MUC1 gene polymorphism in three Nelore lines selected for growth and its association with growth and carcass traits

The objective of this study was to describe the VNTR polymorphism of the mucin 1 gene (MUC1) in three Nelore lines selected for yearling weight to determine whether allele and genotype frequencies of this polymorphism were affected by selection for growth. In addition, the effects of the polymorphism on growth and carcass traits were evaluated. Birth, weaning and yearling weights, rump height, Longissimus muscle area, backfat thickness, and rump fat thickness, were analyzed. A total of 295 Nelore heifers from the Beef Cattle Research Center, Instituto de Zootecnia de Sert?ozinho, were used, including 41 of the control line, 102 of the selection line and 152 of the traditional. The selection and traditional lines comprise animals selected for higher yearling weight, whereas control line animals are selected for yearling weight close to the average. Five alleles were identified, with allele 1 being the most frequent in the three lines, especially in the lines selected for higher means for yearling weight. Heterozygosity was significantly higher in the control line. Association analyses showed significant effects of allele 1 on birth weight and weaning weight while the allele 3 exert significant effects on yearling weight and back fat thickness. Despite these findings, application of this marker to marker-assisted selection requires more consistent results based on the genotyping of a larger number of animals in order to increase the accuracy of the statistical analyses.     

Genetic correlations between mature cow weight and productive and reproductive traits in Nellore cattle

We investigated genetic associations between mature cow weight (MW) and weaning weight (WW), yearling weight (YW), weight gain from birth to weaning (GBW), weight gain from weaning to yearling (GWY), weaning hip height (WHH), yearling hip height (YHH), scrotal circumference (SC), and age at first calving (AFC). Data from 127,104 Nellore animals born between 1993 and 2006, belonging to Agropecuária Jacarezinho Ltda., were analyzed. (Co)variance components were obtained by the restricted maximum likelihood method, applying an animal model in a multi-traits analysis. The model included direct genetic and residual effects as random effects, the fixed effects of contemporary group, and the linear and quadratic effects of animal age at recording (except for AFC, GBW, and GWY) and age of cow at calving as covariates (except for MW). The numbers of days from birth to weaning and from weaning to yearling were included as covariates for GBW and GWY, respectively. Estimated direct heritabilities were 0.43 ± 0.02 (MW), 0.33 ± 0.01 (WW), 0.36 ± 0.01 (YW), 0.28 ± 0.02 (GBW), 0.31 ± 0.01 (GWY), 0.44 ± 0.02 (WHH), 0.48 ± 0.02 (YHH), 0.44 ± 0.01 (SC), and 0.16 ± 0.03 (AFC). Genetic correlations between MW and productive traits were positive and of medium to high magnitude (ranging from 0.47 ± 0.03 to 0.71 ± 0.01). A positive and low genetic correlation was observed between MW and SC (0.24 ± 0.04). A negative genetic correlation (-0.19 ± 0.03) was estimated between MW and AFC. Selection to increase weight or weight gains at any age, as well as hip height, will change MW in the same direction. Selection for higher SC may lead to a long-term increase in MW. The AFC can be included in selection indices to improve the reproductive performance of beef cattle without significant changes in MW.     

Comparison on genomic predictions using three GBLUP methods and two single-step blending methods in the Nordic Holstein population

Background

A single-step blending approach allows genomic prediction using information of genotyped and non-genotyped animals simultaneously. However, the combined relationship matrix in a single-step method may need to be adjusted because marker-based and pedigree-based relationship matrices may not be on the same scale. The same may apply when a GBLUP model includes both genomic breeding values and residual polygenic effects. The objective of this study was to compare single-step blending methods and GBLUP methods with and without adjustment of the genomic relationship matrix for genomic prediction of 16 traits in the Nordic Holstein population.

