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Genetic analysis of milk protein composition and of its relationship with renneting properties of individual cow milk
Full text linkMilk coagulation properties (MCP) are a fundamental aspect in cheese production, but un unfavorable trend over year on MCP have been observed in several countries. The cheese yield has decreased, accentuating the necessity to provide dairies with milk well suited for dairy products manufacture. During the past decades the focus of milk production has been kg’s of milk protein, but total milk protein content is a poor indicator of MCP, and the lack of an appropriate high-throughput analysis for routine determination of milk coagulation is currently limiting the opportunity to improve MCP by direct selection. Milk protein composition has long been a subject of interest for worldwide dairy researchers. As a consequence, information on milk protein genotype could be utilized to improve milk protein composition and MCP trough marker assisted selection without having to phenotype large progeny groups. Considering such options, it would be desirable to gain further knowledge about effects of milk protein genetic variants on milk protein composition and on MCP.
Aims of the study were to investigate the effects of CSN2-CSN3 haplotypes (β-κ-casein) and BLG (β-Lactoglobulin, β-LG) genotypes on milk production traits, contents of protein fractions and detailed protein composition; to investigate the effects of CSN2-CSN3 haplotypes, BLG genotypes, contents of milk protein fractions and protein composition on MCP; to investigate the effect exerted by the relative ratio of κ-CN A to κ-CN B content on MCP and industrial cheese yield of three Italian cheese varieties. The final aim was to estimate genetic parameters of major milk protein fractions and estimate genetic and phenotypic correlation between milk protein fractions and MCP.
A new reversed-HPLC method for the separation and quantification of the most common genetic variants of bovine milk proteins was developed and validated testing linearity, repeatability, reproducibility and accuracy. Contents of major protein fractions were measured by this new method in individual milk samples of 2,167 Simmental cows. Protein composition was measured as weight percentage of each casein (CN) fraction to total casein (TCN) and as weight percentage of β-LG to total whey protein (WH). Genotypes at CSN2, CSN3 and BLG loci were also assessed by HPLC and CSN2-CSN3 haplotype probabilities were estimated for each cow. Rennet coagulation time (RCT) and curd firmness (a30) were measured using a computerized renneting meter.
Effects of haplotypes and BLG genotypes on yields were weak or trivial. Haplotypes carrying CSN2 B and CSN3 B exhibited greater TCN and casein number (CI), in comparison with all other haplotypes. Genotype BB at BLG was associated with increased protein, TCN and CI, when compared to genotype AA. Haplotypes including CSN3 B were associated with greater κ-CN content and percentage. Allele CSN2 B was associated with an increase of β-CN content, which occurred at the expense of content of αS1-CN. Haplotypes including allele CSN2 A1 exhibited decreased β-, αS2- and γ-CN concentrations and increased αS1- and κ-CN contents, whereas CSN2 I exerted positive effects on β-CN concentration, without altering other protein fractions content. Effects exerted by haplotypes on CN composition were similar to those exhibited on CN fractions contents. Allele BLG A increased β-LG concentration and altered the β-LG to α-Lactalbumin (α-LA) ratio.
When protein fractions contents or protein composition were not included in the statistical model, haplotypes carrying CSN3 B allele exhibited shorter RCT and greater a30, in comparison with those carrying CSN3 A, and haplotypes carrying CSN2 B allele were responsible for a noticeable decrease of RCT and for an increase of a30, when compared to haplotype A2A. When effects of protein fractions contents or of protein composition were added to the model, no difference across haplotypes due to CSN3 and CSN2 alleles was observed for MCP, with the exception of the effect of CSN2 B on RCT, which remained markedly favorable. Also, the favorable effect exerted by CSN2 B on a30 was mediated by the increase of β-CN B in milk. Conversely, β-CN B is likely to exert a molecular effect on RCT, which does not depend upon variation of β-CN content associated to allele B.
