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Mapping Novel Subcutaneous Angiogenesis Quantitative Trait Loci in [B6×MRL]F2 Mice.

ABSTRACT: Objective: MRL/MpJ mice are known for enhanced healing, but mechanistic details or how specific aspects of wounding (e.g., angiogenesis) contribute to healing are unknown. While previous studies investigated the systemic effects of immunity in MRL/MpJ healing, few have focused on tissue-intrinsic effects. Approach:Ex vivo skin biopsies from MRL/MpJ and C57BL/6J mice were cultured in ex vivo conditions that favor endothelial cell growth to compare their angiogenic potential. We localized enhanced angiogenesis quantitative trait loci (QTL) in an F2 intercross. We then performed an expression analysis in cultured skin biopsies from MRL/MpJ and C57BL/6J mice to determine the pathways that are associated with the capacity for differential growth. Results: MRL/MpJ biopsies have a two- to threefold greater growth potential than C57BL/6J mice, supporting the hypothesis that angiogenesis may contribute to enhanced healing in MRL/MpJ skin. We mapped two QTLs that are unique from previously mapped MRL/MpJ wound healing QTLs and detected interactions between wound healing QTLs and loci in this cross. Additionally, we found that pathways previously implicated in MRL/MpJ healing are also enriched in skin biopsies. Innovation: We have developed a novel approach to determine how specific aspects of tissue development contribute to wound healing that will ultimately lead to the discovery of unidentified genes that contribute to enhanced healing. Conclusion: We have shown that, consistent with previous studies following wound closure in MRL/MpJ mice, vessel growth during healing is also influenced by genetic background. Our ongoing work will identify the genetic factors that should be useful biomarkers or as therapeutic targets for enhanced wound healing.

SUBMITTER: Morales K

PROVIDER: S-EPMC4152795 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Mapping Novel Subcutaneous Angiogenesis Quantitative Trait Loci in [B6×MRL]F2 Mice.

Morales Krista K Rowehl Leahana L Smith Jason J Cole Rich R Liu Fang F Beyer Barb B Herron Bruce J BJ

Advances in wound care 20140901 9

Objective: MRL/MpJ mice are known for enhanced healing, but mechanistic details or how specific aspects of wounding (e.g., angiogenesis) contribute to healing are unknown. While previous studies investigated the systemic effects of immunity in MRL/MpJ healing, few have focused on tissue-intrinsic effects. Approach:Ex vivo skin biopsies from MRL/MpJ and C57BL/6J mice were cultured in ex vivo conditions that favor endothelial cell growth to compare their angiogen ...[more]

PMID: 25207199

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Project description:BACKGROUND: QTL affecting fat deposition related performance traits have been considered in several studies and mapped on numerous porcine chromosomes. However, activity of specific enzymes, protein content and cell structure in fat tissue probably depend on a smaller number of genes than traits related to fat content in carcass. Thus, in this work traits related to metabolic and cytological features of back fat tissue and fat related performance traits were investigated in a genome-wide QTL analysis. QTL similarities and differences were examined between three F2 crosses, and between male and female animals. METHODS: A total of 966 F2 animals originating from crosses between Meishan (M), Pietrain (P) and European wild boar (W) were analysed for traits related to fat performance (11), enzymatic activity (9) and number and volume of fat cells (20). Per cross, 216 (MxP), 169 (WxP) and 195 (WxM) genome-wide distributed marker loci were genotyped. QTL mapping was performed separately for each cross in steps of 1 cM and steps were reduced when the distance between loci was shorter. The additive and dominant components of QTL positions were detected stepwise by using a multiple position model. RESULTS: A total of 147 genome-wide significant QTL (76 at P<0.05 and 71 at P<0.01) were detected for the three crosses. Most of the QTL were identified on SSC1 (between 76-78 and 87-90 cM), SSC7 (predominantly in the MHC region) and SSCX (in the vicinity of the gene CAPN6). Additional genome-wide significant QTL were found on SSC8, 12, 13, 14, 16, and 18. In many cases, the QTL are mainly additive and differ between F2 crosses. Many of the QTL profiles possess multiple peaks especially in regions with a high marker density. Sex specific analyses, performed for example on SSC6, SSC7 and SSCX, show that for some traits the positions differ between male and female animals. For the selected traits, the additive and dominant components that were analysed for QTL positions on different chromosomes, explain in combination up to 23% of the total trait variance. CONCLUSIONS: Our results reveal specific and partly new QTL positions across genetically diverse pig crosses. For some of the traits associated with specific enzymes, protein content and cell structure in fat tissue, it is the first time that they are included in a QTL analysis. They provide large-scale information to analyse causative genes and useful data for the pig industry.

Project description:A new mixed-model method was developed for mapping quantitative trait loci (QTL) by incorporating multiple polygenic covariance structures. First, we used genome-wide markers to calculate six different kinship matrices. We then partitioned the total genetic variance into six variance components, one corresponding to each kinship matrix, including the additive, dominance, additive × additive, dominance × dominance, additive × dominance, and dominance × additive variances. The six different kinship matrices along with the six estimated polygenic variances were used to control the genetic background of a QTL mapping model. Simulation studies showed that incorporating epistatic polygenic covariance structure can improve QTL mapping resolution. The method was applied to yield component traits of rice. We analyzed four traits (yield, tiller number, grain number, and grain weight) using 278 immortal F2 crosses (crosses between recombinant inbred lines) and 1619 markers. We found that the relative importance of each type of genetic variance varies across different traits. The total genetic variance of yield is contributed by additive × additive (18%), dominance × dominance (14%), additive × dominance (48%), and dominance × additive (15%) variances. Tiller number is contributed by additive (17%), additive × additive (22%), and dominance × additive (43%) variances. Grain number is mainly contributed by additive (42%), additive × additive (19%), and additive × dominance (31%) variances. Grain weight is almost exclusively contributed by the additive (73%) variance plus a small contribution from the additive × additive (10%) variance. Using the estimated genetic variance components to capture the polygenic covariance structure, we detected 39 effects for yield, 39 effects for tiller number, 24 for grain number, and 15 for grain weight. The new method can be directly applied to polygenic-effect-adjusted genome-wide association studies (GWAS) in human and other species.

Dataset Information

Mapping Novel Subcutaneous Angiogenesis Quantitative Trait Loci in [B6×MRL]F2 Mice.

Publications

Mapping Novel Subcutaneous Angiogenesis Quantitative Trait Loci in [B6×MRL]F2 Mice.

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