Methods

The data consisted of de-regressed proofs (DRP) for 5 214 genotyped and 9 374 non-genotyped bulls. The bulls were divided into a training and a validation population by birth date, October 1, 2001. Five approaches for genomic prediction were used: 1) a simple GBLUP method, 2) a GBLUP method with a polygenic effect, 3) an adjusted GBLUP method with a polygenic effect, 4) a single-step blending method, and 5) an adjusted single-step blending method. In the adjusted GBLUP and single-step methods, the genomic relationship matrix was adjusted for the difference of scale between the genomic and the pedigree relationship matrices. A set of weights on the pedigree relationship matrix (ranging from 0.05 to 0.40) was used to build the combined relationship matrix in the single-step blending method and the GBLUP method with a polygenetic effect.

Results

Averaged over the 16 traits, reliabilities of genomic breeding values predicted using the GBLUP method with a polygenic effect (relative weight of 0.20) were 0.3% higher than reliabilities from the simple GBLUP method (without a polygenic effect). The adjusted single-step blending and original single-step blending methods (relative weight of 0.20) had average reliabilities that were 2.1% and 1.8% higher than the simple GBLUP method, respectively. In addition, the GBLUP method with a polygenic effect led to less bias of genomic predictions than the simple GBLUP method, and both single-step blending methods yielded less bias of predictions than all GBLUP methods.

Conclusions

The single-step blending method is an appealing approach for practical genomic prediction in dairy cattle. Genomic prediction from the single-step blending method can be improved by adjusting the scale of the genomic relationship matrix.     

Alternative parameterizations of relatedness in whole genome association analysis of pre-weaning traits of Nelore-Angus calves

Gestation length, birth weight, and weaning weight of F₂ Nelore-Angus calves (n = 737) with designed extensive full-sibling and half-sibling relatedness were evaluated for association with 34,957 SNP markers. In analyses of birth weight, random relatedness was modeled three ways: 1) none, 2) random animal, pedigree-based relationship matrix, or 3) random animal, genomic relationship matrix. Detected birth weight-SNP associations were 1,200, 735, and 31 for those parameterizations respectively; each additional model refinement removed associations that apparently were a result of the built-in stratification by relatedness. Subsequent analyses of gestation length and weaning weight modeled genomic relatedness; there were 40 and 26 trait-marker associations detected for those traits, respectively. Birth weight associations were on BTA14 except for a single marker on BTA5. Gestation length associations included 37 SNP on BTA21, 2 on BTA27 and one on BTA3. Weaning weight associations were on BTA14 except for a single marker on BTA10. Twenty-one SNP markers on BTA14 were detected in both birth and weaning weight analyses.     

Assessing the Causal Relationship of Maternal Height on Birth Size and Gestational Age at Birth: A Mendelian Randomization Analysis

Background

Observational epidemiological studies indicate that maternal height is associated with gestational age at birth and fetal growth measures (i.e., shorter mothers deliver infants at earlier gestational ages with lower birth weight and birth length). Different mechanisms have been postulated to explain these associations. This study aimed to investigate the casual relationships behind the strong association of maternal height with fetal growth measures (i.e., birth length and birth weight) and gestational age by a Mendelian randomization approach.

Methods and Findings

We conducted a Mendelian randomization analysis using phenotype and genome-wide single nucleotide polymorphism (SNP) data of 3,485 mother/infant pairs from birth cohorts collected from three Nordic countries (Finland, Denmark, and Norway). We constructed a genetic score based on 697 SNPs known to be associated with adult height to index maternal height. To avoid confounding due to genetic sharing between mother and infant, we inferred parental transmission of the height-associated SNPs and utilized the haplotype genetic score derived from nontransmitted alleles as a valid genetic instrument for maternal height. In observational analysis, maternal height was significantly associated with birth length (p = 6.31 × 10⁻⁹), birth weight (p = 2.19 × 10⁻¹⁵), and gestational age (p = 1.51 × 10⁻⁷). Our parental-specific haplotype score association analysis revealed that birth length and birth weight were significantly associated with the maternal transmitted haplotype score as well as the paternal transmitted haplotype score. Their association with the maternal nontransmitted haplotype score was far less significant, indicating a major fetal genetic influence on these fetal growth measures. In contrast, gestational age was significantly associated with the nontransmitted haplotype score (p = 0.0424) and demonstrated a significant (p = 0.0234) causal effect of every 1 cm increase in maternal height resulting in ~0.4 more gestational d. Limitations of this study include potential influences in causal inference by biological pleiotropy, assortative mating, and the nonrandom sampling of study subjects.

