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VCCS HEL and U937 cell line study: fresh and fixed cells

ABSTRACT: This study aims to determine the chromosome content and organisation of two myeloid leukaemia cell lines, HEL and U937. This will be done not only with SNP array data to determine breakpoints and copy number of copy number aberrations, but also with FISH (multicolour FISH, multicolour banding, centromere and single locus FISH) to identify translocation partners, chromosome organistion, centromere content, and provide some information on genome evolution in the cell line. Although several HEL SNP array karyotypes have been published and are available online the information here shows that there are some differences, and the additional FISH tests provide a greater depth of information on genome organisation and derivation of the abnormal chromosomes. The U937 cell line was also studied using DNA from fresh and fixed specimens for comparison of the quality of the SNP array data. Data from cells fixed using standard cytogenetic fixative (3:1 methanol:acetic acid) were compared to data from cells processed directly from tissue culture.

ORGANISM(S): Homo sapiens

PROVIDER: GSE41964 | GEO | 2013/11/30

SECONDARY ACCESSION(S): PRJNA178621

REPOSITORIES: GEO

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Project description:Many studies estimate that chromosomal mosaicism within the cleavage stage human embryo is high. However, comparison of two unique methods of aneuploidy screening of blastomeres within the same embryo has not been conducted and may indicate whether mosaicism is overestimated due to technical inconsistency rather than biological phenomena. The present study investigates the prevalence of chromosomal abnormality and mosaicism found with two different single cell aneuploidy screening techniques.Thirteen arrested cleavage stage embryos were studied. Each was biopsied into individual cells (n=160). The cells from each embryo were randomized into two groups. Those destined for FISH based aneuploidy screening (n=75) were fixed, 1 cell per slide. Cells for SNP microarray based aneuploidy screening (n=85) were put into individual tubes. Microarray was significantly more reliable (96%) than FISH (83%) for providing an interpretable result (P=0.004). Markedly different results were obtained when comparing microarray and FISH results from individual embryos. Mosaicism was significantly less commonly observed by microarray (4 of 13 embryos; 31%) than by FISH (13 of 13 embryos; 100%)(P=0.0005). Although FISH evaluated fewer chromosomes per cell and fewer cells per embryo, FISH still displayed significantly more unique genetic diagnoses per embryo (3.2+0.2) than microarray (1.3+0.2)(P<0.0001). This is the first prospective, randomized, blinded, and paired comparison between microarray and FISH based aneuploidy screening. Aneuploidy and mosaicism were less common with microarray. While evaluating a smaller number of chromosomes with a proportionally smaller opportunity for finding mosaicism, FISH still had a dramatically higher level of inter-cell variation in diagnosis. SNP microarray based 24 chromosome aneuploidy screening provides more complete and consistent results than FISH. Affymetrix SNP arrays were processed according to the manufacturer's directions on DNA extracted from 13 arrested cleavage stage embryos and biopsied into individual blastomere cells. Individual blastomeres were randomized and blinded for SNP microarray analysis (n = 85). Afflymetrix SNP array analysis was successfully completed on 82 blastomeres.

Project description:BACKGROUND: 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.RESULTS: 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.CONCLUSIONS: 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.

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VCCS HEL and U937 cell line study: fresh and fixed cells

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