Genomic evaluation of late-term abortion in cows recorded through Dairy Herd Improvement test plans.

Late-term abortions cause significant economic loss and are of great concern for dairy herds. Late-term abortions >152 d and <251 d of gestation that terminate a lactation or initiate a new lactation have long been recorded by Dairy Herd Improvement (DHI). For 24.8 million DHI lactations, the average recorded incidence of late-term abortions across all years (2001-2018) was 1.2%. However, the 1.3% incidence of abortions reported in 2012 has declined to <1.0% incidence since 2015. Small adjustments were applied to the 82 million daughter pregnancy rate (DPR), 29 million cow conception rate (CCR), and 9 million heifer conception rate (HCR) records to account for late-term abortions more accurately. Fertility credits for CCR and HCR were changed to treat the last breeding as a failure instead of success if the next calving was coded as a late-term abortion. Similarly, when computing DPR, days open is now set to the maximum value of 250 instead of the reported days open if the next reported calving is an abortion. The test of these changes showed very small changes in standard deviation and high correlations (0.997) of adjusted predicted transmitting abilities (PTA) with official PTA from about 20,000 Holstein bulls born since 2000 with >50% reliability. For late-term abortion as a trait, estimated heritability was only 0.001 and PTA had a standard deviation of only 0.1% for recent sires with high reliability (>75%). Young animal genomic PTA have near 50% reliability but range only from -0.5 to +0.4 because of the low incidence and heritability. Genetic trend was slightly favorable and late-term abortion PTA were correlated favorably by 0.27 with net merit, 0.49 with productive life, 0.33 with livability, 0.23 with CCR, 0.20 with HCR, 0.26 with DPR, -0.31 with somatic cell score, -0.24 with daughter stillbirth, and -0.26 with daughter dystocia. Thus, PTA for late-term abortions should not be needed as a separate fertility trait and instead these minor edit changes should suffice. The PTA for late-term abortions would add little value because national evaluations for current fertility traits already account for those economic losses.

Genomic evaluation of dairy heifer livability.

Differences in breeds and sire lines suggest the presence of a genetic component for heifer livability (HLIV). Genomic evaluation for this trait can increase profitability and improve animal health and welfare. Evaluations for HLIV were examined from 3,362,499 calf data records from heifers of all breeds born from 2009 to 2016. Data were obtained from the national cooperator database maintained by the Council on Dairy Cattle Breeding (https://www.uscdcb.com/). The total number of deaths reported was 134,753 (4.01%), which included herds with death loss between 1.5 and 25.5%. Age at death was evaluated and ranged from >2 d of age until the heifer left the herd, with a maximum of 18 mo of age. Records were not included until 3 yr after the birthdate so that live status of contemporaries could be confirmed by a calving date for those animals. Deaths observed until 2 d after birth were considered to be a stillbirth rather than a failure of HLIV. The scale used for analysis of HLIV was 0 (died) or 100 (live), and the heritability estimate was 0.7% based on sire model with restricted maximum likelihood estimation. Genomic predicted transmitting abilities for Holstein ranged from -1.6% to +1.6% with a standard deviation of 0.5%, and genomic predicted transmitting abilities for Jersey ranged from -0.5% to +0.5% with a standard deviation of 0.2%. The mean overall death loss was about 4%. Reliabilities of genomic predictions for young animals averaged 46% for Holsteins and 30% for Jerseys, and corresponding traditional parent average reliabilities averaged 16% and 12%, respectively. Correlations of HLIV were 0.44 with productive life, 0.18 to 0.22 with yield traits, and 0.29 with early first calving on proven Holstein bulls. The HLIV trait had a favorable genetic trend in recent years, likely because of the indirect selection associated with the correlated traits. The trait HLIV should receive 1% of emphasis on the Lifetime Net Merit index, resulting in economic progress worth $50,000/yr. By encouraging more comprehensive recording on calf mortality, the reliabilities of genetic predictions could increase significantly.

Investigating conception rate for beef service sires bred to dairy cows and heifers.

