Genetic and environmental causes of variation in milk production traits of Sahiwal cattle in Pakistan

Developmental programming of production and reproduction in dairy cows: III. Association of level of maternal milk production with offspring's birth weight, survival, productive and reproductive performance and AMH concentration from birth to the first lactation period

Although some studies investigated the relationship of dam milk production (DMP) with offspring birth weight and productive performance, limited information is available on the association of level of DMP with reproductive performance in dairy cows. Therefore, the present study was conducted to understand whether dams with various levels of milk production produce offspring with different fertility. In study I, offspring were classified based on the level of DMP into five categories, including DMP1 (dams with <10.00 × 103 kg of 305-day milk production), DMP2 (dams with ≥10.00 × 103 kg and <12.00 × 103 kg of 305-day milk production), DMP3 (dams with ≥12.00 × 103 kg and <14.00 × 103 kg of 305-day milk production), DMP4 (dams with ≥14.00 × 103 kg and <16.00 × 103 kg of 305-day milk production) and DMP5 (dams with ≥16.00 × 103 kg of 305-day milk production). In study I, data of birth weight, milk yield and reproductive variables of 14,536 offspring born to lactating dams and corresponding data of DMP were retrieved. In study II, blood samples (n = 339) were collected from offspring in various categories of DMP for measurement of serum AMH. Offspring were heavier at birth in DMP4 and DMP5 categories than DMP1 and DMP2 categories (P < 0.05). Milk yield of offspring increased as DMP elevated (P < 0.05); however, offspring in DMP1 and DMP2 categories produced higher milk as compared with their dams during primiparity (P < 0.05) whereas offspring in DMP3, DMP4 and DMP5 categories produced less milk as compared with their dams during primiparity (P < 0.05). Milk fat to protein ratio during the first month of lactation was greater in DMP4 and DMP5 categories than DMP1 category (P < 0.05). Offspring of DMP4 and DMP5 categories were inseminated and conceived at younger ages than offspring of DMP1 category during nulliparity (P < 0.05). Calving to conception interval was longer in DMP5 than DMP1 category in primiparous offspring (P < 0.05), but concentration of AMH did not differ among various categories of DMP (P > 0.05). In conclusion, dams with greater level of milk production produced heavier offspring with higher milk yield but worse transgenerational improvement in milk production and diminished reproductive performance, which were seemingly under higher pressure of negative energy balance during the first month of lactation.

Genome wide mining of SNPs and INDELs through ddRAD sequencing in Sahiwal cattle

The study was conducted in Sahiwal cattle for genome wide identification and annotation of single nucleotide polymorphisms (SNPs) and insertions and deletions (INDELs) in Sahiwal cattle. The double digest restriction-site associated DNA (ddRAD) sequencing, a reduced representation method was used for the identification of variants at nucleotide level. A total of 1,615,211 variants were identified at RD10 and Q30 consisting of 1,480,930 SNPs and 134,281 INDELs with respect to the Bos taurus reference genome. The SNPs were annotated for their location, impact and functional class. The SNPs identified in Sahiwal cattle were found to be associated with a total of 26,229 genes. A total of 1819 SNPs were annotated for 209 candidate genes associated with different production and reproduction traits. The variants identified in the present study may be useful to strengthen the existing bovine SNP chips for reducing the biasness over the taurine cattle breeds. The diversity analysis provides the insight of the genetic architecture of the Sahiwal population Studied. The large genetic variations identified at the nucleotide level provide ample scope for implementing an effective and efficient breed improvement programme for increasing the productivity of Sahiwal cattle.

Influence of non-genetic factors on first lactation and lifetime performance traits in Nili-Ravi buffaloes

The objective of this research was to evaluate the effects of various non-genetic factors on first lactation and lifetime productivity in Nili-Ravi buffaloes, including season of birth, period of birth, age at first calving, season of first calving, period of first calving, and number of lactations completed. The livestock data on first lactation and lifetime performance traits relevant to 501 Nili-Ravi buffaloes were collected from the history sheet of the animal for a period from 1983 to 2017 (i.e., 35 years) and maintained at the Indian Council of Agricultural Research—Central Institute for Research on Buffaloes (ICAR-CIRB) sub-campus, in Nabha, Punjab, India. To evaluate the least-squares means (LSMs) and the effect of non-genetic factors on performance traits, a least-squares analysis model was applied. The overall LSM for age at first calving (AFC) was 45.03 ± 0.40 months and ranged from 34 to 54 months. The results indicated that the effect of AFC was highly significant (p ≤ 0.01) on first lactation total milk yield (FLTMY), first lactation standard milk yield (305 days or less) (FLSMY), first peak milk yield (FPY), and first lactation length (FLL) in the Nili-Ravi breed of buffaloes. FLTMY, FLSMY, and FPY were highest (2,250.08 ± 48.16 kg, 1,944.68 ± 31.20 kg, and 9.32 ± 0.16 kg/day, respectively) for animals with an AFC of 42–48 months. Furthermore, FLTMY, FLSMY, and FLL were highest (2,411.02 ± 68.68 kg, 2,008.81 ± 44.49 kg, and 357.43 ± 8.13 days, respectively) in animals that first calved in the autumn season. However, the lowest first dry period (FDP), first service period (FSP), and first calving interval (FCI) (110.63 ± 7.42 days, 125.48 ± 9.04 days, and 443.63 ± 9.00 days, respectively) were found for animals that first calved in the rainy season. The overall LSM for herd life (HL), productive life (PL), productive days (PDs), unproductive days (UDs), total lifetime milk yield (total LTMY), standard lifetime milk yield (standard LTMY), milk yield per day of productive life (MY/PL), milk yield per day of productive days (MY/PDs), and milk yield per day of herd life (MY/HL) were estimated as 3,779.84 ± 31.86 days, 2,078.55 ± 24.32 days, 1,552.74 ± 20.06 days, 525.81 ± 12.44 days, 10,229.71 ± 195.31 kg, 9,203.64 ± 173.52 kg, 4.86 ± 0.08 kg/day, 6.46 ± 0.08 kg/day, and 2.66 ± 0.04 kg/day, respectively. The effect of AFC on HL, PDs, UDs, total LTMY, and standard LTMY was highly significant (p ≤ 0.01). Furthermore, the effect of season of first calving on HL, PL, and PDs was significant (p ≤ 0.05). In addition, the effect of the period of first calving on HL, PDs, standard LTMY, and total LTMY was significant (p ≤ 0.05). In these contexts, it can be concluded that the buffaloes of the Nili-Ravi breed with an AFC of 42–48 months performed better than animals with a later AFC in terms of production, reproduction, and lifetime traits.

