JDS
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Interpretive Summary
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Khatib, H.
Right arrow Articles by Dekkers, J. C. M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Khatib, H.
Right arrow Articles by Dekkers, J. C. M.
J. Dairy Sci. 88:1208-1213
© American Dairy Science Association, 2005.

Association of the Protease Inhibitor Gene with Production Traits in Holstein Dairy Cattle

H. Khatib1, E. Heifetz2 and J. C. M. Dekkers2

1 Department of Dairy Science, University of Wisconsin, Madison 53706
2 Department of Animal Science, Iowa State University, Ames 50011

Corresponding author: H. Khatib; e-mail: hkhatib{at}wisc.edu.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 ACKNOWLEDGEMENTS
 REFERENCES
 
Positional, comparative candidate gene analysis and previous quantitative trait loci linkage mapping results were used to search for candidate genes affecting milk production and reproduction traits in dairy cattle. The protease inhibitor (PI) gene was chosen for examination, and 5 single nucleotide polymorphisms were detected in coding regions of the gene by direct sequencing of reverse transcription-polymerase chain reaction products from a wide range of cattle tissues. A total of 6 different intragenic haplotypes were identified in North American Holstein population, and these were examined for associations with milk production traits in 24 half-sib families comprising 1007 sons utilizing a granddaughter design. One common haplotype was associated with increased milk and fat yields, increased productive life, and decreased somatic cell score. Another common haplotype was associated with decreased productive life and increased somatic cell score. One rare haplotype was associated with decreased milk, fat, and protein yields and increased milk protein percentage; another rare haplotype was associated with decreased milk yield, increased protein percentage, and decreased productive life. The observation that the PI gene is associated with analogous traits in humans demonstrates the effectiveness of the positional comparative candidate gene analysis that utilizes information about genes present in chromosomal regions with conserved synteny in other species.

Key Words: candidate gene • quantitative trait loci • intragenic haplotype • dairy cow

Abbreviation key: DPR = daughter pregnancy rate, DYD = daughter yield deviation, PI = protease inhibitor, PL = productive life, QTG = quantitative trait gene, RT-PCR = reverse transcription-PCR, SNP = single nucleotide polymorphism


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 ACKNOWLEDGEMENTS
 REFERENCES
 
A major objective of genomic research in livestock species at present is to identify, map, and characterize individual QTL that affect production traits. A review of publications from the last decade demonstrates that a genome scan using anonymous markers has been used as the primary approach for QTL mapping in dairy cattle (Mosig et al., 2001; Bovenhuis and Schrooten, 2002; Khatkar et al., 2004). Such studies usually identify large confidence intervals for location of the QTL, typically of the order of 20 to 30 cM. Moreover, when applying such information in marker-assisted selection, the phase of marker-QTL associations must be established separately for each family. There is, however, an increasing interest in the candidate gene approach for identifying the actual genes corresponding to the QTL (Rothschild and Soller, 1997). The candidate gene approach ideally identifies the causative genes behind QTL, but more likely, it identifies markers that are close enough to the causative mutation that they are in linkage disequilibrium across the population (Dekkers, 2004). The candidate gene approach has been applied to different genes in cattle. Lien et al. (1995) studied the casein gene in a granddaughter design and showed an association of casein haplotypes with yields of milk and milk protein. Lagziel et al. (1996) used a single strand conformation polymorphism method for detection of polymorphisms and definition of intragenic haplotypes in the bovine growth hormone gene in the Israeli Holstein cattle population. One haplotype was found to have a highly significant positive effect on milk protein percentage. Grisart et al. (2002) reported the first positional cloning of a QTL in cattle that is associated with a significant increase in milk fat yield and a decrease in milk protein yield. These studies and others warrant exploiting the candidate gene approach to search for quantitative trait genes (QTG) in dairy cattle.

Investigation of the effect of the protease inhibitor (PI) gene on milk production and other traits was chosen because previous genome scans identified QTL affecting production and health traits on bovine chromosome 21. Heyen et al. (1999) reported a putative QTL affecting milk yield and protein yield in linkage with microsatellite marker D21S27 at a position 56 cM from the centromere. Also, Rodriguez-Zas et al. (2002) reported that a QTL located at 56 cM was associated with variation in SCS and milk protein yield. Mosig et al. (2001) reported that a QTL at 67.3 cM was associated with milk protein percentage.