To test if the lack of effect of κ-CN genetic variant would have been observed also on cheese yield, milks with different κ-CN A to κ-CN B content ratios were separately manufactured to produce Montasio, Asiago and Caciotta cheese. Milk was characterized by having similar composition in terms of protein, TCN, CI, CN composition, β-CN composition and pH. Milk with the higher proportion of κ-CN B (HIGHB) exhibited similar coagulation properties but a higher cheese yield in all the investigated cheese in comparison with milk with a lower proportion of κ-CN B (LOWB). However, the increment of yield observed for HIGHB milk in Montasio cheese was ascribed to a greater fat content of HIGHB milk in comparison with LOWB milk. The probability of HIGHB milk giving a cheese yield 5 % greater than that of LOWB milk ranged from 51 to 67 % for Montasio cheese, but was lower than 21 % for Asiago and Caciotta cheeses. Thus, the ratio of κ-CN A to κ-CN B content did not relevantly affect industrial cheese yield when milks of similar CN composition were processed, and an indirect effect due to the higher κ-CN content of κ-CN B milk on cheese yield is to be suggested.
Values of heritability for αS1-CN%, κ-CN% and β-CN% were similar and ranging from 0.61 to 0.70, whereas heritability of αS2-CN%, γ-CN% and β-LG% were 0.28, 0.29 and 0.33, respectively. When CSN2-CSN3 haplotype and BLG genotype were accounted for by the model, heritability estimates of all the protein fractions became similar suggesting that proteins synthesis is regulated by specific genes which control the overall production of milk protein. Genetic correlations among the contents of the five CN fractions and between CN fractions and WH fractions were generally low. Generally, all the CN fractions were also moderately positively correlated with WH. When data where adjusted for CSN2-CSN3 haplotype and BLG genotype, genetic correlations among the contents of protein fractions markedly increased confirming that all the fractions undergone a common regulation. The content and the relative proportion of κ-CN were not genetically correlated with RCT, αS1- and αS2-CN were unfavourately correlated with RCT, but increasing the content of β-CN in milk would result in a shorter RCT. Stronger curds were associated with higher κ-CN and β-CN, and with lower αS1-, αS2-, and γ-CN contents and proportions. Results confirm the lack of favorable associations between TCN and MCP indicating that other traits, i.e. milk protein fractions, should be used for the genetic improvement of cheese-making properties.Le proprietà di coagulazione del latte (MCP) sono un aspetto fondamentale nella produzione di formaggio, tuttavia, negli ultimi anni, è stato registrato un andamento sfavorevole della coagulazione del latte in diversi Paesi. La resa in formaggio è diminuita, accentuando la necessità di fornire i caseifici con latte più adatto per la trasformazione in formaggio. Nel corso degli ultimi decenni il miglioramento genetico si è focalizzato sui kg di proteina del latte, ma il contenuto totale di proteina non sembra essere un buon indicatore delle MCP, e la mancanza di un metodo di analisi che consenta la determinazione delle MCP su larga scala attualmente limita la possibilità di migliorare le MCP attraverso una selezione diretta. La composizione proteica del latte è stato a lungo oggetto di interesse per i ricercatori di tutto il mondo. Di conseguenza, le informazioni sul genotipo delle proteine del latte potrebbero essere utilizzate per migliorare la composizione della proteina oppure nella selezione assistita da marcatori per migliorare le MCP, senza dover fenotipizzare grandi gruppi di progenie. Alla luce di tali possibilità, sarebbe auspicabile poter acquisire ulteriori conoscenze sugli effetti delle varianti genetiche delle proteine sulla composizione proteica del latte e sulle MCP.
Obiettivi di questa tesi sono stati: studiare gli effetti dell’aplotipo CSN2-CSN3 (β-κ-caseina) e del genotipo al locus BLG (β-lattoglobulina, β-LG) su caratteri produttivi, contenuto di frazioni proteiche e composizione proteica; studiare gli effetti dell’aplotipo CSN2-CSN3 e del genotipo al locus BLG, del contenuto di frazioni proteiche e della composizione proteica sulle MCP, studiare l'effetto esercitato dal rapporto relativo tra κ-CN A e B sulle MCP e sulla resa industriale in tre varietà di formaggi italiani. Inoltre, ultimo obiettivo del lavoro è stato la stima dei parametri genetici delle principali frazioni proteiche del latte e delle correlazioni genetiche e fenotipiche tra le frazioni proteiche e le MCP.
