Hot topic: a unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score

The first national single-step, full-information (phenotype, pedigree, and marker genotype) genetic evaluation was developed for final score of US Holsteins. Data included final scores recorded from 1955 to 2009 for 6,232,548 Holsteins cows. BovineSNP50 (Illumina, San Diego, CA) genotypes from the Cooperative Dairy DNA Repository (Beltsville, MD) were available for 6,508 bulls. Three analyses used a repeatability animal model as currently used for the national US evaluation. The first 2 analyses used final scores recorded up to 2004. The first analysis used only a pedigree-based relationship matrix. The second analysis used a relationship matrix based on both pedigree and genomic information (single-step approach). The third analysis used the complete data set and only the pedigree-based relationship matrix. The fourth analysis used predictions from the first analysis (final scores up to 2004 and only a pedigree-based relationship matrix) and prediction using a genomic based matrix to obtain genetic evaluation (multiple-step approach). Different allele frequencies were tested in construction of the genomic relationship matrix. Coefficients of determination between predictions of young bulls from parent average, single-step, and multiple-step approaches and their 2009 daughter deviations were 0.24, 0.37 to 0.41, and 0.40, respectively. The highest coefficient of determination for a single-step approach was observed when using a genomic relationship matrix with assumed allele frequencies of 0.5. Coefficients for regression of 2009 daughter deviations on parent-average, single-step, and multiple-step predictions were 0.76, 0.68 to 0.79, and 0.86, respectively, which indicated some inflation of predictions. The single-step regression coefficient could be increased up to 0.92 by scaling differences between the genomic and pedigree-based relationship matrices with little loss in accuracy of prediction. One complete evaluation took about 2h of computing time and 2.7 gigabytes of memory. Computing times for single-step analyses were slightly longer (2%) than for pedigree-based analysis. A national single-step genetic evaluation with the pedigree relationship matrix augmented with genomic information provided genomic predictions with accuracy and bias comparable to multiple-step procedures and could account for any population or data structure. Advantages of single-step evaluations should increase in the future when animals are pre-selected on genotypes.

A relationship matrix including full pedigree and genomic information

Dense molecular markers are being used in genetic evaluation for parts of the population. This requires a two-step procedure where pseudo-data (for instance, daughter yield deviations) are computed from full records and pedigree data and later used for genomic evaluation. This results in bias and loss of information. One way to incorporate the genomic information into a full genetic evaluation is by modifying the numerator relationship matrix. A naive proposal is to substitute the relationships of genotyped animals with the genomic relationship matrix. However, this results in incoherencies because the genomic relationship matrix includes information on relationships among ancestors and descendants. In other words, using the pedigree-derived covariance between genotyped and ungenotyped individuals, with the pretense that genomic information does not exist, leads to inconsistencies. It is proposed to condition the genetic value of ungenotyped animals on the genetic value of genotyped animals via the selection index (e.g., pedigree information), and then use the genomic relationship matrix for the latter. This results in a joint distribution of genotyped and ungenotyped genetic values, with a pedigree-genomic relationship matrix H. In this matrix, genomic information is transmitted to the covariances among all ungenotyped individuals. The matrix is (semi)positive definite by construction, which is not the case for the naive approach. Numerical examples and alternative expressions are discussed. Matrix H is suitable for iteration on data algorithms that multiply a vector times a matrix, such as preconditioned conjugated gradients.

Computing procedures for genetic evaluation including phenotypic, full pedigree, and genomic information

Currently, genomic evaluations use multiple-step procedures, which are prone to biases and errors. A single-step procedure may be applicable when genomic predictions can be obtained by modifying the numerator relationship matrix A to H = A + A(Delta), where A(Delta) includes deviations from expected relationships. However, the traditional mixed model equations require H(-1), which is usually difficult to obtain for large pedigrees. The computations with H are feasible when the mixed model equations are expressed in an alternate form that also applies for singular H and when those equations are solved by the conjugate gradient techniques. Then the only computations involving H are in the form of Aq or A(Delta)q, where q is a vector. The alternative equations have a nonsymmetric left-hand side. Computing A(Delta)q is inexpensive when the number of nonzeros in A(Delta) is small, and the product Aq can be calculated efficiently in linear time using an indirect algorithm. Generalizations to more complicated models are proposed. The data included 10.2 million final scores on 6.2 million Holsteins and were analyzed by a repeatability model. Comparisons involved the regular and the alternative equations. The model for the second case included simulated A(Delta). Solutions were obtained by the preconditioned conjugate gradient algorithm, which works only with symmetric matrices, and by the bi-conjugate gradient stabilized algorithm, which also works with nonsymmetric matrices. The convergence rate associated with the nonsymmetric solvers was slightly better than that with the symmetric solver for the original equations, although the time per round was twice as much for the nonsymmetric solvers. The convergence rate associated with the alternative equations ranged from 2 times lower without A(Delta) to 3 times lower for the largest simulated A(Delta). When the information attributable to genomics can be expressed as modifications to the numerator relationship matrix, the proposed methodology may allow the upgrading of an existing evaluation to incorporate the genomic information.

