So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

Current research in meat color

This paper presents the 12th update of the human obesity gene map, which incorporates published results up to the end of October 2005. Evidence from single-gene mutation obesity cases, Mendelian disorders exhibiting obesity as a clinical feature, transgenic and knockout murine models relevant to obesity, quantitative trait loci (QTL) from animal cross-breeding experiments, association studies with candidate genes, and linkages from genome scans is reviewed. As of October 2005, 176 human obesity cases due to single-gene mutations in 11 different genes have been reported, 50 loci related to Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and causal genes or strong candidates have been identified for most of these syndromes. There are 244 genes that, when mutated or expressed as transgenes in the mouse, result in phenotypes that affect body weight and adiposity. The number of QTLs reported from animal models currently reaches 408. The number of human obesity QTLs derived from genome scans continues to grow, and we now have 253 QTLs for obesity-related phenotypes from 61 genome-wide scans. A total of 52 genomic regions harbor QTLs supported by two or more studies. The number of studies reporting associations between DNA sequence variation in specific genes and obesity phenotypes has also increased considerably, with 426 findings of positive associations with 127 candidate genes. A promising observation is that 22 genes are each supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. The electronic version of the map with links to useful publications and relevant sites can be found at http://obesitygene.pbrc.edu.

/pdf/the-human-obesity-gene-map-the-2005-update-3zvtci1u6f.pdf

The human obesity gene map: the 2005 update.

This paper presents the eleventh update of the human obesity gene map, which incorporates published results up to the end of October 2004. Evidence from single-gene mutation obesity cases, Mendelian disorders exhibiting obesity as a clinical feature, transgenic and knockout murine models relevant to obesity, quantitative trait loci (QTLs) from animal cross-breeding experiments, association studies with candidate genes, and linkages from genome scans is reviewed. As of October 2004, 173 human obesity cases due to single-gene mutations in 10 different genes have been reported, and 49 loci related to Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and causal genes or strong candidates have been identified for most of these syndromes. There are 166 genes which, when mutated or expressed as transgenes in the mouse, result in phenotypes that affect body weight and adiposity. The number of QTLs reported from animal models currently reaches 221. The number of human obesity QTLs derived from genome scans continues to grow, and we have now 204 QTLs for obesity-related phenotypes from 50 genome-wide scans. A total of 38 genomic regions harbor QTLs replicated among two to four studies. The number of studies reporting associations between DNA sequence variation in specific genes and obesity phenotypes has also increased considerably with 358 findings of positive associations with 113 candidate genes. Among them, 18 genes are supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. Overall, >600 genes, markers, and chromosomal regions have been associated or linked with human obesity phenotypes. The electronic version of the map with links to useful publications and genomic and other relevant sites can be found at http://obesitygene.pbrc.edu.

https://onlinelibrary.wiley.com/doi/pdf/10.1038/oby.2005.50

The human obesity gene map: the 2004 update.

