Changes of vectors of selection for piglet’s newborn weight during population formation in new environment conditions

Тип работы:
Общие и комплексные проблемы естественных и точных наук

Узнать стоимость новой

Детальная информация о работе

Выдержка из работы

ISSN 313−4836 (Online)
Gene pools
UDC 636. 4:575. 174:591.4 doi: 10. 15 389/agrobiology. 2014.6. 86rus
doi: 10. 15 389/agrobiology. 2014.6. 86eng
Novosibirsk State Agrarian University, 160, ul. Dobrolyubova, Novosibirsk, 630 039 Russia, e-mail knyser@rambler. ru- 2Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, 10, prosp. Lavrentieva, Novosibirsk, 630 090 Russia, e-mail nsv1956@mail. ru Received August 13, 2013
Studying changes of gene pools of populations of the domestic animals caused by selection and reflecting micro evolutionary processes, represents both practical and theoretical interest. As a rule, in such works the qualitative traits controlled by the principle «one genotype — one phenotype» are used that significantly simplifies the analysis. We investigated dynamic processes in Landrace population of domestic pigs (Sus scrofa domesticus), having estimated a variation of one of continuous quantitative traits, the newborn piglet weight, for which similar relationship is not unambiguous. Statistical analysis of the zootechnical register data was carried out on more than 26 thousand pigs that were born within 23 years at an experimental farm (Novosibirsk Province), being the regional authorized Landrace breed nucleus. Ancestors of the formed population were delivered from Latvia in the early 1960s. They were the elite young animals estimated on a standard complex of selection traits. The entire period of existence of population the formation of its breeding nuclear was carried out on a complex of traits according to existing Instruction for estimation of breeding value of pigs. As the Instruction didn’t contain standards on a large newborn weight, the selection on the specified trait wasn’t made. The changes of statistical parameters of the newborn weight in piglets were estimated for each year of the observation, because the analyzed livestock was not a model laboratory population, but a typical breeding commercial herd in which continuous variability of a trait is interfaced to continuous «sliding» alternations of generations and the variability of age structure. During long-time analysis of the dynamics of this unselected trait, the directional (moving) selection on genotypes for the loci controlling growth rate of pigs in ontogenesis (in pre- and post-natal periods) is revealed. In the populations where such selection works, the newborn weight of piglets can be used for forecasting pig weight during the postnatal period. Application of «parent-descendant» regression on the newborn weight allowed to estimate the duration of a population gene pool adaptation to new environment. It appeared that process of adaptation lasted nearly two decades that made five full changes of the generations. In the same population at the same time the stabilizing selection optimized an individual animal weight at birth, cutting both minimum and maximum values. The described mechanism includes cyclic vector changes towards driving selection against the stabilizing selection vectors and thus maintains the population polymorphism on loci which control prenatal growth and large weight in the newborns. An observed unevenness of wavy change of these cycles should be also noted.
Keywords: pigs, Sus scrofa domesticus, Landrace, population, adaptation, piglet’s newborn weight, regression, the vector of selection, directional (moving) selection, stabilizing selection, microevolution processes.
Changes in gene pools of population caused by selection or occurred due to a random gene drift are constantly attracting attention of the researchers (13), and in many works the domestic pigs were studied in this connection (4−12). However, the qualitative traits are mostly estimated as more simple because of a strong concordance of each specific genotype to a single phenotype according to the «one genotype-one phenotype» principle. For long time of our studying variations of qualitative traits the results of both practical and theoretical interest have been obtained (13−17). Importantly, once the quantitative trait changes were first statistically analyzed, a number of genetic determinations peculiar spe-
cifically to domestic animals were found out (18). Besides, the traits used in pig breeding were shown to reflect trends related to artificial selection rather then to natural. So we tried to find the trait convenient for estimation of the natural selection vectors. The number of nipples was first used, but it was good to indicate random factors affecting quantitative traits (19) and poor reflected the intrapopulation changes because of discreteness and a narrow variation range (18, 19). A newborn piglet weight was next tested. This is a continual quantitative trait with indefinite relationship of a genotype to the phenotype, meaning the same phenotype appeared in different genotypes and multiple trait values are observed in the same genotype (20). As far as a piglet weight at birth is a perinatal growth trait its variation in heterozygotes contains the ranges of variations in homozygotes on each allele (21). Reasonably, a piglet birth weight, being a continuous quantitative trait with rather wide variation range and known genetic control, was used as a quantitative trait (22−26).
