Identification of polymorphisms influencing feed intake and efficiency in beef cattle

Feed efficiency is an economically important trait in beef cattle. Net feed efficiency, measured as residual feed intake (RFI), is the difference between actual feed intake and the predicted feed intake required for maintenance and gain of the animal. SNPs that show associations with RFI may be useful quantitative trait nucleotides for marker-assisted selection. This study identified associations between SNPs underlying five RFI QTL on five bovine chromosomes (BTA2, 5, 10, 20 and 29) with measures of dry matter intake (DMI), RFI and feed conversion ratio (FCR) in beef cattle. Six SNPs were found to have effects on RFI (P < 0.05). The largest single SNP allele substitution effect for RFI was -0.25 kg/day located on BTA2. The combined effects of the SNPs found significant in this experiment explained 6.9% of the phenotypic variation of RFI. Not all the RFI SNPs showed associations with DMI and FCR even though these traits are highly correlated with RFI (r = 0.77 and r = 0.62 respectively). This shows that these SNPs may be affecting the underlying biological mechanisms of feed efficiency beyond feed intake control and weight gain efficiency. These SNPs can be used in marker-assisted selection but first it will be important to verify these effects in independent populations of cattle.     

Genetic parameters for performance,feed efficiency,and carcass traits in Senepol heifers

Improving feed efficiency is a key breeding goal in the beef cattle industry. In this study, we estimated the genetic parameters for feed efficiency and carcass traits in Senepol cattle raised in tropical regions. Various indicators of feed efficiency [gain to feed ratio (G:F), feed conversion ratio (FCR), residual weight gain (RG), residual intake and body weight gain (RIG), and residual feed intake (RFI)] as well as growth [final BW, average daily gain (ADG), and DM intake (DMI)], and carcass [rib-eye area (REA), backfat thickness (BF), intramuscular fat score, and carcass conformation score] traits were included in the study. After data editing, records from 1 393 heifers obtained between 2009 and 2018 were used for the analyses. We fitted an animal model that included contemporary group (animals from the same farm that were evaluated in the same test season) as the fixed effect, and a linear effect of animal age at the beginning of the test as a covariate; in addition to random direct additive genetic and residual effects. The (co)variance components were estimated by Bayesian inference in uni- and bivariate analyses. Our results showed that feed efficiency indicators derived from residual variables such as RG, RIG, and RFI can be improved through genetic selection (h² = 0.14 ± 0.06, 0.13 ± 0.06, and 0.20 ± 0.08, respectively). Variables calculated as ratios such as G:F and FCR were more influenced by environmental factors (h² = 0.08 ± 0.05 and 0.09 ± 0.05), and were, therefore, less suitable for use in breeding programs. The traits with the greatest and impact on genetic progress in feed efficiency were ADG, REA, and BF. The traits with the greatest and least impact on growth and carcass traits were RG and RFI, respectively. Selection for feed efficiency will result in distinct overall effects on the growth and carcass traits of Senepol heifers. Direct selection for lower RFI may reduce DMI and increase carcass fatness at the finishing stage, but it might also result in reduced growth and muscle deposition. Residual BW gain is associated with the highest weight gain and zero impact on REA and BF, however, it is linked to higher feed consumption. Thus, the most suitable feed efficiency indicator was RIG, as it promoted the greatest decrease in feed intake concomitant with faster growth, with a similar impact on carcass traits when compared to the other feed efficiency indicators.     

Invited review: Improving feed efficiency of beef cattle – the current state of the art and future challenges