The PI gene belongs to the superfamily of serine proteinase inhibitors that includes C1 esterase, antithrombin, and {alpha}1-antichymotrypsin, among others. The primary role of PI is to protect tissues against proteolytic digestion by neutrophil elastase. Possible roles of PI in the immune response include inhibition of lymphocyte toxicity and inhibition of chemotaxis (Blank and Brantly, 1994). Additionally, it has been reported that the PI protein is present in human milk and might increase survival of milk proteins by various mechanisms (Chowanadisai and Lonnerdal, 2002).

Based on the aforementioned studies, it was decided to further investigate the association of PI with quantitative traits in dairy cattle. In this paper, we describe identification of intragenic haplotypes in the PI gene in Holstein cattle and their effects on economic traits in the US Holstein population.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 CONCLUSIONS
 ACKNOWLEDGEMENTS
 REFERENCES
 
Experimental Structure
Holstein semen samples were obtained from the Cooperative Dairy DNA Repository, which is maintained by the USDA Bovine Functional Genomics Laboratory. Semen samples of 30 half-sib families (Weller et al., 1990) composed of 1258 sons were obtained for QTG analysis. Daughter yield deviation (DYD) data for the traits of interest [milk protein yield, milk protein percentage, milk fat yield, milk fat percentage, milk yield, SCS, daughter pregnancy rate (DPR), and productive life (PL)] were obtained from the Animal Improvement Programs Laboratory (http://www.aipl.arsusda.gov). Correlations of the DYD values of the 1007 sons and the average and minimum values of the reliability for each trait are shown in Table 1Go.


View this table:
[in this window]
[in a new window]
  		Table 1. Correlations among the daughter yield deviation (DYD) values of the 1007 sons and the average and the minimum reliabilities of the studied traits.
 
Detection of single nucleotide polymorphisms.
Single nucleotide polymorphisms (SNP) were detected by direct sequencing of reverse transcription-PCR (RT-PCR) products from the cattle tissues. To detect polymorphisms in the exons of the PI gene (GenBank accession number X63129), 2 sets of primers, PI7–PI9 and PI3–PI6 (Table 2Go), were designed to amplify the total cDNA sequence of the gene. Total RNA was extracted from a wide range of tissues from 5 fetuses and 5 adult cows obtained from a local slaughterhouse. After dissection, tissues were immediately chilled on ice and submerged in an appropriate volume of RNALater RNA stabilization reagent (QIAGEN, Valencia, CA). Total RNA was extracted using the RNeasy kit (QIAGEN). Reverse transcription was performed with the OneStep RT–PCR kit (QIAGEN) using cDNA-specific primers (Table 2Go). The temperature cycles were as follows: 50°C for 30 min (reverse transcription); 95°C for 15 min (initial PCR activation step); followed by 32 cycles of 94°C for 45 s, touchdown annealing from 65°C to 53°C for 45 s (–2°C per cycle), and 72°C for 45 s; and a final extension at 72°C for 7 min.


View this table:
[in this window]
[in a new window]
  		Table 2. Primer sequences used in amplification of cDNA and genomic fragments.
 
Products from PCR and RT-PCR were purified from the amplification solution using GFX PCR DNA Purification Kit (Amersham Biosciences, Little Chalfont, UK). Sequencing reactions consisted of 2 µL of BigDye Terminator mix (Applied Biosystems, Foster City, CA), 6 µL of dilution buffer [200 mM Tris HCl (pH 9.0); 5 mM MgCl2], 5 pmol of primer, and 0.04 to 0.1 µg of template DNA in a final reaction volume of 20 µL. Cycle conditions were an initial denaturation at 96°C for 3 min; then 50 cycles of 96°C for 10 s and 58°C for 4 min; followed by 7 min at 72°C. Excess dye terminators were removed using the CleanSeq magnetic bead sequencing reaction clean up kit (Agencourt Biosciences Corporation, Beverly, MA). The samples were eluted from the beads in 50 µL of deionized H2O. Ten microliters of each sample were electrophoresed on an Applied Biosystems 3730XL automated DNA sequencing instrument using 50-cm capillary arrays and POP-6 polymer. Data were analyzed using Applied Biosystems version 5.0 of Sequencing Analysis. The SNP were identified by visually inspecting each base in sequencing traces.