Conclusions

Our results demonstrate that the observed association between maternal height and fetal growth measures (i.e., birth length and birth weight) is mainly defined by fetal genetics. In contrast, the association between maternal height and gestational age is more likely to be causal. In addition, our approach that utilizes the genetic score derived from the nontransmitted maternal haplotype as a genetic instrument is a novel extension to the Mendelian randomization methodology in casual inference between parental phenotype (or exposure) and outcomes in offspring.     

Genome-Wide Association for Growth Traits in Canchim Beef Cattle

Studies are being conducted on the applicability of genomic data to improve the accuracy of the selection process in livestock, and genome-wide association studies (GWAS) provide valuable information to enhance the understanding on the genetics of complex traits. The aim of this study was to identify genomic regions and genes that play roles in birth weight (BW), weaning weight adjusted for 210 days of age (WW), and long-yearling weight adjusted for 420 days of age (LYW) in Canchim cattle. GWAS were performed by means of the Generalized Quasi-Likelihood Score (GQLS) method using genotypes from the BovineHD BeadChip and estimated breeding values for BW, WW, and LYW. Data consisted of 285 animals from the Canchim breed and 114 from the MA genetic group (derived from crossings between Charolais sires and ½ Canchim + ½ Zebu dams). After applying a false discovery rate correction at a 10% significance level, a total of 4, 12, and 10 SNPs were significantly associated with BW, WW, and LYW, respectively. These SNPs were surveyed to their corresponding genes or to surrounding genes within a distance of 250 kb. The genes DPP6 (dipeptidyl-peptidase 6) and CLEC3B (C-type lectin domain family 3 member B) were highlighted, considering its functions on the development of the brain and skeletal system, respectively. The GQLS method identified regions on chromosome associated with birth weight, weaning weight, and long-yearling weight in Canchim and MA animals. New candidate regions for body weight traits were detected and some of them have interesting biological functions, of which most have not been previously reported. The observation of QTL reports for body weight traits, covering areas surrounding the genes (SNPs) herein identified provides more evidence for these associations. Future studies targeting these areas could provide further knowledge to uncover the genetic architecture underlying growth traits in Canchim cattle.     

Effect of nutritional flushing on the productivity of Finnish Landrace ewes

In the autumn (October–December), Finnish Landrace ewes aged 1 year (yearling), 4–5 years (mature) and 7–8 years (older) were fed forages with no supplemented (control) or supplemented daily with 150 g (diet 150) or 300 g (diet 300) of concentrates per ewe in order to determine the effect of energy supply to initiate flushing on ewe productivity. Concurrently, in the summer (August–September), yearling and mature ewes were fed 0, 300 or 450 g of concentrates daily for 17 or 34 days. Concentrate supplement prior to and during mating had little effect on the live weight, however mature ewes gained weight in the summer. In the autumn, increasing proportion of concentrate in the diet reduced the length of the mating period in the yearling ewes (P=0.03) however, diet combination had no significant effect of age on conception. In August and early September, flushing did not hasten the onset of estrus and only 25% of the young ewes and 83% of the adult ewes were mated successfully. The flushing diet had no effect on the prolificacy in yearling and older ewes. In contrast, prolificacy and number of lambs weaned increased (P<0.05) for mature ewes on diet 150. In the autumn, there was a significant influence of flushing on the litter weight at birth and live weight gain from birth to weaning for older ewes however, diet 300 and the control were similar. Although litter weight at birth and weaning tended to be higher in the summer for ewes supplemented with concentrate for 34 days, the number of ewes required for a significant influence due to diet and length of flushing combination were not adequate. It was concluded that little is to be gained in lamb production by flushing ewes of the Finnish Landrace breed.     