Improvements in feed efficiency of beef cattle have the potential to increase producer profitability and simultaneously lower the environmental footprint of beef production. Although there are many different approaches to measuring feed efficiency, residual feed intake (RFI) has increasingly become the measure of choice. Defined as the difference between an animal’s actual and predicted feed intake (based on weight and growth), RFI is conceptually independent of growth and body size. In addition, other measurable traits related to energy expenditure such as estimates of body composition can be included in the calculation of RFI to also force independence from these traits. Feed efficiency is a multifactorial and complex trait in beef cattle and inter-animal variation stems from the interaction of many biological processes influenced, in turn, by physiological status and management regimen. Thus, the purpose of this review was to summarise and interpret current published knowledge and provide insight into research areas worthy of further investigation. Indeed, where sufficient suitable reports exist, meta-analyses were conducted in order to mitigate ambiguity between studies in particular. We have identified a paucity of information on the contribution of key biological processes, including appetite regulation, post-ruminal nutrient absorption, and cellular energetics and metabolism to the efficiency of feed utilisation in cattle. In addition, insufficient information exists on the relationship between RFI status and productivity-related traits at pasture, a concept critical to the overall lifecycle of beef production systems. Overall, published data on the effect of RFI status on both terminal and maternal traits, coupled with the moderate repeatability and heritability of the trait, suggest that breeding for improved RFI, as part of a multi-trait selection index, is both possible and cumulative, with benefits evident throughout the production cycle. Although the advent of genomic selection, with associated improved prediction accuracy, will expedite the introgression of elite genetics for feed efficiency within beef cattle populations, there are challenges associated with this approach which may, in the long-term, be overcome by increased international collaborative effort but, in the short term, will not obviate the on-going requirement for accurate measurement of the primary phenotype.     

The genetic parameters of feed efficiency and its component traits in the turkey (Meleagris gallopavo)

Residual feed intake (RFI) and feed conversion ratio (FCR) can be incorporated into a breeding program as traits to select for feed efficiency. Alternatively, the direct measures used to calculate RFI and FCR can be analyzed to determine the underlying variation in the traits that impact overall efficiency. These constituent traits can then be appropriately weighted in an index to achieve genetic gain. To investigate feed efficiency in the turkey, feed intake and weight gain were measured on male primary breeder line turkeys housed in individual feeding cages from 15 to 19 weeks of age. The FCR and RFI showed moderate heritability values of 0.16 and 0.21, respectively. Feed intake, body weight, and weight gain were also moderately heritable (0.25, 0.35, and 0.18, respectively). Weight gain was negatively correlated to feed conversion ratio and was not genetically correlated to RFI. Body weight had a small and positive genetic correlation to RFI (0.09) and FCR (0.12). Feed intake was positively genetically correlated to RFI (0.62); however, there was no genetic correlation between feed intake and FCR. These estimates of heritability and the genetic correlations can be used in the development of an index to improve feed efficiency and reduce the cost of production.     

Impact of including growth,carcass and feed efficiency traits in the breeding goal for combined milk and beef production systems

Improving feed efficiency in dairy cattle could result in more profitable and environmentally sustainable dairy production through lowering feed costs and emissions from dairy farming. In addition, beef production based on dairy herds generates fewer greenhouse gas emissions per unit of meat output than beef production from suckler cow systems. Different scenarios were used to assess the profitability of adding traits, excluded from the current selection index for Finnish Ayrshire, to the breeding goal for combined dairy and beef production systems. The additional breeding goal traits were growth traits (average daily gain of animals in the fattening and rearing periods), carcass traits (fat covering, fleshiness and dressing percentage), mature live weight (LW) of cows and residual feed intake (RFI) traits. A breeding scheme was modeled for Finnish Ayrshire under the current market situation in Finland using the deterministic simulation software ZPLAN+. With the economic values derived for the current production system, the inclusion of growth and carcass traits, while preventing LW increase generated the highest improvement in the discounted profit of the breeding program (3.7%), followed by the scenario where all additional traits were included simultaneously (5.1%). The use of a selection index that included growth and carcass traits excluding LW, increased the profit (0.8%), but reduced the benefits resulted from breeding for beef traits together with LW. A moderate decrease in the profit of the breeding program was obtained when adding only LW to the breeding goal (−3.1%), whereas, adding only RFI traits to the breeding goal resulted in a minor increase in the profit (1.4%). Including beef traits with LW in the breeding goal showed to be the most potential option to improve the profitability of the combined dairy and beef production systems and would also enable a higher rate of self-sufficiency in beef. When considering feed efficiency related traits, the inclusion of LW traits in the breeding goal that includes growth and carcass traits could be more profitable than the inclusion of RFI, because the marginal costs of measuring LW can be expected to be lower than for RFI and it is readily available for selection. In addition, before RFI can be implemented as a breeding objective, the genetic correlations between RFI and other breeding goal traits estimated for the studied population as well as information on the most suitable indicator traits for RFI are needed to assess more carefully the consequences of selecting for RFI.     