In this research our goal was to find out whether a piglets' weight at birth is influenced by artificial or by natural selection whereas the population of domestic pigs are being newly formed due to adaptation to unusual environmental conditions.
Technique. Landrace domestic pigs (Sus scrofa domesticus) born from 1964 to 1965 and from 1967 to 1986 at an experimental farm (Novosibirsk Province) were analyzed. Ancestors of the formed population were delivered from Latvia in the early 1960s. They were the elite young animals with an estimated standard complex of selection traits (27). During the observation the rearing technologies and feeding were as described (28, 29). Twice a day the animals were fed with standard SK compound feeds (Russia) according to the recommended rations (30).
The entire period of existence of the population the breeding for a complex of traits was carried out according to the Instruction for estimation of pigs' breeding value which didn’t contain standards of a large animal weight (9) or a newborn weight. At a breed herd formation the piglets were twice selected, particularly in 2 month of age when weaned and in 5 months of age when a remount group of 25% of breed nucleus was formed.
To evaluate the trait dynamics, the statistical parameters were annually compared. An average piglets' birth weight in each year was compared to those of their parents, exactly 21 461 piglets from 312 paternal boars and 1181 sows were estimated. Additionally, to evaluate the upper limit of the trait values a total of 26 086 newborn piglets from 2587 litters were weighed.
The data were processed by common statistical methods (31).
Results. The experimental piggery was the regional authorized Landrace breed nucleus. In the population adapted to Siberian environment no targeted selection for an above standard animal weight was used. In created population its value was increasing for 23 years, mostly in the parent animals from the reproductive herd nucleus and in much less extent in their offspring.
A year was the least period for comparison since the analyzed livestock was not a model laboratory population, but a typical breeding commercial herd. In such a herd the reproductive nucleus consists of animals of different ages and is constantly renewing due to some new boars and sows included while the others discarded because of age or other reasons. Thus, a change of generations in the herd is a continuous process extended in time. At that an annual variability of the trait is linked to a continued change of generations and the age structure of breeding stock. As the latter was almost the same among years, being subject only to random variations, a calendar year as a time unit was reasonably used in a
comparative study of the trait dynamics.
A birth (kg) variation in piglets and their parents in a Landras pig population during long adaptation to unusual environmental conditions (experimental farm, Novosibirsk Province)
Year Descendants Boars Sows Regression coefficient (bxv)
n M±m n M±m n M±m boar- descendant|saw- descendant
1964 524 0. 98±0. 007 9p 1. 40±0. 116 40p 1. 24±0. 040 -0. 006 0. 091
1965 405 1. 14±0. 012 14 1. 08±0. 074 31 1. 13±0. 032 -0. 140 -0. 403
1967 262 1. 16±0. 013 10 1. 19±0. 038 28 1. 15±0. 041 -0. 670 -0. 163
1968 355 1. 20±0. 007 6 1. 18±0. 048 30 1. 14±0. 046 -0. 111 -0. 123
1969 592 1. 29±0. 019 10 1. 38±0. 092 56 1. 36±0. 046 0. 212 0. 098
1970 1027 1. 26±0. 004 22 1. 48±0. 063 100 1. 35±0. 030 -0. 007 0. 032
1971 1116 1. 38±0. 009 17 1. 37±0. 051 94 1. 45±0. 032 -0. 189 0. 231
1972 1506 1. 47±0. 007 24 1. 38±0. 074 106 1. 46±0. 030 -0. 063 0. 034