The widespread use of sexed semen on US dairy cows and heifers has led to an excess of replacement heifers' calves, and the sale prices for those calves are much lower than in the past. Females not selected to produce the next generation of replacement heifers are increasingly being bred to beef bulls to produce crossbred calves for beef production. The purpose of this study was to investigate the use of beef service sires bred to dairy cows and heifers and to provide a tool for dairy producers to evaluate beef service sires' conception. Sire conception rate (SCR) is a phenotypic evaluation of service sire fertility that is routinely calculated for US dairy bulls. A total of 268,174 breedings were available, which included 36 recognized beef breeds and 7 dairy breeds. Most of the beef-on-dairy inseminations (95.4%) were to Angus (AN) bulls. Because of the limited number of records among other breeds, we restricted our final evaluations to AN service sires bred to Holstein (HO) cows. Service-sire inbreeding and expected inbreeding of resulting embryo were set to zero because pedigree data for AN bulls were unavailable. There were 233,379 breedings from 1,344 AN service sire to 163,919 HO cows. A mean (SD) conception rate of 33.8% (47.3%) was observed compared with 34.3% (47.5%) for breedings with HO sires mated to HO cows. Publishable AN bulls were required to have ≥100 total matings, ≥10 matings in the most recent 12 mo, and breedings in at least 5 herds. Mean SCR reliability was 64.5% for 116 publishable bulls, with a maximum reliability of 99% based on 25,217 breedings. Average SCR was near zero (on AN base) with a range of -5.1 to 4.4. Breedings to HO heifers were also examined, which included 19,437 breedings (443 AN service sire and 15,971 HO heifers). A mean (SD) conception rate of 53.0% (49.9%) was observed, compared with 55.3% (49.7%) for breedings with a HO sire mated to a HO heifer. Beef sires were used more frequently in cows known to be problem breeders, which explains some of the difference in conception rate. Mean service number was 1.92 and 2.87 for HO heifers and 2.13 and 3.04 for HO cows mated to HO and AN sires, respectively. Mating dairy cows and heifers to beef bulls may be profitable if calf prices are higher, fertility is improved, or if practices such as sexed semen, genomic testing, and improved cow productive life allow herd owners to produce both higher quality dairy replacement and increased income from market calves.

High-density genome-wide association study for residual feed intake in Holstein dairy cattle.

Improving feed efficiency (FE) of dairy cattle may boost farm profitability and reduce the environmental footprint of the dairy industry. Residual feed intake (RFI), a candidate FE trait in dairy cattle, can be defined to be genetically uncorrelated with major energy sink traits (e.g., milk production, body weight) by including genomic predicted transmitting ability of such traits in genetic analyses for RFI. We examined the genetic basis of RFI through genome-wide association (GWA) analyses and post-GWA enrichment analyses and identified candidate genes and biological pathways associated with RFI in dairy cattle. Data were collected from 4,823 lactations of 3,947 Holstein cows in 9 research herds in the United States. Of these cows, 3,555 were genotyped and were imputed to a high-density list of 312,614 SNP. We used a single-step GWA method to combine information from genotyped and nongenotyped animals with phenotypes as well as their ancestors' information. The estimated genomic breeding values from a single-step genomic BLUP were back-solved to obtain the individual SNP effects for RFI. The proportion of genetic variance explained by each 5-SNP sliding window was also calculated for RFI. Our GWA analyses suggested that RFI is a highly polygenic trait regulated by many genes with small effects. The closest genes to the top SNP and sliding windows were associated with dry matter intake (DMI), RFI, energy homeostasis and energy balance regulation, digestion and metabolism of carbohydrates and proteins, immune regulation, leptin signaling, mitochondrial ATP activities, rumen development, skeletal muscle development, and spermatogenesis. The region of 40.7 to 41.5 Mb on BTA25 (UMD3.1 reference genome) was the top associated region for RFI. The closest genes to this region, CARD11 and EIF3B, were previously shown to be related to RFI of dairy cattle and FE of broilers, respectively. Another candidate region, 57.7 to 58.2 Mb on BTA18, which is associated with DMI and leptin signaling, was also associated with RFI in this study. Post-GWA enrichment analyses used a sum-based marker-set test based on 4 public annotation databases: Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, Reactome pathways, and medical subject heading (MeSH) terms. Results of these analyses were consistent with those from the top GWA signals. Across the 4 databases, GWA signals for RFI were highly enriched in the biosynthesis and metabolism of amino acids and proteins, digestion and metabolism of carbohydrates, skeletal development, mitochondrial electron transport, immunity, rumen bacteria activities, and sperm motility. Our findings offer novel insight into the genetic basis of RFI and identify candidate regions and biological pathways associated with RFI in dairy cattle.

Defining the optimal period length and stage of growth or lactation to estimate residual feed intake in dairy cows.