Un nuovo metodo di analisi HPLC a fase inversa per la separazione e la quantificazione delle più comuni varianti genetiche delle proteine del latte bovino è stato sviluppato e validato attraverso test di linearità, ripetibilità, riproducibilità e accuratezza. Il contenuto delle principali frazioni proteiche è stato misurato con questo nuovo metodo in campioni di latte individuale di 2,167 bovine di razza Simmental. La composizione proteica è stata espressa come percentuale in peso di ogni frazione caseinica rispetto al contenuto totale di caseina (TCN) e come percentuale del peso della β-LG sul totale di proteine del siero (WH). Il genotipo ai loci CSN2, CSN3 e BLG è stato determinato tramite HPLC e le probabilità aplotipiche per gli aplotipi CSN2-CSN3 sono state stimate per ogni animale. Tempo di coagulazione (RCT) e consistenza del coagulo (a30) sono stati misurati utilizzando un lattodinamografo.
Gli effetti dell’aplotipo delle caseine e del genotipo al locus BLG sui caratteri produttivi sono stati limitati o trascurabili. Gli aplotipi contenenti gli alleli CSN2 B e CSN3 B hanno mostrato valori più elevati di TCN e un indice caseinico (CI) superiore, rispetto a tutti gli altri aplotipi. Il genotipo BB al locus BLG è stato associato ad un aumento del contenuto proteico e ad un CI superiore rispetto al genotipo AA. Gli aplotipi contenenti l’allele CSN3 B sono stati associati a contenuti e percentuali di κ-CN maggiori. L’allele CSN2 B è risultato associato con un aumento del contenuto di β-CN, che si è verificato a scapito del contenuto di αS1-CN. Gli aplotipi che includevano la variante CSN2 A1 hanno mostrato una diminuzione del contenuto di β-, αS2- e γ-CN e un aumento del contenuto di αS1- e κ-CN, mentre la variante CSN2 I ha esercitato effetti positivi sulla concentrazione di β-CN, senza alterare il contenuto delle altre frazioni proteiche. L’allele A al locus BLG è stato associato ad una maggiore concentrazione di β-LG e ad un più elevato rapporto tra β-LG e α-lattoalbumina (α-LA).
Quando il contenuto delle frazioni proteiche o la composizione della proteina non erano inclusi nel modello statistico, gli aplotipi contenenti l’allele CSN3 B erano associati ad RCT più brevi ed a30 maggiori, rispetto a quelli che includevano l’allele CSN3 A, e gli aplotipi contenenti la variante CSN2 B erano responsabili di una notevole diminuzione dei valori di RCT e per valori di a30 maggiori, rispetto agli aplotipi contenente la variante A2. Quando gli effetti del contenuto delle frazioni proteiche o della composizione proteica sono stati inclusi nel modello statistico, nessuna differenza tra aplotipi riconducibile agli alleli ai loci CSN3 e CSN2 è stata osservata per le MCP, con l'eccezione dell’effetto della CSN2 B su RCT, che è rimasto molto favorevole. L'effetto favorevole esercitato dall’allele CSN2 B su a30 è risultato mediato dall’aumento di β-CN B nel latte. Al contrario, la β-CN B esercita probabilmente un effetto diretto su RCT, che non dipende dalla variazione del contenuto di β-CN associato all’allele B.
