E. Kalm

Genetic correlations of growth, backfat thickness and exterior with stayability in large white and landrace sows

Abstract Backfat thickness, daily gain, and five exterior traits were measured in 36 814 Large White and Landrace gilts from nucleus and multiplier herds. Functional stayability, defined as survived (1) or not (0), from first to second (STAY12) and from first to third litter (STAY123) was available for 13 760 of these animals in a commercial multiplier environment. Heritabilities and genetic correlations of longevity and growth performance and exterior traits were estimated by linear models. Heritability estimates for STAY12 and STAY123 in Large White were 0.08 and 0.10, and in Landrace 0.07 and 0.11, respectively. The corresponding genetic standard deviations for STAY123 were 0.118 and 0.126 in Large White and Landrace, respectively. Antagonistic genetic correlations were found between stayability traits and backfat thickness and daily gain. Estimates ranged from −0.06 to −0.32 for daily gain and from 0.11 to 0.27 for backfat thickness in both lines. Genetic correlations with leg score were about zero in Large White and positive (from 0.19 to 0.36) in Landrace, whereas genetic relationships with other exterior traits were near zero. We conclude that the selection for longevity is possible because of high genetic standard deviations of the stayability traits and that an antagonism exists between growth performance and longevity, whereas a better leg status decreases involuntary culling.

Genetic association between feed intake and feed intake behaviour at different stages of growth of group-housed boars

Abstract Voluntary feed intake, feed intake pattern and performance traits were recorded on 3188 group housed boars of Landrace and Large White tested from day 100 to day 170. Measurements of feed intake and feed intake behaviour were obtained by electronic feed dispensers (ACEMO) under ad libitum conditions. Heritabilities of feed intake in periods 1 to 5 and over the entire test period were estimated to be 0.16, 0.24, 0.30, 0.27, 0.26, and 0.22, respectively. The maximum heritability of daily feed intake in the third time period on test corresponds to about 130 days of age at about 85 kg of weight. Daily feed intake in this period showed a high genetic correlation with the average feed intake over the whole performance test (rg = 0.91). Estimates of genetic correlations between daily feed intake and feed conversion ratio, residual feed intake, average daily gain or backfat thickness were 0.04, 0.97, 0.62 and 0.42, respectively. Boars feed intake activities decreased over time while time per day in the feeder was almost constant. Traits of feed intake behaviour as feeding rate, feed intake/visit, number of visits, time per visit, and time per day in the feeder showed high heritabilities of 0.44, 0.51, 0.43, 0.42, and 0.43, respectively, but genetic correlations with performance and carcass traits were generally low. One exception was the behavioural trait time per day in the feeder with its moderate genetic correlations to daily feed intake (rg = 0.44) and average daily gain on test (rg = 0.32). Selection for lean growth will improve lean growth feed efficiency as indicated by the negative correlation of −0.47. But more efficient may be the use of the component traits, lean content, daily feed intake and daily gain in particular of the most informative test period.

Combined analysis of data from two granddaughter designs: A simple strategy for QTL confirmation and increasing experimental power in dairy cattle

A joint analysis of five paternal half-sib Holstein families that were part of two different granddaughter designs (ADR- or Inra-design) was carried out for five milk production traits and somatic cell score in order to conduct a QTL confirmation study and to increase the experimental power. Data were exchanged in a coded and standardised form. The combined data set (JOINT-design) consisted of on average 231 sires per grandsire. Genetic maps were calculated for 133 markers distributed over nine chromosomes. QTL analyses were performed separately for each design and each trait. The results revealed QTL for milk production on chromosome 14, for milk yield on chromosome 5, and for fat content on chromosome 19 in both the ADR- and the Inra-design (confirmed within this study). Some QTL could only be mapped in either the ADR- or in the Inra-design (not confirmed within this study). Additional QTL previously undetected in the single designs were mapped in the JOINT-design for fat yield (chromosome 19 and 26), protein yield (chromosome 26), protein content (chromosome 5), and somatic cell score (chromosome 2 and 19) with genomewide significance. This study demonstrated the potential benefits of a combined analysis of data from different granddaughter designs.

