ESTIMATION OF GENETIC RELATIONSHIPS AMONG MILK RECORDS FOR FIRST THREE LACTATIONS USING REML FOR AN ANIMAL MODEL

In dairy cattle breeding, genetic relationships among lactation records are of special interest because most selection operated on first lactations. This selection also complicates estimation of genetic parameters. Techniques which give estimates unbiased by selection should be used. Estimation was done using EM-type REML for an animal model neglecting relationships across herds. Records were from 3,070 Holstein cows which had the fist lactation recorded. Estimates after 17 rounds of iteration for heritabilities and genetic correlations were: h21=.33, h22=.32, h23=.33, r12=.88, r13= .83, r23= .86. Within herd-year-season phenotypic standard deviations were 1,223 kg, 1,323 kg, and 1,265 kg

Auswirkungen differenzierter ökologischer Bewirtschaftung von Ansaat- und Dauergrünland auf Futterangebot, Fressverhalten sowie Weideleistung und Schlachtreife von Ochsen und Färsen

Von 2004 bis 2006 wurde durch die Universität Halle-Wittenberg am ZTT Iden der LLFG Sachsen-Anhalt ein Versuch zur Weidemast von Rindern auf 26 ha extensiv ökologisch bewirtschaftetem Dauergrünland in zwei Düngungsstufen (0 und 70 kg N/ha) durchgeführt. Die jährlich zwei Versuchsherden bestanden aus je circa 30 Absetzern (Ochsen und Färsen) üblicher Gebrauchskreuzungen (2004; tragende HF-Färsen). Der Tierbesatz lag bei max. 1 - 1,4 GV/ha. Die Versuchsflächen (vier Koppeln/Herde) lagen auf drei, bezüglich Bodenart, Feuchtigkeit und Pflanzenbestand, unterschiedlichen Standorten. Die Artenzahl war vom vorhandenen Pflanzenbestand zu Versuchsbeginn abhängig. Ein Flächentyp (Ansaatgrünland, leichter Boden) zeigte sich äußerst problematisch hinsichtlich Pflanzenbestand und Ertrag. Im überständigen Aufwuchs wurden vorwiegend Blattmasse enthaltende Bestandesschichten bevorzugt und Stängel und Blüten verschmäht. Die Energiekonzentrationen und Verdaulichkeiten des aufgenommenen Futters lagen deutlich über denen im Mittel des Futterangebotes, wobei der Unterschied besonders gegen Ende einer Teilflächenbeweidung deutlich wurde. Die Tiere waren in der Lage, durch die Futterselektion sehr lange ein hohes Qualitätsniveau zu halten und somit rückläufige Qualitätsentwicklungen zu einem guten Teil auszugleichen. Die Alkanmethode erwies sich mit der Unterscheidung ledig nach Artengruppen und für Untersuchungen von teils überständigen Pflanzenaufwüchsen zur Ermittlung einer artengruppenspezifischen Futterselektion als ungeeignet. Bezüglich des Tierverhaltens konnten zwischen beiden Herden signifikante, geringfügige Unterschiede festgestellt werden. Die mittleren Lebendmassezunahmen lagen bei über 800g pro Tag und waren hinsichtlich der Düngungsvarianten nicht signifikant unterschiedlich. Die Schlachtkörper sowohl der Ochsen wurden mit U und R (Fleischigkeit) eingestuft. Bei über 80 % der Tiere wurde die angestrebte Fettklasse 3 erzielt

Genetics of lactation persistency

peer reviewedLactation persistency, often simply called persistency, in general can be defined as the ability to maintain yields during the lactation. Persistency has an impact on feed costs, health, and fertility. Of these three components affected by persistency, the impact of persistency on health, i.e. metabolic stress of the cow leading to health problems, may be most important nowadays. Numerous suggestions for criteria of persistency exist. Often simple ratios of part-lactation yields, e.g. the ratio of yield in the first and last 100 days of lactation, have been used. New approaches have used results from the application of random regression test day models developed for the genetic evaluation of yield traits. Many studies have unfortunately neglected the effect of gestation on persistency but acknowledged that an improved persistency should lead to an improved reproductive performance. Both relationships should be considered in genetic analyses and recommendations for improvement of management decisions. Today the correct description of persistency plays a prominent role to obtain correct genetic evaluations based on test day yields. But, although apparently trivial, a direct genetic analysis of lactation persistency and even more an inclusion of this trait into selection programmes clearly is a complicated task. A reason for this, amongst others, is that management strategies for feeding during the lactation and handling of the reproductive performance that are most often not recorded, are likely to mask the real persistency. Future studies on the genetics of persistency should also seek a strong interaction of geneticists and physiologists as persistency is fundamentally confounded with the problem of metabolic stress. Today, a recommendation of the inclusion of persistency in selection programmes appears to be premature and more studies, e. g. on the association of persistency with longevity, could aid in this process.Genetic Improvement of Functional Traits in Cattle (GIFT) - Concerted Actio

