Use of methane production data for genetic prediction in beef cattle: A review.

Methane (CH4) is a greenhouse gas that is produced and emitted from ruminant animals through enteric fermentation. Methane production from cattle has an environmental impact and is an energetic inefficiency. In the beef industry, CH4 production from enteric fermentation impacts all three pillars of sustainability: environmental, social, and economic. A variety of factors influence the quantity of CH4 produced during enteric fermentation, including characteristics of the rumen and feed composition. There are several methodologies available to either quantify or estimate CH4 production from cattle, all with distinct advantages and disadvantages. Methodologies include respiration calorimetry, the sulfur-hexafluoride tracer technique, infrared spectroscopy, prediction models, and the GreenFeed system. Published studies assess the accuracy of the various methodologies and compare estimates from different methods. There are advantages and disadvantages of each technology as they relate to the use of these phenotypes in genetic evaluation systems. Heritability and variance components of CH4 production have been estimated using the different CH4 quantification methods. Agreement in both the amounts of CH4 emitted and heritability estimates of CH4 emissions between various measurement methodologies varies in the literature. Using greenhouse gas traits in selection indices along with relevant output traits could provide producers with a tool to make selection decisions on environmental sustainability while also considering productivity. The objective of this review was to discuss factors that influence CH4 production, methods to quantify CH4 production for genetic evaluation, and genetic parameters of CH4 production in beef cattle.

Heritability and variance component estimation for feed and water intake behaviors of feedlot cattle.

Feed and water intake are two important aspects of cattle production that greatly impact the profitability, efficiency, and sustainability of producers. Feed and, to a lesser degree, water intake have been studied previously; however, there is little research on their associated animal behaviors and there is a lack of standardized phenotypes for these behaviors. Feed and water intakes obtained with an Insentec system (Hokofarm Group, The Netherlands) from 830 crossbred steers were used to compute five intake behaviors for both feed and water: daily sessions (DS), intake rate (IR), session size (SS), time per session (TS), and session interval (SI). Variance components and heritabilities were estimated for each trait. Heritabilities for feed intake behaviors were 0.50 ±â€…0.12, 0.63 ±â€…0.12, 0.40 ±â€…0.13, 0.35 ±â€…0.12, and 0.60 ±â€…0.12 for DS, IR, SS, TS, and SI, respectively. Heritabilities for water intake behaviors were 0.56 ±â€…0.11, 0.88 ±â€…0.07, 0.70 ±â€…0.11, 0.54 ±â€…0.12, and 0.80 ±â€…0.10 for NS, IR, SS, TS, and SI, respectively. Daily dry matter intake (DDMI) and daily water intake (DWI) had heritabilities of 0.57 ±â€…0.11 and 0.44 ±â€…0.11. Phenotypic correlations varied between pairs of traits (-0.83 to 0.82). Genetic correlations between DDMI and feed intake behaviors were moderate to high, while genetic correlations between DWI and water intake behaviors were low to moderate. Several significant single nucleotide polymorphisms (SNP) were identified for the feed and water intake behaviors. Genes and previously reported quantitative trait loci near significant SNPs were evaluated. The results indicated that feed and water intake behaviors are influenced by genetic factors and are heritable, providing one additional route to evaluate or manipulate feed and water intake.

Feed and water intake are important aspects of cattle production to understand because they impact producer profitability and sustainability. While feed intake and, to a lesser degree, water intake have previously been studied, the associated feeding and drinking behaviors are relatively unknown and lack standardized phenotypes. Using individual animal feed and water intake records, five behaviors were evaluated for feed and water intake from crossbred feedlot steers. The behaviors evaluated were daily sessions (no./d), session size (kg), time per session (s), intake rate (g/s), and session interval (min). The impact of season (winter vs. summer) and bunk management (ad libitum vs. slick) on feeding and drinking behaviors was evaluated. Heritability and variance components were estimated for all feeding and drinking behaviors. Pairwise phenotypic correlations between behaviors were discussed. The relationship between intake and feeding or drinking behaviors was evaluated with genetic correlations. A genome-wide association study identified several significant single nucleotide polymorphisms for feeding and drinking behaviors. The results indicate that feeding and drinking behaviors are heritable and may be one additional route to evaluate feed and water intake.

Variance component estimation and genome-wide association of predicted methane production in crossbred beef steers.

