DNA Assisted Selection – A Realistic Perspective

Breathtaking advances are occurring in the knowledge and understanding of the structure, sequence and function of DNA. The entire genetic blueprint, or DNA code, has now been deciphered for humans, mice and a variety of other organisms. This modern-day “Genomic Revolution” may be one of the most important periods in the scientific history of humankind, promising diagnostics and therapeutics for numerous diseases and maladies. In animal agriculture, and particularly in beef cattle improvement, the payoffs of the “Genomic Revolution” have seemingly been few and far between. DNA information on cattle is now routinely used for determining parentage and for quality control, and a handful of DNA diagnostic tests are available for a small number of relatively simple traits. However, the true potential of harnessing genomic technologies in beef cattle awaits application of DNA testing for production traits such as carcass composition and quality, growth, reproduction and overall health status. If properly developed and delivered, these diagnostic tools may assist genetic improvement by increasing accuracy of the selection process, while simultaneously lowering the time required in order to reach and effect selection decisions. Alternatively, DNA tests can be used as tools to sort cattle and properly match a genetic profile with management decisions such as feeding and use of implants. In the long-term, assuming public acceptance of GMOs, the cattle genome may eventually be engineered to design novel animals and beef products

Obesity genes: so close and yet so far...

Little is known about genetic variants that predispose individuals toward leanness or fatness. This minireview highlights recent advances in the study of human populations, animal models and synergistic efforts as described by De Luca and colleagues in BMC Genetics, which are beginning to harvest low-hanging fruit in the search for obesity genes

Epistatic interactions of genes influence within-individual variation of physical activity traits in mice

A number of quantitative trait loci (QTLs) recently have been discovered that affect various activity traits in mice, but their collective impact does not appear to explain the consistently moderate to high heritabilities for these traits. We previously suggested interactions of genes, or epistasis, might account for additional genetic variability of activity, and tested this for the average distance, duration and speed run by mice during a 3 week period. We found abundant evidence for epistasis affecting these traits, although, recognized that epistatic effects may well vary within individuals over time. We therefore conducted a full genome scan for epistatic interactions affecting these traits in each of seven three-day intervals. Our intent was to assess the extent and trends in epistasis affecting these traits in each of the intervals. We discovered a number of epistatic interactions of QTLs that influenced the activity traits in the mice, the majority of which were not previously found and appeared to affect the activity traits (especially distance and speed) primarily in the early or in the late age intervals. The overall impact of epistasis was considerable, its contribution to the total phenotypic variance varying from an average of 22–35% in the three traits across all age intervals. It was concluded that epistasis is more important than single-locus effects of genes on activity traits at specific ages and it is therefore an essential component of the genetic architecture of physical activity

Sex-, Diet-, and Cancer-Dependent Epistatic Effects on Complex Traits in Mice

The genetic basis of quantitative traits such as body weight and obesity is complex, with several hundred quantitative trait loci (QTLs) known to affect these and related traits in humans and mice. It also has become increasingly evident that the single-locus effects of these QTLs vary considerably depending on factors such as the sex of the individuals and their dietary environment, and we were interested to know whether this context-dependency also applies to two-locus epistatic effects of QTLs as well. We therefore conducted a genome scan to search for epistatic effects on 13 different weight and adiposity traits in an F2 population of mice (created from an original intercross of the FVB strain with M16i, a polygenic obesity model) that were fed either a control or a high-fat diet and half of which harbored a transgene (PyMT) that caused the development of metastatic mammary cancer. We used a conventional interval mapping approach with SNPs to scan all 19 autosomes, and found extensive epistasis affecting all of these traits. More importantly, we also discovered that the majority of these epistatic effects exhibited significant interactions with sex, diet, and/or presence of PyMT. Analysis of these interactions showed that many of them appeared to involve QTLs previously identified as affecting these traits, but whose single-locus effects were variously modified by two-locus epistatic effects of other QTLs depending on the sex, diet, or PyMT environment. It was concluded that this context-dependency of epistatic effects is an important component of the genetic architecture of complex traits such as those contributing to weight and obesity

Genetic determinants of voluntary exercise

Variation in voluntary exercise behavior is an important determinant of long-term human health. Increased physical activity is used as a preventative measure or therapeutic intervention for disease, and a sedentary lifestyle has generally been viewed as unhealthy. Predisposition to engage in voluntary activity is heritable and induces protective metabolic changes, but its complex genetic/genomic architecture has only recently begun to emerge. We first present a brief historical perspective and summary of the known benefits of voluntary exercise. Second, we describe human and mouse model studies using genomic and transcriptomic approaches to reveal the genetic architecture of exercise. Third, we discuss the merging of genomic information and physiological observations, revealing systems and networks that lead to a more complete mechanistic understanding of how exercise protects against disease pathogenesis. Finally, we explore potential regulation of physical activity through epigenetic mechanisms, including those that persist across multiple generations

Genomic mapping of social behavior traits in a F2 cross derived from mice selectively bred for high aggression