Acupuncture as a complementary therapy to the pharmacological treatment of osteoarthritis of the knee: randomised controlled trial

OBJECTIVES

To analyse the efficacy of acupuncture as a complementary therapy to the pharmacological treatment of osteoarthritis of the knee, with respect to pain relief, reduction of stiffness, and increased physical function during treatment; modifications in the consumption of diclofenac during treatment; and changes in the patient's quality of life.

DESIGN

Randomised, controlled, single blind trial, with blinded evaluation and statistical analysis of results.

SETTING

Pain management unit in a public primary care centre in southern Spain, over a period of two years.

PARTICIPANTS

97 outpatients presenting with osteoarthritis of the knee.

INTERVENTIONS

Patients were randomly separated into two groups, one receiving acupuncture plus diclofenac (n = 48) and the other placebo acupuncture plus diclofenac (n = 49).

MAIN OUTCOME MEASURES

The clinical variables examined included intensity of pain as measured by a visual analogue scale; pain, stiffness, and physical function subscales of the Western Ontario and McMaster Universities (WOMAC) osteoarthritis index; dosage of diclofenac taken during treatment; and the profile of quality of life in the chronically ill (PQLC) instrument, evaluated before and after the treatment programme.

RESULTS

88 patients completed the trial. In the intention to treat analysis, the WOMAC index presented a greater reduction in the intervention group than in the control group (mean difference 23.9, 95% confidence interval 15.0 to 32.8) The reduction was greater in the subscale of functional activity. The same result was observed in the pain visual analogue scale, with a reduction of 26.6 (18.5 to 34.8). The PQLC results indicate that acupuncture treatment produces significant changes in physical capability (P = 0.021) and psychological functioning (P = 0.046). Three patients reported bruising after the acupuncture sessions.

CONCLUSIONS

Acupuncture plus diclofenac is more effective than placebo acupuncture plus diclofenac for the symptomatic treatment of osteoarthritis of the knee.

Efficient computation of the genomic relationship matrix and other matrices used in single-step evaluation

Genomic evaluations can be calculated using a unified procedure that combines phenotypic, pedigree and genomic information. Implementation of such a procedure requires the inverse of the relationship matrix based on pedigree and genomic relationships. The objective of this study was to investigate efficient computing options to create relationship matrices based on genomic markers and pedigree information as well as their inverses. SNP maker information was simulated for a panel of 40 K SNPs, with the number of genotyped animals up to 30 000. Matrix multiplication in the computation of the genomic relationship was by a simple 'do' loop, by two optimized versions of the loop, and by a specific matrix multiplication subroutine. Inversion was by a generalized inverse algorithm and by a LAPACK subroutine. With the most efficient choices and parallel processing, creation of matrices for 30 000 animals would take a few hours. Matrices required to implement a unified approach can be computed efficiently. Optimizations can be either by modifications of existing code or by the use of efficient automatic optimizations provided by open source or third-party libraries.

Genetic evaluation using single-step genomic best linear unbiased predictor in American Angus