Residual feed intake (RFI) is an estimate of animal feed efficiency, calculated as the difference between observed and expected feed intake. Expected intake typically is derived from a multiple regression model of dry matter intake on energy sinks, including maintenance and growth in growing animals, or maintenance, gain in body reserves, and milk production in lactating animals. The best period during the production cycle of a dairy cow to estimate RFI is not clear. Here, we characterized RFI in growing Holstein heifers (RFIGrowth; ∼10 to 14 mo of age; n = 226) and cows throughout a 305-d lactation (RFILac-Full; n = 118). The goals were to characterize relationships between RFI estimated at different production stages of the dairy cow; determine effects of selection for efficiency during growth on subsequent lactation and feed efficiency; and identify the most desirable testing scheme for RFILac-Full. For RFIGrowth, intake was predicted from multiple linear regression of metabolizable energy (ME) intake on mid-test body weight (BW)0.75 and average daily gain (ADG). For RFILac-Full, predicted intake was based on regression of BW0.75, ADG, and energy-corrected milk yield. Mean energy intake of the least and most efficient growing heifers (±0.5 standard deviations from mean RFIGrowth of 0) differed by 3.01 Mcal of ME/d, but the groups showed no difference in mid-test BW or ADG. Phenotypic correlation between RFIGrowth and RFI of heifers estimated in the first 100 d in milk (RFILac100DIM; n = 130) was 0.37. Ranking of these heifers as least (mean + 0.5 standard deviations), middle, or most efficient (mean - 0.5 standard deviations) based on RFIGrowth resulted in 43% maintaining the same ranking by RFILac100DIM. On average, the most efficient heifers ate 3.27 Mcal of ME/d less during the first 100 DIM than the least efficient heifers, but exhibited no differences in average energy-corrected milk yield, ADG, or BW. The correlation between RFILac100DIM and RFILac-Full was 0.72. Thus, RFIGrowth may serve as an indicator trait for RFI during lactation, and selection for heifers exhibiting low RFIGrowth should improve overall herd feed efficiency during lactation. Correlation analysis between RFILac-Full (10 to 305 DIM) and subperiod estimates of RFI during lactation indicated a test period of 64 to 70 d in duration occurring between 150 to 220 DIM provided a reliable approximation (r ≥ 0.90) of RFILac-Full among the test periods evaluated.

Genomic evaluation of age at first calving.

From their time of birth until their first lactation, dairy heifers incur management, health, and feed expenses while not producing milk. Much effort has been made to estimate optimal ages of first calving (AFC) for cows to reduce these costs, which can be as high as $2.50 per day, and ensure that animals are productive earlier in life. To identify AFC for 3 dairy cattle breeds (Holstein, Jersey, and Brown Swiss) that maximizes production, we retrieved phenotypic records for more than 14 million cows calving between 1997 and 2015 from the US national dairy database. The mean AFC for Holstein and Jersey has decreased by 2.4 and 2.7 mo, respectively, since 2006. When comparing the association of AFC with production and fertility traits, we found that decreased AFC was correlated with greater fertility and higher milk yield for all but the earliest group (18 to 20 mo). We also identified an unfavorable correlation of lower AFC with increasing stillbirth rates in Holstein (0.047 least squares means compared with a baseline of 24 mo) and Brown Swiss (0.062 least squares means). Finally, we identified favorable genetic correlations of lower AFC with lifetime net merit, heifer conception rate, cow conception rate, and daughter pregnancy rate in Holstein and Jersey cattle, and favorable correlations for net merit and heifer conception rate in Brown Swiss. To maximize lifetime production and reduce the effects of AFC on stillbirth, the AFC that maximizes production for Holstein and Brown Swiss is 21 to 22 mo, and for Jersey it is 20 to 21 mo. However, the effect of AFC on stillbirth reduces the benefits of calving at very young ages. Calculated genomic predicted transmitting ability for AFC showed an improvement in reliability of 20 percentage points in genomic young bulls compared with parent averages in Holstein, suggesting that genomic testing can improve selection for this trait.

Reducing animal sequencing redundancy by preferentially selecting animals with low-frequency haplotypes.

Many studies leverage targeted whole-genome sequencing (WGS) experiments to identify rare and causal variants within populations. As a natural consequence of their experimental design, many of these surveys tend to sequence redundant haplotype segments due to their high frequency in the base population, and the variants discovered within sequencing data are difficult to phase. We propose a new algorithm, called inverse weight selection (IWS), that preferentially selects individuals based on the cumulative presence of rare frequency haplotypes to maximize the efficiency of WGS surveys. To test the efficacy of this method, we used genotype data from 112,113 registered Holstein bulls derived from the US national dairy database. We demonstrate that IWS is at least 6.8% more efficient than previously published methods in selecting the least number of individuals required to sequence all haplotype segments ≥4% frequency in the US Holstein population. We also suggest that future surveys focus on sequencing homozygous haplotype segments as a first pass to achieve a 50% reduction in cost with an added benefit of phasing variant calls efficiently. Together, this new selection algorithm and experimental design suggestion significantly reduce the overall cost of variant discovery through WGS experiments, making surveys for causal variants influencing disease and production even more efficient.

Comparison of single-trait to multi-trait national evaluations for yield, health, and fertility.