(Co)Variance components and genetic parameter estimates for growth traits in Moghani sheep

Genetic parameters were estimated for birth weight (BW), weaning weight (WW), yearling weight (YW), average daily gain from birth to weaning (ADG1) and average daily gain from weaning to yearling (ADG2) in Moghani sheep. Maximum number of data was 4237 at birth, but only 1389 records at yearling were investigated. The data was collected from 1995 to 2007 at the Breeding Station of Moghani sheep in Jafarabad, Moghan, Iran. (Co)Variance components and genetic parameters were estimated with different models which including direct effects, with and without maternal additive genetic effects as well as maternal permanent environmental effects using restricted maximum likelihood (REML) method. The most appropriate model for each trait was determined based on likelihood ratio tests and Akaike's Information Criterion (AIC). Maternal effects were important only for pre-weaning traits. Direct heritability estimates for BW, ADG1, WW, ADG2 and YW were 0.07, 0.08, 0.09, 0.09 and 0.17, respectively. Fractions of variance due to maternal permanent environmental effects on phenotypic variance were 0.08 for ADG1. Maternal heritability estimates for BW and WW were 0.18 and 0.06, respectively. Multivariate analysis was performed using the most appropriate models obtained in univariate analysis. Direct genetic correlations among studied traits were positive and ranged from 0.37 for BW–ADG2 to 0.85 for ADG1–YW. Maternal genetic correlation estimate between BW and WW was 0.33. Phenotypic and environmental correlation estimates were generally lower than those of genetic correlation. Low direct heritability estimates imply that mass selection for these traits results in slow genetic gain.     

Genetic parameters and relationships between growth traits and scrotal circumference measured at different ages in Nellore cattle

Records from 106,212 Nellore animals, born between 1998 and 2006, were used to estimate (co)variance components and genetic parameters for birth weight (BW), average weight gains from birth to weaning (GBW), average weight gains from weaning to after yearling (GWAY), weaning hip height (WHH), postweaning hip height (PHH) and scrotal circumferences at 9 (SC9), 12 (SC12) and 15 (SC15) months of age. (Co)variance components were estimated by an animal model using multi-trait analysis. Heritability estimates for BW, GBW, GWAY, WHH, PHH, SC9, SC12 and SC15 were 0.31 ± 0.01; 0.25 ± 0.02; 0.30 ± 0.04; 0.51 ± 0.04; 0.54 ± 0.04; 0.39 ± 0.01; 0.41 ± 0.01 and 0.44 ± 0.02, respectively. Genetic correlations between growth traits ranged from 0.09 ± 0.01 to 0.88 ± 0.01, thereby implying that, at any age, selection to increase average weight gains will also increase stature. Genetic correlations between BW and average weight gains with scrotal circumferences were all positive and moderate (0.15 ± 0.03 to 0.38 ± 0.01). On the other hand, positive and low genetic associations were estimated between hip height and scrotal circumference at different ages (0.09 ± 0.01 to 0.17 ± 0.02). The results of this study pointed out that selection to larger scrotal circumferences in males will promote changes in average weight gains. In order to obtain Nellore cattle with the stature and size suitable for the production system, both weight gain and hip height should be included in a selection index.     

Milk production and composition,and progeny performance in young ewes with high merit for rapid growth and muscle and fat accumulation

In ewe lambs, acceleration of growth and accumulation of both muscle and fat leads to earlier sexual maturity and better reproductive performance. The next stage in the development of this theme is to test whether these aspects of growth in young ewes affect milk production in their first lactation and the growth of their first progeny. We studied 75 young Merino ewes that had known phenotypic values for depth of eye muscle (EMD) and fat (FAT), and known Australian Sheep Breeding Values for post-weaning weight (PWT) and depths of eye muscle (PEMD) and fat (PFAT). They lambed for the first time at 1 year of age. Their lambs were weighed weekly from birth to weaning at 10 weeks to determine live weight gain and weaning weight. Progeny birth weight was positively associated with live weight gain and weaning weight (P<0.001). The PWT of the mothers was positively associated with birth weight (P<0.01), live weight gain and weaning weight of the progeny (P<0.05); however, these progeny traits were not influenced by EMD, FAT, PEMD, PFAT of the mothers (P>0.05). The PWT of the sire was positively associated with live weight gain (P<0.05) and weaning weight of the progeny (P<0.01). At around day 20 postpartum, we measured milk production and milk composition (fat, protein, lactose, total solids). Milk production was influenced positively by birth type (single or twin; P<0.05) and negatively by birth weight (P<0.05), but not by mother phenotype or genotype, sire genotype of the mother or the sex of the progeny (P>0.05). The concentrations of fat, protein, lactose and total solids in the milk were not affected by the phenotype or genotype of the mothers or of the sires of the mothers, or by the sex of the progeny (P>0.05). We conclude that selection of young Merino ewes for better growth, and more rapid accumulation of muscle and fat, will lead to progeny that are heavier at birth, grow faster and are heavier at weaning. Moreover, milk production and composition do not seem to be affected by the genetic merit of the mother for post-weaning live weight or PEMD or PFAT. Therefore, Merino ewes can lamb at 1 year of age without affecting the production objectives of the Merino sheep industry.     

