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Joao L Rocha

Publications and source records attributed to Joao L Rocha.

4 recordsLinked to original sources
PubMed2004

A large-sample QTL study in mice: II. Body composition.

Using lines of mice having undergone long-term selection for high and low growth, a large-sample (n = approximately 1,000 F2) experiment was conducted to gain further understanding of the genetic architecture of complex polygenic traits. Composite interval mapping on data from male F2 mice (n = 552) detected 50 QTL on 15 chromosomes impacting weights of various organ and adipose subcomponents of growth, including heart, liver, kidney, spleen, testis, and subcutaneous and epididymal fat depots. Nearly all aggregate growth QTL could be interpreted in terms of the organ and fat subcomponents measured. More than 25% of QTL detected map to MMU2, accentuating the relevance of this chromosome to growth and fatness in the context of this cross. Regions of MMU7, 15, and 17 also emerged as important obesity "hot-spots." Average degrees of directional dominance are close to additivity, matching expectations for body composition traits. A strong QTL congruency is evident among heart, liver, kidney, and spleen weights. Liver and testis are organs whose genetic architectures are, respectively, most and least aligned with that for aggregate body weight. In this study, growth and body weight are interpreted in terms of organ subcomponents underlying the macro aggregate traits, and anchored on the corresponding genomic locations.

Animals↗
PubMed2004

A large-sample QTL study in mice: I. Growth.

By use of long-term selection lines for high and low growth, a large-sample (n = approximately 1,000 F2) experiment was conducted in mice to further understand the genetic architecture of complex polygenic traits. In combination with previous work, we conclude that QTL analysis has reinforced classic polygenic paradigms put in place prior to molecular analysis. Composite interval mapping revealed large numbers of QTL for growth traits with an exponential distribution of magnitudes of effects and validated theoretical expectations regarding gene action. Of particular significance, large effects were detected on Chromosome (Chr) 2. Regions on Chrs 1, 3, 6, 10, 11, and 17 also harbor loci with significant contributions to phenotypic variation for growth. Despite the large sample size, average confidence intervals of approximately 20 cM exhibit the poor resolution for initial estimates of QTL location. Analysis with genome-wide and chromosomal polygenic models revealed that, under certain assumptions, large fractions of the genome may contribute little to phenotypic variation for growth. Only a few epistatic interactions among detected QTL, little statistical support for gender-specific QTL, and significant age effects on genetic architecture were other primary observations from this study.

Animals↗
PubMed2004

A large-sample QTL study in mice: III. Reproduction.

Using lines of mice having undergone long-term selection for high and low growth, a large-sample (n approximately to 1000 F2) experiment was conducted to gain further understanding of the genetic architecture of complex polygenic traits. Composite interval mapping on data from 10-week-old F2 females (n = 439) detected 15 quantitative trait loci (QTLs) on 5 chromosomes that influence reproduction traits characterized at day 16 of gestation. These QTL are broadly categorized into two groups: those where effects on the number of live fetuses (LF) were accompanied by parallel effects on the number of dead fetuses (DF), and those free of such undesirable effects. QTL for ovulation rate (OR) did not overlap with QTL for litter size, potentially indicating the importance of uterine capacity. Large dominance effects were identified for most QTL detected, and overdominance was also present. The QTL of largest effects were detected in regions of Chromosome 2, where large QTL effects for growth and fatness have also been found and where corroborating evidence from other studies exists. Considerable overlap between locations of QTL for reproductive traits and for growth traits corresponds well with the positive correlations usually observed among these sets of phenotypes. Some support for the relevance of QTL x genetic background interactions in reproduction was detected. Traits with low heritability demand considerably larger sample sizes to achieve effective power of QTL detection. This is unfortunate as traits with low heritability are among those that could most benefit from QTL-complemented breeding and selection strategies in food animal production.

Animals↗