Predictive ability of genomic EBV when using single-step genomic BLUP (ssGBLUP) in Angus cattle was investigated. Over 6 million records were available on birth weight (BiW) and weaning weight (WW), almost 3.4 million on postweaning gain (PWG), and over 1.3 million on calving ease (CE). Genomic information was available on, at most, 51,883 animals, which included high and low EBV accuracy animals. Traditional EBV was computed by BLUP and genomic EBV by ssGBLUP and indirect prediction based on SNP effects was derived from ssGBLUP; SNP effects were calculated based on the following reference populations: ref_2k (contains top bulls and top cows that had an EBV accuracy for BiW ≥0.85), ref_8k (contains all parents that were genotyped), and ref_33k (contains all genotyped animals born up to 2012). Indirect prediction was obtained as direct genomic value (DGV) or as an index of DGV and parent average (PA). Additionally, runs with ssGBLUP used the inverse of the genomic relationship matrix calculated by an algorithm for proven and young animals (APY) that uses recursions on a small subset of reference animals. An extra reference subset included 3,872 genotyped parents of genotyped animals (ref_4k). Cross-validation was used to assess predictive ability on a validation population of 18,721 animals born in 2013. Computations for growth traits used multiple-trait linear model and, for CE, a bivariate CE-BiW threshold-linear model. With BLUP, predictivities were 0.29, 0.34, 0.23, and 0.12 for BiW, WW, PWG, and CE, respectively. With ssGBLUP and ref_2k, predictivities were 0.34, 0.35, 0.27, and 0.13 for BiW, WW, PWG, and CE, respectively, and with ssGBLUP and ref_33k, predictivities were 0.39, 0.38, 0.29, and 0.13 for BiW, WW, PWG, and CE, respectively. Low predictivity for CE was due to low incidence rate of difficult calving. Indirect predictions with ref_33k were as accurate as with full ssGBLUP. Using the APY and recursions on ref_4k gave 88% gains of full ssGBLUP and using the APY and recursions on ref_8k gave 97% gains of full ssGBLUP. Genomic evaluation in beef cattle with ssGBLUP is feasible while keeping the models (maternal, multiple trait, and threshold) already used in regular BLUP. Gains in predictivity are dependent on the composition of the reference population. Indirect predictions via SNP effects derived from ssGBLUP allow for accurate genomic predictions on young animals, with no advantage of including PA in the index if the reference population is large. With the APY conditioning on about 10,000 reference animals, ssGBLUP is potentially applicable to a large number of genotyped animals without compromising predictive ability.

Using recursion to compute the inverse of the genomic relationship matrix

Computing the inverse of the genomic relationship matrix using recursion was investigated. A traditional algorithm to invert the numerator relationship matrix is based on the observation that the conditional expectation for an additive effect of 1 animal given the effects of all other animals depends on the effects of its sire and dam only, each with a coefficient of 0.5. With genomic relationships, such an expectation depends on all other genotyped animals, and the coefficients do not have any set value. For each animal, the coefficients plus the conditional variance can be called a genomic recursion. If such recursions are known, the mixed model equations can be solved without explicitly creating the inverse of the genomic relationship matrix. Several algorithms were developed to create genomic recursions. In an algorithm with sequential updates, genomic recursions are created animal by animal. That algorithm can also be used to update a known inverse of a genomic relationship matrix for additional genotypes. In an algorithm with forward updates, a newly computed recursion is immediately applied to update recursions for remaining animals. The computing costs for both algorithms depend on the sparsity pattern of the genomic recursions, but are lower or equal than for regular inversion. An algorithm for proven and young animals assumes that the genomic recursions for young animals contain coefficients only for proven animals. Such an algorithm generates exact genomic EBV in genomic BLUP and is an approximation in single-step genomic BLUP. That algorithm has a cubic cost for the number of proven animals and a linear cost for the number of young animals. The genomic recursions can provide new insight into genomic evaluation and possibly reduce costs of genetic predictions with extremely large numbers of genotypes.

Genetic components of heat stress for dairy cattle with multiple lactations

Data included 585,119 test-day records for milk, fat, and protein yields from the first, second, and third parities of 38,608 Holsteins in Georgia. Daily temperature-humidity indexes (THI) were available from public weather stations. Models included a repeatability test-day model with a random regression on a function of THI and a test-day random regression model using linear splines with knots at 5, 50, 200, and 305 d in milk and a function of THI. Random effects were additive genetic and permanent environmental in the repeatability model and additive genetic, permanent environmental, and herd year in the random regression model. Additionally, models included fixed effects for herd test day, calving age, milking frequency, and lactation stage. Phenotypic variance increased by 50 to 60% from the first to second parity for all yield traits with the repeatability model and by 12 to 15% from the second to third parity. General additive genetic variance increased by 25 to 35% from the first to second parity for all yield traits but decreased slightly from the second to third parity for milk and protein yields. Genetic variance for heat tolerance doubled from the first to second parity and increased by 20 to 100% from the second to third parity. Genetic correlations among general additive effects were lowest between the first and second parities (0.84 to 0.88) and were highest between the second and third parities (0.96 to 0.98). Genetic correlations among parities for the effect of heat tolerance ranged from 0.56 to 0.79. Genetic correlations between general and heat-tolerance effects across parities and yield traits ranged from -0.30 to -0.50. With the random regression model, genetic variance for heat tolerance for milk yield was approximately one-half that of the repeatability model. For milk yield, the most negative genetic correlation (approximately -0.45) between general and heat-tolerance effects was between 50 and 200 d in milk for the first parity and between 200 and 305 d in milk for the second and third parities. The genetic variance of heat tolerance increased substantially from the first to third parity. Genetic estimates of heat tolerance may be inflated with the repeatability model because of timing of lactations to avoid peak yield during hot seasons.