Enteric methane is a potent greenhouse gas and represents an escape of energy from the ruminant digestive system. Additive genetic variation in methane production suggests that genetic selection offers an opportunity to diminish enteric methane emissions. Logistic and monetary difficulties in directly measuring methane emissions can make genetic evaluation on an indicator trait such as predicted methane production a more appealing option, and inclusion of genotyping data can result in greater genetic progress. Three predicted methane production traits were calculated for 830 crossbred steers fed in seven groups. The methane prediction equations used included mathematical models from Ellis et al. (2007), Mills et al. (2003), and IPCC (2019). Pearson correlations between the traits were all greater than 0.99, indicating that each prediction equation behaved similarly. Further, the Spearman correlations between the estimated breeding values for each trait were also 0.99, which suggests any of the predicted methane models could be used without substantially changing the ranking of the selection candidates. The heritabilities of Ellis, Mills, and IPCC predicted methane production were 0.60, 0.62, and 0.59, respectively. A genome-wide association study identified one single nucleotide polymorphism (SNP) that reached the threshold for significance for all of the traits on chromosome 7 related to oxidoreductase activity. Additionally, the SNP slightly below the significance threshold indicate genes related to collagen, intracellular microtubules, and DNA transcription may play a role in predicted methane production or its component traits.

Cattle produce methane, a greenhouse gas, as a byproduct of their digestion. It is possible to breed for animals which naturally produce less methane; however, measuring animals for methane production can be difficult or expensive and is required for effective selection. Therefore, an alternative solution is to use a mathematical model to predict methane production and select for animals with low predicted methane. The heritability of predicted methane production from each model ranged from 0.59 to 0.62. Animals were ranked nearly identical, regardless of model used. A genome-wide association study was also conducted to determine what loci may be related to predicted methane production. One significant locus was identified on chromosome 7 related to oxidoreductase activity. Other loci approaching significance showed that genes related to collagen production, intracellular microtubule binding, and DNA transcription may be related to predicted methane production. In particular, collagen turnover may have a relationship to predicted methane because it affects growth rate, which is driven by dry matter intake, which, in turn, is the primary driver of predicted methane production.

Characterization of the number of spot samples required for quantification of gas fluxes and metabolic heat production from grazing beef cows using a GreenFeed.

Enteric fermentation from cattle results in greenhouse gas production that is an environmental concern and also an energetic loss. Several methods exist to quantify gas fluxes; however, an open circuit gas quantification system (OCGQS) allows for unencumbered quantification of methane (CH4), carbon dioxide (CO2), and oxygen (O2) from grazing cattle. While previous literature has proven the accuracy of an OCGQS, little work has been done to establish the minimum number of spot samples required to best evaluate an individual grazing animal's gas fluxes and metabolic heat production. A GreenFeed system (C-Lock Inc.) was used to collect at least 100 spot samples each from 17 grazing cows. The mean gas fluxes and metabolic heat production were computed starting from the first 10 visits (forward) and increasing by increments of 10 until an animal had 100 visits. Mean gas fluxes and metabolic heat production were also computed starting from visit 100 (reverse) in increments of 10 using the same approach. Pearson and Spearman correlations were computed between the full 100 visits and each shortened visit interval. A large increase in correlations were seen between 30 and 40 visits. Thus, mean forward and reverse gas fluxes and metabolic heat production were also computed starting at 30 visits and increasing by 2 until 40 visits. The minimum number of spot samples was determined when correlations with the full 100 visits were greater than 0.95. The results indicated that the minimum numbers of spot samples needed for accurate quantification of CH4, CO2, and O2 gas fluxes are 38, 40, and 40, respectively. Metabolic heat production can be calculated using gas fluxes collected by the OCGQS with 36 spot samples. Practically, calculation of metabolic heat production will require 40 spot samples because the component gases for metabolic heat calculation require up to 40 spot samples. Published literature from nongrazing (confined) environments recommended a similar number of total spot samples. Large variation existed around the average number of spot samples for an animal per day, therefore a wide range of test durations may be needed to meet the same number of spot samples in different populations. For this reason, protocols for the OCGQS should be based on the total number of spot samples, rather than a test duration.

Enteric fermentation in ruminant livestock species produces methane (CH4), which has negative effects on the environment and producer profitability. Gas fluxes from livestock species can be quantified with an open-circuit gas quantification system (OCGQS) or GreenFeed (C-Lock Inc., Rapid City, SD). However, little work has been done to establish a standardized protocol for OCGQS use in grazing beef cows. The minimum number of spot samples for quantification of CH4, carbon dioxide (CO2), oxygen (O2), and metabolic heat production was determined for grazing beef cows. The minimum number of spot samples needed for accurate quantification of CH4 was 38. Forty spot samples were needed to quantify CO2 and O2. Metabolic heat production can be calculated using CH4, CO2, and O2 gas fluxes from the OCGQS with 36 spot samples. Approximately 30 d were needed for animals in the current study to obtain the recommended number of visits for gas quantification, but this could vary across studies depending on the frequency of animals visiting the unit. There was large variability in the duration needed to obtain the recommended number of spot samples. Therefore, OCGQS protocols should include a minimum number of spot samples rather than a test duration.

Effects of diet on feed intake, weight change, and gas emissions in beef cows.