Identification of candidate genes for congenital splay leg in piglets by alternative analysis of DNA microarray data

The congenital splay leg syndrome in piglets is characterized by a temporarily impaired functionality of the hind leg muscles immediately after birth. Etiology and pathogenetic mechanisms for the disease are still not well understood. We compared genome wide gene expression of three hind leg muscles (M. adductores, M. gracilis and M. sartorius) between affected piglets and their healthy littermates with the GeneChip® Porcine Genome Array (Affymetrix) in order to identify candidate genes for the disease. Data analysis with standard algorithms revealed no significant differences between both groups. By application of an alternative approach, we identified 63 transcripts with differences in two muscles and 5 genes differing between the groups in three muscles. The expression of six selected genes (SQSTM1, SSRP1, DDIT4, ENAH, MAF, and PDK4) was investigated with SYBRGreen RT - Real time PCR. The differences obtained with the microarray analysis could be confirmed and demonstrate the validity of the alternative approach to microarray data analysis. Four genes with different expression levels in at least two muscles (SQSTM1, SSRP1, DDIT4, and MAF) are assigned to transcriptional cascades related to cell death and may thus indicate pathways for further investigations on congenital splay leg in piglets

Cubic-spline interpolation to estimate effects of inbreeding on milk yield in first lactation Holstein cows

Milk yield records (305d, 2X, actual milk yield) of 123,639 registered first lactation Holstein cows were used to compare linear regression (y = β0 + β1X + e), quadratic regression, (y = β0 + β1X + β2X2 + e) cubic regression (y = β0 + β1X + β2X2 + β3X3 +e) and fixed factor models, with cubic-spline interpolation models, for estimating the effects of inbreeding on milk yield. Ten animal models, all with herd-year-season of calving as fixed effect, were compared using the Akaike corrected-Information Criterion (AICc). The cubic-spline interpolation model with seven knots had the lowest AICc, whereas for all those labeled as “traditional”, AICc was higher than the best model. Results from fitting inbreeding using a cubic-spline with seven knots were compared to results from fitting inbreeding as a linear covariate or as a fixed factor with seven levels. Estimates of inbreeding effects were not significantly different between the cubic-spline model and the fixed factor model, but were significantly different from the linear regression model. Milk yield decreased significantly at inbreeding levels greater than 9%. Variance component estimates were similar for the three models. Ranking of the top 100 sires with daughter records remained unaffected by the model used

Estimation of Genetic (Co)Variances for Milk Yield in First Three Lactations Using an Animal Model and Restricted Maximum Likelihood

Genetic relationships among lactation records are of interest because most selection of bulls is on first lactations. Selection also complicates estimation of genetic parameters. Techniques unbiased by selection should be used. Estimation of genetic and environmental (co)variances was done using restricted maximum likelihood with an expectation-maximization algorithm for an animal model. The algorithm involved solving mixed model equations by direct inversion of coefficient matrix that became feasible by neglecting relationships across herds. From data consisting of first to third lactation milk records of New York Holsteins, two computationally manageable subsets were selected of 15 herds each totaling 3070 and 2900 cows. Each cow had a recorded first lactation and a recorded second lactation if she had a recorded third record. Herds were chosen according to frequency of related animals and about 200 cows per herd. After 18 rounds of iteration, changes in estimates between successive rounds were con- Stantly decreasing and small. Estimates averaged from both subsets gave heritabilities of h12 = .33, h22 = .33, h32 = .34, genetic correlations of rg12 = .86, rg13 = .85, rg23 = .87, and phenotypic correlations of rp12 = .57, rp13 = .52, rp23 = .65

Application of selection index calculations to determine selection strategies in genomic breeding programs