1973 1652 1. 33±0. 012 14 1. 39±0. 075 122 1. 46±0. 025 -0. 067 0. 018
1974 1255 1. 42±0. 005 15 1. 37±0. 064 98 1. 43±0. 025 -0. 030 0. 037
1975 1066 1. 35±0. 009 15 1. 39±0. 070 73 1. 44±0. 025 -0. 070 -0. 042
1976 748 1. 42±0. 010 16 1. 44±0. 055 74 1. 51±0. 025 -0. 056 0. 029
1977 1329 1. 18±0. 008 22 1. 56±0. 056 92 1. 49±0. 017 0. 038 0. 024
1978 1451 1. 28±0. 007 26 1. 18±0. 076 109 1. 24±0. 026 0. 052 -0. 028
1979 1720 1. 35±0. 007 30 1. 47±0. 040 115 1. 35±0. 023 0. 007 0. 029
1980 1187 1. 31±0. 008 32 1. 48±0. 047 101 1. 36±0. 023 -0. 045 -0. 141
1981 1663 1. 34±0. 007 33 1. 56±0. 063 128 1. 34±0. 024 -0. 009 0. 085
1982 1114 1. 34±0. 010 29 1. 51±0. 039 79 1. 44±0. 033 0. 224 -0. 059
1983 724 1. 45±0. 012 24 1. 59±0. 062 67 1. 47±0. 037 0. 046 0. 134
1984 562 1. 30±0. 014 15 1. 55±0. 061 53 1. 49±0. 046 0. 110 0. 191
1985 853 1. 24±0. 010 23 1. 55±0. 058 74 1. 47±0. 034 0. 203 0. 171
1986 350 1. 12±0. 009 10 1. 32±0. 053 31 1. 37±0. 038 -0. 150 -0. 022
Total 21 461 1. 32±0. 002 312 1. 44±0. 017 1181 1. 38±0. 008
r 0. 33- unreliable 0. 61- P & lt- 0. 01 0. 57- P & lt- 0. 01
Comments. 1964, 1969, 1973, 1977, 1981 and 1985 are the years of complete change of the parental animals in the breed nucleus) — p in upper index marks offspring of the animals delivered from Latvia- M±m is an average value and the error- r is a correlation coefficient between year and the birth weight.
In the basic experiment only piglets individually weighed as well as both their parents were considered (Table) that allow to indicate a correct trends in the trait changes regarding random variation and annual succession of the breed nucleus.
For the trait a positive trend was found reliable (P & lt- 0. 01) in parents and unreliable in the population as a whole, being probably observed due to expression in the parent animal groups (Fig. 1).
Thus, the animals from reproductive nucleus were selected for an increased birth weight while its influence on the population was insufficient. Herewith, the changes resulted from three factors, namely natural selection for the early postnatal viability, a positive correlation between the weights at birth and at weaning, as demonstrated by the curves (Fig. 2) constructed according to published data (29), and a standardizing selection for total weight specific to domestic animals (18). The first two factors significantly increased probability of more large animals inclusion into effective nucleus of the population. Providing both prenatal and postnatal growth is genetically controlled by the same loci, a standardizing selection for total weight could influence a newborn weight despite the fact that artificial selection for weigh at remount herd formation first occurred in 2 month
Fig. 1. Birth weight trends in Landras pig population and its reproductive nucleus during long adaptation to unusual environmental conditions: ¦ - descendant,? — boars, О — sows (experimental farm, Novosibirsk Province).
old animals, as thereat required (27).
The observed trends on the birth weight in parental groups and reliable differences between the breeding males and females (ta = 3. 06, P & lt- 0. 01) resulted from the standardizing selection. More clear positive trend (see Fig. 1) and higher birth weight (see Table) in boars resulted from much more strong selection compared to sows. A summarizing vector of the discussed three factors obviously was directed not to the birth weight increase, but to the high rate of prenatal and postnatal growth. Therefore, in the effective part of the population there are the individuals not just large at birth but also fast growing during postnatal period.