Associations of DNA markers with meat quality traits in pigs with emphasis on drip loss

Phenotypic information on 1155 market pigs for several pig meat quality traits, was collected. Genotypes on 12 DNA markers, including RYR1 and PRKAG3 I199V, were also obtained on all pigs to investigate the relationship between genetic markers and meat quality. The RYR1 gene had the highest impact on meat quality, however, several other markers showed significant effects on one or more traits. Animals heterozygous at the RYR1 locus were significantly inferior in almost all meat quality traits, except ultimate pH value, initial conductivity and redness of the meat. Drip loss from case-ready meat (measured from 1 to 7 days post-mortem) was 43% higher for heterozygotes than animals of the stress resistant genotype. The homozygous genotype II at position I199V of the PRKAG3 locus also resulted in less drip loss than genotypes IV and VV, regardless of the method and time of measurement. Furthermore, the favourable genotype related to higher ultimate pH and darker meat. Both loci significantly affected the intercept, linear and quadratic terms of fitted drip loss development curves. The favourable genotypes showed a lower drip loss after one day of measurement and a slower increase and a more linear development over time. Whilst the RYR1 and PRKAG3 markers influenced numerous meat quality traits, some of the other markers were also found to have significant effects on one or two meat quality traits. Markers at MC4R and HMGA1 loci significantly affected drip loss, whereas LDHA, CAST (Hpy188I) and ATP2A1 influenced pH value. In addition, the marker ATP2A1 was associated with variation in intramuscular fat content in M. longissimus dorsi. GLUT4 affected temperature 45min post-mortem and several markers (MC4R, LDHA, GLUT4, HMGA1, CAST (Hpy188I and PvuII)) influenced one or two of the different colour measurements. The markers at MC4R, CKM, AGRP, PRKAG3, and HMGA1 loci were tested for their interactions with RYR1 regarding drip loss. Only AGRP showed a significant interaction, but this was based on only a few animals with the homozygous genotype for one allele. Our results suggest that genetic markers provide a useful tool to improve meat quality in pigs independently from RYR1, especially the mutation I199V in the PRKAG3 gene.

Comparison of different methods for determination of drip loss and their relationships to meat quality and carcass characteristics in pigs

Samples of the M. longissimus dorsi of 776 pigs from three commercial lines were used to compare two methods for measuring drip loss, referred to as the EZ-DripLoss and bag methods. Furthermore, relationships between drip loss and other meat quality and carcass traits were analysed. The bag method used a slice of M. longissimus dorsi of approximately 120 g hung in an airtight container whereas the EZ-DripLoss method used two samples of approximately 10 g placed in drip loss containers. In the bag method, samples taken at 24 h post-mortem were measured 24 and 48 h after sampling and average drip loss was 1.94% and 3.33% at 24 and 48 h, respectively. Correlation between these consecutive measurements was high (r=0.98). Using the EZ-DripLoss method, drip loss of samples taken at 24 h post-mortem was measured 48 h after sampling and showed an average value of 4.97%. Correlation between the drip loss obtained using EZ-DripLoss and bag methods was high (r=0.86). Relationships between drip loss and other meat quality traits were similar for both methods. Highest correlations were observed between drip loss and pH(45) (r=-0.52 and -0.48 using EZ-DripLoss method(48) and bag method(48), respectively) and the lowest to Minolta a (∗) value (r=0.11 and 0.09, respectively). Correlations among several carcass traits, such as lean content, and drip loss were low or not significant. Low associations between loin eye area (cm(2)) and drip loss were obtained regardless of the method used to determine drip loss (r=0.21 and 0.18 using EZ-DripLoss method(48) and bag method(48), respectively). For routine measurements, the EZ-DripLoss method is recommended because it showed a high correlation with the bag method but is easier to perform and is more standardised.