Per verificare se la mancanza di effetto diretto delle varianti genetiche di κ-CN sarebbe stato osservato anche sulla resa in formaggio, latte con differenti rapporti tra κ-CN A e B sono stati lavorati separatamente per la produzione di Montasio, Asiago e Caciotta. Il latte lavorato aveva composizione simile in termini di proteina, TCN, CI, composizione caseinica, composizione della β-CN e pH simile. Il latte con la percentuale maggiore di κ-CN B (HIGHB) ha presentato valori di MCP simili, ma una resa superiore in tutti i tipi di formaggio esaminati, rispetto al latte con una percentuale inferiore di κ-CN B (LOWB). Tuttavia, l'incremento di resa osservato per il formaggio Montasio è stato attribuito a un maggior contenuto di grasso del latte HIGHB in confronto con il latte LOWB. La probabilità del latte HIGHB di dare un formaggio con una resa del 5% superiore a quella del latte LOWB variava dal 51 al 67% per il Montasio, ma è stata inferiore al 21% per Asiago e Caciotta. Il rapporto tra le varianti A e B di κ-CN non ha quindi influito in modo rilevante sulla resa casearia industriale, quando la composizione del latte era bilanciata per la composizione caseinica, ed è possibile supporre pertanto che vi sia un effetto indiretto delle varianti di κ-CN sulla resa casearia, a causa del più elevato contenuto di κ-CN associato alla variante B.
I valori di ereditabilità per αS1-CN%, κ-CN% e β-CN% erano simili e variabili da 0.61 al 0.70, mentre l’ereditabilità di αS2-CN%, γ-CN% e β-LG% erano 0.28, 0.29 e 0.33, rispettivamente. Quando l’effetto dell’aplotipo CSN2-CSN3 e del genotipo al locus BLG sono stati inclusi nel modello, le stime di ereditabilità di tutte le frazioni proteiche sono divenute simili suggerendo che la sintesi di proteine del latte sia sottoposta a un controllo genetico da parte di geni specifici che controllano il livello generale di proteina del latte. Le correlazioni genetiche tra il contenuto delle 5 frazioni caseiniche e tra le frazioni caseiniche e le frazioni sieriche erano generalmente basse. In generale, tutte le frazioni caseiniche erano anche moderatamente positivamente correlata con WH, suggerendo che vi sia una regolazione generale del livello di proteina del latte che coinvolge contemporaneamente TCN e WH. Quando l’effetto dell’aplotipo CSN2-CSN3 e del genotipo al locus BLG sono stati inclusi nel modello, le correlazioni genetiche tra i contenuti delle frazione proteiche sono aumentate significativamente, supportando l’ipotesi che tutte le frazioni siano oggetto di una regolazione generale. Il contenuto di κ-CN del latte non è risultato essere geneticamente correlato con RCT, αS1- and αS2-CN hanno mostrato una correlazione sfavorevole con RCT, mentre un aumento della β-CN nel latte sarebbe a favore di RCT più brevi. Coaguli più consistenti sono stati associati ad un maggior contenuto di κ-CN e β-CN e ad un minor contenuto di αS1-, αS2-, e γ-CN. I risultati ottenuti confermano la mancanza di un’associazione favorevole tra TCN e MCP, sottolineando l’esigenza di utilizzare altri caratteri, come il contenuto delle frazioni proteiche, per il miglioramento genetico delle proprietà casearie del latte
Glycosylation of κ-casein: Genetic and nongenetic variation and effects on rennet coagulation properties of milk.