Fig. 2. Viability of sucking piglets (1) and their weight at weaning in 8 weeks of age (2) as related to birth weight (consorted according to published data) (29).
Piglet’s birth weight is polygenically controlled (20, 21) with an expressed indefinite relationship between genotype and phenotype, meaning not only effects of ran-domnicity but also probable adequate response to external impact. The influence of both these factors may be described by the regression of a parental phenotype on the deFig. 3. Krtl, weight пдо*" coefBcient m Landras pig _ popuia- scendant phenotype. Thus, the tion during long adaptation to unusual environmental conditions: 1 — boar-descendant, 2 — sow-descendant, 3 — trend both ambiguities, ne. for the of boar on descendant regression coefficient, 4 — trend of genotype-phenotype relation-sow on descendant regression coefficient (experimental farm, ships in a parent and its off-Novoabmk Provmce). spring, could be considered.
The Landras pigs delivered from Baltic region to West Siberia for introduction had to adapt to unusual conditions. As a result, a gene pool has changed during formation of a new population. According to the analyzed trait, these changes were estimated by a linear regression trends for both boars' and sows' phenotypes on that of their offspring (see Table, Fig. 3).
On the curves the longest initial segments of the negative regression coefficient should be noted (see Fig. 3). Suggestible, under unusual feeding and housing conditions the piglets born larger were more viable during sucking period and also gaining greater weight by weaning (see Fig. 2) (29). As a result, the population was subjected to selection for the high rate of prenatal and postnatal growth. Obviously, initially in the population the analyzed phenotype was poor related to genotype. Therefore, in the offspring the birth weight did not exceed an average value in the population even if the parents were larger at birth, resulting in negative regression coefficients. Selection for high growth rate during ontogenesis gradually decreased indetermination of the relationship between genotype and phenotype to a positive parent-descendant regression level occurred 15 years after the adaptation started (see Fig. 3). It probably means that the animals
with relatively stable and locally adapted relationship of the genotype to phenotype exceeded in rate, if compared to those with unstable relationship.
Hereby, a selection for increased birth weigh was really found in the studied population. Nevertheless, the weigh of newborns remained relatively unchanged due to genetic and physiological mechanisms acting towards stabilization within the limits of sows' and offspring viability. In other words, birth weigh can vary in different population as well as in the same population among the years (see Table) but within definite range, so that the selection for the trait can not be effective in the essence. The lowest values are obviously limited by the high death rate in small piglets. Optimization of the birth weight in the population should correlate with some other traits. Particularly in pig as a prolific animal there is a collision between birth weight of a piglet and the number of piglets in the litter resulting in negative correlation of these traits (32). Similar correlation was also observed in the population studied (r = -0. 82- P & lt- 0. 001).
A probable factor limiting birth weigh is a total offspring weight. Abstractly, a curve of its dependence on piglets' number must contain two segments, of which the first tended to a population maximum, looking as an upward sloping line, and the second fluctuated around the horizontal line somewhat below the maximum level. The piglets with no data on their parents' weight, a total of 26 086 newborns including those stillborn from 2587 litters, were additionally analyzed to verify this suggestion. The highest weight in the sample was 28.8 kg (Fig. 4, A). We compared a reliability of approximation R2 (Microsoft Excel) for the most frequent numbers of piglets in the litter to find the end of the first segment. In case of 12, 13 and 14 piglets R2 was
0. 9880, 0. 9905 and 0. 9823, respectively. So the ascending and horizontal segments corresponded to the numbers from 1 to 13 and from 14 to 19, respectively. For the first and second segments the correlation coefficients between size of the litter and weight of the litter at birth were +0. 995 (P & lt- 0. 001) and +0. 039 (unreliable), in the other words, the curve quite well described a relationship between the litter weight at birth and the number of piglets per litter (see Fig. 4, A). The litter weight at birth is related both to the number of piglets per litter and the piglet’s weight at birth, in turn, both being physiologically limited by the maternal physiological capabilities. As a result, a negative correlation occurs between fetus number and weight. Thus the second curve of relationship between birth weight and number of piglets in the litter should obviously be
Figc. 4. Litter weight (A) and averages birth weight (B) depending on number of piglets in a litter in Landras pig population during long adaptation to unusual environmental conditions: 1 — actual distribution, 2 — trend line (experimental farm, Novosibirsk Province).