Genetic trends estimation for body weights of Kermani sheep at different ages using multivariate animal models

The objective of the present study was to estimate genetic trends for body weight traits at different ages in Kermani lambs. Data collected from 1993 to 2006 by the Kermani Breeding Station were analyzed. Genetic trends were estimated for birth weight (BW), weaning weight (WW), 6-month weight (6MW), 9-month weight (9MW) and yearling weight (YW). Maximum number of data was 2654 at birth, but only 1124 at yearling. Different appropriate models for investigation of each trait using multivariate analysis were applied. Variance component were estimated using Simplex procedure and breeding values of animals were predicted with Best Linear Unbiased Prediction (BLUP) methodology under multi-trait animal models. Genetic trends of studied traits were estimated by regressing mean of breeding values on birth year. Direct genetic trends were positive and significant for BW (p < 0.05) WW, 6MW, 9MW and YW (p < 0.01) and were 2, 125, 91, 81 and 156 g/year, respectively. Also, maternal trend for BW was positive and highly significant (p < 0.01) and was 3 g/year.     

Genome-Wide Association Studies for Growth and Meat Production Traits in Sheep

Background

Growth and meat production traits are significant economic traits in sheep. The aim of the study is to identify candidate genes affecting growth and meat production traits at genome level with high throughput single nucleotide polymorphisms (SNP) genotyping technologies.

Methodology and Results

Using Illumina OvineSNP50 BeadChip, we performed a GWA study in 329 purebred sheep for 11 growth and meat production traits (birth weight, weaning weight, 6-month weight, eye muscle area, fat thickness, pre-weaning gain, post-weaning gain, daily weight gain, height at withers, chest girth, and shin circumference). After quality control, 319 sheep and 48,198 SNPs were analyzed by TASSEL program in a mixed linear model (MLM). 36 significant SNPs were identified for 7 traits, and 10 of them reached genome-wise significance level for post-weaning gain. Gene annotation was implemented with the latest sheep genome Ovis_aries_v3.1 (released October 2012). More than one-third SNPs (14 out of 36) were located within ovine genes, others were located close to ovine genes (878bp-398,165bp apart). The strongest new finding is 5 genes were thought to be the most crucial candidate genes associated with post-weaning gain: s58995.1 was located within the ovine genes MEF2B and RFXANK, OAR3_84073899.1, OAR3_115712045.1 and OAR9_91721507.1 were located within CAMKMT, TRHDE, and RIPK2 respectively. GRM1, POL, MBD5, UBR2, RPL7 and SMC2 were thought to be the important candidate genes affecting post-weaning gain too. Additionally, 25 genes at chromosome-wise significance level were also forecasted to be the promising genes that influencing sheep growth and meat production traits.

Conclusions

The results will contribute to the similar studies and facilitate the potential utilization of genes involved in growth and meat production traits in sheep in future.     