Flexible software was designed to replace the current animal model programs used for national genetic evaluations. Model improvements included (1) multi-trait processing, (2) multiple fixed class and regression variables, (3) differing models for different traits, (4) random regressions, and (5) foreign data included using pseudo-records. Computational improvements included (6) parallel processing, (7) renumbering class variables to equation numbers within the program so that estimated effects are output with original identification numbers, and (8) reliability computed within the same program. When applied to 3 fertility traits of 27,971,895 cows and heifers, the new model used daughter pregnancy rate as a correlated trait to improve heifer and cow conception rate evaluations for older animals and in herd-years where records are missing, and also added information from crossbreds. When applied to 7 traits and 76,846,327 lactation records of 30,064,300 cows, gains in accuracy were small for yield and somatic cell score, moderate for daughter pregnancy rate, and larger for productive life for recent bulls compared with single-trait evaluations. For very old bulls, multi-trait gains were also large for protein because lactation records were available only for milk and fat. Multi-trait productive life was computed with exact rather than approximate methods; however, correlated information from conformation was excluded, reducing advantages of the new model over the previous software. Estimates of breed differences, inbreeding depression, and heterosis were similar to previous estimates; new estimates were obtained for conception rates. Predictions were compared by truncating 4 yr of data, and genetic trend validation was applied to all breed-trait combinations. The estimates of trend account for increases in inbreeding across time. Incorporation of foreign data gave correlations above 0.98 for new with previous evaluations of foreign Holstein bulls, but lower for other breeds. The 7-trait model required 35 GB of memory and 3 d to converge using 7 processors. The new software was implemented for fertility traits in 2013 and is scheduled for implementation with yield, somatic cell score, and productive life in 2014. Further revision of the models and software may be needed in the near future to account for genomic preselection.

Genomic evaluation, breed identification, and discovery of a haplotype affecting fertility for Ayrshire dairy cattle.

Genomic evaluations of dairy cattle in the United States have been available for Brown Swiss, Holsteins, and Jerseys since 2009. As of January 2013, 1,023 Ayrshires had genotypes in the North American database. Evaluation accuracy was assessed using genomic evaluations based on 646 bulls with 2008 traditional evaluations to predict daughter performance of up to 180 bulls in 2012. Mean gain in reliability over parent average for all traits was 8.2 percentage points. The highest gains were for protein yield (16.9 percentage points), milk yield (16.6 percentage points), and stature (16.2 percentage points). Twelve single nucleotide polymorphisms were useful for Ayrshire breed determination. Fewer breed-determining SNP were available for Ayrshires than for Holsteins, Jerseys, and Brown Swiss because of the similarity of Ayrshires and Holsteins. A haplotype that affects fertility was identified on chromosome 17 and traces back in the genotyped population to the bull Selwood Betty's Commander (born in 1953). The haplotype carrier frequency for genotyped Ayrshires was 26.1%. Sire conception rate was decreased by 4.3 ± 2.5 percentage points for carriers of the haplotype as determined by 618 matings of carrier sire by carrier maternal grandsire. Genomic evaluations for Ayrshires were officially implemented in the United States in April 2013.

Short communication: Use of young bulls in the United States.

The availability of genomic evaluations since 2008 has resulted in many changes to dairy cattle breeding programs. One such change has been the increased contribution of young bulls (0.8 to 3.9 yr old) to those programs. The increased use of young bulls was investigated using pedigree data and breeding records obtained from the US national dairy database (Beltsville, MD). The adoption of genotyping was so rapid that by 2009, >90% of all Holstein artificial insemination (AI) service sires and 86% of Jersey AI service sires were genotyped, regardless of age. The percentage of sons sired by young bulls increased by 49 percentage points (10% in 2008 compared with 59% in 2012) due to the onset of genomic evaluations for Holsteins and by 46 percentage points for Jerseys (11 and 57%, respectively). When limiting these data to sons retained for breeding purposes through AI, the increase was even more dramatic, increasing approximately 80 percentage points from 2008 to 2012 for both Holsteins and Jerseys (1, 5, 28, 52, and 81% for Holsteins and 3, 4, 43, 46, and 82% for Jerseys from 2008 through 2012). From US breeding records from 2007 through 2012, 24,580,793 Holstein and 1,494,095 Jersey breedings were examined. Young bulls accounted for 28% and 25% of Holstein and Jersey breedings in 2007, respectively. These percentages increased to 51% of Holstein and 52% of Jersey breedings in 2012, representing 23- and 27-percentage-unit increases, respectively. Matings to genotyped young bulls have rapidly increased while the use of nongenotyped bulls has diminished since the onset of genomics. Mean sire age for Holstein male progeny born in 2012 was 2.7 yr younger than males born in 2006, and 1.3 yr younger for females; corresponding values for Jerseys were 2.3 and 0.9 yr. Holstein male offspring had an increase of 281 kg between 2006 and 2012, compared with 197 kg between 2000 and 2006 for parent averages (PA) for milk, an increase of 84 kg between the 2 periods. Jersey male offspring had an increase of 49 kg between the 2 periods. To demonstrate the economic impact of the differential use of young bulls, herds were grouped by the frequency of their use of young bulls, and average PTA for milk and net merit for cows that were bred in 2003 through 2012 were calculated. In 2012, herds using >75% young bulls created offspring that had a PA of +52 kg for milk and +$58 net merit compared with herds using no young bulls. Jersey herds using >75% young bulls created offspring that had a PA of +142 kg for milk and +$63 for net merit compared with herds using no young bulls. Use of young bulls has greatly reduced the generation interval and improved the rate of genetic gain since the implementation of genomic evaluations.