Intramuscular fat (IMF) content plays a key role in various quality traits of meat. IMF content varies between species, between breeds and between muscle types in the same breed. Other factors are involved in the variation of IMF content in animals, including gender, age and feeding. Variability in IMF content is mainly linked to the number and size of intramuscular adipocytes. The accretion rate of IMF depends on the muscle growth rate. For instance, animals having a high muscularity with a high glycolytic activity display a reduced development of IMF. This suggests that muscle cells and adipocytes interplay during growth. In addition, early events that influence adipogenesis inside the muscle (i.e proliferation and differentiation of adipose cells, the connective structure embedding adipocytes) might be involved in interindividual differences in IMF content. Increasing muscularity will also dilute the final fat content of muscle. At the metabolic level, IMF content results from the balance between uptake, synthesis and degradation of triacylglycerols, which involve many metabolic pathways in both adipocytes and myofibres. Various experiments revealed an association between IMF level and the muscle content in adipocyte-type fatty acid-binding protein, the activities of oxidative enzymes, or the delta-6-desaturase level; however, other studies failed to confirm such relationships. This might be due to the importance of fatty acid fluxes that is likely to be responsible for variability in IMF content during the postnatal period rather than the control of one single pathway. This is evident in the muscle of most fish species in which triacylglycerol synthesis is almost zero. Genetic approaches for increasing IMF have been focused on live animal ultrasound to derive estimated breeding values. More recently, efforts have concentrated on discovering DNA markers that change the distribution of fat in the body (i.e. towards IMF at the expense of the carcass fatness). Thanks to the exhaustive nature of genomics (transcriptomics and proteomics), our knowledge on fat accumulation in muscles is now being underpinned. Metabolic specificities of intramuscular adipocytes have also been demonstrated, as compared to other depots. Nutritional manipulation of IMF independently from body fat depots has proved to be more difficult to achieve than genetic strategies to have lipid deposition dependent of adipose tissue location. In addition, the biological mechanisms that explain the variability of IMF content differ between genetic and nutritional factors. The nutritional regulation of IMF also differs between ruminants, monogastrics and fish due to their digestive and nutritional particularities.

https://researchrepository.murdoch.edu.au/6455/1/fat_content_in_meat%2Dproducing_animals.pdf

Intramuscular fat content in meat-producing animals: development, genetic and nutritional control, and identification of putative markers.

Genome scans can be employed to identify chromosomal regions and eventually genes (quantitative trait loci or QTL) that control quantitative traits of economic importance. A three-generation resource family was developed by using two Berkshire grand sires and nine Yorkshire grand dams to detect QTL for growth and body composition traits in pigs. A total of 525 F2 progeny were produced from 65 matings. All F2 animals were phenotyped for birth weight, 16-day weight, growth rate, carcass weight, carcass length, back fat thickness, and loin eye area. Animals were genotyped for 125 microsatellite markers covering the genome. Least squares regression interval mapping was used for QTL detection. All carcass traits were adjusted for live weight at slaughter. A total of 16 significant QTL, as determined by a permutation test, were detected at the 5% chromosome-wise level for growth traits on Chromosomes (Chrs) 1, 2, 3, 4, 6, 7, 8, 9, 11, 13, 14, and X, of which two were significant at the 5% genome-wise level and two at the 1% genome-wise level (on Chrs 1, 2, and 4). For composition traits, 20 QTL were significant at the 5% chromosome-wise level (on Chrs 1, 4, 5, 6, 7, 12, 13, 14, 18), of which one was significant at the 5% genome-wise level and three were significant at the 1% genome-wise level (on Chrs 1, 5, and 7). For several QTL the favorable allele originated from the breed with the lower trait mean.

/pdf/a-molecular-genome-scan-analysis-to-identify-chromosomal-3od06zg76g.pdf

A molecular genome scan analysis to identify chromosomal regions influencing economic traits in the pig. II. Meat and muscle composition