Invited review: Improving feed efficiency in dairy production: challenges and possibilities

Despite substantial advances in milk production efficiency of dairy cattle over the last 50 years, rising feed costs remain a significant threat to producer profitability. There also is a greater emphasis being placed on reducing the negative impacts of dairy production on the environment; thus means to lower greenhouse gas (GHG) emissions and nutrient losses to the environment associated with cattle production are being sought. Improving feed efficiency among dairy cattle herds offers an opportunity to address both of these issues for the dairy industry. However, the best means to assess feed efficiency and make genetic progress in efficiency-related traits among lactating cows without negatively impacting other economically important traits is not entirely obvious. In this review, multiple measurements of feed efficiency for lactating cows are described, as well as the heritability of the traits and their genetic and phenotypic correlations with other production traits. The measure of feed efficiency, residual feed intake is discussed in detail in terms of the benefits for its selection, how it could be assessed in large commercial populations, as well as biological mechanisms contributing to its variation among cows, as it has become a commonly used method to estimate efficiency in the recent scientific literature.     

Genetic and phenotypic correlations among feed efficiency,production and selected conformation traits in dairy cows

The difficulties and costs of measuring individual feed intake in dairy cattle are the primary factors limiting the genetic study of feed intake and utilisation, and hence the potential of their subsequent industry-wide applications. However, indirect selection based on heritable, easily measurable, and genetically correlated traits, such as conformation traits, may be an alternative approach to improve feed efficiency. The aim of this study was to estimate genetic and phenotypic correlations among feed intake, production, and feed efficiency traits (particularly residual feed intake; RFI) with routinely recorded conformation traits. A total of 496 repeated records from 260 Holstein dairy cows in different lactations (260, 159 and 77 from first, second and third lactation, respectively) were considered in this study. Individual daily feed intake and monthly BW and body condition scores of these animals were recorded from 5 to 305 days in milk within each lactation from June 2007 to July 2013. Milk yield and composition data of all animals within each lactation were retrieved, and the first lactation conformation traits for primiparous animals were extracted from databases. Individual RFI over 301 days was estimated using linear regression of total 301 days actual energy intake on a total of 301 days estimated traits of metabolic BW, milk production energy requirement, and empty BW change. Pair-wise bivariate animal models were used to estimate genetic and phenotypic parameters among the studied traits. Estimated heritabilities of total intake and production traits ranged from 0.27±0.07 for lactation actual energy intake to 0.45±0.08 for average body condition score over 301 days of the lactation period. RFI showed a moderate heritability estimate (0.20±0.03) and non-significant phenotypic and genetic correlations with lactation 3.5 % fat-corrected milk and average BW over lactation. Among the conformation traits, dairy strength, stature, rear attachment width, chest width and pin width had significant (P<0.05) moderate to strong genetic correlations with RFI. Combinations of these conformation traits could be used as RFI indicators in the dairy genetic improvement programmes to increase the accuracy of the genetic evaluation of feed intake and utilisation included in the index.     