Infectivity of turnip mosaic potyvirus cDNA clones and transcripts on the systemic host Arabidopsis thaliana and local lesion hosts

Full-length cDNA clones of turnip mosaic virus were assembled under the control of T7 or 35S promoter. The 35S or nopaline synthase terminator signals were introduced downstream the full length cDNA controlled by 35S promoter. Both the capped in vitro transcripts from T7 controlled template, and the cDNAs from 35S controlled plasmids were infectious on Arabidopis thaliana plants according to systemically induced symptoms and to ELISA assays. The cDNAs from 35S controlled plasmids induced local lesions in Chenopodium amaranticolor and Chenopodium quinoa plants. A spontaneous silent C/T transition, giving rise to an additional SpeI restriction site, not present in the original viral RNA template, was used as a marker of the origin of infection.

Single-point acupuncture and physiotherapy for the treatment of painful shoulder: a multicentre randomized controlled trial

OBJECTIVE

Evaluate the efficacy of acupuncture associated with physiotherapy for patients with painful shoulder.

METHODS

In a multicentre controlled randomized study, participants were recruited with a clinical diagnosis of unilateral subacromial syndrome from six rehabilitation medicine departments belonging to the Public Health System in two Spanish regions. All participants received 15 sessions of physiotherapy during the 3 weeks that the treatment lasted and were randomized to additionally receive, once a week, acupuncture or mock TENS (transcutaneous electrical nerve stimulation). The primary outcome measure was the change in the Constant-Murley Score (CMS) for functional assessment of the shoulder, at 4 weeks after randomization. This study is registered as an International Standard Randomized Controlled Trial, number ISRCTN28687220.

RESULTS

A total of 425 patients were recruited. The mean score (s.d.) on the CMS had increased by 16.6 (15.6) points among the acupuncture group, compared with 10.6 (13.5) points in the control group, and the mean difference between the two groups was statistically significant (6.0 points; 95% CI 3.2, 8.8 points; P < 0.001). By the end of the treatment, 53% of the patients in the acupuncture group had decreased their consumption of analgesics, compared with a corresponding 30% among the control group (P < 0.001).

CONCLUSIONS

Single-point acupuncture in association with physiotherapy improves shoulder function and alleviates pain, compared with physiotherapy as the sole treatment. This improvement is accompanied by a reduction in the consumption of analgesic medicaments.

Implementation of genomic recursions in single-step genomic best linear unbiased predictor for US Holsteins with a large number of genotyped animals

The objectives of this study were to develop and evaluate an efficient implementation in the computation of the inverse of genomic relationship matrix with the recursion algorithm, called the algorithm for proven and young (APY), in single-step genomic BLUP. We validated genomic predictions for young bulls with more than 500,000 genotyped animals in final score for US Holsteins. Phenotypic data included 11,626,576 final scores on 7,093,380 US Holstein cows, and genotypes were available for 569,404 animals. Daughter deviations for young bulls with no classified daughters in 2009, but at least 30 classified daughters in 2014 were computed using all the phenotypic data. Genomic predictions for the same bulls were calculated with single-step genomic BLUP using phenotypes up to 2009. We calculated the inverse of the genomic relationship matrix GAPY(-1) based on a direct inversion of genomic relationship matrix on a small subset of genotyped animals (core animals) and extended that information to noncore animals by recursion. We tested several sets of core animals including 9,406 bulls with at least 1 classified daughter, 9,406 bulls and 1,052 classified dams of bulls, 9,406 bulls and 7,422 classified cows, and random samples of 5,000 to 30,000 animals. Validation reliability was assessed by the coefficient of determination from regression of daughter deviation on genomic predictions for the predicted young bulls. The reliabilities were 0.39 with 5,000 randomly chosen core animals, 0.45 with the 9,406 bulls, and 7,422 cows as core animals, and 0.44 with the remaining sets. With phenotypes truncated in 2009 and the preconditioned conjugate gradient to solve mixed model equations, the number of rounds to convergence for core animals defined by bulls was 1,343; defined by bulls and cows, 2,066; and defined by 10,000 random animals, at most 1,629. With complete phenotype data, the number of rounds decreased to 858, 1,299, and at most 1,092, respectively. Setting up GAPY(-1) for 569,404 genotyped animals with 10,000 core animals took 1.3h and 57 GB of memory. The validation reliability with APY reaches a plateau when the number of core animals is at least 10,000. Predictions with APY have little differences in reliability among definitions of core animals. Single-step genomic BLUP with APY is applicable to millions of genotyped animals.