The objective of this study was to examine the effects of diet energy density on ranking for dry matter intake (DMI), residual feed intake (RFI), and greenhouse gas emissions. Forty-two mature, gestating Angus cows (600 ± 69 kg body weight [BW]; body condition score [BCS] 5.3 ± 1.1) with a wide range in DMI expected progeny difference (-1.38 to 2.91) were randomly assigned to two diet sequences; forage then concentrate (FC) or concentrate then forage (CF). The forage diet consisted of long-stem native grass hay plus protein supplement (HAY; 1.96 Mcal ME/kg DM). The concentrate diet consisted of 35% chopped grass hay and 65% concentrate feeds on a dry matter basis (MIX; 2.5 Mcal ME/kg DM). The GreenFeed Emission Monitoring system was used to determine carbon dioxide (CO2), oxygen (O2), and methane (CH4) flux. Cow performance traits, ultrasound back fat and rump fat, feed DMI, and gas flux data were analyzed in a crossover design using a mixed model including diet, period, and sequence as fixed effects and pen and cow within sequence as random effects. For all measured traits excluding DMI, there was a diet × sequence interaction (P < 0.05). The correlation between MIX and HAY DMI was 0.41 (P = 0.067) and 0.47 (P = 0.03) for FC and CF sequences, respectively. There was no relationship (P > 0.66) between HAY and MIX average daily gain (ADG), regardless of sequence. Fifty-seven percent of the variation in DMI was explained by metabolic BW, ADG, and BCS for both diets during the first period. During the second period, the same three explanatory variables accounted for 38% and 37% of the variation in DMI for MIX and HAY diets, respectively. The negative relationship between BCS and DMI was more pronounced when cows consumed the MIX diet. There was no relationship between MIX and HAY RFI, regardless of sequence (P > 0.18). During the first period, correlations for CO2, CH4, and O2 with MIX DMI were 0.69, 0.81, and 0.56 (P ≤ 0.015), respectively, and 0.76, 0.74, and 0.64 (P < 0.01) with HAY DMI. During the second period, correlations for CO2, CH4, and O2 with MIX DMI were 0.62, 0.47, and 0.56 (P ≤ 0.11), respectively. However, HAY DMI during the second period was not related to gas flux (P > 0.47). Results from this experiment indicate that feed intake of two energy-diverse diets is moderately correlated while ADG while consuming the two diets is not related. Further experimentation is necessary to determine if gas flux data can be used to predict feed intake in beef cows.

The beef cow utilizes about 74% of total feed energy required to produce beef. Therefore, a more thorough understanding of feed intake, weight gain, and feed efficiency traits in the beef cow is fundamental to reducing cost and improving the environmental footprint of beef production. In this experiment, feed intake, weight gain, and greenhouse gas emissions were studied using a crossover design (two study periods) and two diets diverse in energy density and physical characteristics; hay or a hay/concentrate mixed diet. Feed intake of the hay diet was moderately, positively correlated to feed intake when cows consumed the mixed diet. However, there was no correlation in weight gain when cows consumed hay compared to weight gain when cows consumed the mixed diet. There was generally a strong correlation between feed intake and greenhouse gas emissions during the first feeding period. However, there was no correlation between greenhouse gas fluxes and feed intake when cows consumed hay after they had first received the mixed diet. Further research is necessary to determine if greenhouse gas flux data can be used as a reliable proxy for feed intake in beef cows.

Genetic parameter estimates for feet and leg traits in Red Angus cattle.

The objective of this study was to estimate genetic parameters for feet and leg traits, relationships within feet and leg traits, and relationships between feet and leg traits and production traits in Red Angus cattle. Subjective scores for 14 traits including body condition score (BCS), front hoof angle (FHA), front heel depth (FHD), front claw shape (FCS), rear hoof angle (RHA), rear heel depth (RHD), rear claw shape (RCS), size of hoof (SIZE), front side view (FSV), knee orientation (KNEE), front hoof orientation (FHO), rear side view (RSV), rear view (RV), and a composite score (COMP) were collected by trained evaluators on 1,720 Red Angus cattle. All traits except COMP were scored as intermediate optimum traits. Performance data, and EPD were obtained on all animals measured and a three-generation pedigree was obtained from the Red Angus Association of America (RAAA) that contained 13,306 animals. Data were modeled using a linear bivariate animal model with random additive genetic and residual effects, and fixed effects of age and contemporary group (herd-year) implemented in ASREML 4.0. Heritability estimates of BCS, FHA, FHD, FCS, RHA, RHD, RCS, SIZE, FSV, KNEE, FHO, RSV, RV, and COMP were 0.11, 0.20, 0.17, 0.09, 0.19, 0.25, 0.17, 0.36, 0.16, 0.17, 0.17, 0.30, 0.14, and 0.12, respectively. These results demonstrate feet and leg traits are lowly to moderately heritable. Strong, positive genetic correlations were observed between FHA and FHD (0.89), FHA and RHA (0.88), FHD and RHA (0.85), FHA and RHD (0.85), FHD and RHD (0.94), and FHO and KNEE (0.95), indicating these traits were highly related to each other. Strong and negative genetic correlations were observed between KNEE and FSV (-0.59) and FHO and FSV (-0.75). The strongest Pearson correlation between front limb traits (FHA, FHD, FSV, FHO, KNEE, and COMP) and Stayability EPD (STAY) was FSV (r = 0.16) and for rear limb traits (RHA, RHD, RCS, RSV, RV, and COMP) and STAY was RCS (r = -0.12). This suggests cattle with more slope to the angle of the shoulder and cattle with less evidence of hoof curl may stay in the herd longer. Further investigation into the economic viability of feet and leg trait genetic prediction with a larger population of animals is required to help validate these findings.