Effects of non-genetic factors on production traits of Inner Mongolia cashmere goats in China

The effects of age, sex, age of dam, year of production, herd, and type of birth on cashmere weight, fiber diameter, fiber length, body weight at birth, weaning and yearling in goats, were based on 12 years data from an Inner Mongolia Albas cashmere goat stock farm. The year of production had significant influence on cashmere weight, fiber diameter and length, and body weight of yearlings and adult goats. Year had no significant effect on weaning weight. In the yearling, males produced more cashmere and were heavier in body weights at birth, weaning and 1 year of age than the females. Adult males were significantly heavier than adult females in cashmere weight, fiber diameter and length, and body weight. In the yearling, age of dam had a significant effect on cashmere weight, fiber diameter and length, body weights at birth, weaning and 1 year of age. In the adult, age of dam also had a significant effect on fiber diameter and body weight. Dams aged 2–4 years produced offsprings with a higher cashmere production than those at older ages. In the yearling, type of birth had significant effects on body weight at birth, weaning and 1 year of age, and fiber length. The herd-within-year effects were significant for all traits studied whereas sex×year effects were significant for cashmere weight and body weights at birth, weaning and 1 year of age. These results indicate that the estimation of breeding value in a selection scheme for cashmere production would be more precise following adjustment for age structures, age of dam, sex, type of birth, herd and significant interactions.     

Genetic parameters for growth, reproductive and maternal traits in a multibreed meat sheep population

The genetic parameters for growth, reproductive and maternal traits in a multibreed meat sheep population were estimated by applying the Average Information Restricted Maximum Likelihood method to an animal model. Data from a flock supported by the Programa de Melhoramento Genético de Caprinos e Ovinos de Corte (GENECOC) were used. The traits studied included birth weight (BW), weaning weight (WW), slaughter weight (SW), yearling weight (YW), weight gain from birth to weaning (GBW), weight gain from weaning to slaughter (GWS), weight gain from weaning to yearling (GWY), age at first lambing (AFL), lambing interval (LI), gestation length (GL), lambing date (LD - number of days between the start of breeding season and lambing), litter weight at birth (LWB) and litter weight at weaning (LWW). The direct heritabilities were 0.35, 0.81, 0.65, 0.49, 0.20, 0.15 and 0.39 for BW, WW, SW, YW, GBW, GWS and GWY, respectively, and 0.04, 0.06, 0.10, 0.05, 0.15 and 0.11 for AFL, LI, GL, LD, LWB and LWW, respectively. Positive genetic correlations were observed among body weights. In contrast, there was a negative genetic correlation between GBW and GWS (-0.49) and GBW and GWY (-0.56). Positive genetic correlations were observed between AFL and LI, LI and GL, and LWB and LWW. These results indicate a strong maternal influence in this herd and the presence of sufficient genetic variation to allow mass selection for growth traits. Additive effects were of little importance for reproductive traits, and other strategies are necessary to improve the performance of these animals.     

Genome-wide association study of birth weight in sheep

Birth weight is the earliest available growth trait with considerable impacts on lamb survivability and growth performance traits. This study was conducted to perform a genome-wide association study of birth weight in a meat-type sheep. A total of 132 Lori-Bakhtiari sheep were selected based on estimated of breeding values (EBVs) for BW analyses. The selected animals were genotyped using Illumina Ovine SNP50 Bead Chip. After quality control, a total of 41 323 single-nucleotide polymorphisms (SNPs) and 130 sheep were used for subsequent analyses. Plink 1.90 beta software was used for the analyses. Seven SNPs on chromosomes 1, 16, 19 and 22 were detected based on genome-wide unadjusted P-values (P <10⁻⁶), which jointly accounted for 1.2% of total genetic variation. However, based on Bonferroni-adjusted P-values, only three SNPs on chromosome 1 had significant associations with EBVs for birth weight (P <0.05), which jointly explained 0.8% of total genetic variation. A total of seven genes were found in 50 kb intervals from the three significant SNPs on chromosome 1, but only three genes, including RAB6B (a member of RAS oncogene family), Tf serotransferrin and GIGYF2 (a GRB10 interacting GYF protein 2), could be considered as candidate genes for birth weight in future studies. The results of this study may facilitate potential use of the genes involving in growth and production traits for genetic improvement of productivity in sheep.     

