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GENETICS AND BREEDING
Effects of Maternal Lineages Grouped by Mitochondrial Genotypeson Milk Yield and Compositlon1
M. M. SCHUTZ,2 A. E. FREEMAN, G. L. UNDBERG, and D. C. BEITZ3Department of Animal Science
Iowa State UniversityAmes 50011
ABSTRACT
Maternal lineages grouped by severalmethods of classification usingmitochondrial DNA sequence characteristics were evaluated with animalmodels. Maternal pedigrees for cattlefrom a selection experiment begun in1968 were traced to the earliest femalemember in the Holstein-Friesian HerdBook, and foundation females were assigned to maternal lineages. Mitochondrial DNA displacement loop sequencedata were available for 36 lineages; allcows within lineages were considered tobe identical for useful DNA sequencepolymorphisms. Maternal lineages weregrouped according to base pair substitution at a single locus, clustering based ondisplacement loop sequences, or genotypes defined by sequence and restrictionsite differences. Base pair substitution(adenine to guanine) at nucleotide 169defined two maternal lineage groups thatdiffered significantly for fat yield andpercentage and estimated milk energy.Clustering the 36 maternal lineages byusing 16 mitochondrial DNA displacement loop sequence differences produced24 groups that significantly influencedfat percentage and energy concentrationin milk. Decreasing the number ofclustered groups from 24 to 14 producedg~oups that differed at some polymorphicsItes but remained identical for most.The F statistics for 14 groups were
Received June 19, 1992,Accepted September 29, 1992.IJoumal Paper Number J-14915 of the Iowa Agricul
l~ and Home Economics Experiment Station, Ames.Project Number 1053.
2Present address: Animal Improvement ProgramsLaboratory, USDA-ARS, Belrsville. MD 20705·2350.
3Department of Biochemistry and Biophysics.
larger. but significant outcomes were observed for the same trajts. Genotypegroups previously defined by sequenceand restriction fragment length differences did not have a significant effect onyield or composition of cows in 29maternal lineages.(Key words: maternal lineage, cytoplasmic inheritance, mitochondrial inheritance, mitochondrial deoxyribonucleic acid clustering)
Abbreviation key: D =displacement, mtDNA= mitochondrial DNA, nt = nucleotide.
INTRODUCTION
Several reports have suggested the existenceo.f .maternal lineage effects on yield or compoSItIOn (2, 5, II, 23) and reproduction (2, 4, 20,22); those results indicate the possibility ofcytoplasmic inheritance of genetic effects.Mitochondrial DNA (mtDNA) is a probablesource of such cytoplasmic effects becausemitochondria in metazoans are thought to betransmitted predominantly from female parents~o o~fspring (7), although limited biparentalmhentance of mtDNA has been established inmussels (10) and mice (6).
. Some reports. have challenged the sigmficance of prevIous estimates of cytoplasmicinheritance by using simulated data (14) oranalysis of trios of daughters, dams, and grandams (21). Nevertheless, the ability of welldefined animal models to partition maternalinfluences into cytoplasmic and additivegenetic components has been demonstrated(25). Southwood et al. (25) used simulateddat~ and ~e or incorrect models containingaddltlve dIrect, additive maternal, cytoplasmic,and error variances and concluded that certainanimal models correctly partition these components of varjance. Schutz et al. (23) found thatadditive maternal variation of nUClear originwas negligible for yield and composition traitsof dairy cattle.
1993 J Dairy Sci 76:621--629 621
GENETICS AND BREEDING
Effects of Maternal Lineages Grouped by Mitochondrial Genotypeson Milk Yield and Compositlon1
M. M. SCHUTZ,2 A. E. FREEMAN, G. L. UNDBERG, and D. C. BEITZ3Department of Animal Science
Iowa State UniversityAmes 50011
ABSTRACT
Maternal lineages grouped by severalmethods of classification usingmitochondrial DNA sequence characteristics were evaluated with animalmodels. Maternal pedigrees for cattlefrom a selection experiment begun in1968 were traced to the earliest femalemember in the Holstein-Friesian HerdBook, and foundation females were assigned to maternal lineages. Mitochondrial DNA displacement loop sequencedata were available for 36 lineages; allcows within lineages were considered tobe identical for useful DNA sequencepolymorphisms. Maternal lineages weregrouped according to base pair substitution at a single locus, clustering based ondisplacement loop sequences, or genotypes defined by sequence and restrictionsite differences. Base pair substitution(adenine to guanine) at nucleotide 169defined two maternal lineage groups thatdiffered significantly for fat yield andpercentage and estimated milk energy.Clustering the 36 maternal lineages byusing 16 mitochondrial DNA displacement loop sequence differences produced24 groups that significantly influencedfat percentage and energy concentrationin milk. Decreasing the number ofclustered groups from 24 to 14 producedg~oups that differed at some polymorphicsItes but remained identical for most.The F statistics for 14 groups were
Received June 19, 1992,Accepted September 29, 1992.IJoumal Paper Number J-14915 of the Iowa Agricul
l~ and Home Economics Experiment Station, Ames.Project Number 1053.
2Present address: Animal Improvement ProgramsLaboratory, USDA-ARS, Belrsville. MD 20705·2350.
3Department of Biochemistry and Biophysics.
larger. but significant outcomes were observed for the same trajts. Genotypegroups previously defined by sequenceand restriction fragment length differences did not have a significant effect onyield or composition of cows in 29maternal lineages.(Key words: maternal lineage, cytoplasmic inheritance, mitochondrial inheritance, mitochondrial deoxyribonucleic acid clustering)
Abbreviation key: D =displacement, mtDNA= mitochondrial DNA, nt = nucleotide.
INTRODUCTION
Several reports have suggested the existenceo.f .maternal lineage effects on yield or compoSItIOn (2, 5, II, 23) and reproduction (2, 4, 20,22); those results indicate the possibility ofcytoplasmic inheritance of genetic effects.Mitochondrial DNA (mtDNA) is a probablesource of such cytoplasmic effects becausemitochondria in metazoans are thought to betransmitted predominantly from female parents~o o~fspring (7), although limited biparentalmhentance of mtDNA has been established inmussels (10) and mice (6).
. Some reports. have challenged the sigmficance of prevIous estimates of cytoplasmicinheritance by using simulated data (14) oranalysis of trios of daughters, dams, and grandams (21). Nevertheless, the ability of welldefined animal models to partition maternalinfluences into cytoplasmic and additivegenetic components has been demonstrated(25). Southwood et al. (25) used simulateddat~ and ~e or incorrect models containingaddltlve dIrect, additive maternal, cytoplasmic,and error variances and concluded that certainanimal models correctly partition these components of varjance. Schutz et al. (23) found thatadditive maternal variation of nUClear originwas negligible for yield and composition traitsof dairy cattle.
1993 J Dairy Sci 76:621--629 621
622 SCHUTZ ET AL.
Mitochondrial DNA sequence differsamong dairy cattle (3. 17). Koehler (15) usedrestriction enzymes to detect 11 polymorphisms among maternal lineages. and two additional polymorphisms occurred within lineages. One polymorphism within a singlelineage seemed to result from a single mutational event, but the other polymorphism occurred within several lineages and is considered to be heteroplasmic for lineages (16). Noother such sites of heteroplasmy have beendocumented. Johnston et al. (1991. unpublished data) identified 10 nucleotide (nt) substitutions in the displacement (D) loop ofmtDNA from five breeds of dairy cattle usingrestriction analysis. Lindberg et al. (19) sequenced entire mtDNA D loops of 36 maternallineages and identified 48 sites of nt substitution (plus one deletion) and two variablelength regions. In addition, Johnston (13) observed 11 different sequences in ribosomalRNA subunits of mtDNA in 38 lineages ofHolsteins.
Studies associating maternal lineages withyield and composition traits have definedmaternal lineage sources as foundation cows inthe herd studied (2, 11, 20) or as maternallineage matriarchs identified by tracing maternal pedigrees to the beginning of a herd book(5, 23). Defining maternal lineages this wayhas several disadvantages. In either definition.several lineages may have a single commonmaternal ancestor before earliest recorded pedigree information. Also, misidentification ofmaternal ancestors or erroneously recordedregistration numbers lead to incorrect assignment to lineages. Most commonly. branches ofa single maternal pedigree are inadvertentlydefined as separate maternal lineages. Thesedisadvantages suggest that previous studiesmay have underestimated the true impact ofcytoplasmic effects on milk yield andreproduction.