Genetic parameter estimation for beef bull semen attributes.

Improvements in bull reproductive performance are necessary to optimize the efficiency of cattle production. Female fertility has been enhanced through assisted reproductive technologies as well as genetic selection; however, improving beef bull fertility has been largely ignored. Phenotypes routinely collected at bull semen collection facilities are believed to affect fertility and provide the phenotypes necessary for a genetic evaluation. The first objective of this study was to determine the significant fixed effects for modeling beef bull fertility using data from bull semen collection facilities. The second objective was to estimate variance components, heritabilities, repeatabilities, and correlations between beef bull semen attributes. Beef bull fertility phenotypes including volume (VOL), concentration (CONC), number of spermatozoa (NSP), initial motility (IMot), post-thaw motility (PTMot), 3-h post-thaw motility (3HRPTMot), percentage of normal spermatozoa (%NORM), primary abnormalities (PRIM), and secondary abnormalities (SEC) were obtained from two bull semen collection facilities. A total of 1,819 Angus bulls with 50,624 collection records were analyzed. Of the fixed class and covariate effects tested, the significant class effects were collection location and collection day within year and the significant covariate effects included age at collection, days since previous collection, and cumulative comprehensive climate index (CCI). For this study, the CCI was calculated for a 75-d period including the 61-d spermatogenesis cycle and 14-d epididymal transit time. The 75 d prior to collection accounted for the environmental stress a bull may have experienced over the course of development of the spermatozoa, which was more significant than the CCI calculated for collection day or spermatogenesis start date. Pre-thaw beef bull semen traits had low heritability estimates of 0.11 ± 0.02 (VOL), 0.09 ± 0.02 (CONC), 0.08 ± 0.02 (NSP), and 0.12 ± 0.03 (IMot). Heritabilities of post-thaw beef bull semen attributes were more variable at 0.10 ± 0.02 (PTMot), 0.05 ± 0.04 (3HRPTMot), 0.10 ± 0.04 (%NORM), 0.03 ± 0.03 (PRIM), and 0.18 ± 0.04 (SEC). Correlations of breeding values for these traits with scrotal circumference (SC) expected progeny difference (EPD) are low. The low to moderate heritability estimates indicate that genetic improvement can be made in beef bull semen quality traits if new tools are developed to augment the scrotal circumference EPD that are currently available within the industry.

Selection for bull fertility: a review.

Fertility is a critically important factor in cattle production because it directly relates to the ability to produce the offspring necessary to offset costs in production systems. Female fertility has received much attention and has been enhanced through assisted reproductive technologies, as well as genetic selection; however, improving bull fertility has been largely ignored. Improvements in bull reproductive performance are necessary to optimize the efficiency of cattle production. Selection and management to improve bull fertility not only have the potential to increase conception rates but also have the capacity to improve other economically relevant production traits. Bull fertility has reportedly been genetically correlated with traits such as average daily gain, heifer pregnancy, and calving interval. Published studies show that bull fertility traits are low to moderately heritable, indicating that improvements in bull fertility can be realized through selection. Although female fertility has continued to progress according to increasing conception rates, the reported correlation between male and female fertility is low, indicating that male fertility cannot be improved by selection for female fertility. Correlations between several bull fertility traits, such as concentration, number of spermatozoa, motility, and number of spermatozoa abnormalities, vary among studies. Using male fertility traits in selection indices would provide producers with more advanced selection tools. The objective of this review was to discuss current beef bull fertility measurements and to discuss the future of genetic evaluation of beef bull fertility and potential genetic improvement strategies.

Characterization of water intake and water efficiency in beef cattle1,2.