Bovine β-defensins: Identification and characterization of novel bovine β-defensin genes and their expression in mammarygland tissue

Abstractβ-Defensin genes code for multifunctional peptides with a broad-range antimicrobial activity. In this project we hypothesized that β-defensin genes may be candidate genes for resistance to mastitis. In this article we describe the identification and genomic characterization of eight bovine β-defensin genes, including six novel defensin genes and two pseudogenes. Expression in the bovine mammary gland of one of the novel genes, DEFB401, has been demonstrated, as well as the expression of LAP, TAP, DEFB1, BNBD3, BNBD9, and BNBD12. For genomic characterization, 20 BACs from two different bovine BAC libraries (RZPD numbers 750 and 754) were isolated by PCR screening with β-defensin consensus primers derived from published sequences. PCR products from BACs generated with consensus primers have been subcloned and sequenced, revealing a total of 16 genes and two pseudogenes. Six novel β-defensin genes share the typical exon–intron structure and are highly homologous to published bovine β-defensin genes. They are named DEFB401–DEFB405 and LAP-like, and two novel pseudogenes are named EBD-P and EBD-P2. Analysis of mammary gland tissue-derived cDNA from nine cows with different clinical findings demonstrated the expression of several β-defensin genes mentioned above. First results indicate that the lactational status of the cow presumably has no influence on gene expression. Competent knowledge of antimicrobial activity of β-defensins from literature, the abundance of β-defensin mRNA in the bovine mammary gland, and the inducibility of some genes give first evidence that β-defensins may play a role in local host defense during udder infections.

A mammary gland EST showing linkage disequilibrium to a milk production QTL on bovine Chromosome 14

As part of a genome scan, ESTs derived from mammary gland tissue of a lactating cow were used as candidate genes for quantitative trait loci (QTL), affecting milk production traits. Resource families were genotyped with 247 microsatellite markers and 4 polymorphic ESTs. It was shown by linkage analysis that one of these ESTs, KIEL_E8, mapped to the centromeric region of bovine Chromosome (Chr) 14. Regression analysis revealed the presence of a QTL, with significant effect on milk production, in this chromosome region, and analysis of variance showed no significant interaction of marker genotype and family. The estimated significant differences between homozygous marker genotypes were 140 kg milk, −5.02 kg fat yield, and 2.58 kg protein yield for the first 100 days of lactation. Thus, there was strong evidence for a complete or nearly complete linkage disequilibrium between KIEL_E8 and the QTL. To identify the biological function of KIEL_E8, we extended the sequence for 869 bp by 5′-RACE. A 560-bp fragment of this shows a 90.9% similarity to a gene encoding a cysteine- and histidine-rich cytoplasmic protein in mouse. Although such a protein may have a regulatory function for lactation and a linkage disequilibrium between the EST marker and the QTL has been observed, it remains to be elucidated whether they are identical or not. Nevertheless, KIEL_E8 will be an efficient marker to perform marker-assisted selection in the Holstein-Friesian population.

Developments of carcass cuts, organs, body tissues and chemical body composition during growth of pigs

Abstract A serial slaughter trial was carried out to examine the developmental change of physical and chemical body compositionin pigs highly selected for lean content. A total of 48 pigs (17 females and 31 castrated males) were serially slaughteredand chemically analysed. Eight pigs were slaughtered at 20, 30, 60, 90, 120 and 140kg live weight, (LW) respectively.The carcass was chilled and the left carcass side was dissected into the primal carcass cuts ham, loin, shoulder, bellyand neck. Each primal carcass cut was further dissected into lean tissue, bones and rind. Additionally, the physical andchemical body composition was obtained for the total empty body as well as for the three fractions soft tissue, bones andviscera. Viscera included the organs, blood, empty intestinal tract and leaf fat. The relationship between physical orchemical body composition and empty body weight (EBWT) at slaughter was assessed using allometric equations (log 10 y ¼ log 10 a þ b log 10 EBWT). Dressing percentage increased from 69·4 to 85·2% at 20 to 120kg and then decreased to83·1% at 140kg LW, whereas percentage of soft tissue, bones and viscera changed from 23·5 to 33·0%, 10·1 to 6·3%and 14·7 to 10·3%, respectively, during the entire growth period. Substantial changes in proportional weights of carcasscuts on the left carcass side were obtained for loin (10·5 to 17·5%) and belly (11·3 to 13·8%) during growth from 20 to140kg. Soft tissue fraction showed an allometric coefficient above 1 (b ¼ 1·14) reflecting higher growth rate in relation tothe total empty body. The coefficients for the fractions bones and viscera were substantially below 1 with b ¼ 0·77 and0·79, respectively, indicating substantial lower growth relative to growth of the total empty body. Lean tissue allometricgrowth rate of different primal cuts ranged from b ¼ 1·02 (neck) to 1·28 (belly), whereas rates of components associatedwith fat tissue growth rate ranged from b ¼ 0·62 (rind of belly) to 1·79 (backfat). For organs, allometric growth rate rangedfrom b ¼ 0·61 (liver) to 0·90 (spleen). For the entire empty body, allometric accretion rate was 1·01, 1·75, 1·02 and 0·85for protein, lipid, ash and water, respectively. Extreme increase in lipid deposition was obtained during growth from 120 to140kg growth. This was strongly associated with an increase in backfat and leaf fat in this period. Interestingly, breedsselected for high leanness such as Pie´train sired progeny showed an extreme increase in lipid accretion at a range of LWfrom 120 to 140kg, which indicates that selection has only postponed the lipid deposition to an higher weight comparedwith the normally used final weight of 100kg on the performance test. The estimates obtained for allometric growth ratesof primal carcass cuts, body tissue and chemical body composition can be used to predict changes in weight of carcasscuts, determine selection goals concerning lean tissue growth, food intake capacity, etc. and generally as inputparameters for pig growth models that can be used to improve the efficiency of the entire pig production system for pigshighly selected for lean content.Keywords: allometry, body composition, carcass composition, growth, organs, pigs.