Use of residual feed intake in Holsteins during early lactation shows potential to improve feed efficiency through genetic selection.

Improved feed efficiency is a primary goal in dairy production to reduce feed costs and negative impacts of production on the environment. Estimates for efficiency of feed conversion to milk production based on residual feed intake (RFI) in dairy cattle are limited, primarily due to a lack of individual feed intake measurements for lactating cows. Feed intake was measured in Holstein cows during the first 90 d of lactation to estimate the heritability and repeatability of RFI, minimum test duration for evaluating RFI in early lactation, and its association with other production traits. Data were obtained from 453 lactations (214 heifers and 239 multiparous cows) from 292 individual cows from September 2007 to December 2011. Cows were housed in a free-stall barn and monitored for individual daily feed consumption using the GrowSafe 4000 System (GrowSafe Systems, Ltd., Airdrie, AB, Canada). Animals were fed a total mixed ration 3 times daily, milked twice daily, and weighed every 10 to 14 d. Milk yield was measured at each milking. Feed DM percentage was measured daily, and nutrient composition was analyzed from a weekly composite. Milk composition was analyzed weekly, alternating between morning and evening milking periods. Estimates of RFI were determined as the difference between actual energy intake and predicted intake based on a linear model with fixed effects of parity (1, 2, ≥ 3) and regressions on metabolic BW, ADG, and energy-corrected milk yield. Heritability was estimated to be moderate (0.36 ± 0.06), and repeatability was estimated at 0.56 across lactations. A test period through 53 d in milk (DIM) explained 81% of the variation provided by a test through 90 DIM. Multiple regression analysis indicated that high efficiency was associated with less time feeding per day and slower feeding rate, which may contribute to differences in RFI among cows. The heritability and repeatability of RFI suggest an opportunity to improve feed efficiency through genetic selection, which could reduce feed costs, manure output, and greenhouse gas emissions associated with dairy production.

Technical note: Changes to herd cutoff date in conception rate evaluations.

Service-sire conception rate (SCR) evaluations were implemented for the United States in August 2008. Only inseminations from the most recent 4 yr of breeding records are used for SCR evaluations, and all inseminations must have occurred ≥ 70 d before the data submission deadline for an evaluation. In April 2012, edits for SCR were modified so that all inseminations must have occurred ≥ 70 d before the last herd test date rather than the constant date of 70 d before the data submission deadline. This edit more precisely measures the days of opportunity for a cow to be diagnosed as pregnant or not pregnant following insemination, and is herd specific. The number of inseminations before the edit change was 16,906,385 compared with 16,492,331 after the edit change. Correlations of SCR before and after the edit change were 0.96 for Holsteins and slightly lower for other breeds, with little change in mean or standard deviation. Weekly mean conception rates after the edit change were more stable for the most recent inseminations. The conception rate was 60% at wk 10 before the constant cutoff date (before edit change) compared with 42% at 10 wk before the last herd test date (after the edit change). Similar edits to SCR are applied to heifer conception rate (HCR) and cow conception rate data (CCR), and were changed in August 2012 to use herd-specific cutoff dates. The HCR and CCR correlations before and after the edit change were 0.99 or higher for all breeds, with little change in mean or standard deviation. The new edits improve accuracy of SCR, HCR, and CCR evaluations by accounting for differing opportunity to confirm pregnancy caused by discontinued testing or differences in herd testing schedules.

Factors associated with frequency of abortions recorded through Dairy Herd Improvement test plans.