Fig. 5. Changes in birth weight in Landras pig population during 23 year adaptation to unusual environmental conditions: 1 —
actual, 2 — trend line (experimental farm, Novosibirsk Province).
similar in character but reversed, so that the horizontal segment was followed by inclined line (see Fig. 4, B). Correlation coefficients ® between the number and an average birth weight of piglets in the litter were -0. 467 (unreliable) and -0. 856 (P & lt- 0. 05) for two segments, respectively, being in line with our suggestion. Consequently, it can be asserted that the vector reducing birth weight is a factor of stabilizing natural selection towards optimization of the correlation between piglet weight and number.
As far as the litter size negatively correlates with birth weight per piglet, and standardizing selection for higher litter size as an important economic trait is constantly occurring in the commercial pig populations, its intensification presumably intensifies the natural selection for lower weight of the newborns. After fixation of the alleles encoding optimal number of piglets in the population the selection for an increased birth weight which provides higher viability of sucking piglets should be resumed and continued until the piglet number fall. Then the next cycle should begin, and so it goes on all time during the population existence. Because of a collision between selection for higher birth weight and its upper limitation, the curve should show wavy fluctuations around optimum value for rather long time that exactly was observed in the studied population (Fig. 5). During 23 years there were two waves, when an average birth weight increased from 1. 01 to 1. 46 in 1964 to 1972, then decreased to 1. 18 kg in 1977, and again increased to 1. 45 kg in 1983 and dropped to 1. 13 kg in 1986. Generally, the birth weight as a quantitative trait seems to be influenced by the limitations resulting in elimination of the largest individuals (see Fig. 4) rather then by selection towards higher weight parameters, probable due to some other factors reducing piglet’s weight at birth to an optimal value.
It should be noted that at long-term adaptation the classical population research based on annual dynamics estimation (33) is more effective compared to constructing series based on the limited data (see Table) for the years of complete change of generations in the reproductive herd nucleus. In fact, exactly classical approach is appropriate to studying real but not model populations. Our findings contribute to current knowledge about genetic and breeding aspects of newborn’s weight in pigs (20, 34).
Thus, in Landras pig population formed in the course of adaptation to unusual conditions the directional (moving) selection for the loci controlling growth rate of pigs in ontogenesis, i.e. in prenatal and postnatal periods, is revealed. In the populations where such selection works, the newborn weight of piglets can be used for forecasting pig weight during the postnatal period. A regression of parent-descendant birth weight in the population allows to estimate the time of gene pool adaptation to new environment. Adaptation in the studied population took nearly two decades that made five full changes of generations, and there were two key events observed. First, a predominance of the individuals with reduced ambiguity in genotype-phenotype relationship has been reached
after 15-year adaptation, and secondly, optimization admittedly considered the final adaptation of the population has been achieved 5 years later. In the same population at the same time the stabilizing selection optimizes an individual animal weight at birth, cutting both minimum and maximum values. The described cyclic changes of driving and stabilizing selection vectors seem to provide the population polymorphism on loci which control prenatal growth and large weight in the newborns. An observed unevenness of wavy changes in these cycles should also be noted.
1. Levontin R. Geneticheskie osnovy evolyutsii [Genetic bases of evolution]. Moscow, 1978.
2. Grant V. Evolyutsiya organizmov [Organismic evolution]. Moscow, 1980.
3. Solbrig O., Solbrig D. Populyatsionnaya biologiya i evolyutsiya [Introduction to population biology and evolution]. Moscow, 1982.
4. Ciobanu D.C., Day A.E., Nagy A., Wales R., Rothschild M.F., Plastow G.S. Genetic variation in two conserved local Romanian pig breeds using type 1 DNA markers. Genet. Sel. Evol, 2001, 33: 417−432 (doi: 10. 1186/1297−9686−33−4-417).
