Ontology highlight
ABSTRACT:
PROVIDER: PRJEB73817 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| EUChip60K_Edunnii_v2.vcf.csi | Other | |||
| EUChip60K_Edunnii_v2.vcf.gz | Vcf | |||
| ddRADseq_Edunnii_v3.vcf.csi | Other | |||
| ddRADseq_Edunnii_v3.vcf.gz | Vcf |
Items per page: 5 1 - 4 of 4 |
Similar Datasets
Project description:Comparative performance of two high-throughput genotyping systems, ddRADseq and the SNP platform EUChip60K, for population genetics analyses and Genomic Selection application in Eucalyptus dunnii
2024-03-15 | PRJEB73817 | EVA
Project description:Eucalyptus dunnii Transcriptome or Gene expression
| PRJNA248093 | ENA
Project description:This SuperSeries is composed of the following subset Series: GSE24130: Gene expression in xylem tissue on an Eucalyptus pseudo-testcross population: discovery array probes GSE24195: Gene expression in xylem tissue on an Eucalyptus pseudo-testcross population: genotyping subset of discovery array probes Refer to individual Series
2010-09-18 | E-GEOD-24196 | biostudies-arrayexpress
Project description:Estimating the relationships between individuals is one of the fundamental challenges in many fields. In particular, relationship estimation could provide valuable information for missing persons cases. The recently developed investigative genetic genealogy approach uses high-density single nucleotide polymorphisms (SNPs) to determine close and more distant relationships, in which hundreds of thousands to tens of millions of SNPs are generated either by microarray genotyping or whole-genome sequencing. The current studies usually assume the SNP profiles were generated with minimum errors. However, in the missing person cases, the DNA samples can be highly degraded, and the SNP profiles generated from these samples usually contain lots of errors. In this study, a robust machine learning approach was developed for estimating the relationships with high error SNP profiles. In this approach, a hierarchical classification strategy was employed first to classify the relationships by degree and then the relationship types within each degree separately. As for each classification, feature selection was implemented to gain better performance. Both simulated and real data sets with various genotyping error rates were utilized in evaluating this approach, and the accuracies of this approach were higher than individual measures; namely, this approach was more accurate and robust than the individual measures for SNP profiles with genotyping errors. In addition, the highest accuracy could be obtained by providing the same genotyping error rates in train and test sets, and thus estimating genotyping errors of the SNP profiles is critical to obtaining high accuracy of relationship estimation.
2022-07-27 | GSE209804 | GEO
Project description:Comparison of Genotyping using pooled DNA samples (Allelotyping) and Individual Genotyping using the Affymetrix Genome-Wide Human SNP Array 6.0 In this study, data from 100 DNA samples individually genotyped with the Affymetrix Genome-Wide Human SNP Array 6.0 were used to estimate the error of the pooling approach by comparing the results with those obtained using the same array type but DNA pools each composed of 50 of the same samples. Newly developed and established methods for signal intensity correction were applied. Furthermore, the relative allele intensity signals (RAS) obtained by allelotyping were compared to the corresponding values derived from individual genotyping. Similarly, differences in RAS values between pools were determined and compared.
2013-06-22 | GSE48190 | GEO
Project description:A deeper understanding of the genetics of rice grain starch structure is crucial in tailoring grain digestibility and ensuring cooking quality to meet consumer preferences. Significant association peaks on chromosomes 6 and 7 were identified through genome-wide association study (GWAS) of debranched starch structure from grains of a 320 indica rice diversity panel using genotyping data from the high-density rice array. A systems genetics approach that interrelates starch structure data from GWAS to functional pathways from a gene regulatory network identified known and novel genes with high correlation to the proportion of amylose and amylopectin. A novel SNP in the promoter region of Granule Bound Starch Synthase I (GBSS I) was identified along with seven other SNPs to form haplotypes that discriminate samples into different phenotypic ranges of amylose. A novel GWAS peak on chromosome 7 between LOC_Os07g11020 and LOC_Os07g11520 indexed by a non-synonymous SNP mutation on exon 5 of a bHLH transcription factor was found to elevate the proportion of amylose at the expense of reduced short-chain amylopectin. Linking starch structure with starch digestibility by determining the kinetics of cooked grain amylolysis of selected haplotypes revealed strong association of starch structure with estimated digestibility kinetics. Combining all results from grain quality genomics, systems genetics, and digestibility phenotyping, we propose novel target haplotypes for fine-tuning starch structure in rice through marker-assisted breeding that can be used to alter the digestibility of rice grain, thus offering rice consumers a new diet-based intervention to mitigate the impact of nutrition-related non-communicable diseases.
2016-11-29 | GSE90576 | GEO
Project description:SNP genotyping of human breast tumors
2019-04-17 | GSE100529 | GEO
Project description:Bread aroma is the principal characteristic perceived by the consumer yet it is mostlydisregarded in the product chain. The main aim of this study was to evaluate the potential toinclude bread aroma as a new target criterion into the wheat product chain. The objectivesof our study were to (i) quantify the influence of genetic versus environmental factors onthe bread aroma and quality characteristics, (ii) evaluate whether bread baked from modernwheat varieties differ in terms of aroma from those baked from old varieties and (iii) comparegenomic and metabolomic approaches for their efficiency to predict bread aroma and qualitycharacteristics in a wheat breeding program. Agronomic characters as well as bread aroma andquality traits were assessed for 18 old and 22 modern winter wheat varieties evaluated at up tothree locations in Germany. Metabolite profiles of all 120 flour samples were collected using a7200 GC-QTOF. Considerable differences in the adjusted entry means for all examined breadaroma and quality characters were observed. For aroma, which was rated on a scale from 1 to9, the adjusted entry means varied for the 40 wheat varieties between 3 and 8. In contrast,the aroma of bread prepared from old and modern wheat varieties did not differ significantly(P<0.05). Bread aroma was not significantly (P<0.05) correlated with grain yield, whichsuggested that it is possible to select for the former character in wheat breeding programswithout reducing the gain of selection for the latter. Finally, we have shown that bread aromacan be better predicted using a combination of metabolite and SNP genotyping profiles insteadof the SNP genotyping profile only. In conclusion, we have illustrated possibilities to increasethe quality of wheat for consumers in the product chain.
2019-11-12 | MTBLS1187 | MetaboLights