No full textThe aims of this study were to investigate genetic and nongenetic variation in the degree of glycosylation of κ-casein (κ-CN) and to estimate the effects of glycosylated (G-κCN) and unglycosylated (U-κCN) κ-CN contents on milk coagulation properties of Simmental cows. Measures of contents of the main casein fractions, G-κCN, and U-κCN, and assessment of genotypes at CSN2, CSN3, and BLG were obtained by reversed-phase HPLC analysis of 2,015 individual milk samples. Content of total κ-CN (κ-CNtot, g/L) was the sum of G-κCN and U-κCN, and the glycosylation degree of κ-CN (GD) was measured as the ratio of G-κCN to κ-CNtot. Rennet coagulation time (RCT) and curd firmness were measured by using a computerized renneting meter. Measures of curd firmness were adjusted for RCT before statistical analysis. Variance components of κ-CNtot, G-κCN, U-κCN, and GD were estimated by Bayesian procedures and univariate linear models that included the class effects of the herd-test-day, parity, days in milk, genotypes at milk protein genes, and animal. These class effects, those of G-κCN, U-κCN, and content of other caseins, and the linear effect of milk pH were accounted for by models investigating the influence of κ-CN glycosylation on coagulation properties. The GD ranged from 22 to 76%, indicating that variation in G-κCN depends on the variation both in κ-CNtot and in the efficiency of κ-CN glycosylation. Genotype CSN3 BB exhibited high G-κCN and U-κCN relative to that of CSN3 AA. Heritability of G-κCN, U-κCN, and GD was high and ranged from 0.46 to 0.56. A large proportion of the additive genetic variation in G-κCN and U-κCN was attributable to influence of CSN and BLG, but these genes did not affect variation in GD, and across-genotypes differences in the trait were small or trivial. Average RCT of the milk class having the highest G-κCN was, on average, 2min (standard deviation 0.5) shorter than that of the lowest class. Conversely, U-κCN and content of other caseins were not associated with any effect on RCT, except for a slight delay in coagulation when U-κCN was very high. Curd firmness increased when the contents of both κ-CN fractions and other caseins increased. This study provides evidence that the positive association between RCT and κ-CN content is exclusively attributable to the glycosylated fraction of the protein. Because exploitable additive genetic variation in G-κCN exists, improvement of κ-CN composition through selective breeding might be an effective way to enhance milk coagulation properties
Short communication: Predictive ability of Fourier-transform mid-infrared spectroscopy to assess CSN genotypes and detailed protein composition of buffalo milk
Full text linkThe aim of this work was to test the applicability of Fourier-transform mid-infrared spectroscopy (FT-MIR) for the prediction of the contents of casein (CN) and whey protein fractions in buffalo milk. Buffalo milk samples spectra were collected using a MilkoScan FT2 (Foss, Hillerød, Denmark) over the spectral range from 5,000 to 900 wavenumber × cm(-1). Contents of protein fractions, as well as CSN1S1 and CSN3 genotypes, were assessed by reversed phase HPLC. The highest coefficients of determination in cross-validation (1 - VR) were obtained for the contents (g/L of milk) of total protein and CN (1 - VR = 0.92), followed by the content of β-CN, total whey protein, and αS2-CN (1 - VR of 0.87, 0.77, and 0.63, respectively). Conversely, contents of αS1-CN, γ-CN, glycosylated-κ-CN, total κ-CN, and whey protein fractions were predicted with poor accuracy (1 - VR <0.51). When protein fractions were expressed as percentages to total protein, 1 - VR values were never greater than 0.61 (β-CN). Only 56 and 70% of the observations were correctly classified by discriminant analysis in each of 2 groups of CSN1S1 and CSN3 genotypes, respectively. Results showed that FT-MIR spectroscopy is not applicable when prediction of detailed milk protein composition with high accuracy is required. Predictions may play a role as indicator traits in selective breeding, if the genetic correlation between FT-MIR predictions and measures of milk protein composition are high enough and predictions of protein fraction contents are sufficiently independent from the predicted total protein content
Genetic associations between daily gain and live fleshiness of station-tested young bulls and carcass and meat quality traits of commercial intact males in Piemontese cattle.