Association of milk production traits with genetic variants in exon 5 and intron 3 of bovine growth hormone (bGH) gene in Sahiwal cattle

The main objective of this study was to determine the association of production traits with genetic variants in exon 5 and intron 3 of bovine growth hormone (bGH) gene in Sahiwal cattle. The analyses were based on the detection of single nucleotide polymorphisms (SNPs) in GH-AluI (exon 5) and GH-MspI (intron 3) using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay. The frequency of AluI (L/V) and MspI (T/C) alleles were 86.20/13.70 and 89.80/9.50, respectively. The distribution of the frequency of GH genotypes for LL, LV, and VV were 73.4, 25.5, and 1.0 and for TT, TC, and CC genotypes were 80.9, 17.7, and 13.0, respectively. Season of calving had none but period of calving had significant effect on the studied production traits. The phenotypic data was adjusted for non-genetic factors and regression analysis was done. There was detectable significant effect of the GH-AluI and GH-MspI on the analyzed production traits. The cows with LL genotype had significantly higher milk yield traits than the LV genotype. Similarly, the productive performance of the studied cows with TT genotype was also significantly higher than TC and CC genotypes. Results revealed that the Sahiwal cows with LL and TT genotypes of the bGH locus can be considered to be a favourable genotype for production traits, although these findings need to be confirmed by further research before SNPs can be used in a marker assisted selection program by the animal breeder.

Strategic test-day recording regimes to estimate lactation yield in tropical dairy animals

BACKGROUND

In developing dairy sectors, genetic improvement programs have limited resources and recording of herds is minimal. This study evaluated different methods to estimate lactation yield and sampling schedules with fewer test-day records per lactation to determine recording regimes that (1) estimate lactation yield with a minimal impact on the accuracy of selection and (2) optimise the available resources.

METHODS

Using Sahiwal cattle as a tropical dairy breed example, weekly milk records from 464 cows were used in a simulation study to generate different shaped lactation curves. The daily milk yields from these simulated lactation curves were subset to equally spaced (weekly, monthly and quarterly) and unequally spaced (with four, five or six records per lactation) test-day intervals. Lactation yield estimates were calculated from these subsets using two methods: the test-interval method and Wood's (Nature 216:164-165, 1967) lactation curve model. Using the resulting lactation yields, breeding values were predicted and comparisons were made between the sampling regimes and estimation methods.

RESULTS

The results show that, based on the mean square error of prediction, use of Wood's lactation curve model to estimate total yield was more accurate than use of the test-interval method. However, the differences in the ranking of animals were small, i.e. a 1 to 5% difference in accuracy. Comparisons between the different test-day sampling regimes showed that, with the same number of records per lactation (for example, quarterly and four test-days), strategically timed test-days can result in more accurate estimates of lactation yield than test-days at equal intervals.

CONCLUSIONS

An important outcome of these results is that combining Wood's model for lactation yield estimation and as few as four, five or six strategically placed test-day records can produce estimates of lactation yield that are comparable with estimates based on monthly test-day records using the test-interval method. Furthermore, calculations show that although using fewer test-days results in a decrease in the accuracy of selection, it does provide an opportunity to progeny-test more sires. Thus, using strategically timed test-days and Wood's model to estimate lactation yield, can lead to a more efficient use of the allocated resources.

Heterogeneity of variance for milk traits at climitical regions in Holstein dairy cattle in Iran and the best method(s) for data transformation

In this research, heterogeneity of variance components in cattle populations at climatical regions in the first three lactations was studied. The data set included the following: 161328 records of first, 123369 records of second and 81013 records of third lactations, which was collected by Animal Breeding Center of Iran from 1983 to 2004. Records of three lactations were divided in the base of Domarten method. Bartlett test for heterogeneity of variance components was significant among all subgroups. In order to decrease the heterogeneity of variance components, we used several data transformation methods including Logarithmic, Square root and Arc sin transformations. Logarithmic transformation decreased the heterogeneity of variance components in the three lactations and other methods had not effect for removing the heterogeneity in any group. Genetic parameters and heritability were estimated for three lactations by MATVEC program, using animal model. Results showed that the heritability estimates of milk yield were decreased from the first lactation to the third; also the heritability estimates of transformed data were slightly higher than the original data. Comparison between estimated parameters in single trait and two traits analysis, before and after data transformation, showed that there were not significant differences between derived results.