In the future, water may not be as readily available due to increases in competition from a growing human population, wildlife, and other agricultural sectors, making selection for water efficiency of beef cattle increasingly important. Substantial selection emphasis has recently been placed on feed efficiency in an effort to reduce production costs, but no emphasis has been placed on making cattle more water efficient due to lack of data. Thus, the objective of this study was to calculate water efficiency metrics for cattle and evaluate their relationship to growth, feed intake (FI), and feed efficiency. Individual daily FI and water intake (WI) records were collected on 578 crossbred steers over a 70-d test period. Animals with low water intake ate less feed, had lower gains, and were more water efficient (as defined by water to gain ratio, W/G, and residual water intake, RWI). However, the amount of water consumed by animals had minimal phenotypic relationship with feed efficiency (residual feed intake [RFI], R2 = 0.1050 and feed to gain ratio (F/G) ratio R2 = 0.0726). Cattle that had low DMI consumed less water, had lower gains, had lower RFI, and had higher F/G. The level of feed consumed had minimal relationship with water efficiency. WI, W/G, RWI, and ADG had moderate heritability estimates of 0.39, 0.39, 0.37, and 0.37, respectively. High heritability estimates were observed for DMI and RFI (0.67 and 0.65, respectively). Feed to gain had a low heritability estimate of 0.16. WI had a strong positive genetic correlation with W/G (0.99) and RWI (0.88), thus selecting for decreased WI should also make cattle more water efficient. The genetic correlation between WI and ADG was 0.05; thus, selecting for low WI cattle should have little effect on growth. There is a low to moderate genetic correlation between WI and DMI (0.34). RWI has a positive genetic correlation with W/G ratio (0.89) and F/G ratio (0.42) and is negatively genetically correlated with RFI (-0.57). Water to gain and F/G had a strong positive genetic correlation (0.68). RFI has a positive genetic correlation with W/G ratio (0.37) and F/G (0.88). Minimal antagonisms seem to be present between WI and ADG, although it should be noted that standard errors were large and often not significantly different from zero due to the small sample size. However, care should be taken to ensure that unintended changes do not occur in DMI or other production traits and incorporation of WI into a selection index would likely prove to be the most effective method for selection.

Environmental effects on water intake and water intake prediction in growing beef cattle.

Water is an essential nutrient, but there are few recent studies that evaluate how much water individual beef cattle consume and how environmental factors affect an individual's water intake (WI). Most studies have focused on WI of whole pens rather than WI of individual animals. Thus, the objective of this study was to evaluate the impact of environmental parameters on individual-animal WI across different seasons and develop prediction equations to estimate WI, including within different environments and management protocols. Individual daily feed intake and WI records were collected on 579 crossbred steers for a 70-d period following a 21-d acclimation period for feed and water bunk training. Steers were fed in 5 separate groups over a 3-yr period from May 2014 to March 2017. Individual weights were collected every 14 d and weather data were retrieved from the Oklahoma Mesonet's Stillwater station. Differences in WI as a percent of body weight (WI%) were analyzed accounting for average temperature (TAVG), relative humidity (HAVG), solar radiation (SRAD), and wind speed (WSPD). Seasonal (summer vs. winter) and management differences (ad libitum vs. slick bunk) were examined. Regression analysis was utilized to generate 5 WI prediction equations (overall, summer, winter, slick, and ad libitum). There were significant (P < 0.05) differences in WI between all groups when no environmental parameters were included in the model. Although performance was more similar after accounting for all differences in weather variables, significant (P < 0.05) seasonal and feed management differences were still observed for WI%, but were less than 0.75% of steer body weight. The best linear predictors of daily WI (DWI) were dry mater intake (DMI), metabolic body weights (MWTS), TAVG, SRAD, HAVG, and WSPD. Slight differences in the coefficient of determinations for the various models were observed for the summer (0.34), winter (0.39), ad libitum (0.385), slick bunk (0.41), and overall models (0.40). Based on the moderate R2 values for the WI prediction equations, individual DWI can be predicted with reasonable accuracy based on the environmental conditions that are present, MWTS, and DMI consumed, but substantial variation exists in individual animal WI that is not accounted for by these models.

Test duration for water intake, ADG, and DMI in beef cattle.

Water is an essential nutrient, but the effect it has on performance generally receives little attention. There are few systems and guidelines for collection of water intake (WI) phenotypes in beef cattle, which makes large-scale research on WI a challenge. The Beef Improvement Federation has established guidelines for feed intake (FI) and ADG tests, but no guidelines exist for WI. The goal of this study was to determine the test duration necessary for collection of accurate WI phenotypes. To facilitate this goal, individual daily WI and FI records were collected on 578 crossbred steers for a total of 70 d using an Insentec system at the Oklahoma State University Willard Sparks Beef Research Unit. Steers were fed in five groups and were individually weighed every 14 d. Within each group, steers were blocked by BW (low and high) and randomly assigned to one of four pens containing approximately 30 steers per pen. Each pen provided 103.0 m2 of shade and included an Insentec system containing six feed bunks and one water bunk. Steers were fed a constant diet across groups and DMI was calculated using the average of weekly percent DM within group. Average FI and WI for each animal were computed for increasingly large test durations (7, 14, 21, 28, 35, 42, 49, 56, 63, and 70 d), and ADG was calculated using a regression formed from BW taken every 14 d (0, 14, 28, 42, 56, and 70 d). Intervals for all traits were computed starting from both the beginning (day 0) and the end of the testing period (day 70). Pearson and Spearman correlations were computed for phenotypes from each shortened test period and for the full 70-d test. Minimum test duration was determined when the Pearson correlations were greater than 0.95 for each trait. Our results indicated that minimum test duration for WI, DMI, and ADG were 35, 42, and 70 d, respectively. No comparable studies exist for WI; however, our results for FI and ADG are consistent with those in the literature. Although further testing in other populations of cattle and areas of the country should take place, our results suggest that WI phenotypes can be collected concurrently with DMI, without extending test duration, even if following procedures for decoupled intake and gain tests.