Lindberg et al. (19) demonstrated the potential for 27 restriction endonuclease target sitesin the bovine mtDNA D-loop region to be usedto describe Holstein cytoplasmic genotypes.Single base pair substitutions in bovinemtDNA D loops have been associated withyield and composition differences in Holsteins(3, 23). The objective of this study was todefine maternal lineages according to severaldifferent mtDNA molecular characterizations
Journal of Dairy Science Vol. 76. No.2. 1993
and to associate these new lineage groupingswith yield and composition traits in a herd ofHolsteins.
MATERIALS AND METHODS
Cattle studied were part of a selection experiment begun with the Iowa State UniversityBreeding Research Herd in 1968. Foundationfemales were mated to Holstein AI sires withhigh or average transmitting abilities for milkyield to form two divergent genetic lines.Records initiated through 1988 were includedin analyses.
Genetic backgrounds of original foundationfemales in the herd were quite diverse, butfrequencies of bovine lymphocyte antigengenotypes were similar to those in the USHolstein population (28), strongly suggestingthat nuclear genes are representative of thatpopulation. Cows were bred artificially to siresfrom commercial AI, allowing continuous introduction of nuclear genes.
The herd was assembled through purchasesof 158 foundation females acquired from 38Holstein breeders located throughout Iowa. Because maternal heritage was determined bytracing maternal lineage to the first femalemember recorded in the Holstein-FriesianHerd Book (27), only the 133 foundation registered females were assigned to 81 separatematernal lineages. Thirty-six registered lineages had members remaining in the herd whenrestriction and sequence analysis of themtDNA genome was conducted. There were71 foundation females in these 36 lineages,and they were, on average, 19 generationsremoved from their matriarchs first registeredin the herd book. Among the 36 lineages were6 foundation females in the herd for lineageswith the most foundation females and 1 for thelineage with the fewest. There was a total of728 cows across generations in the 36 maternallineages. These same lineages have been analyzed in previous studies (3, 22, 23).
Mature equivalent (twice daily milking,305-d lactation) milk. fat. and SNF yields andfat and SNF percentages were the yield andcomposition traits available for analysis. Milknet energy is affected by maternal lineages(23). Milk net energy concentration in kilocalories per kilogram was calculated by usinglactation average of test day fat and SNF per-
622 SCHUTZ ET AL.
Mitochondrial DNA sequence differsamong dairy cattle (3. 17). Koehler (15) usedrestriction enzymes to detect 11 polymorphisms among maternal lineages. and two additional polymorphisms occurred within lineages. One polymorphism within a singlelineage seemed to result from a single mutational event, but the other polymorphism occurred within several lineages and is considered to be heteroplasmic for lineages (16). Noother such sites of heteroplasmy have beendocumented. Johnston et al. (1991. unpublished data) identified 10 nucleotide (nt) substitutions in the displacement (D) loop ofmtDNA from five breeds of dairy cattle usingrestriction analysis. Lindberg et al. (19) sequenced entire mtDNA D loops of 36 maternallineages and identified 48 sites of nt substitution (plus one deletion) and two variablelength regions. In addition, Johnston (13) observed 11 different sequences in ribosomalRNA subunits of mtDNA in 38 lineages ofHolsteins.
Studies associating maternal lineages withyield and composition traits have definedmaternal lineage sources as foundation cows inthe herd studied (2, 11, 20) or as maternallineage matriarchs identified by tracing maternal pedigrees to the beginning of a herd book(5, 23). Defining maternal lineages this wayhas several disadvantages. In either definition.several lineages may have a single commonmaternal ancestor before earliest recorded pedigree information. Also, misidentification ofmaternal ancestors or erroneously recordedregistration numbers lead to incorrect assignment to lineages. Most commonly. branches ofa single maternal pedigree are inadvertentlydefined as separate maternal lineages. Thesedisadvantages suggest that previous studiesmay have underestimated the true impact ofcytoplasmic effects on milk yield andreproduction.
Lindberg et al. (19) demonstrated the potential for 27 restriction endonuclease target sitesin the bovine mtDNA D-loop region to be usedto describe Holstein cytoplasmic genotypes.Single base pair substitutions in bovinemtDNA D loops have been associated withyield and composition differences in Holsteins(3, 23). The objective of this study was todefine maternal lineages according to severaldifferent mtDNA molecular characterizations
Journal of Dairy Science Vol. 76. No.2. 1993
and to associate these new lineage groupingswith yield and composition traits in a herd ofHolsteins.
MATERIALS AND METHODS
Cattle studied were part of a selection experiment begun with the Iowa State UniversityBreeding Research Herd in 1968. Foundationfemales were mated to Holstein AI sires withhigh or average transmitting abilities for milkyield to form two divergent genetic lines.Records initiated through 1988 were includedin analyses.
Genetic backgrounds of original foundationfemales in the herd were quite diverse, butfrequencies of bovine lymphocyte antigengenotypes were similar to those in the USHolstein population (28), strongly suggestingthat nuclear genes are representative of thatpopulation. Cows were bred artificially to siresfrom commercial AI, allowing continuous introduction of nuclear genes.
The herd was assembled through purchasesof 158 foundation females acquired from 38Holstein breeders located throughout Iowa. Because maternal heritage was determined bytracing maternal lineage to the first femalemember recorded in the Holstein-FriesianHerd Book (27), only the 133 foundation registered females were assigned to 81 separatematernal lineages. Thirty-six registered lineages had members remaining in the herd whenrestriction and sequence analysis of themtDNA genome was conducted. There were71 foundation females in these 36 lineages,and they were, on average, 19 generationsremoved from their matriarchs first registeredin the herd book. Among the 36 lineages were6 foundation females in the herd for lineageswith the most foundation females and 1 for thelineage with the fewest. There was a total of728 cows across generations in the 36 maternallineages. These same lineages have been analyzed in previous studies (3, 22, 23).
Mature equivalent (twice daily milking,305-d lactation) milk. fat. and SNF yields andfat and SNF percentages were the yield andcomposition traits available for analysis. Milknet energy is affected by maternal lineages(23). Milk net energy concentration in kilocalories per kilogram was calculated by usinglactation average of test day fat and SNF per-
MATERNAL LINEAGE GROUPING 623
centages according to Tyrrell and Reid (26) asfollows:
net energy = 41.84 (fat percentage)+ 22.29 (SNF percentage)- 25.58.
Lactation net energy was calculated by multiplying net energy concentration by matureequivalent milk yield. Records were assignedto year-season of calving subclasses. Seasonswere October to April and May to Septemberto account for winter and summer feeding andmanagement differences; there were an average of 54 records per year-season. Up to 7records per cow were included for analyses.
The 36 maternal lineages were grouped inthree ways, based on characterization ofmtDNA. First, maternal lineages were groupedaccording to their genotype at one particular ntsite. Second, cluster analysis grouped lineagesbased on genotypes defined by 16 polymorphicsites in the mtDNA D loop. Finally, lineageswere grouped according to sequence genotypesfrom a previous report by Lindberg et al. (19).The mtDNA D-loop sequences of these 36lineages have been well documented, and details of the molecular characterizations havebeen reported (15, 16, 18, 19).
Base Pair 169
Lindberg et a1. (19) used mtDNA D loop ntsequence data from 28 of these 36 maternallineages to construct a phylogenetic tree byparsimony analysis. Their analysis generated atwo-part evolutionary tree based on division ofthe population at nt169, which was numberedaccording to the nomenclature of Anderson etal. (1). Nucleotide information for this studywas available for cows from all 36 maternallineages. All members of a single maternallineage were assumed to have an identicalmtDNA genotype with respect to nt169. Spotchecking of more cows in several lineagessupported this assumption. Lineages were classified as identical or polymorphic comparedwith the first published mtDNA sequence (1)at nt169. The effect of these binomial data oneach yield or composition trait was analyzedusing the following single-trait mixed animalmodel:
Yijklp = YSi + Pj + Xk + bl(nt169)+ pep + ap + eijklp, [l ]
where Yijklp = milk, fat, or SNF yield; fat orSNF percentage; energy concentration; or lactation energy; YSi = effect of calving yearseason i (i =1 to 33); Pj =effect of parity j (j =1 to 7); Xk = effect of selection line k (high oraverage); bl = effect of mtDNA D-Ioop sequence 1 (identical or polymorphic) at nt169;pep =permanent environmental effect of cow p(p =1 to 728); ap =additive genetic value ofcow p and was composed of sire and dambreeding values and a Mendelian sampling effect; and eijklp = residual error.