Acupuncture in patients with acute low back pain: a multicentre randomised controlled clinical trial

Reviews of the efficacy of acupuncture as a treatment for acute low back pain have concluded that there is insufficient evidence for its efficacy and that more research is needed to evaluate it. A multicentre randomized controlled trial was conducted at 4 primary-care centres in Spain to evaluate the effects of acupuncture in patients with acute nonspecific low back pain in the context of primary care. A total of 275 patients with nonspecific acute low back pain (diagnosed by their general practitioner) were recruited and assigned randomly to 4 different groups: conventional treatment either alone or complemented by 5 sessions over a 2-week period of true acupuncture, sham acupuncture, or placebo acupuncture per patient. Patients were treated from February 2006 to January 2008. The primary outcome was the reduction in Roland Morris Disability Questionnaire scores of 35% or more after 2weeks' treatment. The patients in the 3 types of acupuncture groups were blinded to the treatments, but those who received conventional treatment alone were not. In the analysis adjusted for the total sample (true acupuncture relative risk 5.04, 95% confidence interval 2.24-11.32; sham acupuncture relative risk 5.02, 95% confidence interval 2.26-11.16; placebo acupuncture relative risk 2.57 95% confidence interval 1.21-5.46), as well as for the subsample of occupationally active patients, all 3 modalities of acupuncture were better than conventional treatment alone, but there was no difference among the 3 acupuncture modalities, which implies that true acupuncture is not better than sham or placebo acupuncture.

Methods to approximate reliabilities in single-step genomic evaluation

Reliability of predictions from single-step genomic BLUP (ssGBLUP) can be calculated by matrix inversion, but that is not feasible for large data sets. Two methods of approximating reliability were developed based on the decomposition of a function of reliability into contributions from records, pedigrees, and genotypes. Those contributions can be expressed in record or daughter equivalents. The first approximation method involved inversion of a matrix that contains inverses of the genomic relationship matrix and the pedigree relationship matrix for genotyped animals. The second approximation method involved only the diagonal elements of those inverses. The 2 approximation methods were tested with a simulated data set. The correlations between ssGBLUP and approximated contributions from genomic information were 0.92 for the first approximation method and 0.56 for the second approximation method; contributions were inflated by 62 and 258%, respectively. The respective correlations for reliabilities were 0.98 and 0.72. After empirical correction for inflation, those correlations increased to 0.99 and 0.89. Approximations of reliabilities of predictions by ssGBLUP are accurate and computationally feasible for populations with up to 100,000 genotyped animals. A critical part of the approximations is quality control of information from single nucleotide polymorphisms and proper scaling of the genomic relationship matrix.

Hot topic: Use of genomic recursions in single-step genomic best linear unbiased predictor (BLUP) with a large number of genotypes

The purpose of this study was to evaluate the accuracy of genomic selection in single-step genomic BLUP (ssGBLUP) when the inverse of the genomic relationship matrix (G) is derived by the "algorithm for proven and young animals" (APY). This algorithm implements genomic recursions on a subset of "proven" animals. Only a relationship matrix for animals treated as "proven" needs to be inverted, and the extra costs of adding animals treated as "young" are linear. Analyses involved 10,102,702 final scores on 6,930,618 Holstein cows. Final score, which is a composite of type traits, is popular trait in the United States and was easily available for this study. A total of 100,000 animals with genotypes were used in the analyses and included 23,000 sires (16,000 with >5 progeny), 27,000 cows, and 50,000 young animals. Genomic EBV (GEBV) were calculated with a regular inverse of G, and with the G inverse approximated by APY. Animals in the proven subset included only sires (23,000), sires+cows (50,000), only cows (27,000), or sires with >5 progeny (16,000). The correlations of GEBV with APY and regular GEBV for young genotyped animals were 0.994, 0.995, 0.992, and 0.992, respectively Later, animals in the proven subset were randomly sampled from all genotyped animals in sets of 2,000, 5,000, 10,000, 15,000, and 20,000; each sample was replicated 4 times. Respective correlations were 0.97 (5,000 sample), 0.98 (10,000 sample), and 0.99 (20,000 sample), with minimal difference between samples of the same size. Genomic EBV with APY were accurate when the number of animals used in the subset is between 10,000 and 20,000, with little difference between the ways of creating the subset. Due to the approximately linear cost of APY, ssGBLUP with APY could support any number of genotyped animals without affecting accuracy.