Comparison of Bayesian models to estimate direct genomic values in multi-breed commercial beef cattle.

BACKGROUND: While several studies have examined the accuracy of direct genomic breeding values (DGV) within and across purebred cattle populations, the accuracy of DGV in crossbred or multi-breed cattle populations has been less well examined. Interest in the use of genomic tools for both selection and management has increased within the hybrid seedstock and commercial cattle sectors and research is needed to determine their efficacy. We predicted DGV for six traits using training populations of various sizes and alternative Bayesian models for a population of 3240 crossbred animals. Our objective was to compare alternate models with different assumptions regarding the distributions of single nucleotide polymorphism (SNP) effects to determine the optimal model for enhancing feasibility of multi-breed DGV prediction for the commercial beef industry. RESULTS: Realized accuracies ranged from 0.40 to 0.78. Randomly assigning 60 to 70% of animals to training (n ≈ 2000 records) yielded DGV accuracies with the smallest coefficients of variation. Mixture models (BayesB95, BayesCπ) and models that allow SNP effects to be sampled from distributions with unequal variances (BayesA, BayesB95) were advantageous for traits that appear or are known to be influenced by large-effect genes. For other traits, models differed little in prediction accuracy (~0.3 to 0.6%), suggesting that they are mainly controlled by small-effect loci. CONCLUSIONS: The proportion (60 to 70%) of data allocated to training that optimized DGV accuracy and minimized the coefficient of variation of accuracy was similar to large dairy populations. Larger effects were estimated for some SNPs using BayesA and BayesB95 models because they allow unequal SNP variances. This substantially increased DGV accuracy for Warner-Bratzler Shear Force, for which large-effect quantitative trait loci (QTL) are known, while no loss in accuracy was observed for traits that appear to follow the infinitesimal model. Large decreases in accuracy (up to 0.07) occurred when SNPs that presumably tag large-effect QTL were over-regressed towards the mean in BayesC0 analyses. The DGV accuracies achieved here indicate that genomic selection has predictive utility in the commercial beef industry and that using models that reflect the genomic architecture of the trait can have predictive advantages in multi-breed populations.

Multiple polyploidy events in the early radiation of nodulating and nonnodulating legumes.

Unresolved questions about evolution of the large and diverse legume family include the timing of polyploidy (whole-genome duplication; WGDs) relative to the origin of the major lineages within the Fabaceae and to the origin of symbiotic nitrogen fixation. Previous work has established that a WGD affects most lineages in the Papilionoideae and occurred sometime after the divergence of the papilionoid and mimosoid clades, but the exact timing has been unknown. The history of WGD has also not been established for legume lineages outside the Papilionoideae. We investigated the presence and timing of WGDs in the legumes by querying thousands of phylogenetic trees constructed from transcriptome and genome data from 20 diverse legumes and 17 outgroup species. The timing of duplications in the gene trees indicates that the papilionoid WGD occurred in the common ancestor of all papilionoids. The earliest diverging lineages of the Papilionoideae include both nodulating taxa, such as the genistoids (e.g., lupin), dalbergioids (e.g., peanut), phaseoloids (e.g., beans), and galegoids (=Hologalegina, e.g., clovers), and clades with nonnodulating taxa including Xanthocercis and Cladrastis (evaluated in this study). We also found evidence for several independent WGDs near the base of other major legume lineages, including the Mimosoideae-Cassiinae-Caesalpinieae (MCC), Detarieae, and Cercideae clades. Nodulation is found in the MCC and papilionoid clades, both of which experienced ancestral WGDs. However, there are numerous nonnodulating lineages in both clades, making it unclear whether the phylogenetic distribution of nodulation is due to independent gains or a single origin followed by multiple losses.

Paralogous radiations of PIN proteins with multiple origins of noncanonical PIN structure.