Quantitative trait loci for chemical body composition traits in pigs and their positional associations with body tissues, growth and feed intake

In this study, quantitative trait loci (QTL) for chemical and physical body composition, growth and feed intake in pigs were identified in a three-generation full-sib population, developed by crossing Pietrain sires with a commercial dam line. Phenotypic data from 315 F(2) animals were available for protein and lipid deposition measured in live animals by the deuterium dilution technique at 30-, 60-, 90-, 120- and 140-kg body weight. At 140-kg body weight, carcass characteristics were measured by the AutoFOM grading system and after dissection. Three hundred and eighty-six animals from 49 families were genotyped for 51 molecular markers covering chromosomes SSC2, SSC4, SSC8, SSC9, SSC10 and SSC14. Novel QTL for protein (lipid) content at 60-kg body weight and protein (lipid) accretion from 120 to 140 kg were detected on SSC9 near several previously detected QTL for lean and fat tissue in neck, shoulder and ham cuts. Another QTL for lipid accretion was found on SSC8, closely associated with a QTL for intramuscular fat content. QTL for daily feed intake were detected on SSC2 and SSC10. The favourable allele of a QTL for food conversion ratio (FCR) on SSC2 was associated with alleles for increased lean tissue and decreased fat tissue. Because no QTL for growth rate were found in the region, the QTL for FCR is most likely due to a change in body composition. These QTL provide insights into the genomic regulation of chemical or physical body composition and its association with feed intake, feed efficiency and growth.

Analysis of feed intake and energy balance of high-yielding first lactating Holstein cows with fixed and random regression models.

At the dairy research farm Karkendamm, the individual roughage intake was measured since 1 September 2005 using a computerised scale system to estimate daily energy balances as the difference between energy intake and calculated energy requirements for lactation and maintenance. Data of 289 heifers with observations between the 11th and 180th day of lactation over a period of 487 days were analysed. Average energy-corrected milk yield, feed intake, live weight and energy balance were 31.8kg, 20.6kg, 584 kg and 13.6 MJ NEL (net energy lactation), respectively, per day. Fixed and random regression models were used to estimate repeatabilities, correlations between cow effects and genetic parameters. The resulting genetic correlations in different lactation stages demonstrate that feed intake and energy balance at the beginning and the middle of lactation are genetically different traits. Heritability of feed intake is low with h2=0.06 during the first days after parturition and increases in the middle of lactation, whereas the energy balance shows the highest heritability with h2=0.34 in the first 30 days of lactation. Genetic correlations between energy balance and feed intake and milk yield, respectively, illustrate that energy balance depends more on feed intake than on milk yield. Genetic correlation between body condition score and energy balance decreases rapidly within the first 100 days of lactation. Hence, to avoid negative effects on health and reproduction as consequences of strong energy deficits at the beginning of lactation, the energy balance itself should be measured and used as a selection criterion in this lactation stage. Since the number of animals is rather small for a genetic analysis, the genetic parameters have to be evaluated on a more comprehensive dataset.