Water requirements of beef production can be reduced by genetic selection

Growing concerns regarding sustainability in agriculture include the availability of drinking water, which is putting pressure on livestock production, especially the beef sector, for more efficient practices. Thus, genetic parameters were estimated for traits related to water intake and water use efficiency in Senepol cattle. Senepol females (n = 925) and males (n = 191) were evaluated in performance tests carried out from 2014 to 2019. Daily dry matter intake (DMI) and water intake (WI) were recorded by electronic feed and water bunks (Intergado Ltd.). Other traits assessed included average daily gain (ADG); mid-test metabolic BW (BW^0.75); residual water intake based on ADG (RWI_ADG), estimated as the residual of the linear regression equation of WI on ADG and BW^0.75; residual water intake based on DMI (RWI_DMI), estimated as the residual of the linear regression equation of WI on DMI and BW^0.75 (RWI_DMI); water conversion ratio (= WI/ADG); gross water efficiency (GWE = ADG/WI); residual feed intake estimated as the residual of the linear regression equation of DMI on ADG and BW^0.75 (RFI); feed conversion ratio (= DMI/ADG) and gross feed efficiency. Genetic (co)variances were estimated with bivariate analyses. The heritabilities for WI, RWI_ADG and RWI_DMI were 0.38, 0.36 and 0.33, respectively. Water conversion ratio, RWI_ADG and RWI_DMI showed positive genetic and phenotypic correlations with WI, whereas GWE was negatively correlated with WI, suggesting that traits related to water use efficiency may be useful to identify cattle with reduced WI. Water intake showed positive genetic (r = 0.79) and phenotypic (r = 0.60) correlations with DMI, suggesting the use of WI to estimate DMI in future studies. Both RWI_ADG and RWI_DMI were genetically correlated with RFI (0.67 and 0.57, respectively) and ADG (0.49 and 0.44, respectively), showing that RWI is positively associated with feed efficiency, but has an antagonistic relationship with growth. This antagonism, however, may be managed using selection indexes. Genetic improvement of water use efficiency in Senepol cattle is possible through selection and may reduce the water requirements of beef production systems.     

Expression of candidate genes for residual feed intake in Angus cattle

Residual feed intake (RFI) has been adopted in Australia for the purpose of genetic improvement in feed efficiency in beef cattle. RFI is the difference between the observed feed intake of an animal and the predicted feed intake based on its size and growth rate over a test period. Gene expression of eight candidate genes (AHSG, GHR, GSTM1, INHBA, PCDH19, S100A10, SERPINI2 and SOD3), previously identified as differentially expressed between divergent lines of high‐ and low‐RFI animals, was measured in an unselected population of 60 steers from the Angus Society Elite Progeny Test Program using quantitative real‐time PCR. Results showed that the levels of gene expression were significantly correlated with RFI. The genes explain around 33.2% of the phenotypic variance in RFI, and prediction equations using the expression data are reasonably accurate estimators of RFI. The association of these genes with economically important traits, such as other feed efficiency‐related traits and fat, growth and carcass traits, was investigated as well. The expression of these candidate genes was significantly correlated with feed conversion ratio and daily feed intake, which are highly associated with RFI, suggesting a functional role for these genes in modulating feed utilisation. The expression of these genes did not show any association with average daily gain, eye muscle area and carcass composition.     

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.     

Systems Biology Analysis Merging Phenotype,Metabolomic and Genomic Data Identifies Non-SMC Condensin I Complex,Subunit G (NCAPG) and Cellular Maintenance Processes as Major Contributors to Genetic Variability in Bovine Feed Efficiency

Feed efficiency is a paramount factor for livestock economy. Previous studies had indicated a substantial heritability of several feed efficiency traits. In our study, we investigated the genetic background of residual feed intake, a commonly used parameter of feed efficiency, in a cattle resource population generated from crossing dairy and beef cattle. Starting from a whole genome association analysis, we subsequently performed combined phenotype-metabolome-genome analysis taking a systems biology approach by inferring gene networks based on partial correlation and information theory approaches. Our data about biological processes enriched with genes from the feed efficiency network suggest that genetic variation in feed efficiency is driven by genetic modulation of basic processes relevant to general cellular functions. When looking at the predicted upstream regulators from the feed efficiency network, the Tumor Protein P53 (TP53) and Transforming Growth Factor beta 1 (TGFB1) genes stood out regarding significance of overlap and number of target molecules in the data set. These results further support the hypothesis that TP53 is a major upstream regulator for genetic variation of feed efficiency. Furthermore, our data revealed a significant effect of both, the Non-SMC Condensin I Complex, Subunit G (NCAPG) I442M (rs109570900) and the Growth /differentiation factor 8 (GDF8) Q204X (rs110344317) loci, on residual feed intake and feed conversion. For both loci, the growth promoting allele at the onset of puberty was associated with a negative, but favorable effect on residual feed intake. The elevated energy demand for increased growth triggered by the NCAPG 442M allele is obviously not fully compensated for by an increased efficiency in converting feed into body tissue. As a consequence, the individuals carrying the NCAPG 442M allele had an additional demand for energy uptake that is reflected by the association of the allele with increased daily energy intake as observed in our study.     