Year-season, parity, selection line, and Dloop sequence at nt169 were considered to befixed effects. Confounding was not detectedbetween polymorphism at nt169 and otherfixed effects. Permanent environment, animaladditive genetic, and residual effects were considered to be random and independently distributed with expectations equal to O. Varianceamong permanent environments was var(pe) =I~pe' where I is an identity matrix, and vari-
ance among animals was var(a) =A~, whereA is the numerator relationship matrix. MatrixA included sires and dams of all cows withrecords in the herd, sire and paternal grandsirerelationships among AI bulls represented bydaughters with records, and 25 unknownparent groups for a total of 950 animal equations. Estimates of variances for each yield orcomposition trait were obtained from Schutz etal. (23).
The effect of nt substitution at nt169 was ofprimary interest. Significance of this substitution effect (under the null hypothesis that effect of all mtDNA D-loop sequences are thesame) was tested by solution of mixed modelconjugate normal equations (8, 9, 23). Suchtests of significance are exact under the assumption of normality if estimates of variancesare assumed to be accurate.
Maternal Lineage Clusters
The same 36 maternal lineages weregrouped by clustering techniques that werebased on mtDNA D-Ioop sequence information. The 17 most frequent sequence substitution sites in maternal lineages in this herd were
Journal of Dairy Science Vol. 76, No.2, 1993
MATERNAL LINEAGE GROUPING 623
centages according to Tyrrell and Reid (26) asfollows:
net energy = 41.84 (fat percentage)+ 22.29 (SNF percentage)- 25.58.
Lactation net energy was calculated by multiplying net energy concentration by matureequivalent milk yield. Records were assignedto year-season of calving subclasses. Seasonswere October to April and May to Septemberto account for winter and summer feeding andmanagement differences; there were an average of 54 records per year-season. Up to 7records per cow were included for analyses.
The 36 maternal lineages were grouped inthree ways, based on characterization ofmtDNA. First, maternal lineages were groupedaccording to their genotype at one particular ntsite. Second, cluster analysis grouped lineagesbased on genotypes defined by 16 polymorphicsites in the mtDNA D loop. Finally, lineageswere grouped according to sequence genotypesfrom a previous report by Lindberg et al. (19).The mtDNA D-loop sequences of these 36lineages have been well documented, and details of the molecular characterizations havebeen reported (15, 16, 18, 19).
Base Pair 169
Lindberg et a1. (19) used mtDNA D loop ntsequence data from 28 of these 36 maternallineages to construct a phylogenetic tree byparsimony analysis. Their analysis generated atwo-part evolutionary tree based on division ofthe population at nt169, which was numberedaccording to the nomenclature of Anderson etal. (1). Nucleotide information for this studywas available for cows from all 36 maternallineages. All members of a single maternallineage were assumed to have an identicalmtDNA genotype with respect to nt169. Spotchecking of more cows in several lineagessupported this assumption. Lineages were classified as identical or polymorphic comparedwith the first published mtDNA sequence (1)at nt169. The effect of these binomial data oneach yield or composition trait was analyzedusing the following single-trait mixed animalmodel:
Yijklp = YSi + Pj + Xk + bl(nt169)+ pep + ap + eijklp, [l ]
where Yijklp = milk, fat, or SNF yield; fat orSNF percentage; energy concentration; or lactation energy; YSi = effect of calving yearseason i (i =1 to 33); Pj =effect of parity j (j =1 to 7); Xk = effect of selection line k (high oraverage); bl = effect of mtDNA D-Ioop sequence 1 (identical or polymorphic) at nt169;pep =permanent environmental effect of cow p(p =1 to 728); ap =additive genetic value ofcow p and was composed of sire and dambreeding values and a Mendelian sampling effect; and eijklp = residual error.
Year-season, parity, selection line, and Dloop sequence at nt169 were considered to befixed effects. Confounding was not detectedbetween polymorphism at nt169 and otherfixed effects. Permanent environment, animaladditive genetic, and residual effects were considered to be random and independently distributed with expectations equal to O. Varianceamong permanent environments was var(pe) =I~pe' where I is an identity matrix, and vari-
ance among animals was var(a) =A~, whereA is the numerator relationship matrix. MatrixA included sires and dams of all cows withrecords in the herd, sire and paternal grandsirerelationships among AI bulls represented bydaughters with records, and 25 unknownparent groups for a total of 950 animal equations. Estimates of variances for each yield orcomposition trait were obtained from Schutz etal. (23).
The effect of nt substitution at nt169 was ofprimary interest. Significance of this substitution effect (under the null hypothesis that effect of all mtDNA D-loop sequences are thesame) was tested by solution of mixed modelconjugate normal equations (8, 9, 23). Suchtests of significance are exact under the assumption of normality if estimates of variancesare assumed to be accurate.
Maternal Lineage Clusters
The same 36 maternal lineages weregrouped by clustering techniques that werebased on mtDNA D-Ioop sequence information. The 17 most frequent sequence substitution sites in maternal lineages in this herd were
Journal of Dairy Science Vol. 76, No.2, 1993
624 SCHUTZ ET AL.
described by Schutz et al. (22). One of thosesites, nt363, was hypervariable and, therefore.not useful for clustering of lineages. For eachof the remaining 16 nt positions. maternallineages were classified as identical or polymorphic with respect to the first publishedbovine mtDNA sequence (l). Each lineage hada total of 16 values, and lineages with the samepolymorphisms were equal in their combination of identical or polymorphic indicators.
A matrix of distances between maternallineages based on binomial sequence data wascomputed as 1 - Jaccard coefficient for eachpair of lineages. Jaccard coefficients (12) aremeasures of similarity calculated as
Jaccard coefficient (i.j) =nj/(n 1 + n2 + n3)
where nl =number of nt sites polymorphic inboth maternal lineages i and j. n2 = number ofnt sites polymorphic only in maternal lineage i,and n3 = number of nt sites polymorphic onlyin maternal lineage j. Number of nt sites notpolymorphic in either maternal lineage doesnot enter the equation because this occurrencewould be far more common and because inclusion would decrease the impact of polymorphic sites in determining similarities ordistances between lineages. Thus, a matrix ofdistances was created that was of the order ofthe number of maternal lineages. The matrixwas symmetric with zeros on diagonals andI - Jaccard coefficients on the off-diagonals.Off-diagonals for two maternal lineages withidentical polymorphisms also were zero.
Based on the matrix of pairwise distances.maternal lineages were organized into the mosthomogeneous groups possible by averagelinked cluster analysis (24). Average linkageclustering of groups is based on average distance between pairs of observations (one ineach group) and on making all possible comparisons of each member of one group witheach member of the group being compared.This clustering method tends to form clusterswith small variances and avoids extremeresults inherent to other methods that consideronly the nearest or farthest members from eachgroup compared.
Two lineages were not polymorphic at all16 nt sites. These lineages were joined to forma single cluster but were not so assigned byaverage linkage analysis, which only joined
Journal of Dairy Science Vol. 76. No.2. 1993
clusters on the basis of polymorphic nt sites.The 36 lineages were grouped into maternallineage clusters of either 24 groups (clustering1) or 14 groups (clustering 2) for separateanalyses. The term "clustering" is used insteadof "cluster" to avoid confusion with the individually clustered groups. With cluster analysis, any number of clusters may be chosen.Clustering into 24 groups was the first clustering for which the normalized distance betweengroups joined was greater than O. Clusteringinto 14 groups was somewhat arbitrarily chosen as the smallest number of groups for whichthe joined groups had normalized distances ofless than .6.
