Associations between Leptin Gene Polymorphisms and Production, Live Weight, Energy Balance, Feed Intake, and Fertility in Holstein Heifers

Abstract

Leptin is a 16-kDa protein synthesized by adipose tissue and is involved in regulation of feed intake, energy balance, fertility, and immune functions. Since evidence of a genetic correlation between start of luteal activity and energy balance, milk yield, and live weights is present, we investigated the association of genetic differences in the bovine leptin gene with these traits. Between 1990 and 1997, a total of 613 Holstein-Friesian heifers of two genetic groups with known pedigree were followed from parturition until d 105 of lactation. During the first 15 wk of lactation live weight, feed intake, and milk yield were measured for 565 cows. The start of luteal activity was set at the first day with a progesterone concentration higher than 3 ng/ml. In addition to the interval between calving and start of luteal activity, analyses were performed for average milk yield, percentage fat, protein, and lactose in milk, dry matter intake, feed intake, energy balance, and live weight over the first 15 wk of lactation. All 613 cows were genotyped for two restricted fragment length polymorphisms and for the BM1500 microsatellite, all located at the leptin gene locus. Significances of the genotype effects were estimated using the approximated F-statistic provided by ASREML. Fixed effects were year-season, genetic group, and a quadratic polynomial for age at calving. Animal was fitted as a random effect including the additive relationship between animals to account for background genes. Firstly, each genotype effect was fitted in turn, and secondly the other restriction fragment length polymorphisms were fitted as a cofactor to take into account effects of linkage disequilibrium. Thirdly, sire x genotype interaction was investigated. Heifers with the RFLP1-AB genotype produce 1.32 kg/d more milk and consume 0.73 kg/d more food compared with the RFLP1-AA genotype. No effects were found for start of luteal activity. When linkage disequilibrium with the other markers was taken into account and DMI was included as fixed effect in the model a 0.96 kg/d higher milk yield was still found. Assuming that no pleiotropic effects on traits such as immunity and milk production in later lactations exist, future breeding programs favoring the RFLP1 B-allele can yield a higher milk production without negatively affecting energy balance and fertility. The prospects are good because in this study the frequency of the RFLP1 AB- and BB-genotypes were only 18.5 and 0.2%, respectively.

ANXA9, SLC27A3, FABP3 and FABP4 single nucleotide polymorphisms in relation to milk production traitsin Jersey cows

“…PIT-1). Statistically significant associations between polymorphisms in these genes and milk production traits have been found (Kamiński et al, 2002;Liefers et al, 2002;Zwierzchowski et al, 2002;Maj et al, 2004;Kulig, 2005). Other genes of interest in this area include genes encoding enzymes which participate in fatty acid metabolism as well as genes encoding fatty acid binding and transport proteins (Hradecká et al, 2008).…”

Effect of dietary energy source on energy balance, production, metabolic disorders and reproduction in lactating dairy cattle

“…A status of NEB decreases LH pulse frequency, growth rate and diameter of the dominant follicle, weight of the corpus luteum (CL), peri-estrous hormone concentrations like estradiol (E2) and progesterone (P4) [11,24,25,[36][37][38][39]. In addition, NEB has been related to more days till the first observed estrus postpartum (pp) [12,16,40], more days till first ovulation [8,11,22,32], more days open pp [41], decreased conception rates following artificial insemination [14,21,25,41] and lower pregnancy rates [15].…”

Genome-wide associations for feed utilisation complex in primiparous Holstein–Friesian dairy cows from experimental research herds in four European countries

“…Few studies have looked at the individual gene level for explaining genetic variation in feed intake. Examples are leptin, growth hormone or DGAT1 (Liefers et al, 2002;Liefers et al, 2005;Banos et al, 2008;Oikonomou et al, 2009), but the recent availability of fast-throughput genotyping platforms with dense genome-wide markers has reduced the cost of genotyping considerably, making whole-genome association studies a viable alternative. Potentially, functional processes and (quantitative trait loci) QTL that underlie the genetic variation in the feed utilisation complex might be identified.…”