Genetic parameters for feed efficiency in Romane rams and responses to single-generation selection

Feeding costs represent one of the highest expenditures in animal production systems. Breeding efficient animals that express their growth potential while eating less is therefore a major objective for breeders. We estimated the genetic parameters for feed intake, feed efficiency traits (residual feed intake (RFI) and feed conversion ratio (FCR)), growth and body composition traits in the Romane meat sheep breed. In these traits, selection responses to single-generation divergent selection on RFI were evaluated. From 2009 to 2016, a total of 951 male lambs were tested for 8 weeks starting from 3 months of age. They were weighed at the beginning and at the end of the testing period. Backfat thickness and muscle depth were recorded at the end of the testing period through ultrasound measurements. Feed intake was continuously recorded over the testing period using the automatic concentrate feeders. The heritability of RFI was estimated at 0.45 ± 0.08, which was higher than the heritability of FCR (0.30 ± 0.08). No significant genetic correlations were observed between RFI and growth traits. A favourable low negative genetic correlation was estimated between RFI and muscle depth (−0.30 ± 0.15), though additional data are needed to confirm these results. The selection of low RFI sires based on their breeding values led to the production of lambs eating significantly less concentrate (3% decrease in the average daily feed intake), but with the same growth as lambs from sires selected based on high RFI breeding values. We concluded that in meat sheep, RFI is a heritable trait that is genetically independent of post-weaning growth and body composition traits. A one-generation divergent selection based on RFI breeding values highlighted that substantial gains in feeding costs can be expected in selection schemes for meat sheep breeds.     

Genomic selection for feed efficiency in dairy cattle

Feed is a major component of variable costs associated with dairy systems and is therefore an important consideration for breeding objectives. As a result, measures of feed efficiency are becoming popular traits for genetic analyses. Already, several countries account for feed efficiency in their breeding objectives by approximating the amount of energy required for milk production, maintenance, etc. However, variation in actual feed intake is currently not captured in dairy selection objectives, although this could be possible by evaluating traits such as residual feed intake (RFI), defined as the difference between actual and predicted feed (or energy) intake. As feed intake is expensive to accurately measure on large numbers of cows, phenotypes derived from it are obvious candidates for genomic selection provided that: (1) the trait is heritable; (2) the reliability of genomic predictions are acceptable to those using the breeding values; and (3) if breeding values are estimated for heifers, rather than cows then the heifer and cow traits need to be correlated. The accuracy of genomic prediction of dry matter intake (DMI) and RFI has been estimated to be around 0.4 in beef and dairy cattle studies. There are opportunities to increase the accuracy of prediction, for example, pooling data from three research herds (in Australia and Europe) has been shown to increase the accuracy of genomic prediction of DMI from 0.33 within country to 0.35 using a three-country reference population. Before including RFI as a selection objective, genetic correlations with other traits need to be estimated. Weak unfavourable genetic correlations between RFI and fertility have been published. This could be because RFI is mathematically similar to the calculation of energy balance and failure to account for mobilisation of body reserves correctly may result in selection for a trait that is similar to selecting for reduced (or negative) energy balance. So, if RFI is to become a selection objective, then including it in an overall multi-trait selection index where the breeding objective is net profit is sensible, as this would allow genetic correlations with other traits to be properly accounted for. If genetic parameters are accurately estimated then RFI is a logical breeding objective. If there is uncertainty in these, then DMI may be preferable.     