Technical note: recursive algorithm for inbreeding coefficients assuming nonzero inbreeding of unknown parents

A recursive algorithm to calculate inbreeding coefficients was modified to account for nonzero inbreeding of unknown parents. The modification was done by changing one part of a recursive formula in which the inbreeding of an animal with at least one unknown parent is not zero and replacing it by the mean inbreeding of all animals born the same year. The algorithm is iterative. Testing involved 17 million US Holsteins. Convergence was reached in 6 rounds. The computing time per round was 4 min, twice as fast as the VanRaden algorithm based on the tabular method. The recursive algorithm is very simple; however, it requires that the recursion takes into account the order of animals. After a simple modification, the algorithm provides a very good approximation of inbreeding when the pedigree is unordered.

Nucleotide sequence of Chinese rape mosaic virus (oilseed rape mosaic virus), a crucifer tobamovirus infectious on Arabidopsis thaliana

The complete nucleotide sequence of Chinese rape mosaic virus has been determined. The virus is a member of the tobamovirus genus of plant virus and is able to infect Arabidopsis thaliana (L.) Heynh systemically. The analysis of the sequence shows a gene array that seems to be characteristic of crucifer tobamoviruses and which is slightly different from the one most frequently found in tobamoviruses. Based on gene organization and on comparisons of sequence homologies between members of the tobamoviruses, a clustering of crucifer tobamoviruses is proposed that groups the presently known crucifer tobamovirus into two viruses with two strains each. A name change of Chinese rape mosaic virus to oilseed rape mosaic virus is proposed.

Using moxibustion in primary healthcare to correct non-vertex presentation: a multicentre randomised controlled trial

OBJECTIVE

To compare the effectiveness of additional moxibustion at point BL67 with moxibustion at a non-specific acupuncture point and with usual care alone to correct non-vertex presentation.

METHODS

This was a multicentre randomised controlled trial in which 406 low-risk pregnant women with a fetus in ultrasound breech presentation, with a gestational age of 33-35 weeks, were assigned to (1) true moxibustion at point BL67 plus usual care; (2) moxibustion at SP1, a non-specific acupuncture point (sham moxibustion) plus usual care; or (3) usual care alone. The primary outcome was cephalic presentation at birth. Women were recruited at health centres in primary healthcare.

RESULTS

In the true moxibustion group, 58.1% of the full-term presentations were cephalic compared with 43.4% in the sham moxibustion group (RR 1.34, 95% CI 1.05 to 1.70) and 44.8% of those in the usual care group (RR 1.29, 95% CI 1.02 to 1.64). The reduction in RR of the primary outcome in women allocated to the true moxibustion group compared with the usual care group was 29.7% (95% CI 3.1% to 55.2%) and the number needed to treat was 8 (95% CI 4 to 72). There were no severe adverse effects during the treatment.

CONCLUSIONS

Moxibustion at acupuncture point BL67 is effective and safe to correct non-vertex presentation when used between 33 and 35 weeks of gestation. We believe that moxibustion represents a treatment option that should be considered to achieve version of the non-vertex fetus.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN10634508.

Acupuncture for fibromyalgia in primary care: a randomised controlled trial

OBJECTIVES

To evaluate the efficacy of an individualised acupuncture protocol for patients with fibromyalgia.

METHODS

Randomised controlled multicentre trial, blinded to participants and to data analysts. Conducted in three primary care centres in southern Spain. A total of 164 participants aged over 17 years and diagnosed with fibromyalgia were enrolled in this trial; 153 participants completed the study. Participants were randomly assigned to either the real intervention (individualised acupuncture, IA) or the sham intervention (sham acupuncture, SA). In both the IA and SA groups, one session per week (lasting 20 min) was provided, in addition to usual pharmacological treatment. The primary outcome was change in pain intensity at 10 weeks.

RESULTS

Intention-to-treat analysis revealed that the decrease in pain intensity at 10 weeks was greater (p=0.001) in the IA group (-41.0%, 95% CI -47.2% to -34.8%) than in the SA group (-27.1%, 95% CI -33.2% to -20.9%). During the follow-up period, significant differences (p<0.01) in favour of the IA group persisted at 12 months (IA: -19.9%, 95% CI -24.6% to -15.1%; vs SA: -6.2%, 95% CI -11.2% to -1.2%).

CONCLUSIONS

Individualised acupuncture treatment in primary care in patients with fibromyalgia proved efficacious in terms of pain relief, compared with placebo treatment. The effect persisted at 1 year, and its side effects were mild and infrequent. Therefore, the use of individualised acupuncture in patients with fibromyalgia is recommended.