The plant hormone auxin is a conserved regulator of development which has been implicated in the generation of morphological novelty. PIN-FORMED1 (PIN) auxin efflux carriers are central to auxin function by regulating its distribution. PIN family members have divergent structures and cellular localizations, but the origin and evolutionary significance of this variation is unresolved. To characterize PIN family evolution, we have undertaken phylogenetic and structural analyses with a massive increase in taxon sampling over previous studies. Our phylogeny shows that following the divergence of the bryophyte and lycophyte lineages, two deep duplication events gave rise to three distinct lineages of PIN proteins in euphyllophytes. Subsequent independent radiations within each of these lineages were taxonomically asymmetric, giving rise to at least 21 clades of PIN proteins, of which 15 are revealed here for the first time. Although most PIN protein clades share a conserved canonical structure with a modular central loop domain, a small number of noncanonical clades dispersed across the phylogeny have highly divergent protein structure. We propose that PIN proteins underwent sub- and neofunctionalization with substantial modification to protein structure throughout plant evolution. Our results have important implications for plant evolution as they suggest that structurally divergent PIN proteins that arose in paralogous radiations contributed to the convergent evolution of organ systems in different land plant lineages.

Worldwide patterns of ancestry, divergence, and admixture in domesticated cattle.

The domestication and development of cattle has considerably impacted human societies, but the histories of cattle breeds and populations have been poorly understood especially for African, Asian, and American breeds. Using genotypes from 43,043 autosomal single nucleotide polymorphism markers scored in 1,543 animals, we evaluate the population structure of 134 domesticated bovid breeds. Regardless of the analytical method or sample subset, the three major groups of Asian indicine, Eurasian taurine, and African taurine were consistently observed. Patterns of geographic dispersal resulting from co-migration with humans and exportation are recognizable in phylogenetic networks. All analytical methods reveal patterns of hybridization which occurred after divergence. Using 19 breeds, we map the cline of indicine introgression into Africa. We infer that African taurine possess a large portion of wild African auroch ancestry, causing their divergence from Eurasian taurine. We detect exportation patterns in Asia and identify a cline of Eurasian taurine/indicine hybridization in Asia. We also identify the influence of species other than Bos taurus taurus and B. t. indicus in the formation of Asian breeds. We detect the pronounced influence of Shorthorn cattle in the formation of European breeds. Iberian and Italian cattle possess introgression from African taurine. American Criollo cattle originate from Iberia, and not directly from Africa with African ancestry inherited via Iberian ancestors. Indicine introgression into American cattle occurred in the Americas, and not Europe. We argue that cattle migration, movement and trading followed by admixture have been important forces in shaping modern bovine genomic variation.

Data access for the 1,000 Plants (1KP) project.

The 1,000 plants (1KP) project is an international multi-disciplinary consortium that has generated transcriptome data from over 1,000 plant species, with exemplars for all of the major lineages across the Viridiplantae (green plants) clade. Here, we describe how to access the data used in a phylogenomics analysis of the first 85 species, and how to visualize our gene and species trees. Users can develop computational pipelines to analyse these data, in conjunction with data of their own that they can upload. Computationally estimated protein-protein interactions and biochemical pathways can be visualized at another site. Finally, we comment on our future plans and how they fit within this scalable system for the dissemination, visualization, and analysis of large multi-species data sets.

Cyclotide discovery in Gentianales revisited--identification and characterization of cyclic cystine-knot peptides and their phylogenetic distribution in Rubiaceae plants.

Cyclotides are a unique class of ribosomally synthesized cysteine-rich miniproteins characterized by a head-to-tail cyclized backbone and three conserved disulfide-bonds in a knotted arrangement. Originally they were discovered in the coffee-family plant Oldenlandia affinis (Rubiaceae) and have since been identified in several species of the violet, cucurbit, pea, potato, and grass families. However, the identification of novel cyclotide-containing plant species still is a major challenge due to the lack of a rapid and accurate analytical workflow in particular for large sampling numbers. As a consequence, their phylogeny in the plant kingdom remains unclear. To gain further insight into the distribution and evolution of plant cyclotides, we analyzed ∼300 species of >40 different families, with special emphasis on plants from the order Gentianales. For this purpose, we have developed a refined screening methodology combining chemical analysis of plant extracts and bioinformatic analysis of transcript databases. Using mass spectrometry and transcriptome-mining, we identified nine novel cyclotide-containing species and their related cyclotide precursor genes in the tribe Palicoureeae. The characterization of novel peptide sequences underlines the high variability and plasticity of the cyclotide framework, and a comparison of novel precursor proteins from Carapichea ipecacuanha illustrated their typical cyclotide gene architectures. Phylogenetic analysis of their distribution within the Psychotria alliance revealed cyclotides to be restricted to Palicourea, Margaritopsis, Notopleura, Carapichea, Chassalia, and Geophila. In line with previous reports, our findings confirm cyclotides to be one of the largest peptide families within the plant kingdom and suggest that their total number may exceed tens of thousands.

Detection of selective sweeps in cattle using genome-wide SNP data.