A region on BTA14 that includes the positional candidate genes LYPLA1, XKR4 and TMEM68 is associated with feed intake and growth phenotypes in cattle(1)

Feed cost for beef cattle is the largest expense incurred by cattle producers. The development of genetic markers to enhance selection of more efficient animals that require less feed while still achieving acceptable levels of production has the potential to substantially reduce production costs. A genome‐wide marker association approach based on the Illumina BovineSNP50 BeadChip? was used to identify genomic regions affecting average daily feed intake (ADFI), average daily gain (ADG) and residual feed intake traits in a population of 1159 crossbred steers. This approach identified a region on BTA14 from 22.02 to 23.92 Mb containing several single‐nucleotide polymorphisms (SNPs) that have significant association with at least one of the traits. Two genes in this region, lysophospholipase 1 (LYPLA1) and transmembrane protein 68 (TMEM68), appeared to be logical positional and functional candidate genes. LYPLA1 deacylates ghrelin, a hormone involved in the regulation of appetite in the rat stomach, while TMEM68 is expressed in bovine rumen, abomasum, intestine and adipose tissue in cattle, and likely affects lipid biosynthetic processes. SNPs lying in or near these two genes were identified by sequencing a subset of animals with extreme phenotypes. A total of 55 SNPs were genotyped and tested for association with the same population of steers. After correction for multiple testing, five markers within 22.79–22.84 Mb, located downstream of TMEM68, and between TMEM68 and the neighbouring gene XKR4, were significant for both ADFI and ADG. Genetic markers predictive of feed intake and weight gain phenotypes in this population of cattle may be useful for the identification and selection of animals that consume less feed, although further evaluation of these markers for effects on other production traits and validation in additional populations will be required.     

Serum metabolites associated with feed efficiency in black angus steers

Introduction

Improving feed utilization in cattle is required to reduce input costs, increase production, and ultimately improve sustainability of the beef cattle industry. Characterizing metabolic differences between efficient and non-efficient animals will allow stakeholders to identify more efficient cattle during backgrounding.

Objectives

This study used an untargeted metabolomics approach to determine differences in serum metabolites between animals of low and high residual feed intake.

Methods

Residual feed intake was determined for 50 purebred Angus steers and 29 steers were selected for the study steers based on low versus high feed efficiency. Blood samples were collected from steers and analyzed using untargeted metabolomics via mass spectrometry. Metabolite data was analyzed using Metaboanalyst, visualized using orthogonal partial least squares discriminant analysis, and p-values derived from permutation testing. Non-esterified fatty acids, urea nitrogen, and glucose were measured using commercially available calorimetric assay kits. Differences in metabolites measured were grouped by residual feed intake was measured using one-way analysis of variance in SAS 9.4.

Results

Four metabolites were found to be associated with differences in feed efficiency. No differences were found in other serum metabolites, including serum urea nitrogen, non-esterified fatty acids, and glucose.

Conclusions

Four metabolites that differed between low and high residual feed intake have important functions related to nutrient utilization, among other functions, in cattle. This information will allow identification of more efficient steers during backgrounding.

     

肉牛剩余采食量相关瘤胃及粪便微生物特征比较分析

本试验旨在研究不同剩余采食量（residual feed intake, RFI）相关肉牛胃肠道微生物物种组成及相对丰度、微生物基因功能注释与富集特征。选取30头牛进行81 d饲喂试验,试验结束后选取极端RFI个体各5头屠宰并采集瘤胃液及肠道末端粪便样用于宏基因组测序。结果表明：共获得259 045.47 Mb有效数据,组装得到 4 318 393条Scaftigs,基因预测得到7 008 053个开放阅读框（ORFs）。进行物种注释后发现粪便样中Top10物种相对丰度在高剩余采食量（high residual feed intake, HRFI）、低剩余采食量（low residual feed intake, LRFI）组间无差异（P>0.05）,瘤胃液中的Top10微生物在LRFI组的相对丰度均低于HRFI组;粪便中、瘤胃液中优势菌门均为拟杆菌门和厚壁菌门;粪便中的优势属为拟杆菌属,瘤胃液中的优势属为普雷沃菌属。LefSe分析显示,在粪便中LRFI组的丹毒丝菌纲（Erysipelotrichia）显著富集（P<0.05）,瘤胃液中差异最显著的是甲烷杆菌纲（Methanobacteria）,且该菌在HRFI组的相对丰度显著高于LRFI组（P<0.05）。使用KEGG、eggNOG和CAZy数据库进行功能注释分析表明,在胃肠道中微生物的一些功能基因的丰度与RFI的分组有关。不同RFI肉牛瘤胃液、粪便中的微生物结构存在显著差异,丹毒丝菌纲、甲烷杆菌纲可能是区分肉牛饲料效率的潜在生物标志物之一。     