DNA Genotyping
Genomic DNA was extracted from semen samples with proteinase K and phenol/chloroform after the procedures of Kappes et al. (2000). The DNA concentration was measured using a spectrophotometer (Ultraspec 2100 Pro; Amersham Biosciences). A total of 24 Holstein sires and their 1007 Holstein sons were genotyped in this study. The 24 sires and 160 of their sons were genotyped by direct sequencing; 874 sons were genotyped by PCR-RFLP analysis using the restriction enzymes RsaI and SfaNI, as one of the detected SNP was in a RsaI recognition site and 2 SNP were in the SfaNI recognition sites. Two pairs of primers, PI7–PI11 and PI15–PI9, were designed to amplify genomic DNA flanking SNP that were detected in the cDNA sequence analysis. The PI7 and PI11 primers were used to amplify DNA fragments for sequencing and for PCR-RFLP with SfaNI; primers PI9 and PI15 were used to amplify DNA fragments for PCR-RFLP analysis with RsaI. The PI15 primer was designed in the intronic sequence (accession no. AY426761). Amplification of genomic DNA was performed in 25 µL of reaction volume, which included 50 ng of genomic DNA, 50 ng of each primer, 200 µM of each dNTP, 2.5 µL of 10X PCR buffer (Promega, Madison, WI), and 0.3 U of Taq DNA polymerase (Promega). The temperature cycles were as follows: 95°C for 5 min; 32 cycles of 94°C for 45 s, touchdown annealing from 63°C to 50°C for 45 s (–2°C per cycle), 72°C for 45 s; and a final extension at 72°C for 7 min.

Inferring Haplotypes
Intragenic haplotypes can be inferred from SNP genotype information (Lagziel et al., 1996). In this study, haplotypes were inferred in one or more of the following ways.

Statistical Analyses
To test whether marker haplotypes have significant associations with the trait, the following allele substitution model was fitted to the DYD data (Batra et al., 1989; Weigel et al., 1990; Sharif et al., 1999):


where Yij is the DYD of the trait for son j of sire i; µ is the mean; sirei is the effect of sire i; Aijk = 0, 1, 2 is the number of copies of haplotype k present in the individual ij, where A0 represents the most frequent of M marker haplotypes (in this case haplotype D) and the remaining haplotypes are denoted A1, ...Ak,..., A(M–1); ßk are partial regression coefficients corresponding to effect of haplotype k as a deviation from the effect of the most frequent haplotype (A0), which is set to zero to make the model have full rank; and eij is the random error associated with the individual ij. This model was fitted using weighted least squares with weights based on reliability (Israel and Weller, 1998). Significance of associations was determined for each trait separately by an F-test on the sum of squares explained by the combined effect of haplotypes. Then, for traits with significant associations, estimates of the effect of individual haplotypes, as a deviation from the effect of the most frequent haplotype (D), were evaluated for significance.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 CONCLUSIONS
 ACKNOWLEDGEMENTS
 REFERENCES
 
Intragenic Haplotypes in Holstein
Several methods can be used to uncover polymorphisms in candidate genes. Here, a direct sequencing method to determine intragenic haplotypes in the examined samples was used. In the search for polymorphisms in the PI gene in Holsteins, 5 SNP were identified, as were 6 intragenic haplotypes (A through F) (Table 3Go). The 6 haplotypes in Holstein may have derived from one another by point mutations that generated additional SNP plus some recombination among haplotypes. Based on genotyping Jersey, Bos indicus, and Bison bison individuals (data not shown), we assume that the consensus haplotype is GCGGC (denoted 1 to 1-1 to 1-1), which corresponds to haplotype E. Then, the C haplotype may have derived from E by a single point mutation: 1 to 1-1 to 1-2, and A from C by 2 further point mutations: 2 to 1-1 to 2-2. Haplotype D may have derived from E by 2 point mutations: 1 to 2-2 to 1-1. Haplotype B (1 to 2-2 to 1-2) may have derived by recombination between C (1 to 1-1 to 1-2) and D (1 to 2-2 to 1-1) and F (2 to 1-1 to 2-1) by recombination between A (2 to 1-1 to 2-2-) and D (1 to 2-2 to 1-1) or E (1 to 1-1 to 1-1).


