promoter region. CaPOP genes are homologous to arabidopsis At1g20380, encoding a post-proline cleaving enzyme that acts on substrates shorter than 30 amino acids. Ectopic expression of CaPOP1 under its native promoter in transgenic arabidopsis resulted in more secondary branches than in the wild type. This is the first study to successfully isolate CaPOP genes and characterize their expression in the developing tissues of coffee. This study also identified a novel role for prolyl oligopeptidase in control of branching. Eight coffee trees of 'Typica' ('K') and six trees of 'Tall Mokka' ('M') cultivar were used in this study. The trees were equally divided into two groups 'A' and 'B' for each cultivar ('MA','MB', 'KA' and 'KB') and treated as biological replicates. Eight two channel microarray hybridizations were done in following pairs: MA x KA, MA x KB, MB x KA, MB x KB and dye swap replicate of each pair. Summary: Two-sample experiment: Tall Mokka vs. Typica . 8 Hybridizations. 2 Biological replicates per sample. 1 Dye swap per array.
2011-08-03 | E-GEOD-31179 | biostudies-arrayexpress
Project description:Human genome structural variants (SVs) are caused by diverse mutational mechanisms. We used orthogonal long- and short-read sequencing technologies to investigate end products of de novo chromosome 17p11.2 rearrangements and query the molecular mechanisms underlying both recurrent and non-recurrent events. For non-recurrent events we found microhomology and microhomeology at the breakpoint junctions, an excess of deletion rearrangements on paternally-derived haplotypes, and elucidated recalcitrant breakpoints. Our data indicate an increased rate of clustered single nucleotide variant mutation in cis that is not present with recurrent rearrangement of the genome at the same locus. Indel and single nucleotide mutations are associated with both copy number gains and losses of 17p11.2, occur up to ~1 Mb away from the breakpoint junctions, and favor C>G transversion substitutions; results suggesting that single stranded DNA is formed during the genesis of the SV and providing compelling support for a microhomology-mediated break-induced replication mechanism for SV formation.
2019-01-17 | GSE125208 | GEO
Project description:Human genome structural variants (SVs) are caused by diverse mutational mechanisms. We used orthogonal long- and short-read sequencing technologies to investigate end products of de novo chromosome 17p11.2 rearrangements and query the molecular mechanisms underlying both recurrent and non-recurrent events. For non-recurrent events we found microhomology and microhomeology at the breakpoint junctions, an excess of deletion rearrangements on paternally-derived haplotypes, and elucidated recalcitrant breakpoints. Our data indicate an increased rate of clustered single nucleotide variant mutation in cis that is not present with recurrent rearrangement of the genome at the same locus. Indel and single nucleotide mutations are associated with both copy number gains and losses of 17p11.2, occur up to ~1 Mb away from the breakpoint junctions, and favor C>G transversion substitutions; results suggesting that single stranded DNA is formed during the genesis of the SV and providing compelling support for a microhomology-mediated break-induced replication mechanism for SV formation.
2019-01-17 | GSE125209 | GEO
Project description:Human genome structural variants (SVs) are caused by diverse mutational mechanisms. We used orthogonal long- and short-read sequencing technologies to investigate end products of de novo chromosome 17p11.2 rearrangements and query the molecular mechanisms underlying both recurrent and non-recurrent events. For non-recurrent events we found microhomology and microhomeology at the breakpoint junctions, an excess of deletion rearrangements on paternally-derived haplotypes, and elucidated recalcitrant breakpoints. Our data indicate an increased rate of clustered single nucleotide variant mutation in cis that is not present with recurrent rearrangement of the genome at the same locus. Indel and single nucleotide mutations are associated with both copy number gains and losses of 17p11.2, occur up to ~1 Mb away from the breakpoint junctions, and favor C>G transversion substitutions; results suggesting that single stranded DNA is formed during the genesis of the SV and providing compelling support for a microhomology-mediated break-induced replication mechanism for SV formation.
2019-01-17 | GSE125207 | GEO
Project description:<p><strong>BACKGROUND:</strong> Genomic prediction (GP) based on single nucleotide polymorphisms (SNP) has become a broadly used tool to increase the gain of selection in plant breeding. However, using predictors that are biologically closer to the phenotypes such as transcriptome and metabolome may increase the prediction ability in GP. The objectives of this study were to (i) assess the prediction ability for three phenotypic traits using different omic datasets including sequence variants (SV), deleterious SV (dSV), tolerant SV (tSV), expression presence/absence variation (ePAV), gene expression (GE), transcript expression (TE), and metabolites (M) as single predictors in comparison to those using a SNP array; (ii) investigate the improvement in prediction ability when combining multiple omic datasets information to predict phenotypic variation in barley breeding programs; (iii) explore the relationship between genes and metabolites to unravel the metabolic pathway of the three above mentioned phenotypic traits.</p><p><strong>RESULTS:</strong> The prediction ability from genomic best linear unbiased prediction (GBLUP) for the three traits using dSV information was higher than when using tSV, all SV information, or the SNP array. Any predictors from the transcriptome (GE, TE, as well as ePAV) and metabolome provided higher prediction abilities compared to the SNP array and SV on average across the three traits. In addition, some (di)-similarity existed between different omic datasets, and therefore provided complementary biological perspectives to phenotypic variation. Optimal combining the information of dSV, TE, ePAV, as well as metabolites into GP models could improve the prediction ability over that of the single predictors alone.</p><p><strong>CONCLUSIONS:</strong> The use of integrated omic datasets in GP model is highly recommended. Furthermore, we evaluated a cost-effective approach generating 3’end mRNA sequencing with transcriptome data extracted from seedling without losing prediction ability in comparison to the full-length mRNA sequencing, paving the path for the use of such prediction methods in commercial breeding programs.</p>
2022-03-18 | MTBLS1561 | MetaboLights