Genome-wide association study of economically important traits in Charolais and Limousin beef cows

Genomic selection has proven effective for advancing genetic gain for key profit traits in dairy cattle production systems. However, its impact to-date on genetic improvement programs for beef cattle has been less effective. Despite this, the technology is thought to be particularly useful for low heritability traits such as those associated with reproductive efficiency. The objective of this study was to identify genetic variants associated with key determinants of reproductive and overall productive efficiency in beef cows. The analysis employed a large dataset derived from the national genetic evaluation program in Ireland for two of the most predominant beef breeds, viz. Charolais (n = 5 244 cows) and Limousin (n = 7 304 cows). Single nucleotide polymorphisms (SNPs) were identified as being statistically significantly associated (adj. P < 0.05) with both reproductive and productive traits for both breed types. However, there was little across breed commonality, with only two SNPs (rs110240246 and rs110344317; adj. P < 0.05) located within the genomic regions of the LCORL and MSTN genes respectively, identified in both Charolais and Limousin populations, associated with traits including carcass weight, cull-cow weight and live-weight. Significant SNPs within the MSTN gene were also associated with both reproduction and production related traits within each breed. Finally, traits including calving difficulty, calf mortality and calving interval were associated with SNPs within genomic regions comprising genes involved in cellular growth and lipid metabolism. Genetic variants identified as associated with both important reproductive efficiency and production related traits from this study warrant further analyses for their potential incorporation into breeding programmes to support the sustainability of beef cattle production.     

Assessment of residual body weight gain and residual intake and body weight gain as feed efficiency traits in the turkey (Meleagris gallopavo)

Background

Since feed represents 70% of the total cost in poultry production systems, an animal’s ability to convert feed is an important trait. In this study, residual feed intake (RFI) and residual body weight gain (RG), and their linear combination into residual feed intake and body weight gain (RIG) were studied to estimate their genetic parameters and analyze the potential differences in feed intake between the top ranked birds based on the criteria for each trait.

Methods

Phenotypic and genetic analyses were completed on 8340 growing tom turkeys that were measured for feed intake and body weight gain over a four-week period from 16 to 20 weeks of age.

Results

The heritabilities of RG and RIG were 0.19 ± 0.03 and 0.23 ± 0.03, respectively. Residual body weight gain had moderate genetic correlations with feed intake (−0.41) and body weight gain (0.43). All three linear combinations to form the RIG traits had genetic correlations ranging from −0.62 to −0.52 with feed intake, and slightly weaker, 0.22 to 0.34, with body weight gain. Sorted into three equal groups (low, medium, high) based on RG, the most efficient group (high) gained 0.62 and 1.70 kg more (P < 0.001) body weight than that of the medium and low groups, yet the feed intake for the high group was less (P < 0.05) than that of the medium group (19.52 vs. 19.75 kg). When separated into similar partitions, the high RIG group (most efficient) had both the lowest (P < 0.001) feed intake (18.86 vs. 19.57 and 20.41 kg) and the highest (P < 0.001) body weight gain (7.41 vs. 7.03 and 6.43 kg) relative to the medium and low groups, respectively.

Conclusions

The difference in feed intake between the top ranked birds based on different residual feed efficiency traits may be small when looking at the average individual, however, when extrapolated to the production level, the lower feed intake values could lead to significant savings in feed costs over time.