Frequency of abortions recorded through Dairy Herd Improvement (DHI) testing was summarized for cows with lactations completed from 2001 through 2009. For 8.5 million DHI lactations of cows that had recorded breeding dates and were >151 d pregnant at lactation termination, the frequency of recorded abortions was 1.31%. Effects of year, herd-year, month, and pregnancy stage at lactation termination; parity; breed; milk yield; herd size; geographic region; and state within region associated with DHI-recorded abortion were examined. Abortions recorded through DHI (minimum gestation of 152 d required) were more frequent during early gestation; least squares means (LSM) were 4.38, 3.27, 1.19, and 0.59% for 152 to 175, 176 to 200, 201 to 225, and 226 to 250 d pregnant, respectively. Frequency of DHI-recorded abortions was 1.40% for parity 1 and 1.01% for parity ≥ 8. Abortion frequency was highest from May through August (1.42 to 1.53%) and lowest from October through February (1.09 to 1.21%). Frequency of DHI-recorded abortions was higher for Holsteins (1.32%) than for Jerseys (1.10%) and other breeds (1.27%). Little relationship was found between DHI-recorded abortions and herd size. Abortion frequencies for effects should be considered to be underestimated because many abortions, especially those caused by genetic recessives, go undetected. Therefore, various nonreturn rates (NRR; 60, 80, …, 200 d) were calculated to document pregnancy loss confirmed by the absence of homozygotes in the population. Breeding records for April 2011 US Department of Agriculture sire conception rate evaluations were analyzed with the model used for official evaluations with the addition of an interaction between carrier status of the service sire (embryo's sire) and cow sire (embryo's maternal grandsire). Over 13 million matings were examined using various NRR for Holstein lethal recessive traits (brachyspina and complex vertebral malformation) and undesirable recessive haplotypes (HH1, HH2, and HH3) as well as >61,000 matings for a Brown Swiss haplotype (BH1), and 670,000 matings for a Jersey haplotype (JH1). Over 80% of fertility loss occurred by 60 d after breeding for BH1, HH3, and JH1, by 80 d for HH2, by 100 d for BY, and by 180 d for HH1. For complex vertebral malformation, fertility loss increased from 40 to 74% across gestation. Association of undesirable recessives with DHI-recorded abortions ranged from 0.0% for Jerseys to 2.4% for Holsteins.

The structure of nanocomposite 1D cationic conductor crystal@SWNT.

Nanocomposites consisting of one-dimensional (1D) crystals of the cationic conductors CuI, CuBr and AgBr inside single-walled carbon nanotubes, mainly (n, 0), were obtained using the capillary technique. 1D crystal structure models were proposed based on the high resolution transmission electron microscopy performed on a FEI Titan 80-300 at 80 kV with aberration correction. According to the models and image simulations there are two modifications of 1D crystal: hexagonal close-packed bromine (iodine) anion sublattice (growth direction <001>) and 1D crystal cubic structure (growth direction <112>) compressed transversely to the nanotube (D(m) ∼1.33 nm) axis. Tentatively this kind of 1D crystal can be considered as monoclinic. One modification of the anion sublattice reversibly transforms into the other inside the nanotube, probably initiated by electron beam heating. As demonstrated by micrographs, copper or silver cations can occupy octahedral positions or are statistically distributed across two tetrahedral positions. A 1DAgBr@SWNT (18, 0; 19, 0) pseudoperiodic 'lattice distortion' is revealed resulting from convolution of the nanotube wall function image with 1D cubic crystal function image.

Triennial Lactation Symposium: Opportunities for improving milk production efficiency in dairy cattle.

Increasing feed costs and the desire to improve environmental stewardship have stimulated renewed interest in improving feed efficiency of livestock, including that of US dairy herds. For instance, USDA cost projections for corn and soybean meal suggest a 20% increase over 2010 pricing for a 16% protein mixed dairy cow ration in 2011, which may lead to a reduction in cow numbers to maintain profitability of dairy production. Furthermore, an October 2010 study by The Innovation Center for US Dairy to assess the carbon footprint of fluid milk found that the efficiency of feed conversion is the single greatest factor contributing to variation in the carbon footprint because of its effects on methane release during enteric fermentation and from manure. Thus, we are conducting research in contemporary US Holsteins to identify cows most efficient at converting feed to milk in temperate climates using residual feed intake (RFI), a measure used successfully to identify the beef cattle most efficient at converting feed to gain. Residual feed intake is calculated as the difference between predicted and actual feed intake to support maintenance and production (e.g., growth in beef cattle, or milk in dairy cattle). Heritability estimates for RFI in dairy cattle reported in the literature range from 0.01 to 0.38. Selection for a decreased RFI phenotype can reduce feed intake, methane production, nutrient losses in manure, and visceral organ weights substantially in beef cattle. We have estimated RFI during early lactation (i.e., to 90 d in milk) in the Beltsville Agricultural Research Center Holstein herd and observed a mean difference of 3.7 kg/d (P < 0.0001) in actual DMI between the efficient and inefficient groups (±0.5 SD from the mean RFI of 0), with no evidence of differences (P > 0.20) in mean BW, ADG, or energy-corrected milk exhibited between the 2 groups. These results indicate promise for using RFI in dairy cattle to improve feed conversion to milk. Previous and current research on the use of RFI in lactating dairy cattle are discussed, as well as opportunities to improve production efficiency of dairy cattle using RFI for milk production.