Clusterings of maternal lineages were analyzed with the following animal model:
Yijkmp = P. + YSi + Pj + Xk + mIcm+ pep + ap + eijk.mp' [2]
where all effects are as previously defined,except that mIcm was the fixed effect of maternal lineage cluster group m (m = 1 to 24 forclustering 1 and m = I to 14 for clustering 2).Assumptions, expectations, and variances ofrandom effects are as defined previously. Confounding was not detected between clustergroups and other fixed effects. Residuals(eijkmp) obtained with either clustering I orclustering 2 from this model were examinedwith a model consisting of actual maternallineages traced by pedigree. Size of maternallineage effects on the residuals were used tocompare the ability of the two clusterings toaccount for maternal lineage differences.
Sequence Genotypes
Lindberg (18) reported that restriction fragment length polymorphism and sequence datacould accurately describe mitochondrial genotypes of bovine cytoplasmic lil)eages. In hisreport [Table 2 (18)]. 29 lineages were assigned to 21 genotypes according to restrictionenzyme and sequence analyses. Sequence information was obtained on two or more members of each lineage, and sequence differenceswere confirmed. if detectable. by restrictionenzyme analysis. One of the 29 lineages wasnot registered. and maternal ancestry could notbe verified through registry information, butcows in this lineage were included in this
624 SCHUTZ ET AL.
described by Schutz et al. (22). One of thosesites, nt363, was hypervariable and, therefore.not useful for clustering of lineages. For eachof the remaining 16 nt positions. maternallineages were classified as identical or polymorphic with respect to the first publishedbovine mtDNA sequence (l). Each lineage hada total of 16 values, and lineages with the samepolymorphisms were equal in their combination of identical or polymorphic indicators.
A matrix of distances between maternallineages based on binomial sequence data wascomputed as 1 - Jaccard coefficient for eachpair of lineages. Jaccard coefficients (12) aremeasures of similarity calculated as
Jaccard coefficient (i.j) =nj/(n 1 + n2 + n3)
where nl =number of nt sites polymorphic inboth maternal lineages i and j. n2 = number ofnt sites polymorphic only in maternal lineage i,and n3 = number of nt sites polymorphic onlyin maternal lineage j. Number of nt sites notpolymorphic in either maternal lineage doesnot enter the equation because this occurrencewould be far more common and because inclusion would decrease the impact of polymorphic sites in determining similarities ordistances between lineages. Thus, a matrix ofdistances was created that was of the order ofthe number of maternal lineages. The matrixwas symmetric with zeros on diagonals andI - Jaccard coefficients on the off-diagonals.Off-diagonals for two maternal lineages withidentical polymorphisms also were zero.
Based on the matrix of pairwise distances.maternal lineages were organized into the mosthomogeneous groups possible by averagelinked cluster analysis (24). Average linkageclustering of groups is based on average distance between pairs of observations (one ineach group) and on making all possible comparisons of each member of one group witheach member of the group being compared.This clustering method tends to form clusterswith small variances and avoids extremeresults inherent to other methods that consideronly the nearest or farthest members from eachgroup compared.
Two lineages were not polymorphic at all16 nt sites. These lineages were joined to forma single cluster but were not so assigned byaverage linkage analysis, which only joined
Journal of Dairy Science Vol. 76. No.2. 1993
clusters on the basis of polymorphic nt sites.The 36 lineages were grouped into maternallineage clusters of either 24 groups (clustering1) or 14 groups (clustering 2) for separateanalyses. The term "clustering" is used insteadof "cluster" to avoid confusion with the individually clustered groups. With cluster analysis, any number of clusters may be chosen.Clustering into 24 groups was the first clustering for which the normalized distance betweengroups joined was greater than O. Clusteringinto 14 groups was somewhat arbitrarily chosen as the smallest number of groups for whichthe joined groups had normalized distances ofless than .6.
Clusterings of maternal lineages were analyzed with the following animal model:
Yijkmp = P. + YSi + Pj + Xk + mIcm+ pep + ap + eijk.mp' [2]
where all effects are as previously defined,except that mIcm was the fixed effect of maternal lineage cluster group m (m = 1 to 24 forclustering 1 and m = I to 14 for clustering 2).Assumptions, expectations, and variances ofrandom effects are as defined previously. Confounding was not detected between clustergroups and other fixed effects. Residuals(eijkmp) obtained with either clustering I orclustering 2 from this model were examinedwith a model consisting of actual maternallineages traced by pedigree. Size of maternallineage effects on the residuals were used tocompare the ability of the two clusterings toaccount for maternal lineage differences.
Sequence Genotypes
Lindberg (18) reported that restriction fragment length polymorphism and sequence datacould accurately describe mitochondrial genotypes of bovine cytoplasmic lil)eages. In hisreport [Table 2 (18)]. 29 lineages were assigned to 21 genotypes according to restrictionenzyme and sequence analyses. Sequence information was obtained on two or more members of each lineage, and sequence differenceswere confirmed. if detectable. by restrictionenzyme analysis. One of the 29 lineages wasnot registered. and maternal ancestry could notbe verified through registry information, butcows in this lineage were included in this
MATERNAL LINEAGE GROUPING 625
TABLE I. Yield and composition traits for 1800 recordsof 728 cows in 36 maternal lineages.
TABLE 2. Effect of mitochondrial DNA nucleotide 169type on yield and composition traits.
Trait
MEl Milk, kgME Fat, kgFat percentageSNF, kgSNF. %Energy concentration, kcallkgLactation energy. Mcal
8085288
3.63745
9.21732
5888
so1771
60.44
165.40
501225
Trait
ME3 Milk, kgME Fat, kgFat percentageSNF, kgSNF, %Energy concentration, kcallkgLactation energy, Mcal
Effectl
34939
.1649
.068
277
.962.77**3.30**1.481.563.05**2.30*
lMature equivalent (twice daily milking. 305-d lactation).
portion of this study because genotype as defined by mtDNA D-loop sequence was known(19).
The model employed to examine effects ofmtDNA genotypes on yield and compositiontraits was
Yijknp = YSi + Pj + sk + gn + pep+ ap + Cijknp. [3]
where all effects again were as previously defined, except that gn was the fixed effect ofmtDNA genotype n (n = 1 to 21). Numbers offixed effect classes remained the same; however, because the number of lineages wasfewer, there were only 1407 records of 572cows (pCp, p =572) and 787 animal equationsin these 29 maternal lineages.
RESULTS AND DISCUSSION
Base Pair 169
Overall means and standard deviations ofrecords of all cows in the available 36 maternallineages are in Table 1. Of the 728 cows inthese lineages, 583 (80.1 %) were polymorphicat mtDNA D loop nt169 with respect to thefirst published sequence (1). Probably, thatfirst cow had a sequence that was less commonthan that of the entire Holstein population.These 583 cows had 1468 records versus 332records for 145 cows identical to the referencesequence.
Table 2 has effect of nt169 sequence typeon yield and composition traits. Adenine toguanine transition on heavy strand mtDNA atnt169 had highly significant effects on fatyield and percentage and on energy concentra-
lPolymorphic minus identical effects for which sequence was classified as identical or polymorphic withrespect to the first published sequence by Anderson et aI.(I).
2The null hypothesis is that effects of identical andpolymorphic sequences are the same; df = 1759.
3Mature equivalent (twice daily milking, 305-d lactation).
*p> t ~ .05.
**P > t ~ .01.
tion (P > t ~ .01). The effect on lactationenergy concentration also was significant (P >t ~ .05). Previous reports (2, 23) based oncytoplasmic lineages suggested a larger impacton fat and energy than on milk volume. Schutzet al. (22) also reported a larger effect on fatyield than on milk yield when adenine toguanine transition at nt169 was analyzed concurrently with other mtDNA D-loop sequencedifferences in the same lineages.
Lindberg (18) determined that sequencepolymorphism at nt169 marked an evolutionarily important bifurcation in phylogenetic treesbased on mtDNA sequence information, Suchdistinct lineages may have evolved while theywere geographically separated. Furthermore,separation may have been accompanied bydifferences in artificial selection, potentiallyleading to significant effects on yield or composition that are similar to those observed inthis study.