Genome-Wide Association Mapping for Identification of Quantitative Trait Loci for Rectal Temperature during Heat Stress in Holstein Cattle

Heat stress compromises production, fertility, and health of dairy cattle. One mitigation strategy is to select individuals that are genetically resistant to heat stress. Most of the negative effects of heat stress on animal performance are a consequence of either physiological adaptations to regulate body temperature or adverse consequences of failure to regulate body temperature. Thus, selection for regulation of body temperature during heat stress could increase thermotolerance. The objective was to perform a genome-wide association study (GWAS) for rectal temperature (RT) during heat stress in lactating Holstein cows and identify SNPs associated with genes that have large effects on RT. Records on afternoon RT where the temperature-humidity index was ≥78.2 were obtained from 4,447 cows sired by 220 bulls, resulting in 1,440 useable genotypes from the Illumina BovineSNP50 BeadChip with 39,759 SNP. For GWAS, 2, 3, 4, 5, and 10 adjacent SNP were averaged to identify consensus genomic regions associated with RT. The largest proportion of SNP variance (0.07 to 0.44%) was explained by markers flanking the region between 28,877,547 and 28,907,154 bp on Bos taurus autosome (BTA) 24. That region is flanked by U1 (28,822,883 to 28,823,043) and NCAD (28,992,666 to 29,241,119). In addition, the SNP at 58,500,249 bp on BTA 16 explained 0.08% and 0.11% of the SNP variance for 2- and 3-SNP analyses, respectively. That contig includes SNORA19, RFWD2 and SCARNA3. Other SNPs associated with RT were located on BTA 16 (close to CEP170 and PLD5), BTA 5 (near SLCO1C1 and PDE3A), BTA 4 (near KBTBD2 and LSM5), and BTA 26 (located in GOT1, a gene implicated in protection from cellular stress). In conclusion, there are QTL for RT in heat-stressed dairy cattle. These SNPs could prove useful in genetic selection and for identification of genes involved in physiological responses to heat stress.     

QTLs associated with dry matter intake,metabolic mid-test weight,growth and feed efficiency have little overlap across 4 beef cattle studies

Background

The identification of genetic markers associated with complex traits that are expensive to record such as feed intake or feed efficiency would allow these traits to be included in selection programs. To identify large-effect QTL, we performed a series of genome-wide association studies and functional analyses using 50 K and 770 K SNP genotypes scored in 5,133 animals from 4 independent beef cattle populations (Cycle VII, Angus, Hereford and Simmental × Angus) with phenotypes for average daily gain, dry matter intake, metabolic mid-test body weight and residual feed intake.

Results

A total of 5, 6, 11 and 10 significant QTL (defined as 1-Mb genome windows with Bonferroni-corrected P-value <0.05) were identified for average daily gain, dry matter intake, metabolic mid-test body weight and residual feed intake, respectively. The identified QTL were population-specific and had little overlap across the 4 populations. The pleiotropic or closely linked QTL on BTA 7 at 23 Mb identified in the Angus population harbours a promising candidate gene ACSL6 (acyl-CoA synthetase long-chain family member 6), and was the largest effect QTL associated with dry matter intake and mid-test body weight explaining 10.39% and 14.25% of the additive genetic variance, respectively. Pleiotropic or closely linked QTL associated with average daily gain and mid-test body weight were detected on BTA 6 at 38 Mb and BTA 7 at 93 Mb confirming previous reports. No QTL for residual feed intake explained more than 2.5% of the additive genetic variance in any population. Marker-based estimates of heritability ranged from 0.21 to 0.49 for residual feed intake across the 4 populations.

Conclusions

This GWAS study, which is the largest performed for feed efficiency and its component traits in beef cattle to date, identified several large-effect QTL that cumulatively explained a significant percentage of additive genetic variance within each population. Differences in the QTL identified among the different populations may be due to differences in power to detect QTL, environmental variation, or differences in the genetic architecture of trait variation among breeds. These results enhance our understanding of the biology of growth, feed intake and utilisation in beef cattle.     