No full textThe aim of this study was to investigate genetic relationships between beef traits of station-tested young bulls and carcass and meat quality traits (MQ) of commercial intact males in Piemontese cattle. Phenotypes for daily gain (DG) and live fleshiness traits (width at withers: WW; shoulder muscularity: SM; loin width: LW; loin thickness: LT; thigh muscularity: TM; thigh profile: TP) and thinness of the shin bone (BT) were available for 3,109 and 2,183 performance-tested young bulls, respectively. Carcass daily gain (CDG), carcass conformation (SEUS), pH at 24 h (pH24h) and 8 d after slaughter (pH8d), lightness (L*), redness (a*), yellowness (b*), hue angle (HA), saturation index (SI), drip loss (DL), cooking loss (CL), and shear force (SF) were assessed for 1,208 commercial intact males. (Co) variance components were estimated in a set of twelve 9-traits analyses using REML and linear animal models including all performance-test traits and 1 carcass or MQ trait at a time. Heritabilities ± SE of beef traits ranged from 0.26 ± 0.03 (LW) to 0.47 ± 0.01 (DG), whereas those of carcass traits and MQ from 0.06 ± 0.03 (CL) to 0.63 ± 0.04 (HA). The genetic correlation (rg) between DG and CDG was 0.75 ± 0.10, indicating that DG, as measured at the test station, is a good indicator of the carcass gain achieved by commercial animals under farms conditions. Daily BW gain of station-tested bulls correlated positively with color traits (from 0.11 ± 0.12 to 0.54 ± 0.09), ph8d (rg ± SE = 0.31 ± 0.11), DL (rg ± SE = 0.29 ± 0.17), and CL (rg ± SE = 0.27 ± 0.18). Live fleshiness of station-tested bulls exhibited genetic correlations with MQ of commercial animals that were positive for L* and b* (from 0.13 ± 0.08 to 0.65 ± 0.14) and negative for pH (from –0.27 ± 0.15 to –0.57 ± 0.11), CL (from –0.16 ± 0.23 to –0.43 ± 0.22), and SF (TM: rg ± SE = –0.31 ± 0.15; TP: rg ± SE = –0.41 ± 0.17). The thinness of the shin bone correlated unfavorably with CDG (rg ± SE = –0.74 ± 0.07) and favorably with SEUS (rg ± SE = 0.65 ± 0.17), CL (rg ± SE = –0.39 ± 0.13), and SF (rg ± SE = –0.32 ± 0.17). The estimated genetic correlations indicate that selection to increase DG, as measured at the test station, exerts moderate adverse effects on MQ. Because selection emphasis is greater for live fleshiness than for DG, the correlated response in MQ and carcass traits is expected to be influenced to a greater extent by selection for muscularity, even though these traits are less heritable than DG
Direct and social effects on variation of carcass and ham quality traits in Italian heavy pigs.
No full textEffects of variation in milk coagulation properties on cheese yield, curd composition and recovery rates of the main milk constituents measured by micro-cheese making.
No full textEffect of parity, days in milk, and milk yield on detailed milk protein composition in Mediterranean water buffalo.
No full textThe effects of some nongenetic factors on milk protein fraction contents and relative proportions were estimated in 606 individual milk samples of Mediterranean water buffalo. Content of α(S1)-casein (CN), α(S2)-CN, β-CN, γ-CN, κκ-CN, glycosylated κ-CN (glyco-κ-CN), α-lactalbumin, and β-lactoglobulin was measured by reversed-phase HPLC. Relative contents of α(S1)-CN%, α(S2)-CN%, β-CN%, and κ-CN% were, respectively, 32.1, 17.1, 34.5, and 15.7%, whereas γ-CN% accounted for 0.6% of total casein content. Increasing total casein content in milk would result in a greater proportion of β-CN% at the expense of all of the other major casein fractions, especially of κ-CN%. Values of α(S2)-CN%, β-CN%, and γ-CN% tended to decrease with parity, although their variations were not significant, whereas α(S1)-CN% and glyco-κ-CN% showed the opposite trend. Contents of most protein fractions showed the typical trends observed for milk components as lactation progressed, with high contents in early lactation, a minimum in midlactation, followed by a gradual increase toward the latter part of lactation. Values of α(S1)-CN% increased during lactation, whereas α(S2)-CN% decreased. The proportion of β-CN% had its maximum value between 60 and 160 d of lactation, followed by a decrease, whereas κ-CN% had its minimum value in early lactation (<60 d) and remained relatively constant in the period of mid and late lactation. Glyco-κ-CN% and β-lactoglobulin% decreased in the first part of lactation, to reach their minimum values in midlactation, followed by an increase. Milk of top-producing buffaloes, compared with that of low-producing ones, had a significantly greater value of β-CN% and glyco-κ-CN%, and lower proportion of α(S1)-CN%. The possible effect exerted by protein genetic variants in affecting variation of milk protein fraction contents and relative proportions should be further considered to better get insight into buffalo milk protein composition