No known gene products are coded by theD loop of mtDNA, but the D loop is a site ofimportant transcriptional and replicational controls. Differences in yield or composition associated with sequence polymorphism in thatregion of mtDNA may relate to control ofmtDNA function or may serve as markers forimportant sequence variation elsewhere in themtDNA genome, which is inherited in its entirety. Therefore, mtDNA D-Ioop polymorphism may become established in artificially
Journal of Dairy Science Vol. 76, No.2, 1993
MATERNAL LINEAGE GROUPING 625
TABLE I. Yield and composition traits for 1800 recordsof 728 cows in 36 maternal lineages.
TABLE 2. Effect of mitochondrial DNA nucleotide 169type on yield and composition traits.
Trait
MEl Milk, kgME Fat, kgFat percentageSNF, kgSNF. %Energy concentration, kcallkgLactation energy. Mcal
8085288
3.63745
9.21732
5888
so1771
60.44
165.40
501225
Trait
ME3 Milk, kgME Fat, kgFat percentageSNF, kgSNF, %Energy concentration, kcallkgLactation energy, Mcal
Effectl
34939
.1649
.068
277
.962.77**3.30**1.481.563.05**2.30*
lMature equivalent (twice daily milking. 305-d lactation).
portion of this study because genotype as defined by mtDNA D-loop sequence was known(19).
The model employed to examine effects ofmtDNA genotypes on yield and compositiontraits was
Yijknp = YSi + Pj + sk + gn + pep+ ap + Cijknp. [3]
where all effects again were as previously defined, except that gn was the fixed effect ofmtDNA genotype n (n = 1 to 21). Numbers offixed effect classes remained the same; however, because the number of lineages wasfewer, there were only 1407 records of 572cows (pCp, p =572) and 787 animal equationsin these 29 maternal lineages.
RESULTS AND DISCUSSION
Base Pair 169
Overall means and standard deviations ofrecords of all cows in the available 36 maternallineages are in Table 1. Of the 728 cows inthese lineages, 583 (80.1 %) were polymorphicat mtDNA D loop nt169 with respect to thefirst published sequence (1). Probably, thatfirst cow had a sequence that was less commonthan that of the entire Holstein population.These 583 cows had 1468 records versus 332records for 145 cows identical to the referencesequence.
Table 2 has effect of nt169 sequence typeon yield and composition traits. Adenine toguanine transition on heavy strand mtDNA atnt169 had highly significant effects on fatyield and percentage and on energy concentra-
lPolymorphic minus identical effects for which sequence was classified as identical or polymorphic withrespect to the first published sequence by Anderson et aI.(I).
2The null hypothesis is that effects of identical andpolymorphic sequences are the same; df = 1759.
3Mature equivalent (twice daily milking, 305-d lactation).
*p> t ~ .05.
**P > t ~ .01.
tion (P > t ~ .01). The effect on lactationenergy concentration also was significant (P >t ~ .05). Previous reports (2, 23) based oncytoplasmic lineages suggested a larger impacton fat and energy than on milk volume. Schutzet al. (22) also reported a larger effect on fatyield than on milk yield when adenine toguanine transition at nt169 was analyzed concurrently with other mtDNA D-loop sequencedifferences in the same lineages.
Lindberg (18) determined that sequencepolymorphism at nt169 marked an evolutionarily important bifurcation in phylogenetic treesbased on mtDNA sequence information, Suchdistinct lineages may have evolved while theywere geographically separated. Furthermore,separation may have been accompanied bydifferences in artificial selection, potentiallyleading to significant effects on yield or composition that are similar to those observed inthis study.
No known gene products are coded by theD loop of mtDNA, but the D loop is a site ofimportant transcriptional and replicational controls. Differences in yield or composition associated with sequence polymorphism in thatregion of mtDNA may relate to control ofmtDNA function or may serve as markers forimportant sequence variation elsewhere in themtDNA genome, which is inherited in its entirety. Therefore, mtDNA D-Ioop polymorphism may become established in artificially
Journal of Dairy Science Vol. 76, No.2, 1993
626 SCHUTZ ET AL.
selected populations when affected traits depend on control of transcription and replicationof mtDNA. Alternatively, sequence variantsmay by chance alone become fixed in subpopulations with differences in mtDNA genecoding regions.
Maternal Lineage Clusters
Data for analysis of maternal lineageclusters were the same as for the previous
analysis (Table 1). Assignment of lineages tocluster groups and number of cows in eachcluster group are shown in Table 3. Lineagesin a cluster group are separated by doublespaces. With 24 cluster groups, only a singlecluster (maternal lineages 14 and 18) hadmembers with differing genotypes. All otherclusters were identical for these 16 nt indicatedin Table 3.
With 14 cluster groups, members of a singlegroup obviously had more diverse genotypes,
TABLE 3. Assignment of 36 maternal lineages to 24 (clustering I) or 14 (clustering 2) groups by c1usteringl
Clustering Clustering 2
Binomial BinomialMaternal Number sequence Maternal Number sequencelineage of cows codes2 lineage of cows codes
20 47 000IOOOOOOOOOOOO 20 47 oo00000000סס000129 0001OOOOOOOOOOOO 29 ooo00ooo00סס00013 133 ooסס0ooooo0ס0011 2 203 ooooooo01סoס0011
32 ooסס0ooooo0ס0011 3 0oooooo00סס00110
33 0011000000000000 32 ooooooo00סoס0011
41 0011000000000000 33 ooo00ooo00סס0011
51 0oooooסoo0סס0011 37 001100000000001161 0011000000000000 40 00ll00000000000177 0011000000000000 41 0oooooסoo0סס0011
2 45 00 II 000000000001 51 ooסס0ooooo0ס0011
40 0011000000000001 58 0ooooo00011ס0011
17 42 0010000000000000 61 00110000ooo0000052 0010000000000000 77 00110000ooo0000037 25 oooooooסoס0011 11 17 42 00100000ooo0000058 ooooooo11סoס0011 52 00 I0ססooo00ooo0014 43 ooססoo1סס0111001 13 99 011100000000000018 ooסס0ooooo1ס0111 14 ooססoo1סס011100110 30 oo1000סס10110001 18 01110000ooo1ססoo
55 23 0oooooס101100010 66 oo1000ססooסס0111
13 9 0111000000000000 10 53 oo1000סס1011000166 47 oo1000ססooסס0111 55 1011000100000000
8 15 00III OOOOOOOOOOO 8 45 001110000000000067 30 ooססoo10סס001110 67 0011100000100000
5 12 ooסס oo00000סס110 5 21 ooסס 11000000000057 9 oooooooסoס000111 57 000II 1000000000039 19 000 Iססoo I0ססoo10 39 41 oo10000010סס0001
74 7 0oooooסoo1סס0001 69 ooססoo1100סס0001
45 9 00 0oooooס1100110 74 ooססoo1000סס0001
60 22 ooסס001100010100 45 31 ooסס00110011000069 15 oo00ססoo11סס0001 60 oo00סס0011000101
4 7 0oooooסoo1סס0010 4 7 oo10000000סס0010
75 45 0oooooo11סס0011 0 75 45 0oooooo11סס0011 071 35 ooסס001111100001 71 35 ooססoo1סס0011111
22 23 oo1סס001 0oooooס I 22 23 0010000 I0000000135 36 OOOOOOOOOOOOOOOO 35 36 ooo00ooo00000סס0
46 OOOOOOOOOOOOOOOO 46 oo000000ooo00סס0
lBoldfacing marks every other cluster group.
2Binomial sequence codes are for nucleotides 8,106.169.216,16022.16049.16057.16058.16074.16085,16111.16113.16141,16230,16231, and 16247, respectively. and Is correspond to sites that are polymorphic with respect to thefirst published bovine mitochondrial DNA sequence (I).
Journal of Dairy Science Vol. 76. No.2. 1993
626 SCHUTZ ET AL.
selected populations when affected traits depend on control of transcription and replicationof mtDNA. Alternatively, sequence variantsmay by chance alone become fixed in subpopulations with differences in mtDNA genecoding regions.