Evaluations for service-sire conception rate for heifer and cow inseminations with conventional and sexed semen.

Service-sire conception rate (SCR), a phenotypic fertility evaluation based on conventional (nonsexed) inseminations from parities 1 through 5, was implemented for the United States in August 2008. The SCR model contains the categorical fixed effects of parity for lactations 1 to 5; state-year-month of insemination group; 6 standardized milk yield groups; service number for inseminations 1 to 7; cow age; and herd-yearseason-parity-registry status class. Covariate effects for service-sire and mating inbreeding coefficients were linear regressions fit as deviations from the overall mean. Random effects included service-sire age group; AI organization-insemination year group; individual service sire; cow's genetic ability to conceive; cow's permanent environmental effect; and residual. Using insemination data from 2005 through 2009, the SCR procedure was applied separately for nulliparous heifer inseminations with conventional semen (SCR(H(conv))), cow inseminations with conventional semen (SCR(C(conv))), nulliparous heifer inseminations with sexed semen (SCR(H(sexed))), and cow inseminations with sexed semen (SCR(C(sexed))). Holstein and Jersey bulls with ≥300 and ≥200 artificial inseminations, respectively, in ≥10 herds and with ≥100 breedings during the 12 mo before evaluation were examined. The number of bulls evaluated for SCR in January 2010 was 270 Holsteins and 16 Jerseys for SCR(H(conv)) 2,309 Holsteins and 214 Jerseys for SCR(C(conv)) 114 Holsteins and 6 Jerseys for SCR(H(sexed)) and 25 Holsteins and 7 Jerseys for SCR(C(sexed)). The mean SCR for each evaluation category was set to 0; Holstein standard deviations were 2.55% for SCR(H(conv)) 2.21% for SCR(C(conv)) 4.29% for SCR(H(sexed)) and 2.39% for SCR(C(sexed)). The mean Holstein reliabilities were 82, 79, 75, and 73%, respectively. Correlations for Holstein SCR between conventional and sexed semen averaged near zero (−0.21 to 0.18). Predicted correlations between true SCR were −0.27 to 0.24. In contrast, correlations between Holstein heifers and cows were high (0.66 to 0.76), and predicted true correlations averaged near 1.0 (0.82 to 1.03). Correlations for Jerseys were often larger, although based on fewer inseminations and service sires compared with Holsteins. Some rankings for SCR could benefit from combining cow and heifer data but should be kept separate for conventional and sexed semen inseminations.

Harmful recessive effects on fertility detected by absence of homozygous haplotypes.

Five new recessive defects were discovered in Holsteins, Jerseys, and Brown Swiss by examining haplotypes that had a high population frequency but were never homozygous. The method required genotypes only from apparently normal individuals and not from affected embryos. Genotypes from the BovineSNP50 BeadChip (Illumina, San Diego, CA) were examined for 58,453 Holsteins, 5,288 Jerseys, and 1,991 Brown Swiss with genotypes in the North American database. Haplotypes with a length of ≤ 75 markers were obtained. Eleven candidate haplotypes were identified, with the earliest carrier born before 1980; 7 to 90 homozygous haplotypes were expected, but none were observed in the genomic data. Expected numbers were calculated using either the actual mating pattern or assuming random mating. Probability of observing no homozygotes ranged from 0.0002 for 7 to 10⁻45 for 90 expected homozygotes. Phenotypic effects were confirmed for 5 of the 11 candidate haplotypes using 14,911,387 Holstein, 830,391 Jersey, and 68,443 Brown Swiss records for conception rate. Estimated effect for interaction of carrier service sire with carrier maternal grandsire ranged from -3.0 to -3.7 percentage points, which was slightly smaller than the -3.9 to -4.6 percentage points expected for lethal recessives but slightly larger than estimated effects for previously known lethal alleles of -2.5 percentage points for brachyspina and -2.9 percentage points for complex vertebral malformation. Conception rate was coded as a success only if the gestation went to term or the cow was confirmed to be pregnant. Estimated effect of carrier interaction for stillbirth rate based on 10,876,597 Holstein and 25,456 Jersey records was small. Thus, lethal effects may include conception, gestation, and stillbirth losses. Carrier frequency has been >20% for many years for the confirmed defect in Jerseys and is currently 16% for the defect in Brown Swiss. The 3 defects discovered in Holsteins have carrier frequencies of 2.7 to 6.4% in the current population. For previously known defects, map locations and lack of homozygotes were consistent with the literature and lethal recessive inheritance, but numbers of expected homozygotes for some were small because of low frequency. Very large genotypic and phenotypic data sets allow efficient detection of smaller and less frequent effects. Haplotype tests can help breeders avoid carrier matings for such defects and reduce future frequencies.