Effects of k-CN glycosylation on rennet coagulation properties of milk in Simmental cattle
No full textContents of casein fractions are known to affect coagulation properties and
cheese yield of milk, but studies on the effects of κ-CN composition on variation
of coagulation properties of milk are still very scarce. Effects exerted by κ-CN composition on variation of milk coagulation properties (MCP) were investigated using 2,084 individual milk samples of Simmental cows. Rennet coagulation time (RCT), and curd firmness (A30) were measured using a computerized renneting meter. Milk protein composition and genotypes at CSN2, CSN3 and BLG were obtained by reversed-phase HPLC. The percentage ratios of κ-CN (κCN%), of Glycosylated-κ-CN (G-κCN%), and Unglycosylated-κ-CN (U-κCN%) to total casein were measured. The degree of glycosylation (GD) was measured as the percentage ratio of glycosylated-κ-CN to total κ-CN. A difference of 1.7 min (corresponding to 0.37 SD of the trait) was observed for the average RCT of the two extreme classes
of κCN% content. RCT decreased when κCN% and G-κCN% increased, whereas U-κCN% exhibited a slightly unfavourable effect on the onset of the coagulation process. A slight decrease of RCT was also observed for high GD, although this effect was less clear than that of G-κCN%. A favourable effect of κCN%, G-κCN% and GD on A30was also detected
Short communication: Mid-infrared spectroscopy prediction of fine milk composition and technological properties in Italian Simmental
Full text linkThe objective of this study was to evaluate the ability of mid-infrared predictions of fine milk composition and technological traits to serve as a tool for large-scale phenotyping of the Italian Simmental population. Calibration equations accurately predicted the fatty acid profile of the milk, but we obtained moderate or poor accuracy for detailed protein composition, coagulation properties, curd yield and composition, lactoferrin, and concentration of major minerals. To evaluate the role of infrared predictions as indicator traits of fine milk composition in indirect selective breeding programs, the genetic parameters of the traits predicted using mid-infrared spectra need to be estimated
Genetic analysis of Spondylosis Deformans and effect of inbreeding on the degree of osteophytes development in Italian Boxer dogs
No full textSpondylosis deformans is a degenerative disease of the spine exhibiting the presence of one or more osteophytes, showing different degrees of development at the level of vertebral bodies (Morgan, 1967). A recent study (Carnier et al., 2004), although conducted on a relatively small sample of Italian Boxer dogs, showed that additive genetic variation for the degree of osteophytes development (DOD) is large enough to be exploited in specific breeding programs.
The high prevalence of diseases and defects in pure dog breeds might be due to high selection intensities in genetically closed populations (Ubbink, 1998). Inbreeding affects mostly fitness traits and traits which are of qualitative inheritance but also quantitative traits (Klemetsdal, 1998). Mäki et al. (2001) reported estimates of inbreeding depression on hip and elbow dysplasia in six dog breeds in Finland, but no previous studies dealing with inbreeding depression on DOD in Boxer dogs are available. The aims of this study were to infer (co)variance component for DOD and to asses the effect of inbreeding depression on DOD in the Italian Boxer dog population. In conclusion The degree of osteophytes development shows exploitable additive genetic variation. Its extent in the area between the 11th and 13th thoracic vertebrae is of particular importance because it is strictly correlated to the degree of osteophytes development of all the other sites, and has a moderate heritability. A slightly detrimental effect have been noticed for the inbreeding, especially for group of dogs with F greater than 10%
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