BACKGROUND: Rapid response to selection was previously observed in mice selected for high levels of inter-male aggression based on number of attacks displayed in a novel social interaction test after isolation housing. Attack levels in this high aggression line (NC900) increased significantly within just four generations of selective breeding, suggesting the presence of a locus with large effect. We conducted an experiment using a small (n ≈ 100) F(2 )cross between the ICR-derived, non-inbred NC900 strain and the low aggression inbred strain C57BL/6J, genotyped for 154 fully informative SNPs, to determine if a locus with large effect controls the high-aggression selection trait. A second goal was to use high density SNP genotyping (n = 549,000) in the parental strains to characterize residual patterns of heterozygosity within NC900, and evaluate regions that are identical by descent (IBD) between NC900 and C57BL/6J, to determine what impacts these may have on accuracy and resolution of quantitative trait locus (QTL) mapping in the F(2 )cross. RESULTS: No evidence for a locus with major effect on aggressive behavior in mice was identified. However, several QTL with genomewide significance were mapped for aggression on chromosomes 7 and 19 and other social behavior traits on chromosomes 4, 7, 14, and 19. High density genotyping revealed that 28% of the genome is still segregating among the six NC900 females used to originate the F(2 )cross, and that segregating regions are present on every chromosome but are of widely different sizes. Regions of IBD between NC900 and C57BL/6J are found on every chromosome but are most prominent on chromosomes 10, 16 and X. No significant differences were found for amounts of heterozygosity or prevalence of IBD in QTL regions relative to global analysis. CONCLUSIONS: While no major gene was identified to explain the rapid selection response in the NC900 line, transgressive variation (i.e. where the allele from the C57BL/6J increased attack levels) and a significant role for dominant gene action were hallmarks of the genetic architecture for aggressive behavior uncovered in this study. The high levels of heterozygosity and the distribution of minor allele frequency observed in the NC900 population suggest that maintenance of heterozygosity may have been under selection in this line

Genetic variation for body weight change in mice in response to physical exercise

Abstract Background Physical activity is beneficial in reducing the weight gain and associated health problems often experienced by individuals as they age, but the association of weight change with physical activity remains complex. We tested for a possible genetic basis for this association between 9-12-week body weight change (WTC) and the distance, duration, and speed voluntarily run by 307 mice in an F2 population produced from an intercross of two inbred strains (C57L/J and C3H/HeJ) that differed dramatically in their physical activity levels. Results In this population WTC did show the expected negative association with the physical activity traits, but only the phenotypic correlation of WTC with speed (-0.18) reached statistical significance. Using an interval mapping approach with single-nucleotide polymorphism markers, we discovered five (four suggestive and one significant) quantitative trait loci (QTLs) affecting body weight change, only one of which appeared to show pleiotropic effects on the physical activity traits as well. Genome-wide epistasis scans also detected several pairwise interactions of QTLs with pleiotropic effects on WTC and the physical activity traits, but these effects made a significant contribution (51%) only to the covariance of WTC with speed. Conclusion It was concluded that the genetic contribution to the phenotypic association between WTC and the physical activity traits in this population of mice was primarily epistatic in origin, restricted to one measure of physical activity, and could be quite variable among different populations depending on the genetic background, experimental design and traits assessed

Rapid communication: Linkage mapping of the porcine Agouti gene

Genus and Species. Sus scrofa. Locus. Porcine agouti gene. Source and Description of Primers. The forward primer was designed from pig sequence (GenBank accession no. AF018166) and the reverse primer was developed from comparing the homologous regions of mouse and bovine agouti sequences (GenBank accession no. L06451 and X99691, respectively). The primers were used to amplify approximately 1.4 kb of the porcine agouti gene fragment spanning exons 2 and 3. Sequences of the PCR fragment revealed 83% and 89% exonic identities to the corresponding human and bovine agouti nucleotide sequences, respectively. The porcine agouti sequence has been submitted to GenBank, accession no. AF133261

Inferring genetic architecture of complex traits using Bayesian integrative analysis of genome and transcriptome data

Abstract Background To understand the genetic architecture of complex traits and bridge the genotype-phenotype gap, it is useful to study intermediate -omics data, e.g. the transcriptome. The present study introduces a method for simultaneous quantification of the contributions from single nucleotide polymorphisms (SNPs) and transcript abundances in explaining phenotypic variance, using Bayesian whole-omics models. Bayesian mixed models and variable selection models were used and, based on parameter samples from the model posterior distributions, explained variances were further partitioned at the level of chromosomes and genome segments. Results We analyzed three growth-related traits: Body Weight (BW), Feed Intake (FI), and Feed Efficiency (FE), in an F2 population of 440 mice. The genomic variation was covered by 1806 tag SNPs, and transcript abundances were available from 23,698 probes measured in the liver. Explained variances were computed for models using pedigree, SNPs, transcripts, and combinations of these. Comparison of these models showed that for BW, a large part of the variation explained by SNPs could be covered by the liver transcript abundances; this was less true for FI and FE. For BW, the main quantitative trait loci (QTLs) are found on chromosomes 1, 2, 9, 10, and 11, and the QTLs on 1, 9, and 10 appear to be expression Quantitative Trait Locus (eQTLs) affecting gene expression in the liver. Chromosome 9 is the case of an apparent eQTL, showing that genomic variance disappears, and that a tri-modal distribution of genomic values collapses, when gene expressions are added to the model. Conclusions With increased availability of various -omics data, integrative approaches are promising tools for understanding the genetic architecture of complex traits. Partitioning of explained variances at the chromosome and genome-segment level clearly separated regulatory and structural genomic variation as the areas where SNP effects disappeared/remained after adding transcripts to the model. The models that include transcripts explained more phenotypic variance and were better at predicting phenotypes than a model using SNPs alone. The predictions from these Bayesian models are generally unbiased, validating the estimates of explained variances