Multi-Trait GWAS and New Candidate Genes Annotation for Growth Curve Parameters in Brahman Cattle

Understanding the genetic architecture of beef cattle growth cannot be limited simply to the genome-wide association study (GWAS) for body weight at any specific ages, but should be extended to a more general purpose by considering the whole growth trajectory over time using a growth curve approach. For such an approach, the parameters that are used to describe growth curves were treated as phenotypes under a GWAS model. Data from 1,255 Brahman cattle that were weighed at birth, 6, 12, 15, 18, and 24 months of age were analyzed. Parameter estimates, such as mature weight (A) and maturity rate (K) from nonlinear models are utilized as substitutes for the original body weights for the GWAS analysis. We chose the best nonlinear model to describe the weight-age data, and the estimated parameters were used as phenotypes in a multi-trait GWAS. Our aims were to identify and characterize associated SNP markers to indicate SNP-derived candidate genes and annotate their function as related to growth processes in beef cattle. The Brody model presented the best goodness of fit, and the heritability values for the parameter estimates for mature weight (A) and maturity rate (K) were 0.23 and 0.32, respectively, proving that these traits can be a feasible alternative when the objective is to change the shape of growth curves within genetic improvement programs. The genetic correlation between A and K was -0.84, indicating that animals with lower mature body weights reached that weight at younger ages. One hundred and sixty seven (167) and two hundred and sixty two (262) significant SNPs were associated with A and K, respectively. The annotated genes closest to the most significant SNPs for A had direct biological functions related to muscle development (RAB28), myogenic induction (BTG1), fetal growth (IL2), and body weights (APEX2); K genes were functionally associated with body weight, body height, average daily gain (TMEM18), and skeletal muscle development (SMN1). Candidate genes emerging from this GWAS may inform the search for causative mutations that could underpin genomic breeding for improved growth rates.     

Association od the DdeI growth hormone gene polymorphism with some performance traits in Polish Large White and Czech Large White x Polish Large White pigs

The genotypes of growth hormone gene polymorphisms (GH-DdeI, GH-MspI, GH-HaeII, GH-ApaI, GH-CfoI) were determined in 78 pigs [Czech Large White sires (CLWsire line) x Polish Large White (PLW) sows, Polish Large White sires x Polish Large White sows], by the PCR-RFLP method. Preliminary studies found only GH DdeI polymorphism to be associated with performance traits. The associations of this polymorphism with growth and carcass traits were investigated. The linear model included the effects of candidate genes, genetic groups, sex and linear covariables of age at slaughter and body weight at weaning. The DdeI polymorphism of the GH gene showed associations with carcass length (P 相似文献   

Genetic and non-genetic parameter estimates for growth traits and Kleiber ratios in Dorper × indigenous sheep

Genetic improvement programme will only be successful when accompanied by a good understanding of the influence of different environmental factors, knowledge of the genetic parameters and the genetic relationships between the traits of interest. This study aimed to evaluate the influence of non-genetic factors on growth traits and Kleiber ratios and to estimate genetic parameters for early growth traits in Dorper × indigenous crossbred sheep. The effects of fixed factors were analysed by the general linear model procedure of statistical analysis system, while the genetic parameters were estimated using a WOMBAT computer program fitted animal model. The overall least-square mean for birth weight (BRW), weaning weight (3MW), six-month weight, nine-month weight, and yearling weight were 3.03 ± 0.02, 14.5 ± 0.18, 20.4 ± 0.26, 24.8 ± 0.31, and 28.3 ± 0.40 kg, respectively. The overall least-square mean for Kleiber ratio from birth to weaning (KR1), weaning to six months, six to nine months and nine months to yearling age were 16.8 ± 0.10, 6.41 ± 0.17, 4.55 ± 0.21 and 3.38 ± 0.20 g/kg of metabolic weight, respectively. The inclusion of maternal genetic effect had a significant influence on BRW, and it explains 20% of the phenotypic variation. The total heritability estimates for BRW, 3MW, birth to weaning average daily weight gain and KR1 were 0.10, 0.14, 0.16 and 0.12, respectively. The phenotypic correlation varied from ?0.11 ± 0.05 to 0.98 ± 0.02, whereas the direct genetic correlation ranged from ?0.32 ± 0.40 to 0.98 ± 0.17. The mean inbreeding coefficient was 0.105% with an annual rate of 0.02%. The heritability estimates for growth traits and Kleiber ratio suggest that slow genetic progress would be expected from the selection. However, the integration of selection with crossbreeding programme can enhance genetic gain. Therefore, selection should be conducted based on breeding values estimated from multiple information sources to increase the selection response.