On the mechanism of carbon nanotube formation: the role of the catalyst.

This work examines the recent developments in non-traditional catalyst-assisted chemical vapour deposition of carbon nanotubes (CNTs) with a view to determining the essential role of the catalyst in nanotube growth. A brief overview of the techniques reliant on the structural reorganization of carbon to form CNTs is provided. Additionally, CNT synthesis methods based upon ceramic, noble metal, and semiconducting nanoparticle catalysts are presented. Experimental evidence is provided for CNT growth using noble metal and semiconducting nanoparticle catalysts. A model for CNT growth consistent with the experimental results is proposed, in which the structural reorganization of carbon to form CNTs is paramount.

Use of sexed semen and its effect on conception rate, calf sex, dystocia, and stillbirth of Holsteins in the United States.

Use of sexed semen for artificial insemination of US Holstein heifers (1.3 million breedings) and cows (10.8 million breedings) in Dairy Herd Improvement herds was characterized by breeding year, parity, service number, region, herd size, and herd milk yield. Sexed semen was used for 1.4, 9.5, and 17.8% of all reported breedings for 2006, 2007, and 2008, respectively, for heifers, and for 0.1, 0.2, and 0.4%, respectively, for cows. For 2008 sexed semen breedings, 80.5 and 68.6% of use was for first services of heifers and cows, respectively. For cows, 63.1% of 2008 sexed semen use was for first parity. Mean sexed semen use within herd was the greatest for heifers in the Southwest (36.2%) and for cows in the Mideast (1.3%). Mean sexed semen use increased for heifers but changed little for cows as either herd size or herd mean milk yield increased. Availability of sexed semen was examined for Holstein bulls in active AI service; of 700 bulls born after 1993, 37% had sexed semen marketed by mid August 2009. Active AI bulls with marketed sexed semen were superior to average active AI bulls for evaluations of yield traits, productive life, somatic cell score, daughter pregnancy rate, service-sire calving ease, service-sire stillbirth, final score, sire conception rate, and lifetime net merit. The effect of sexed semen use on conception rate, calf sex, dystocia, and stillbirth also was examined for heifers and cows. Mean conception rate for heifers was 56% for conventional and 39% for sexed semen; corresponding conception rates for cows were 30 and 25%. For single births from sexed semen breedings, around 90% were female. Dystocia and stillbirth were more frequent for heifers (6.0 and 10.4%, respectively, for conventional semen; 4.3 and 11.3%, respectively, for sexed semen) than for cows (2.5 and 3.6%, respectively, for conventional semen; 0.9 and 2.7%, respectively, for sexed semen). Difficult births declined by 28% for heifers and 64% for cows with sexed semen use. Stillbirths were more prevalent for twin births except for sexed semen heifer breedings. Stillbirths of single male calves of heifers were more frequent for breedings with sexed semen (15.6%) than conventional semen (10.8%); a comparable difference was not observed for cows, for which stillbirth frequency of single male calves even decreased (2.6 vs. 3.6%). Overall stillbirth frequency was reduced by sexed semen use for cows but not for heifers.

Selection and management of DNA markers for use in genomic evaluation.

To facilitate routine genomic evaluation, a database was constructed to store genotypes for 50,972 single nucleotide polymorphisms (SNP) from the Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA). Multiple samples per animal are allowed. All SNP genotypes for a sample are stored in a single row. An indicator specifies whether the genotype for a sample was selected for use in genomic evaluation. Samples with low call rates or pedigree conflicts are designated as unusable. Among multiple samples that qualify for use in genomic evaluation, the one with the highest call rate is designated as usable. When multiple samples are stored for an animal, a composite is formed during extraction by using SNP genotypes from other samples to replace missing genotypes. To increase the number of SNP available, scanner output for approximately 19,000 samples was reprocessed. Any SNP with a minor allele frequency of > or = 1% for Holsteins, Jerseys, or Brown Swiss was selected, which was the primary reason that the number of SNP used for USDA genomic evaluations increased. Few parent-progeny conflicts (< or = 1%) and a high call rate (> or = 90%) were additional requirements that eliminated 2,378 SNP. Because monomorphic SNP did not degrade convergence during estimation of SNP effects, a single set of 43,385 SNP was adopted for all breeds. The use of a database for genotypes, detection of conflicts as genotypes are stored, online access for problem resolution, and use of a single set of SNP for genomic evaluations have simplified tracking of genotypes and genomic evaluation as a routine and official process.