High-capacity assay to quantify the clonal heterogeneity in potency of mesenchymal stem cells

O’Connor, Kim C.; Russell, Katie C.; Phinney, Donald G.; Lacey, Michelle; Barrilleaux, Bonnie L.; Meyertholen, Kristin

doi:10.1186/1753-6561-5-s8-o14

Cited by 3 publications

(4 citation statements)

References 3 publications

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“…Genotype × Environment (G × E) interaction is an important component of genetic variability (Crossa et al, 2010 , 2011 ). Various genomic selection studies have included G × E effect while predicting the values in across environments (Heffner et al, 2011b ; Resende et al, 2011 ), within environments or group of environments (Burgueño et al, 2012 ; Dawson et al, 2013 ; Ly et al, 2013 ; Heslot et al, 2014 ) or using marker-by-environment predictions (Jarquín et al, 2014 ; Lopez-Cruz et al, 2015 ).…”

Section: Discussionmentioning

confidence: 99%

Genomic Selection for Drought Tolerance Using Genome-Wide SNPs in Maize

et al. 2017

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Traditional breeding strategies for selecting superior genotypes depending on phenotypic traits have proven to be of limited success, as this direct selection is hindered by low heritability, genetic interactions such as epistasis, environmental-genotype interactions, and polygenic effects. With the advent of new genomic tools, breeders have paved a way for selecting superior breeds. Genomic selection (GS) has emerged as one of the most important approaches for predicting genotype performance. Here, we tested the breeding values of 240 maize subtropical lines phenotyped for drought at different environments using 29,619 cured SNPs. Prediction accuracies of seven genomic selection models (ridge regression, LASSO, elastic net, random forest, reproducing kernel Hilbert space, Bayes A and Bayes B) were tested for their agronomic traits. Though prediction accuracies of Bayes B, Bayes A and RKHS were comparable, Bayes B outperformed the other models by predicting highest Pearson correlation coefficient in all three environments. From Bayes B, a set of the top 1053 significant SNPs with higher marker effects was selected across all datasets to validate the genes and QTLs. Out of these 1053 SNPs, 77 SNPs associated with 10 drought-responsive transcription factors. These transcription factors were associated with different physiological and molecular functions (stomatal closure, root development, hormonal signaling and photosynthesis). Of several models, Bayes B has been shown to have the highest level of prediction accuracy for our data sets. Our experiments also highlighted several SNPs based on their performance and relative importance to drought tolerance. The result of our experiments is important for the selection of superior genotypes and candidate genes for breeding drought-tolerant maize hybrids.

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Section: Discussionmentioning

confidence: 99%

Genomic Selection for Drought Tolerance Using Genome-Wide SNPs in Maize

et al. 2017

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“…If the 435 individuals were used for GS modelling, the number of markers required would be at least 200 M (20 Gbp per 100 bp). However, significant GEBVs with 0·3–0·83 accuracy were obtained using 3406–3938 SNPs in full-sib families with Loblolly pine (Table 2 ; Isik et al , 2011 ; Resende et al , 2011 ). This large disparity in the number of required markers is caused by the different length in the marker interval with a significant LD intensity in an unrelated mapping population and full-sib families.…”

Section: The Practice Of Gs In Plant Breedingmentioning

confidence: 99%

“…GS of perennial crops is considered to be more effective than annual crops because of their long generation times. GEBV predictions based on empirical data were presented for Loblolly pine and eucalyptus at the IUFRO Tree Biotechnology Conference 2011 (Table 2 ; Grattapaglia et al , 2011 ; Isik et al , 2011 ; Resende et al , 2011 ). All cases used full-sib families as test populations and the number of individuals ranged from 149 to 920.…”

Section: Recent Progress In Gs Studiesmentioning

confidence: 99%

Will genomic selection be a practical method for plant breeding?

2012

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BackgroundGenomic selection or genome-wide selection (GS) has been highlighted as a new approach for marker-assisted selection (MAS) in recent years. GS is a form of MAS that selects favourable individuals based on genomic estimated breeding values. Previous studies have suggested the utility of GS, especially for capturing small-effect quantitative trait loci, but GS has not become a popular methodology in the field of plant breeding, possibly because there is insufficient information available on GS for practical use.ScopeIn this review, GS is discussed from a practical breeding viewpoint. Statistical approaches employed in GS are briefly described, before the recent progress in GS studies is surveyed. GS practices in plant breeding are then reviewed before future prospects are discussed.ConclusionsStatistical concepts used in GS are discussed with genetic models and variance decomposition, heritability, breeding value and linear model. Recent progress in GS studies is reviewed with a focus on empirical studies. For the practice of GS in plant breeding, several specific points are discussed including linkage disequilibrium, feature of populations and genotyped markers and breeding scheme. Currently, GS is not perfect, but it is a potent, attractive and valuable approach for plant breeding. This method will be integrated into many practical breeding programmes in the near future with further advances and the maturing of its theory.

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“…However, the ability of MSCs to survive and differentiate in vitro has proven a poor predictor of their ability to repair tissue . Efforts to increase MSC potency by deriving populations from single cells have failed to increase the proportion of MSCs in the subsequent population of passaged cells . Also, strategies for enriching MSCs exploiting one or more cell‐surface markers have gained favor, particularly for markers such as stromal precursor antigen‐1 (STRO‐1) , SSEA‐4 , CD49a , CD271 , CD146 , leptin receptor , and the use of size‐sorting from adherent cultures of bone marrow aspirates .…”

Section: Introductionmentioning

confidence: 99%

Establishing Criteria for Human Mesenchymal Stem Cell Potency

Samsonraj¹,

et al. 2015

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This study sought to identify critical determinants of mesenchymal stem cell (MSC) potency using in vitro and in vivo attributes of cells isolated from the bone marrow of age‐ and sex‐matched donors. Adherence to plastic was not indicative of potency, yet capacity for long‐term expansion in vitro varied considerably between donors, allowing the grouping of MSCs from the donors into either those with high‐growth capacity or low‐growth capacity. Using this grouping strategy, high‐growth capacity MSCs were smaller in size, had greater colony‐forming efficiency, and had longer telomeres. Cell‐surface biomarker analysis revealed that the International Society for Cellular Therapy (ISCT) criteria did not distinguish between high‐growth capacity and low‐growth capacity MSCs, whereas STRO‐1 and platelet‐derived growth factor receptor alpha were preferentially expressed on high‐growth capacity MSCs. These cells also had the highest mean expression of the mRNA transcripts TWIST‐1 and DERMO‐1. Irrespective of these differences, both groups of donor MSCs produced similar levels of key growth factors and cytokines involved in tissue regeneration and were capable of multilineage differentiation. However, high‐growth capacity MSCs produced approximately double the volume of mineralized tissue compared to low‐growth capacity MSCs when assessed for ectopic bone‐forming ability. The additional phenotypic criteria presented in this study when combined with the existing ISCT minimum criteria and working proposal will permit an improved assessment of MSC potency and provide a basis for establishing the quality of MSCs prior to their therapeutic application. Stem Cells 2015;33:1878–1891

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High-capacity assay to quantify the clonal heterogeneity in potency of mesenchymal stem cells

Cited by 3 publications

References 3 publications

Genomic Selection for Drought Tolerance Using Genome-Wide SNPs in Maize

Genomic Selection for Drought Tolerance Using Genome-Wide SNPs in Maize

Will genomic selection be a practical method for plant breeding?

Establishing Criteria for Human Mesenchymal Stem Cell Potency

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