Maternal Lineage Clusters
Data for analysis of maternal lineageclusters were the same as for the previous
analysis (Table 1). Assignment of lineages tocluster groups and number of cows in eachcluster group are shown in Table 3. Lineagesin a cluster group are separated by doublespaces. With 24 cluster groups, only a singlecluster (maternal lineages 14 and 18) hadmembers with differing genotypes. All otherclusters were identical for these 16 nt indicatedin Table 3.
With 14 cluster groups, members of a singlegroup obviously had more diverse genotypes,
TABLE 3. Assignment of 36 maternal lineages to 24 (clustering I) or 14 (clustering 2) groups by c1usteringl
Clustering Clustering 2
Binomial BinomialMaternal Number sequence Maternal Number sequencelineage of cows codes2 lineage of cows codes
20 47 000IOOOOOOOOOOOO 20 47 oo00000000סס000129 0001OOOOOOOOOOOO 29 ooo00ooo00סס00013 133 ooסס0ooooo0ס0011 2 203 ooooooo01סoס0011
32 ooסס0ooooo0ס0011 3 0oooooo00סס00110
33 0011000000000000 32 ooooooo00סoס0011
41 0011000000000000 33 ooo00ooo00סס0011
51 0oooooסoo0סס0011 37 001100000000001161 0011000000000000 40 00ll00000000000177 0011000000000000 41 0oooooסoo0סס0011
2 45 00 II 000000000001 51 ooסס0ooooo0ס0011
40 0011000000000001 58 0ooooo00011ס0011
17 42 0010000000000000 61 00110000ooo0000052 0010000000000000 77 00110000ooo0000037 25 oooooooסoס0011 11 17 42 00100000ooo0000058 ooooooo11סoס0011 52 00 I0ססooo00ooo0014 43 ooססoo1סס0111001 13 99 011100000000000018 ooסס0ooooo1ס0111 14 ooססoo1סס011100110 30 oo1000סס10110001 18 01110000ooo1ססoo
55 23 0oooooס101100010 66 oo1000ססooסס0111
13 9 0111000000000000 10 53 oo1000סס1011000166 47 oo1000ססooסס0111 55 1011000100000000
8 15 00III OOOOOOOOOOO 8 45 001110000000000067 30 ooססoo10סס001110 67 0011100000100000
5 12 ooסס oo00000סס110 5 21 ooסס 11000000000057 9 oooooooסoס000111 57 000II 1000000000039 19 000 Iססoo I0ססoo10 39 41 oo10000010סס0001
74 7 0oooooסoo1סס0001 69 ooססoo1100סס0001
45 9 00 0oooooס1100110 74 ooססoo1000סס0001
60 22 ooסס001100010100 45 31 ooסס00110011000069 15 oo00ססoo11סס0001 60 oo00סס0011000101
4 7 0oooooסoo1סס0010 4 7 oo10000000סס0010
75 45 0oooooo11סס0011 0 75 45 0oooooo11סס0011 071 35 ooסס001111100001 71 35 ooססoo1סס0011111
22 23 oo1סס001 0oooooס I 22 23 0010000 I0000000135 36 OOOOOOOOOOOOOOOO 35 36 ooo00ooo00000סס0
46 OOOOOOOOOOOOOOOO 46 oo000000ooo00סס0
lBoldfacing marks every other cluster group.
2Binomial sequence codes are for nucleotides 8,106.169.216,16022.16049.16057.16058.16074.16085,16111.16113.16141,16230,16231, and 16247, respectively. and Is correspond to sites that are polymorphic with respect to thefirst published bovine mitochondrial DNA sequence (I).
Journal of Dairy Science Vol. 76. No.2. 1993
MATERNAL LINEAGE GROUPING 627
TABLE 4. Tests of significance and ranges of estimates for effects of clusters for 36 maternal lineages on yield andcomposition traits.
Clustering II
Range ofestimated
Trait F P>F effect F
ME3 Milk, kg .93 .549 1402 1.03ME Fat, kg 1.15 .282 75 1.33Fat percentage 1.68 .023 .64 2.44SNF. kg .98 .490 135 1.08SNF, % 1.23 .208 .46 1.00Energy concentration, kcallkg 1.58 .041 81 2.19Lactation energy. Mcal 1.07 .375 1245 1.21
Clustering 22
Range ofestimated
P > F effect
.412 1154
.189 71
.002 .58
.375 107
.444 .37
.008 71
.267 1182
124 cluster groups; numerator df = 23. and denominator df = 1737.
214 cluster groups; numerator df = 13. and denominator df = 1747.
3Mature equivalent (twice daily milking, 305-d lactation).
but maternal lineages within a single clusternever differed at more than 3 base pair sitesand that occurred in only one cluster (maternallineages 13, 14, 18, and 66). Clustering provedto be useful in grouping maternal lineages withsimilar mtDNA genotypes.
The 24 groups in clustering 1 had from 17records of 7 cows to 311 records of 133 cows.Clustering I averaged 30.3 cows and 75records per group, and clustering 2 averaged52 cows and 128.6 records per group. Clustering 2 (with 14 groups) had from 19 records of7 cows to 509 records of 203 cows. Significance tests of the effect of cluster groupson yield and composition traits and ranges ofcluster group estimates are in Table 4. Clustering 1 had a significant (P ~ .05) effect on fatpercentage and energy concentration. An effectof further clustering is to increase the variability among groups. Combining maternal lineages into 14 groups increased F statistics forall traits, although clustering 2 had statisticallysignificant effects on the same traits (Table 4).Ranges of estimates were larger forclustering 1, probably because of greater sampling variance associated with smaller groupsin clustering 1.
The F statistics and probabilities were consistent with those previously reported formaternal lineage effects (23). Also, correlations between solutions for the 24 groups inclustering 1 and solutions for the original 36maternal lineages of which the 24 groups werecomposed (23) were moderately high (.80 to
.90). The correlations between solutions for the14 groups of clustering 2 and solutions for the36 maternal lineages were smaller (.57 to .74).That clustering 1 was in somewhat betteragreement with maternal lineage results wasnot surprising because combining fewer lineages than with clustering 2 was more similar tothat analysis.
Coefficients of determination were .806 and.802, respectively, for fat percentage andenergy concentration for Model [2] withclustering 1. The coefficient of determinationwas only slightly less for each trait withclustering 2 than with clustering I and was.805 for fat percentage and .801 for net energyconcentration. Analysis of residuals from themodel with either clustering 1 or clustering 2by using a model including only maternal lineage demonstrated the ability of clustered line-
TABLE 5. Overall means and standard deviations of yieldand composition traits for 1407 records by 572 cows of 21mitochondrial DNA genotypes.
Trait X SD
MEl Milk, kg 7975 1760ME Fat, kg 286 59Fat percentage 3.65 .44SNF. kg 736 164SNF, % 9.23 .39Energy concentration, kealJkg 734 49Lactation energy. Meal 5830 1215
IMature equivalent (twice daily milking, 305-d lactation).
Journal of Dairy Science Vol. 76, No.2, 1993
MATERNAL LINEAGE GROUPING 627
TABLE 4. Tests of significance and ranges of estimates for effects of clusters for 36 maternal lineages on yield andcomposition traits.
Clustering II
Range ofestimated
Trait F P>F effect F
ME3 Milk, kg .93 .549 1402 1.03ME Fat, kg 1.15 .282 75 1.33Fat percentage 1.68 .023 .64 2.44SNF. kg .98 .490 135 1.08SNF, % 1.23 .208 .46 1.00Energy concentration, kcallkg 1.58 .041 81 2.19Lactation energy. Mcal 1.07 .375 1245 1.21
Clustering 22
Range ofestimated
P > F effect
.412 1154
.189 71
.002 .58
.375 107
.444 .37
.008 71
.267 1182
124 cluster groups; numerator df = 23. and denominator df = 1737.
214 cluster groups; numerator df = 13. and denominator df = 1747.
3Mature equivalent (twice daily milking, 305-d lactation).
but maternal lineages within a single clusternever differed at more than 3 base pair sitesand that occurred in only one cluster (maternallineages 13, 14, 18, and 66). Clustering provedto be useful in grouping maternal lineages withsimilar mtDNA genotypes.