TRIAL REGISTRATION NUMBER

ISRCTN60217348.

Post-anthesis sink size in a high-yielding dwarf wheat: yield response to grain number

Experiments to study the effect of grain number per sq metre on kernel weight and grain yield in a high-yielding dwarf spring wheat (Triticum aestivum cv. Yecora 70) were conducted in three seasons (1971–1973) under high-fertility irrigated conditions in north-western Mexico. Crop thinning, shading and carbon dioxide fertilization (reported elsewhere), and crowding treatments, all carried out at or before anthesis, led to a wide range in grain numbers (4000 to 34,000/m2). Results indicated the response of grain yield to changing sink size (grains per sq metre), with the post-anthesis environment identical for all crops each year, and with all but the thinner crops intercepting most of the post-anthesis solar radiation. Kernel weight fell linearly with increase in grain number over the whole range of grain numbers studied, but the rate of fall varied with the season. Grain yield, however, increased, reaching a maximum at grain numbers well above those of crops grown with optimal agronomic management but without manipulation. It was concluded that the grain yield in normal crops was limited by both sink and post-anthesis source. There was some doubt, however, as to the interpretation of results from crowded crops, because of likely artificial increases in crop respiration on the one hand, and on the other, in labile carbohydrate reserves in the crops at anthesis. Also deterioration in grain plumpness (hectolitre weight) complicates the simple inference that further gains in yield can come from increased grain numbers alone.

Genomic prediction for tick resistance in Braford and Hereford cattle

One of the main animal health problems in tropical and subtropical cattle production is the bovine tick, which causes decreased performance, hide devaluation, increased production costs with acaricide treatments, and transmission of infectious diseases. This study investigated the utility of genomic prediction as a tool to select Braford (BO) and Hereford (HH) cattle resistant to ticks. The accuracy and bias of different methods for direct and blended genomic prediction was assessed using 10,673 tick counts obtained from 3,435 BO and 928 HH cattle belonging to the Delta G Connection breeding program. A subset of 2,803 BO and 652 HH samples were genotyped and 41,045 markers remained after quality control. Log transformed records were adjusted by a pedigree repeatability model to estimate variance components, genetic parameters, and breeding values (EBV) and subsequently used to obtain deregressed EBV. Estimated heritability and repeatability for tick counts were 0.19 ± 0.03 and 0.29 ± 0.01, respectively. Data were split into 5 subsets using k-means and random clustering for cross-validation of genomic predictions. Depending on the method, direct genomic value (DGV) prediction accuracies ranged from 0.35 with Bayes least absolute shrinkage and selection operator (LASSO) to 0.39 with BayesB for k-means clustering and between 0.42 with BayesLASSO and 0.45 with BayesC for random clustering. All genomic methods were superior to pedigree BLUP (PBLUP) accuracies of 0.26 for k-means and 0.29 for random groups, with highest accuracy gains obtained with BayesB (39%) for k-means and BayesC (55%) for random groups. Blending of historical phenotypic and pedigree information by different methods further increased DGV accuracies by values between 0.03 and 0.05 for direct prediction methods. However, highest accuracy was observed with single-step genomic BLUP with values of 0.48 for -means and 0.56, which represent, respectively, 84 and 93% improvement over PBLUP. Observed random clustering cross-validation breed-specific accuracies ranged between 0.29 and 0.36 for HH and between 0.55 and 0.61 for BO, depending on the blending method. These moderately high values for BO demonstrate that genomic predictions could be used as a practical tool to improve genetic resistance to ticks and in the development of resistant lines of this breed. For HH, accuracies are still in the low to moderate side and this breed training population needs to be increased before genomic selection could be reliably applied to improve tick resistance.

Use of the vaccination register to evaluate influenza vaccine coverage in seniors in the 2010/11 influenza season, Navarre, Spain

People aged 65 and older have a high risk of suffering from complications of influenza, therefore it is recommended that they receive annual influenza vaccination. However, vaccination coverage falls far short of the target of 75%. In this study we use the vaccination register to evaluate the coverage of influenza vaccine in non-institutionalised persons aged 65 and over in Navarre, Spain, in the 2010/11 season (104,427 persons). Vaccination coverage was 58.6%, lower than the 62.7% coverage in the 2009/10 season. In the multivariate analysis, lower coverage was associated with being female, age under 80 or over 94 years, immigrant status and hospitalisation in the previous year. In contrast, persons with major chronic conditions, high level of dependence or those with more visits to the general practitioner in the previous year had higher vaccination coverage. Influenza vaccination in the previous season was a strong predictor of vaccination in the current season (odds ratio: 37.0, 95% confidence interval: 35.7–38.4). The vaccination register has been shown to be useful to monitor the coverage of influenza vaccination in seniors and may help guide strategies to improve coverage.