5. Allen M.S., M a tiso o-S mith E., Horsburgh A. Pacific «Babes»: issues in the origins and dispersal of Pacific pigs and the potential of mitochondrial DNA analysis. International Journal of Osteoarchaeology, 2001, 11: 4−13 (doi: 10. 1002/oa. 541).
6. Fan B., Wang Z. -G., Li Y. -J., Zhao X. -L., Liu B., Zhao S. -H., Yu M., Li M. -H., Chen S. -L., Xiong T. -A., Li K. Genetic variation analysis within and among Chinese indigenous swine populations using microsatellite markers. Anim. Genet, 2002, 33: 422−427 (doi: 10. 1046/j. 1365−2052. 2002. 898. x).
7. Vega-Pla J.L., Martinez A.M., Cabello A., Rodriguez-Gallardo 1 P.P., D e l g a d o J.V. Preliminary study of individual assignment of Iberian pigs using DNA genetic markers. Arch. Zootec., 2003, 52: 225−230.
8. Fan B., Yang S. -L., Liu B., Yu M., Zhao S. -H., Li K. Characterization of the genetic diversity on natural populations of Chinese miniature pig breeds. Anim. Genet., 2003, 34: 465−476 (doi: 10. 1046/j. 0268−9146. 2003. 1 057. x).
9. Li S. -J., Yang S. -H., Zhao S. -H., Fan B., Yu M., Wang H. -S., Li M. -H., Liu B., Xiong T. -A., Li K. Genetic diversity analyses of 10 indigenous Chinese pig populations based on 20 microsatellites. J. Anim. Sci., 2004, 82: 368−374.
10. Kim T.H., Kim K.S., Choi B.H., Yoon D.H., Jang G.W., Lee K.T., Chung H.Y., Lee H.Y., Park H.S., Lee W. Genetic structure of pig breeds from Korea and China using microsatellite loci analysis. J. Anim. Sci., 2005, 83: 2255−2263.
11. Knyazev S.P., Nikitin S.V., Savina M.A., YUdina O.P., Ermolaev V.I., Gorelov I.G., Danil'-chenko N.V., Fadeeva N.S. Doklady RASKHN, 2004, 2: 35−38.
12. Thuy N.T.D., Melchinger-Wild E., Kuss A.W., Cuong N.V., Bartenschla-g e r H., Geldermann H. Comparison of Vietnamese and European pig breeds using microsatellites. J. Anim. Sci., 2006, 84: 2601−2608 (doi: 10. 2527/jas. 2005−641).
13. Nikitin S.V., Knyazev S.P., Nikolaev A.G., Voloch A.M., Kirichenko A.V., Savina M.A., Yermolaev V.I., Yudina O.P., Bekenev V.A., Aytnazarov R.B. Diversity of wild and domestic pig populations estimated by a set of serum allotypes. Russian Journal of Genetics, 2006, 42(3): 317−326 (doi: 10. 1134/S1022795406030136).
14. Nikitin S.V., Yudin N.S., Knyazev S.P., Aytnazarov R.B., Kobzev V.F., Bekenev V.A., Savina M.A., Yermolaev V.I. Frequency of chromosomes carrying endogenous retroviruses in the populations of domestic pig and wild boar. Russian Journal of Genetics, 2008, 44(6): 686−693 (doi: 10. 1134/S1022795408060082).
15. Nikitin S.V., Knyazev S.P., Shvebel T.I., Goncharenko G.M. Dynamics of heterozygosity and its correlation with fitness in a population of domestic pigs. Russian Journal of Genetics, 2009, 45(10): 1238−1246 (doi: 10. 1134/S1022795409100123).
16. Nikitin S.V., Yudin N.S., Knyazev S.P., Aitnazarov R.B., Bekenev V.A., Deeva V.S., Goncharenko G.M., Kobzev V.F., Savina M.A., Ermolaev V.I. Differentiation of wild boar and domestic pig populations based on the frequency of chromosomes carrying endogenous retroviruses. Natural Science, 2010, 2: 527−534 (doi: 10. 4236/ns. 2010. 26 066).