View this table:
[in this window]
[in a new window]
  		Table 3. Intragenic haplotypes at the protease inhibitor gene1 in Holsteins.
 
Associations of PI Haplotypes with Production Traits in Holsteins
An allele substitution model was used to estimate associations of haplotypes with production traits. In this model, the most frequent haplotype (D) was set to have zero effect. Table 4Go has the results of the analysis of the whole region level of the PI gene. This analysis integrates the information of all haplotypes together to test the significance of the region as a whole. Milk yield, fat yield, protein percentage, and PL showed strong associations with the PI region (P < 0.05), SCS showed a suggestive association (P = 0.10), and fat percentage, protein yield, and DPR did not show significant associations. Table 5Go has the allele substitution effects associated with haplotypes A, B, C, E, and F for traits that were significant in the overall association. Estimates of associations with protein yield, although not significant in the overall test (Table 4Go), are included for completeness.


View this table:
[in this window]
[in a new window]
  		Table 4. Significance of the associations of the protease inhibitor gene region with production traits.
 

View this table:
[in this window]
[in a new window]
  		Table 5. Estimates of substitution effects of haplotypes for the protease inhibitor gene for production traits as a deviation from the effect of the most frequent haplotype (D).
 
Haplotype D was associated with a significant increase in milk yield vs. haplotype B and a less significant increase vs. haplotype C. In addition, haplotype D was associated with a significant increase in fat and protein yield vs. haplotype B; haplotypes A, C, E, and F showed no significant differences from haplotype D. Haplotypes B and C were associated with an increase in milk protein percentage vs. haplotype D. For PL, haplotype D was associated with a significant increase vs. haplotype C and nonsignificant increases vs. haplotypes B, E, and F. On the other hand, haplotype A was associated with an increase in PL vs. haplotype D, although this difference was not significant. For SCS, haplotype D was associated with a significant decrease vs. haplotypes E and A. For milk fat percentage and DPR, haplotypes of the PI gene did not show significant associations.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
CONCLUSIONS
 ACKNOWLEDGEMENTS
 REFERENCES
 
In this paper, a combination of positional comparative candidate gene analysis (Rothschild and Soller, 1997) and previous linkage QTL mapping results (Heyen et al., 1999; Mosig et al., 2001; Rodriguez-Zas et al., 2002) were used to study the association of the PI gene with milk production traits in Holstein dairy cattle.

Five SNP, at positions 164, 269, 284, 407, and 989, were identified in the PI gene in Holsteins (Table 3Go). Genotyping of the 30 Holstein sires by direct sequencing revealed 6 sires homozygous for all 5 SNP and 24 sires that were heterozygous for at least one SNP. The 6 Holstein haplotypes were examined for association with milk production traits, PL, SCS, and DPR in the 24 grandsire families comprising 1007 sons.

Associations of PI Haplotypes with Milk Production Traits
In this study, by using samples from the North American Holstein population, haplotype D of the PI gene was associated with a significant increase in milk yield, increase in milk fat yield, and a decrease in milk protein percentage (Table 5Go). This inverse relationship mirrors the negative phenotypic and genotypic correlations among milk yield, milk fat yield, and milk protein percentage. The action of the PI gene may contribute to this antagonistic relationship. Thus, identification of genes associated with milk production traits using a positional candidate gene approach based on existing linkage mapping results is feasible in dairy cattle.

The PI protein is important in humans for its broad range of activities. Its primary role is to protect tissues from proteolytic destruction by neutrophil elastase. In addition, it has been reported that PI is produced by the human mammary gland and may affect survival of milk proteins such as lactoferrin and lysozyme (Chowanadisai and Lonnerdal, 2002). Consequently, the observation that bovine PI gene haplotypes were associated with milk production traits demonstrates the effectiveness of the positional comparative candidate gene analysis (Rothschild and Soller, 1997) that utilizes information on the genes present in chromosomal regions with conserved synteny in other species.