Establishing relationships among specific quality traits is important if significant progress toward developing improved pork quality is to be realized. As part of a study to examine the individual effects of genes on meat quality traits in pigs, a three-generation resource family was developed. Two Berkshire sires and nine Yorkshire dams were used to produce nine F1 litters. Sixty-five matings were made from the F1 litters to produce four sets of F2 offspring, for a total of 525 F2 animals used in the study. These F2 animals were slaughtered at a commercial facility upon reaching approximately 110 kg. Carcass composition traits, pH measurements, and subjective quality scores were made at 24 h postmortem. Loin samples (n = 525) were collected at 48 h postmortem, and meat quality traits were evaluated. These traits included pH (48 h), Hunter L-values, drip loss, glycolytic potential, ratio of type IIa/IIb myosin heavy chains (IIa/IIb), total lipid, instrumental measures of tenderness using the Star Probe attachment of the Instron, cook loss measurements, and sensory evaluations. Significant phenotypic correlations were found between many carcass, instrumental, and biochemical measurements, and sensory quality traits. Star Probe measurements were significantly correlated with drip loss (0.29), glycolytic potential (0.30), pH (-0.29), total lipid (-0.14), and Hunter L-values (0.28). Drip loss was significantly correlated with glycolytic potential (0.36), pH (-0.28), IIa/IIb (-0.10), and Hunter L-values (0.33). Hunter L-values were also significantly correlated with total lipid (0.33) and IIa/ IIb (-0.11). Sensory tenderness, flavor, and off-flavor scores were significantly correlated with drip loss, pH, and glycolytic potential measurements. Marbling score, total lipid, and drip loss were not significantly correlated with sensory juiciness scores, but cooking loss was. Marbling and total lipid were significantly correlated with firmness scores (0.37 and 0.31, respectively). Taken together, the data in this study suggest that changes in some meat quality traits can affect many other meat quality attributes. The correlations yield information that could aid in directing future studies aimed at understanding the underlying biological mechanisms behind the development of many quality traits.

https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1046&context=ans_pubs

Correlations among selected pork quality traits

Records on 251,296 Yorkshire, 75,262 Duroc, 83,338 Hampshire, and 53,234 Landrace litters born between 1984 and April of 1999 in herds on the National Swine Registry Swine Testing and Genetic Evaluation System were analyzed. Animal model and restricted maximum likelihood procedures were used to estimate variances of animal genetic (a), maternal genetic (m), permanent environmental, and service sire, and the covariances between a and m for number born alive (NBA), litter weight at 21 d (L21WT), and number weaned (NW). Fixed effects of contemporary groups were included in the analysis. Based on a single-trait model, estimates of heritabilities were 0.10, 0.09, 0.08, and 0.08 for NBA; 0.08, 0.07, 0.08, and 0.09 for L21WT; and 0.05, 0.07, 0.05, and 0.05 for NW in the Yorkshire, Duroc, Hampshire, and Landrace breeds, respectively. Estimates of maternal genetic effects were low and ranged from 0.00 to 0.02 for all traits and all breeds. Estimates of permanent environmental effects ranged from 0.03 to 0.08. Estimates of service sire effects ranged from 0.02 to 0.05. A bivariate analysis was used to estimate the genetic correlations among traits. Average genetic correlations over the four breeds were 0.13, 0.15, and 0.71 for NBA with L21WT, NBA with NW, and L21WT with NW, respectively. Average genetic trends were 0.018 pigs/yr, 0.114 kg/yr, and 0.004 pigs/yr for NBA, L21WT, and NW, respectively. Although estimates of heritabilities for litter traits were low and similar across breeds, genetic variances for litter traits were sufficiently large to indicate that litter traits could be improved through selection. This study presents the first set of breed-specific estimates of genetic parameters available from large numbers of field records. It provides information for use in national genetic evaluations.

Genetic parameters and trends for litter traits in U.S. Yorkshire, Duroc, Hampshire, and Landrace pigs.