The 24 groups in clustering 1 had from 17records of 7 cows to 311 records of 133 cows.Clustering I averaged 30.3 cows and 75records per group, and clustering 2 averaged52 cows and 128.6 records per group. Clustering 2 (with 14 groups) had from 19 records of7 cows to 509 records of 203 cows. Significance tests of the effect of cluster groupson yield and composition traits and ranges ofcluster group estimates are in Table 4. Clustering 1 had a significant (P ~ .05) effect on fatpercentage and energy concentration. An effectof further clustering is to increase the variability among groups. Combining maternal lineages into 14 groups increased F statistics forall traits, although clustering 2 had statisticallysignificant effects on the same traits (Table 4).Ranges of estimates were larger forclustering 1, probably because of greater sampling variance associated with smaller groupsin clustering 1.
The F statistics and probabilities were consistent with those previously reported formaternal lineage effects (23). Also, correlations between solutions for the 24 groups inclustering 1 and solutions for the original 36maternal lineages of which the 24 groups werecomposed (23) were moderately high (.80 to
.90). The correlations between solutions for the14 groups of clustering 2 and solutions for the36 maternal lineages were smaller (.57 to .74).That clustering 1 was in somewhat betteragreement with maternal lineage results wasnot surprising because combining fewer lineages than with clustering 2 was more similar tothat analysis.
Coefficients of determination were .806 and.802, respectively, for fat percentage andenergy concentration for Model [2] withclustering 1. The coefficient of determinationwas only slightly less for each trait withclustering 2 than with clustering I and was.805 for fat percentage and .801 for net energyconcentration. Analysis of residuals from themodel with either clustering 1 or clustering 2by using a model including only maternal lineage demonstrated the ability of clustered line-
TABLE 5. Overall means and standard deviations of yieldand composition traits for 1407 records by 572 cows of 21mitochondrial DNA genotypes.
Trait X SD
MEl Milk, kg 7975 1760ME Fat, kg 286 59Fat percentage 3.65 .44SNF. kg 736 164SNF, % 9.23 .39Energy concentration, kealJkg 734 49Lactation energy. Meal 5830 1215
IMature equivalent (twice daily milking, 305-d lactation).
Journal of Dairy Science Vol. 76, No.2, 1993
628 SCHUTZ ET AL.
TABLE 6. Tests of significance and ranges of estimatesfor effects of mitochondrial DNA genotypes on yield andcomposition traits.!
Range ofestimated
Trait F P> F effect
ME2 Milk, kg .99 .465 1334ME Fat, kg .87 .628 51Fat percentage 1.42 .105 1334.38SNF, kg .95 .528 125SNF, % 1.01 .453 .36Energy concentration,
kcaVkg 1.46 .085 76Lactation energy, Meal .90 .584 1016
'Numerator df = 20; denominator df = 1347.
2Mature equivalent (twice daily milking, 305-d lactation).
ages to account for the underlying maternallineage effects. Maternal lineage effects onresiduals could still have been appreciable ifthey were not accounted for by c1usterings.Even with clustering of 36 lineages into 14groups, effects of maternal lineages on residuals from Model [2] were negligible (P ~ ,99).Maternal lineages accounted for more variationin the residuals from Model [2] with clustering2 than with clustering I. Again, this result isexpected because clustering 1 is more analogous to maternal lineages as originally defined.
Clustering lineages into groups based onsequence differences in mtDNA D loops likelygrouped maternal lineages that had similarmtDNA sequences but were defined as distinctlineages because of the limited time availablefor definition based on pedigrees. Because theentire mtDNA genome is transmitted to thecow's offspring, lineages that are similar forD-loop sequences are probably more nearlyidentical for gene-coding regions of mtDNA,too. Therefore, they should express any biological effects similarly.
Sequence Genotypes
The purpose of this analysis was to determine whether economic traits could be associated with lineages assigned to homogeneous groups by sequence and restriction enzymeanalysis. Overall means and standard deviations of records by cows in the 29 maternallineages assigned to 21 genotypes by Lindberget al. (19) are in Table 5. Means and standard
Journal of Dairy Science Vol. 76, No.2, 1993
deviations are similar to those of the 36 lineages from the prior analyses. The 21 genotypeshad from 17 records of 7 cows to 197 recordsof 70 cows. On average, genotypes had 67records and 27,2 cows.
Table 6 has tests of significance of mtDNAgenotypes on yield and composition traits.Genotype approached significance (P ::;; .085)for energy concentration and fat percentage(P ::;; .105) but was not significant at P ::;; .10for any other trait. The F statistics were aslarge or nearly as large as those from testingmaternal lineages in a previous report bySchutz et al. (23), but associated probabilitieswere much larger because of fewer numeratorand denominator degrees of freedom. Rangesof estimates tended to be smaller than forcluster analysis. For Model [3], coefficients ofdetermination were .816 for fat percentage and.807 for net energy concentration. These valueswere somewhat greater than for either clustering in Model [2]. Comparisons must be madecautiously because data were not identical.
CONCLUSIONS
The intent of this work was not so much todetermine optimal methods of grouping cowsby mtDNA differences as to examine the effects on yield and composition of groupsformed by previously proposed methods. Thesignificance of a transition from adenine toguanine at nt169 in the mtDNA D loop on fatand energy produced by dairy cattle may haveevolutionary implications, as proposed byLindberg et al. (19). This present work alsoindicates the benefit of mixed models to associate potentially important mtDNA sequencepolymorphisms with milk yield and composition traits. Maternal lineage groups defined byclustering based on D-loop sequence polymorphism or by mtDNA genotype identificationhad the greatest effect on fat percentage andenergy concentration. The magnitude of theseeffects was similar to that of maternal lineageeffects reported previously (23). Further research may determine mechanisms by whichmtDNA sequence variation affects precise assignment of cows to maternal groups withsimilar mitochondrial genetic value. Optimaldefinition of mitochondrial lineages also willincorporate sequence variation in gene-codingregions of mtDNA, where mitochondrial effects more likely originate.
628 SCHUTZ ET AL.
TABLE 6. Tests of significance and ranges of estimatesfor effects of mitochondrial DNA genotypes on yield andcomposition traits.!
Range ofestimated
Trait F P> F effect
ME2 Milk, kg .99 .465 1334ME Fat, kg .87 .628 51Fat percentage 1.42 .105 1334.38SNF, kg .95 .528 125SNF, % 1.01 .453 .36Energy concentration,
kcaVkg 1.46 .085 76Lactation energy, Meal .90 .584 1016
'Numerator df = 20; denominator df = 1347.
2Mature equivalent (twice daily milking, 305-d lactation).
ages to account for the underlying maternallineage effects. Maternal lineage effects onresiduals could still have been appreciable ifthey were not accounted for by c1usterings.Even with clustering of 36 lineages into 14groups, effects of maternal lineages on residuals from Model [2] were negligible (P ~ ,99).Maternal lineages accounted for more variationin the residuals from Model [2] with clustering2 than with clustering I. Again, this result isexpected because clustering 1 is more analogous to maternal lineages as originally defined.
Clustering lineages into groups based onsequence differences in mtDNA D loops likelygrouped maternal lineages that had similarmtDNA sequences but were defined as distinctlineages because of the limited time availablefor definition based on pedigrees. Because theentire mtDNA genome is transmitted to thecow's offspring, lineages that are similar forD-loop sequences are probably more nearlyidentical for gene-coding regions of mtDNA,too. Therefore, they should express any biological effects similarly.
Sequence Genotypes
The purpose of this analysis was to determine whether economic traits could be associated with lineages assigned to homogeneous groups by sequence and restriction enzymeanalysis. Overall means and standard deviations of records by cows in the 29 maternallineages assigned to 21 genotypes by Lindberget al. (19) are in Table 5. Means and standard
Journal of Dairy Science Vol. 76, No.2, 1993
deviations are similar to those of the 36 lineages from the prior analyses. The 21 genotypeshad from 17 records of 7 cows to 197 recordsof 70 cows. On average, genotypes had 67records and 27,2 cows.