Associations of PI Haplotypes with PL
Productive life is a longevity trait that is measured as a cow’s total months in the milking herd for the first 7 yr of life, with a limit of 10 mo per lactation (VanRaden and Wiggans, 1995). In a whole genome scan for QTL affecting health traits in dairy cattle, Heyen et al. (1999) reported a marker linked to a QTL affecting PL at 85 cM on chromosome 21. Our results for PI represent the first gene found to have an association with such a trait in dairy cattle. Analysis of the whole region at the PI gene showed a significant association with PL (Table 4Go). Haplotype D was associated with a significant increase in PL vs. haplotype C and nonsignificant increases vs. haplotypes B, E, and F; haplotype A was associated with an increase in PL vs. haplotype D. Noting that estimates in Table 5Go are of the effect of one copy of a given haplotype on mean performance of a sire’s daughters, which reflects one-half of the sire’s breeding value, a cow inheriting haplotype D is expected to have double the observed effects vs. inheriting haplotypes B, C, E, or F.

Associations of PI Haplotypes with SCS
Somatic cell score serves as an indicator of mastitis (low SCS is associated with low incidence of mastitis) and as a selection tool to reduce incidence of the disease (Schutz, 1994). Rodriguez-Zas et al. (2002) identified a QTL for SCS at approximately 60 cM on chromosome 21 in one of the families studied and another QTL for SCS at 84 cM. In addition, Heyen et al. (1999) identified a marker linked to a QTL affecting SCS at 33 cM, even though this marker was not highly significant. In this study, haplotypes A and E were associated with a significant increase in SCS vs. haplotype D, with other haplotypes having similar SCS as haplotype D (Table 5Go). Two copies of haplotype E are expected to increase SCS by 0.08, 0.18, 0.24, 0.16, and 0.12 points vs. haplotypes A, B, C, D, and F, respectively. Haplotype E, with a frequency of 26.5% in the Holstein population, was associated with a significant increase in SCS over haplotype D and less significant increase in milk yield vs. haplotypes A, B, and C. Thus, haplotype E increases both SCS and milk yield in the Holstein population.

In view of the observation that PI haplotypes show significant associations with SCS and that QTL for SCS were found in the PI region (Heyen et al., 1999; Rodriguez-Zas et al., 2002), we assume that the PI gene is the actual QTG or in close linkage disequilibrium with the QTG. However, additional fine mapping and molecular work is required to refine the PI region. In addition, the human PI gene plays a major role in the physiologic and biochemical responses in tissue repair of infection or inflammation, either by inactivating proteases at the inflammation sites or other mechanisms (Blank and Brantly, 1994). The human and bovine genes demonstrate high sequence homology (79%); bovine PI might play a similar role to that of the human gene in the immune system, thereby affecting response to mastitis infection.


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
ACKNOWLEDGEMENTS
 REFERENCES
 
In summary, a combination of positional comparative candidate gene analysis (Rothschild and Soller, 1997) and previous QTL linkage mapping results were used to search for candidate genes affecting milk production and reproduction traits in dairy cattle. Given that haplotype D was associated with a decrease in SCS and an increase in milk yield, milk fat yield, milk protein yield, and PL, it would be desirable to make selection decisions favoring this haplotype. Although the causal mutation responsible for the quantitative effects has not been identified, we propose that the PI gene may be the actual QTG or in close linkage disequilibrium with the QTG. In both scenarios, PI haplotype information can be used in genetic improvement programs.


   ACKNOWLEDGEMENTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 ACKNOWLEDGEMENTS
REFERENCES
 
The authors thank P. D. Miller for his critical reading of the manuscript and Valerie Schutzkus for technical assistance. This research was supported by Hatch grant #WIS04736 from the University of Wisconsin-Madison.

Received for publication April 29, 2004. Accepted for publication November 22, 2004.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 ACKNOWLEDGEMENTS
 REFERENCES
 


Batra, T. R., A. J. Lee, and J. S. Gavora. 1989. Class I alleles of the bovine major histocompatibility system and their association with economic traits. J. Dairy Sci. 72:2115–2124.

Blank, C. A., and M. Brantly. 1994. Clinical features and molecular characteristics of {alpha}1-antitrypsin deficiency. Ann. Allergy 72:105–120.[Medline]

Bovenhuis, H., and C. Schrooten. 2002. Quantitative trait loci for milk production traits in dairy cattle. Proc. 7th World Congr. Genet. Appl. Livest. Prod., Montpellier, France.