Conjugated linoleic acid (CLA) was supplemented to crossbred growing-finishing barrows (n = 60) at 0.75% of the total diet. Pigs were randomly assigned to the CLA or control diets based on stress genotype (negative, carrier, or positive). Gain:feed was higher for CLA diet animals (350 g/kg feed) than for control diet animals (330 g/kg feed) independent of genotype (P < 0.05). No differences were observed for ADG for the diets (P = 0.71) or genotype classes (P = 0.40). Postmortem pH was lower (P < 0.01) by 3 h for CLA-supplemented pigs, with no differences in ultimate pH. No differences (P = 0.16) were observed for ultimate pH between the three genotypes. Conjugated linoleic acid-supplemented pigs exhibited less 10th rib fat depth (2.34 cm vs 2.84 cm) and last rib fat depth (2.46 cm vs 2.72 cm) than control pigs (P < 0.05). Loin muscle area (LMA) was not affected (P = 0.18) by CLA supplementation, but LMA was different (P < 0.02) for genotype; positive genotype carcasses had the largest LMA (45.02 cm 2 ) and negative carcasses had the smallest LMA (36.44 cm 2 ). Carrier carcasses were intermediate for LMA (40.76 cm 2 ). Subjective scores for color were not affected (P = 0.98) by CLA but color was different (P < 0.01), with scores of 1.50, 2.40, and 3.1 for positive, carrier, and negative genotypes, respectively. Subjective marbling scores were increased (P < 0.03) in all genotypes with CLA supplementation. Subjective firmness scores were higher (P < 0.06) for CLA-supplemented pigs and were highly correlated (0.89) to marbling scores. The L * values were higher (P < 0.01) for stress-positive pigs at 24 h postmortem. Also, L * values were higher (P < 0.01) for CLA-fed pigs over 7 d of shelf storage. Sensory characteristics were not different with CLA supplementation for tenderness (P = 0.24), juiciness (P = 0.35), or flavor intensity (P = 0.14). This study showed that LMA was increased with stress-carrier and stress-positive genotypes, but lean color was negatively affected with the presence of the stress gene. Conjugated linoleic acid supplementation improves feed efficiency, decreases backfat, and improves pork quality attributes of marbling and firmness of the longissimus muscle. Furthermore, there is seemingly no interaction between the stress-genotype status of pigs and the subsequent effect of CLA on their growth and performance.

Conjugated linoleic acid improves feed efficiency, decreases subcutaneous fat, and improves certain aspects of meat quality in stress-genotype pigs.

An evaluation of porcine longissimus myoglobin concentration was conducted to determine breed and gender differences for myoglobin content, estimate genetic parameters for myoglobin concentration, and determine the relationship between myoglobin content and objective measures of muscle color. Data from centrally tested (n = 255), purebred Yorkshire (42), Duroc (61), Hampshire (17), Chester White (28), Berkshire (67), Poland China (28), and Landrace (12) barrows and gilts from the 1999 National Barrow Show Sire Progeny Test were used. Ultimate pH and Hunter L were measured on the 10th-rib face 24 h postmortem. A section of bone-in loin containing the 10th rib was taken to the Iowa State University Meats Laboratory. At 48 h postmortem, Hunter L, CIE L*, a*, and b*, Japanese color score, and water-holding capacity were measured on the face of the 10th-rib loin chop. A slice from the 10th-rib loin section was evaluated for percentage of i.m. fat. The resulting loin chop was used for the determination of soluble myoglobin concentration (mg/g, wet basis). Chester White, Hampshire, and Duroc pigs had the highest (P < 0.05) myoglobin concentration (0.92, 0.95, and 0.85 mg/g, respectively), whereas Landrace had the lowest (0.62 mg/g; P < 0.05). No gender differences were detected for myoglobin concentration. The heritability estimate for soluble myoglobin concentration was 0.27. Residual correlations between soluble myoglobin and CIE L*, a*, b*, Hunter L (24 h), Hunter L (48 h), and Japanese color score were -0.17, 0.23, -0.15, -0.16, -0.13, and 0.13, respectively. These correlations are low but in the desired direction. The residual correlation between soluble myoglobin and intramuscular fat percent was 0.18. Results show that myoglobin concentration has a moderate heritability and could be used in a selection program to make pork loins darker in color.

Thomas J. Baas

Papers

A molecular genome scan analysis to identify chromosomal regions influencing economic traits in the pig. II. Meat and muscle composition

Correlations among selected pork quality traits

Genetic parameters and trends for litter traits in U.S. Yorkshire, Duroc, Hampshire, and Landrace pigs.

Conjugated linoleic acid improves feed efficiency, decreases subcutaneous fat, and improves certain aspects of meat quality in stress-genotype pigs.

Breed differences and genetic parameters of myoglobin concentration in porcine longissimus muscle