BACKGROUND: The domestication and subsequent selection by humans to create breeds and biological types of cattle undoubtedly altered the patterning of variation within their genomes. Strong selection to fix advantageous large-effect mutations underlying domesticability, breed characteristics or productivity created selective sweeps in which variation was lost in the chromosomal region flanking the selected allele. Selective sweeps have now been identified in the genomes of many animal species including humans, dogs, horses, and chickens. Here, we attempt to identify and characterise regions of the bovine genome that have been subjected to selective sweeps. RESULTS: Two datasets were used for the discovery and validation of selective sweeps via the fixation of alleles at a series of contiguous SNP loci. BovineSNP50 data were used to identify 28 putative sweep regions among 14 diverse cattle breeds. Affymetrix BOS 1 prescreening assay data for five breeds were used to identify 85 regions and validate 5 regions identified using the BovineSNP50 data. Many genes are located within these regions and the lack of sequence data for the analysed breeds precludes the nomination of selected genes or variants and limits the prediction of the selected phenotypes. However, phenotypes that we predict to have historically been under strong selection include horned-polled, coat colour, stature, ear morphology, and behaviour. CONCLUSIONS: The bias towards common SNPs in the design of the BovineSNP50 assay led to the identification of recent selective sweeps associated with breed formation and common to only a small number of breeds rather than ancient events associated with domestication which could potentially be common to all European taurines. The limited SNP density, or marker resolution, of the BovineSNP50 assay significantly impacted the rate of false discovery of selective sweeps, however, we found sweeps in common between breeds which were confirmed using an ultra-high-density assay scored in a small number of animals from a subset of the breeds. No sweep regions were shared between indicine and taurine breeds reflecting their divergent selection histories and the very different environmental habitats to which these sub-species have adapted.

Accurate mass-time tag library for LC/MS-based metabolite profiling of medicinal plants.

We report the development and testing of an accurate mass-time (AMT) tag approach for the LC/MS-based identification of plant natural products (PNPs) in complex extracts. An AMT tag library was developed for approximately 500 PNPs with diverse chemical structures, detected in electrospray and atmospheric pressure chemical ionization modes (both positive and negative polarities). In addition, to enable peak annotations with high confidence, MS/MS spectra were acquired with three different fragmentation energies. The LC/MS and MS/MS data sets were integrated into online spectral search tools and repositories (Spektraris and MassBank), thus allowing users to interrogate their own data sets for the potential presence of PNPs. The utility of the AMT tag library approach is demonstrated by the detection and annotation of active principles in 27 different medicinal plant species with diverse chemical constituents.

Accuracy of direct genomic breeding values for nationally evaluated traits in US Limousin and Simmental beef cattle.

BACKGROUND: In national evaluations, direct genomic breeding values can be considered as correlated traits to those for which phenotypes are available for traditional estimation of breeding values. For this purpose, estimates of the accuracy of direct genomic breeding values expressed as genetic correlations between traits and their respective direct genomic breeding values are required. METHODS: We derived direct genomic breeding values for 2239 registered Limousin and 2703 registered Simmental beef cattle genotyped with either the Illumina BovineSNP50 BeadChip or the Illumina BovineHD BeadChip. For the 264 Simmental animals that were genotyped with the BovineHD BeadChip, genotypes for markers present on the BovineSNP50 BeadChip were extracted. Deregressed estimated breeding values were used as observations in weighted analyses that estimated marker effects to derive direct genomic breeding values for each breed. For each breed, genotyped individuals were clustered into five groups using K-means clustering, with the aim of increasing within-group and decreasing between-group pedigree relationships. Cross-validation was performed five times for each breed, using four groups for training and the fifth group for validation. For each trait, we then applied a weighted bivariate analysis of the direct genomic breeding values of genotyped animals from all five validation sets and their corresponding deregressed estimated breeding values to estimate variance and covariance components. RESULTS: After minimizing relationships between training and validation groups, estimated genetic correlations between each trait and its direct genomic breeding values ranged from 0.39 to 0.76 in Limousin and from 0.29 to 0.65 in Simmental. The efficiency of selection based on direct genomic breeding values relative to selection based on parent average information ranged from 0.68 to 1.28 in genotyped Limousin and from 0.51 to 1.44 in genotyped Simmental animals. The efficiencies were higher for 323 non-genotyped young Simmental animals, born after January 2012, and ranged from 0.60 to 2.04. CONCLUSIONS: Direct genomic breeding values show promise for routine use by Limousin and Simmental breeders to improve the accuracy of predicted genetic merit of their animals at a young age and increase response to selection. Benefits from selecting on direct genomic breeding values are greater for breeders who use natural mating sires in their herds than for those who use artificial insemination sires. Producers with unregistered commercial Limousin and Simmental cattle could also benefit from being able to identify genetically superior animals in their herds, an opportunity that has in the past been limited to seed stock animals.