Estimation of breed and heterosis effects for growth and carcass traits in cattle using published crossbreeding studies

Current genetic evaluations are performed separately for each breed. Multiple breed genetic evaluations, however, assume a common base among breeds, enabling producers to compare cattle of different breed makeup. Breed and heterosis effects are needed in a multibreed evaluation because databases maintained by breed associations include few crossbred animals, which may not be enough to accurately estimate these effects. The objective of this study was to infer breed effects, maternal effects, direct heterosis effects, and maternal heterosis effects for growth and carcass traits using least squares means estimates from crossbreeding studies published in the literature from 1976 to 1996. The data set was formed by recording each least squares mean along with the breed composition, maternal breed composition, and direct and maternal heterozygosity. Each trait was analyzed using a single trait fixed effect model, which included study as a fixed effect and breed composition and heterozygosity as covariates. Breed solutions for each trait were expressed relative to the Angus breed. Direct breed effects for weaning weight ranged from -7.0 +/- 0.67 kg (British Dairy) to 29.3 +/- 0.74 kg (Simmental), and maternal effects ranged from -11.7 +/- 0.24 kg (Hereford) to 31.1 +/- 2.22 kg (Gelbvieh). Direct breed effects for birth weight ranged from -0.5 +/- 0.14 kg (British Dairy) to 10.1 +/- 0.46 kg (Continental Beef), and maternal effects ranged from -7.2 +/- 0.13 kg (Brahman) to 6.0 +/- 1.07 kg (Continental Beef). Direct breed effects ranged from -17.9 +/- 1.64 kg (Brahman) to 21.6 +/- 1.95 kg (Charolais), from -6.5 +/- 1.29 kg (Brahman) to 55.8 +/- 1.47 kg (Continental Beef), from -8.1 +/- 0.48 cm(2) (Shorthorn) to 21.0 +/- 0.48 cm(2) (Continental Beef), and from -1.1 +/- 0.02 cm (Continental Beef) to 0 +/- 0.00 cm (Angus) for postweaning BW gain, carcass weight, LM area, and fat thickness, respectively. The use of literature estimates to predict direct and maternal breed and heterosis effects may supplement their direct prediction in a multibreed evaluation.

Genetic determination of the onset of heat stress on daily milk production in the US Holstein cattle

Existence of individual variation in the onset of heat stress for daily milk yield of dairy cows was assessed. Data included 353,376 test-day records of 38,383 first-parity Holsteins from a random sample of US herds. Three hierarchical models were investigated. Model 1 inferred the value of a temperature-humidity index (THI) at which mean yield began to decline as well as the extent of that decline. Model 2 assumed individual variation in yield decline beyond a common THI threshold. Model 3 additionally assumed individual variation for the onset of heat stress. Deviance information criteria indicated the superiority of model 3 over model 2. For model 2, genetic correlation between milk yield in the absence of heat stress and the THI threshold for heat stress was -0.4 (0.11) [marginal posterior mean (marginal posterior standard deviation)]. For model 3, genetic correlations were -0.53 (0.05) between milk yield and THI threshold and -0.62 (0.08) between milk yield and yield decay beyond the THI threshold. Total standard deviation (sum of additive genetic and permanent environmental standard deviations) for the THI threshold was 3.95 (0.06), and more than half of that variation had an additive genetic origin [56% (5%)]. Because of the high genetic correlation [0.95 (0.03)] between yield decay and THI threshold with model 3, using only one of them as a selection criterion for heat tolerance would modify the other in the desired direction.

Evidence against a direct antimicrobial role of H2O2 in the infection of plants by Erwinia chrysanthemi

We have investigated the role of bacterial resistance to oxidative stress in pathogenesis. The oxyR gene from the pathogenic bacterium Erwinia chrysanthemi has been characterized. It is closely related to that found in Escherichia coli (88% overall amino acid identity). An E. chrysanthemi oxyR mutant strain was constructed by marker exchange. After induction with a sublethal dose of H2O2, this mutant was more sensitive to H2O2 and showed reduced levels of catalase and glutathione reductase activities, compared with the wild type. The oxyR mutant was unable to form individual colonies on agar plates unless catalase was added exogenously. However, it retained full virulence in potato tubers and tobacco leaves. These results suggest that the host-produced H2O2 has no direct antimicrobial effect on the interaction of E. chrysanthemi with the two plant species.