Chowanadisai, W., and B. Lonnerdal. 2002. Alpha(1)-antitrypsin and antichymotrypsin in human milk: Origin, concentrations, and stability. Am. J. Clin. Nutr. 76:828–833.[Abstract/Free Full Text]

Dekkers, J. C. M. 2004. Commercial application of marker- and gene-assisted selection in livestock: Strategies and lessons. J. Anim. Sci. 82:E313–E328.[Abstract/Free Full Text]

Grisart, B., W. Coppieters, F. Farnir, L. Karim, C. Ford, N. Cambisano, M. Mni, S. Reid, R. Spelman, M. George, and R. Snell. 2002. Positional candidate cloning of a QTL in dairy cattle: Identification of a missense mutation in the bovine DGAT1 gene with major effect on milk yield and composition. Genome Res. 12:222–231.[Abstract/Free Full Text]

Heyen, D. W., J. I. Weller, M. Ron, M. Band, J. E. Beever, E. Feldmesser, Y. Da, G. R. Wiggans, P. M. VanRaden, and H. A. Lewin. 1999. A genome scan for QTL influencing milk production and health traits in dairy cattle. Physiol. Genomics 1:165–175.

Israel, C., and J. I. Weller. 1998. Estimation of candidate gene effects in dairy cattle populations. J. Dairy Sci. 81:1653–1662.[Abstract]

Kappes, S. M., G. L. Bennett, J. W. Keele, S. E. Echternkamp, K. E. Gregory, and R. M. Thallman. 2000. Initial results of genomic scans for ovulation rate in a cattle population selected for increased twinning rate. J. Anim. Sci. 78:3053–3059.[Abstract/Free Full Text]

Khatkar, M. S., P. C. Thomson, I. Tammen, and H. W. Raadsma. 2004. Quantitative trait loci mapping in dairy cattle: Review and meta-analysis. Genet. Sel. Evol. 36:163–190.[Medline]

Lagziel, A., E. Lipkin, and M. Soller. 1996. Association between SCCP haplotypes at the bovine growth hormone gene and milk protein percentage. Genetics 142:945–951.[Abstract]

Lien, S., L. Gomez-Raya, T. Steine, E. Fimland, and S. Roger. 1995. Associations between casein haplotypes and milk yield traits. J. Dairy Sci. 78:2047–2056.[Abstract]

Mosig, M., E. Lipkin, G. Khutoreskaya, E. Tchourzyna, M. Soller, and A. Friedmann. 2001. A whole genome scan for quantitative trait loci affecting milk protein percentage in Israeli-Holstein cattle, by means of selective milk DNA pooling in a daughter design, using an adjusted false discovery rate criterion. Genetics 157:1683–1698.[Abstract/Free Full Text]

Rodriguez-Zas, S. L., B. R. Southey, D. W. Heyen, and H. A. Lewin. 2002. Interval and composite interval mapping of somatic cell score, yield, and components of milk in dairy cattle. J. Dairy Sci. 85:3081–3091.[Abstract/Free Full Text]

Rothschild, M. F., and M. Soller. 1997. Candidate gene analysis to detect genes controlling traits of economic importance in domestic livestock. Probe 8:13–22.

Schutz, M. M. 1994. Genetic evaluation of somatic cell scores for United States dairy cattle. J. Dairy Sci. 77:2113–2129.[Abstract]

Sharif, S., B. A. Mallard, B. N. Wilkie, J. M. Sargeant, H. M. Scott, J. C. Dekkers, and K. E. Leslie. 1999. Association of the bovine major histocompatibility complex DRB3 (BoLA-DRB3) with production traits in Canadian dairy cattle. Anim. Genet. 30:157–160.[Medline]

VanRaden, P. M., and G. R. Wiggans. 1995. Productive life evaluations: Calculation, accuracy, and economic value. J. Dairy Sci. 78:631–638.[Abstract]

Weigel, K. A., M. E. J. R. Kehrli, M. J. Stear, and D. H. Kelley. 1990. Association of class I bovine lymphocyte antigen complex alleles with health and production traits in dairy cattle. J. Dairy Sci. 73:2538–2546.[Abstract]

Weller, J., Y. Kashi, and M. Soller. 1990. Daughter and granddaughter design for mapping of quantitative trait loci in dairy cattle. J. Dairy Sci. 73:2525–2537.[Abstract]