Table 6 has tests of significance of mtDNAgenotypes on yield and composition traits.Genotype approached significance (P ::;; .085)for energy concentration and fat percentage(P ::;; .105) but was not significant at P ::;; .10for any other trait. The F statistics were aslarge or nearly as large as those from testingmaternal lineages in a previous report bySchutz et al. (23), but associated probabilitieswere much larger because of fewer numeratorand denominator degrees of freedom. Rangesof estimates tended to be smaller than forcluster analysis. For Model [3], coefficients ofdetermination were .816 for fat percentage and.807 for net energy concentration. These valueswere somewhat greater than for either clustering in Model [2]. Comparisons must be madecautiously because data were not identical.
CONCLUSIONS
The intent of this work was not so much todetermine optimal methods of grouping cowsby mtDNA differences as to examine the effects on yield and composition of groupsformed by previously proposed methods. Thesignificance of a transition from adenine toguanine at nt169 in the mtDNA D loop on fatand energy produced by dairy cattle may haveevolutionary implications, as proposed byLindberg et al. (19). This present work alsoindicates the benefit of mixed models to associate potentially important mtDNA sequencepolymorphisms with milk yield and composition traits. Maternal lineage groups defined byclustering based on D-loop sequence polymorphism or by mtDNA genotype identificationhad the greatest effect on fat percentage andenergy concentration. The magnitude of theseeffects was similar to that of maternal lineageeffects reported previously (23). Further research may determine mechanisms by whichmtDNA sequence variation affects precise assignment of cows to maternal groups withsimilar mitochondrial genetic value. Optimaldefinition of mitochondrial lineages also willincorporate sequence variation in gene-codingregions of mtDNA, where mitochondrial effects more likely originate.
MATERNAL LINEAGE GROUPING 629
ACKNOWLEDGMENTS
Appreciation is expressed to the NationalAssociation of Animal Breeders and EasternArtificial Insemination Cooperative for partialfinancial support. Funding was also providedby US-Israeli Binational Agricultural Researchand Development Grant Number US1519-88R.
REFERENCES
1 Anderson, S., M.H.L. de Bruijn, A. R. Coulson, 1. C.Eperon, F. Sanger, and 1. G. Young. 1982. Completesequence of bovine mitochondrial DNA. J. Mol. Bioi.156:683.
2 Bell, B. R., B. T. McDaniel, and O. W. Robison.1985. Effects of cytoplasmic inheritance on production traits of dairy cattle. 1. Dairy Sci. 68:2038.
3 Brown, D. R., C, M. Koehler, G, L. Lindberg, A. E.Freeman, 1. E. Mayfield, A, M. Myers, M. M. Schutz,and D. C. Beitz. 1989, Molecular analysis of cytoplasmic genetic variation in Holstein cows. J. Anim. Sci.67:1926.
4 Faust, M, A., O. W. Robison, and B. T, McDaniel.1989, The effects of cytoplasm on reproduction andproduction in Holsteins. J. Dairy Sci. 72(Suppl. I):52.(Abstr.)
5 Faust, M. A., O. W. Robison, and B, T. McDaniel.1990. Animal model estimates of cytoplasmic lineconstants for yield in Holsteins. 1. Anim. Breed. Genet. 107:401.
6 Gyllensten, U., D, Wharton, A. Josefsson, and A. C.Wilson, 1991. Patemal inheritance of mitochondrialDNA in mice. Nature (Lond,) 352:255.
7 Gyllensten, U., D. Wharton, and A. C. Wilson, 1985.Maternal inheritance of mitochondrial DNA duringbackcrossing of two species of mice. J. Hered. 76:321.
8 Harville, D, A. 1979, Some useful representations forconstrained mixed model estimation. J. Am, Stat. Assoc, 74:200,
9 Henderson, C. R. 1974. General flexibility of linearmodel techniques for sire evaluation. J. Dairy Sci. 57:963.
10 Hoeh, W. R., K. H. Blakely, and W, M. Brown. 1991.Heteroplasmy suggests limited biparental inheritanceof Mytilus mitochondrial DNA. Science 251:1488.
11 Huizinga, H. A., S. Korver, B, T. McDaniel, and R.Politiek. 1986. Maternal effects due to cytoplasmicinheritance in dairy cattle. Influence on milk production and reproduction traits. Livest. Prod. Sci. 15:11.
12 Jacquard, A. 1974. The Genetic Structure of Populations. Springer-Verlag, Berlin, Germany,
13 Johnston, S, D. 1991. Sequence heterogeneity of bovine mitochondrial ribosomal RNA genes. M.S. Thesis, Iowa State Univ" Ames,
14 Kennedy, B, W. 1986. A further look at evidence forcytoplasmic inheritance of production traits in dairycallie. J. Dairy Sci. 69:3100.
15 Koehler, C. M. 1989. Nucleotide variation in bovinemitochondrial DNA. M.S. Thesis, Iowa State Univ"Ames.
16 Koehler, C. M., G. L. Lindberg, A. E, Freeman, A. M,Myers, 1. E, Mayfield, and D. C. Beitz. 1991. Complete replacement of a bovine mitochondrial genotypein a single generation, Genetics 129:247.
17 Laipis, P, J., M, 1. Van de Walle, and W. W,Hauswirth. 1988, Unequal partitioning of bovinemitochondrial genotypes among siblings, Proc. NatLAcad. Sci. USA 85:8107.
18 Lindberg, G. L. 1989, Sequence heterogeneity of bovine mitochondrial DNA. Ph.D. Diss., Iowa StateUniv. University Microfilm Order No, DA-9014925,Ann Arbor, MI.
19 Lindberg, G. L., C. M. Koehler, S. D. Johnston, D. R.Brown, A. M. Myers, A. E, Freeman, and D. C. Beitz.1989, High frequency of sequence variation in thedisplacement-loop region of bovine mitochondrialDNA. 1. Dairy Sci. 72(Suppl. l):53.(Abstr.)
20 Nib1er, T" F. Reinhardt, and F. Pirchner. 1990. Einfluss Zytoplasmatischer Vererbung auf Milchleistungund Fruchtbarkeit bei Milchvieh. Zuechtungskunde62:179.
21 Reed, P. D., and L. D. Van Vleck. 1987. Lack ofevidence for cytoplasmic illheritance of productiontraits of dairy cattle. J. Dairy Sci. 70:837.
22 Schutz, M. M, 1991. Cytoplasmic and mitochondrialgenetic effects on economic traits in dairy cattle.Ph.D, Diss., Iowa State Univ. University MicrofilmOrder No. 9207254. Ann Arbor, M1.
23 Schutz, M. M., A. E. Freeman, D. C. Beitz, and J. E.Mayfield. 1992. The importance of maternal lineageon milk yield traits of dairy callie. 1. Dairy Sci. 75:1331.
24 Sneath, P.H.A., and R. R. Sokal. 1973. NumericalTaxonomy. W. H. Freeman and Co., San Francisco,CA.
25 Southwood, 0, I., B. W. Kennedy, K. Meyer, and J. P.Gibson, 1989. Estimation of additive maternal andcytoplasmic genetic variances in animal models. 1.Dairy Sci. 72:3006,
26 Tyrrell, H. F., and J. T, Reid, 1965. Prediction of theenergy value of cow's milk. J. Dairy Sci. 48:1215.
27 Wales, T. P" Jr. 1885, Holstein Friesian Herd Book.Egbart, Fid1ar, and Chambers, Davenport, IA.
28 Weigel, K. A., A. E. Freeman, M. E. Kehrli, Jr., M. J.Stear, and D. H. Kelley. 1990, Association of class Ibovine lymphocyte antigen complex alleles withhealth and production traits in dairy cattle, J. DairySci, 73:2538.
Journal of Dairy Science Vol. 76, No.2, 1993
MATERNAL LINEAGE GROUPING 629
ACKNOWLEDGMENTS
Appreciation is expressed to the NationalAssociation of Animal Breeders and EasternArtificial Insemination Cooperative for partialfinancial support. Funding was also providedby US-Israeli Binational Agricultural Researchand Development Grant Number US1519-88R.
REFERENCES
1 Anderson, S., M.H.L. de Bruijn, A. R. Coulson, 1. C.Eperon, F. Sanger, and 1. G. Young. 1982. Completesequence of bovine mitochondrial DNA. J. Mol. Bioi.156:683.
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Journal of Dairy Science Vol. 76, No.2, 1993