The availability of genomic estimated breeding values (GEBV) allows for possible modifications to existing dairy cattle breeding programs. Selection index calculations including genomic and phenotypic observations as index sources were used to determine the optimal number of offspring per genotyped sire with a focus on functional traits and the design of cooperator herds, and to evaluate the importance of a central station test for genotyped bull dams. Evaluation criteria to compare different breeding strategies were correlations between index and aggregate genotype (r(TI)), and the relative selection response percentage (RSR) of an index without single nucleotide polymorphism information in relation to a single nucleotide polymorphism-based index. The number of required daughter records per sire to achieve a predefined r(TI) strongly depends on the accuracy of GEBV (r(mg)) and the heritability of the trait. For a desired r(TI) of 0.8, h(2) = 0.10, and r(mg) = 0.5, at least 57 additional daughters have to be included in the genetic evaluation. Daughter records of genotyped sires are not necessary for optimal scenarios where rmg is greater than or equal to r(TI). There still is a substantial need for phenotypic daughter records, especially for low-heritability functional traits and r(mg) 0.7, the RSR of conventional breeding programs was only 10% of RSR from genomic breeding strategies. As shown in scenarios including 2 traits in the index as well as in the aggregate genotype, the availability of highly accurate GEBV for production traits and low-accuracy GEBV for functional traits increased the risk of widening the gap between selection responses in production and functionality. Counteractions are possible, such as via higher economic weights for low-heritability functional traits. Finally, an alternative selection strategy considering only 2 pathways of selection for genotyped male calves and for cow dams was evaluated. This strategy is competitive with a 4-pathway genomic breeding program if the fraction of selected male calves for the artificial insemination program is below 1% and if selection is focused on functionality, thus pointing to substantial insufficiencies caused by low reliabilities of breeding values for cows for such traits in conventional bull dam selection schemes

Verbesserung der Langlebigkeit von Milchkühen unter besonderer Berücksichtigung ökologischer Zuchtstrategien (Verbundvorhaben)

Ziel des Projektes „LongLife“ war es, Selektionsinstrumente zur Verbesserung der Langlebigkeit und Tiergesundheit für die ökologische Milchrinderzucht zu entwickeln. Vor dem Hintergrund, dass in der ökologischen Milchviehhaltung Langlebigkeit stärker im Fokus steht als in der konventionellen Zucht, wurden in neun ökologisch wirtschaftenden Betrieben Assoziationen zwischen Merkmalen der Tiergesundheit und der Langlebigkeit der Kühe analysiert und Risikoraten für Abgänge („Survival-Analysen“) in verschiedenen Lebensabschnitten der Tiere geschätzt. Die Ergebnisse zeigten, dass Euter-, Klauen-, sowie Stoffwechselerkrankungen einen stark negativen Einfluss auf die Langlebigkeit haben. Das Abgangsrisiko einer Kuh war insbesondere zum Laktationsende erhöht. Die quantitativ-genetischen Untersuchungen ergaben die höchsten genetischen Varianzen für die Langlebigkeit, wenn der Gesundheitsstatus der Tiere im Modell berücksichtigt wurde. Die maternale Linienvarianz war für Merkmale der Langlebigkeit und Tiergesundheit sehr niedrig. In Schätzungen genetischer Korrelationen zwischen ökologischen und konventionellen Haltungsumwelten auf Basis von Pedigree- und SNP-Daten konnten Genotyp-Umwelt-Interaktionen für Merkmale der Langlebigkeit und Tiergesundheit nachgewiesen werden. In genomweiten Assoziationsstudien gelang es weiterhin Gene zu identifizieren, welche in der ökologischen Haltungsumwelt an der Ausprägung der Langlebigkeit beteiligt sind. Mit dem Ziel, den Zuchtfortschritt für Langlebigkeit voranzutreiben und die Wettbewerbsfähigkeit ökologischer Betriebe gegenüber konventionellen Betrieben aufrechterhalten, wurde in „LongLife“ eine erste Lernstichprobe genotypisierter Kühe aus ökologischen Haltungsumwelten aufgebaut. Auf Basis der generierten Ergebnisse ist es final gelungen, einen Gesamtzuchtwert für Langlebigkeit („RZ-LongLife“) zu konzipieren und Anpaarungsschemata zu entwickeln, um zielgerichtet die Langlebigkeit von Milchkühen in ökologischen Betrieben zu verbessern