17. Yermolaev V.I., Savina M.A., Knyazev S.P., Yudin N.S., Aitnazarov R.B., Bekenev V.A., Deeva V.S., Nikitin S.V. Study of swine alpha macroglobulin gene family polymorphism in the context of some problems of animal breeding. Russian Journal of Genetics: Applied Research, 2013, 3(3): 225−232 (doi: 10. 1134/S2079059713030040).
18. Knyazev S.P., Nikitin S.T. Standardizing selection and its consequences for genetic popula-
tion structure. Russian Journal of Genetics, 2011, 47(1): 90−99 (doi: 10. 1134/S1022795411010030).
19. Nikitin S.V., Knyazev S.P., Ermolaev V.I. Model of genetic control of the number and location of nipples in domestic Pig. Russian Journal of Genetics, 2012, 48(11): 11 281 140 (doi: 10. 1134/S1022795412110075).
20. Nikitin S.V., Knyazev S.P., Yermolaev V.I. Genetic components and the uncertainty of the phenotypic realization of the mass of newborns in domestic pigs Sus scrofa. Russian Journal of Genetics, 2014, 50(1): 61−70 (doi: 10. 1134/S1022795414010086).
21. Nikitin S.V., Knyazev S.P., Orlova G.V., Be ken e v V.A., Danil'-chenko N.V. Genetika, 2005, 41(2): 237−245.
22. Quintanilla R., Milan D., Bidanel J. -P. A further look at quantitative trait loci affecting growth and fatness in a cross between Meishan and Large White pig populations. Genet. Sel. Evol., 2002, 34: 193−210 (doi: 10. 1186/1297−9686−34−2-193).
23. Sato S., O yam a da Y., Atsuji K., Nade T., Sato Sh. -I., Kobayashi E., Mitsuhashi T., Nirasawa K., Komatsuda A., Saito Y., Terai S., Haya-s h i T., S u g i m o t o Y. Quantitative trait loci analysis for growth and carcass traits in a Me-ishan x Duroc F2 resource population. J. Anim. Sci., 2003, 81: 2938−2949.
24. Damgaard L.H., Rydhmer L., L0vendahl P., Grandinson K. Genetic parameters for within-litter variation in piglet birth weight and change in within-litter variation during suckling. J. Anim. Sci., 2003, 81: 604−610.
25. Rothschildl M.F., Hu1 Z. -L., Jiang Z. Advances in QTL mapping in pigs. Int. J. Biol. Sci., 2007, 3(3): 192−197 (doi: 10. 7150/ijbs.3. 192).
26. NCBI Map Viewer, 2011 (http: //www. nbci. nlm. nih. gov/projects/mapview/).
27. Instruktsiya po bonitirovke svinei [Instruction for pig valuation]. Moscow, 1976.
28. Volkopyalov B.P. Svinovodstvo [Pig breeding]. Leningrad, 1968.
29. Kabanov V.D. Povyshenie produktivnosti svinei [An increase of pig productivity]. Moscow, 1983.
30. Popov I.S. Kormovye normy i kormovye tablitsy [Feed standards and reference tables]. Moscow, 1948.
31. Lakin G.F. Biometriya [Biometry]. Moscow, 1990.
32. Iogansson I., Ren del'- Ya., Gravert O. Genetika i razvedenie domashnikh zhivotnykh [Genetics and breeding in livestock]. Moscow, 1970.
33. Lyubishchev A.A. Dispersionnyi analiz v biologii [Dispersion analysis in biology]. Moscow, 1986.
34. Knyazev S.P., Nikitin S.V., Ermolaev V.I. Vestnik NGAU (Novosibirskii gosudarstven-nyi agrarnyi universitet), 2013, 1(26): 46−57.

Показать Свернуть
Заполнить форму текущей работой