This article has been cited by other articles:


Home page
 J ANIM SCIHome page
G. J. Hausman, M. V. Dodson, K. Ajuwon, M. Azain, K. M. Barnes, L. L. Guan, Z. Jiang, S. P. Poulos, R. D. Sainz, S. Smith, et al.
BOARD-INVITED REVIEW: The biology and regulation of preadipocytes and adipocytes in meat animals
J Anim Sci, April 1, 2009; 87(4): 1218 - 1246.
[Abstract] [Full Text] [PDF]

Home page
 Poult. Sci.Home page
Y. H. Hong, E.-S. Kim, H. S. Lillehoj, E. P. Lillehoj, and K.-D. Song
Association of resistance to avian coccidiosis with single nucleotide polymorphisms in the zyxin gene
Poult. Sci., March 1, 2009; 88(3): 511 - 518.
[Abstract] [Full Text] [PDF]

Home page
 J DAIRY SCIHome page
G. Rincon, A. Islas-Trejo, J. Casellas, Y. Ronin, M. Soller, E. Lipkin, and J. F. Medrano
Fine mapping and association analysis of a quantitative trait locus for milk production traits on Bos taurus autosome 4
J Dairy Sci, February 1, 2009; 92(2): 758 - 764.
[Abstract] [Full Text] [PDF]

Home page
 JCOHome page
T. S. Jones, S. C. Kaste, W. Liu, C. Cheng, W. Yang, K. G. Tantisira, C.-H. Pui, and M. V. Relling
CRHR1 Polymorphisms Predict Bone Density in Survivors of Acute Lymphoblastic Leukemia
J. Clin. Oncol., June 20, 2008; 26(18): 3031 - 3037.
[Abstract] [Full Text] [PDF]

Home page
 J DAIRY SCIHome page
X. Wang, C. Maltecca, R. Tal-Stein, E. Lipkin, and H. Khatib
Association of Bovine Fibroblast Growth Factor 2 (FGF2) Gene with Milk Fat and Productive Life: An Example of the Ability of the Candidate Pathway Strategy to Identify Quantitative Trait Genes
J Dairy Sci, June 1, 2008; 91(6): 2475 - 2480.
[Abstract] [Full Text] [PDF]

Home page
 J DAIRY SCIHome page
H. Khatib, I. Zaitoun, J. Wiebelhaus-Finger, Y. M. Chang, and G. J. M. Rosa
The Association of Bovine PPARGC1A and OPN Genes with Milk Composition in Two Independent Holstein Cattle Populations
J Dairy Sci, June 1, 2007; 90(6): 2966 - 2970.
[Abstract] [Full Text] [PDF]

Home page
 J DAIRY SCIHome page
H. Khatib, V. Schutzkus, Y. M. Chang, and G. J. M. Rosa
Pattern of Expression of the Uterine Milk Protein Gene and its Association with Productive Life in Dairy Cattle
J Dairy Sci, May 1, 2007; 90(5): 2427 - 2433.
[Abstract] [Full Text] [PDF]

Home page
 J DAIRY SCIHome page
O. Cobanoglu, I. Zaitoun, Y. M. Chang, G. E. Shook, and H. Khatib
Effects of the signal transducer and activator of transcription 1 (STAT1) gene on milk production traits in Holstein dairy cattle.
J Dairy Sci, November 1, 2006; 89(11): 4433 - 4437.
[Abstract] [Full Text] [PDF]

Home page
 J DAIRY SCIHome page
H. Khatib, S. D. Leonard, V. Schutzkus, W. Luo, and Y. M. Chang
Association of the OLR1 Gene with Milk Composition in Holstein Dairy Cattle
J Dairy Sci, May 1, 2006; 89(5): 1753 - 1760.
[Abstract] [Full Text] [PDF]

Home page
 J DAIRY SCIHome page
S. Leonard, H. Khatib, V. Schutzkus, Y. M. Chang, and C. Maltecca
Effects of the Osteopontin Gene Variants on Milk Production Traits in Dairy Cattle
J Dairy Sci, November 1, 2005; 88(11): 4083 - 4086.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Interpretive Summary
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Khatib, H.
Right arrow Articles by Dekkers, J. C. M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Khatib, H.
Right arrow Articles by Dekkers, J. C. M.

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS