Use of continuous genotypes for genomic prediction in sugarcane

Genomic selection in sugarcane faces challenges due to limited genomic tools and high genomic complexity, particularly because of its high and variable ploidy. The classification of genotypes for single nucleotide polymorphisms (SNPs) becomes difficult due to the wide range of possible allele dosages. Previous genomic studies in sugarcane used pseudo-diploid genotyping, grouping all heterozygotes into a single class. In this study, we investigate the use of continuous genotypes as a proxy for allele-dosage in genomic prediction models. The hypothesis is that continuous genotypes could better reflect allele dosage at SNPs linked to mutations affecting target traits, resulting in phenotypic variation. The dataset included genotypes of 1318 clones at 58K SNP markers, with about 26K markers filtered using standard quality controls. Predictions for tonnes of cane per hectare (TCH), commercial cane sugar (CCS), and fiber content (Fiber) were made using parametric, non-parametric, and Bayesian methods. Continuous genotypes increased accuracy by 5%-7% for CCS and Fiber. The pseudo-diploid parametrization performed better for TCH. Reproducing kernel Hilbert spaces model with Gaussian kernel and AK4 (arc-cosine kernel with hidden layer 4) kernel outperformed other methods for TCH and CCS, suggesting that non-additive effects might influence these traits. The prevalence of low-dosage markers in the study may have limited the benefits of approximating allele-dosage information with continuous genotypes in genomic prediction models. Continuous genotypes simplify genomic prediction in polyploid crops, allowing additional markers to be used without adhering to pseudo-diploid inheritance. The approach can particularly benefit high ploidy species or emerging crops with unknown ploidy.

Expression network analysis of bovine skin infested with Rhipicephalus australis identifies pro-inflammatory genes contributing to tick susceptibility

The skin is the primary feeding site of ticks that infest livestock animals such as cattle. The highly specialised functions of skin at the molecular level may be a factor contributing to variation in susceptibility to tick infestation; but these remain to be well defined. The aim of this study was to investigate the bovine skin transcriptomic profiles of tick-naïve and tick-infested cattle and to uncover the gene expression networks that influence contrasting phenotypes of host resistance to ticks. RNA-Seq data was obtained from skin of Brangus cattle with high (n = 5) and low (n = 6) host resistance at 0 and 12 weeks following artificial tick challenge with Rhipicephalus australis larvae. No differentially expressed genes were detected pre-infestation between high and low resistance groups, but at 12-weeks there were 229 differentially expressed genes (DEGs; FDR < 0.05), of which 212 were the target of at least 1866 transcription factors (TFs) expressed in skin. Regulatory impact factor (RIF) analysis identified 158 significant TFs (P < 0.05) of which GRHL3, and DTX1 were also DEGs in the experiment. Gene term enrichment showed the significant TFs and DEGs were enriched in processes related to immune response and biological pathways related to host response to infectious diseases. Interferon Type 1-stimulated genes, including MX2, ISG15, MX1, OAS2 were upregulated in low host resistance steers after repeated tick challenge, suggesting dysregulated wound healing and chronic inflammatory skin processes contributing to host susceptibility to ticks. The present study provides an assessment of the bovine skin transcriptome before and after repeated tick challenge and shows that the up-regulation of pro-inflammatory genes is a prominent feature in the skin of tick-susceptible animals. In addition, the identification of transcription factors with high regulatory impact provides insights into the potentially meaningful gene-gene interactions involved in the variation of phenotypes of bovine host resistance to ticks.

Imputation strategies for genomic prediction using nanopore sequencing

BACKGROUND

Genomic prediction describes the use of SNP genotypes to predict complex traits and has been widely applied in humans and agricultural species. Genotyping-by-sequencing, a method which uses low-coverage sequence data paired with genotype imputation, is becoming an increasingly popular SNP genotyping method for genomic prediction. The development of Oxford Nanopore Technologies' (ONT) MinION sequencer has now made genotyping-by-sequencing portable and rapid. Here we evaluate the speed and accuracy of genomic predictions using low-coverage ONT sequence data in a population of cattle using four imputation approaches. We also investigate the effect of SNP reference panel size on imputation performance.

RESULTS

SNP array genotypes and ONT sequence data for 62 beef heifers were used to calculate genomic estimated breeding values (GEBVs) from 641 k SNP for four traits. GEBV accuracy was much higher when genome-wide flanking SNP from sequence data were used to help impute the 641 k panel used for genomic predictions. Using the imputation package QUILT, correlations between ONT and low-density SNP array genomic breeding values were greater than 0.91 and up to 0.97 for sequencing coverages as low as 0.1 × using a reference panel of 48 million SNP. Imputation time was significantly reduced by decreasing the number of flanking sequence SNP used in imputation for all methods. When compared to high-density SNP arrays, genotyping accuracy and genomic breeding value correlations at 0.5 × coverage were also found to be higher than those imputed from low-density arrays.

CONCLUSIONS

Here we demonstrated accurate genomic prediction is possible with ONT sequence data from sequencing coverages as low as 0.1 × , and imputation time can be as short as 10 min per sample. We also demonstrate that in this population, genotyping-by-sequencing at 0.1 × coverage can be more accurate than imputation from low-density SNP arrays.

Genomic prediction with machine learning in sugarcane, a complex highly polyploid clonally propagated crop with substantial non-additive variation for key traits

Sugarcane has a complex, highly polyploid genome with multi-species ancestry. Additive models for genomic prediction of clonal performance might not capture interactions between genes and alleles from different ploidies and ancestral species. As such, genomic prediction in sugarcane presents an interesting case for machine learning (ML) methods, which are purportedly able to deal with high levels of complexity in prediction. Here, we investigated deep learning (DL) neural networks, including multilayer networks (MLP) and convolution neural networks (CNN), and an ensemble machine learning approach, random forest (RF), for genomic prediction in sugarcane. The data set used was 2912 sugarcane clones, scored for 26,086 genome wide single nucleotide polymorphism markers, with final assessment trial data for total cane harvested (TCH), commercial cane sugar (CCS), and fiber content (Fiber). The clones in the latest trial (2017) were used as a validation set. We compared prediction accuracy of these methods to genomic best linear unbiased prediction (GBLUP) extended to include dominance and epistatic effects. The prediction accuracies from GBLUP models were up to 0.37 for TCH, 0.43 for CCS, and 0.48 for Fiber, while the optimized ML models had prediction accuracies of 0.35 for TCH, 0.38 for CCS, and 0.48 for Fiber. Both RF and DL neural network models have comparable predictive ability with the additive GBLUP model but are less accurate than the extended GBLUP model.

Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies

Mate-allocation strategies in breeding programs can improve progeny performance by harnessing non-additive genetic effects. These approaches prioritise predicted progeny merit over parental breeding value, making them particularly appealing for clonally propagated crops such as sugarcane. We conducted a comparative analysis of mate-allocation strategies, exploring utilising non-additive and heterozygosity effects to maximise clonal performance with schemes that solely consider additive effects to optimise breeding value. Using phenotypic and genotypic data from a population of 2,909 clones evaluated in final assessment trials of Australian sugarcane breeding programs, we focused on three important traits: tonnes of cane per hectare (TCH), commercial cane sugar (CCS), and Fibre. By simulating families from all possible crosses (1,225) with 50 progenies each, we predicted the breeding and clonal values of progeny using two models: GBLUP (considering additive effects only) and extended-GBLUP (incorporating additive, non-additive, and heterozygosity effects). Integer linear programming was used to identify the optimal mate-allocation among selected parents. Compared to breeding value-based approaches, mate-allocation strategies based on clonal performance yielded substantial improvements, with predicted progeny values increasing by 57% for TCH, 12% for CCS, and 16% for fibre. Our simulation study highlights the effectiveness of mate-allocation approaches that exploit non-additive and heterozygosity effects, resulting in superior clonal performance. However, there was a notable decline in additive gain, particularly for TCH, likely due to significant epistatic effects. When selecting crosses based on clonal performance for TCH, the inbreeding coefficient of progeny was significantly lower compared to random mating, underscoring the advantages of leveraging non-additive and heterozygosity effects in mitigating inbreeding depression. Thus, mate-allocation strategies are recommended in clonally propagated crops to enhance clonal performance and reduce the negative impacts of inbreeding.

Multi-breed genomic evaluation for tropical beef cattle when no pedigree information is available

BACKGROUND

It has been challenging to implement genomic selection in multi-breed tropical beef cattle populations. If commercial (often crossbred) animals could be used in the reference population for these genomic evaluations, this could allow for very large reference populations. In tropical beef systems, such animals often have no pedigree information. Here we investigate potential models for such data, using marker heterozygosity (to model heterosis) and breed composition derived from genetic markers, as covariates in the model. Models treated breed effects as either fixed or random, and included genomic best linear unbiased prediction (GBLUP) and BayesR. A tropically-adapted beef cattle dataset of 29,391 purebred, crossbred and composite commercial animals was used to evaluate the models.

RESULTS

Treating breed effects as random, in an approach analogous to genetic groups allowed partitioning of the genetic variance into within-breed and across breed-components (even with a large number of breeds), and estimation of within-breed and across-breed genomic estimated breeding values (GEBV). We demonstrate that moderately-accurate (0.30-0.43) GEBV can be calculated using these models. Treating breed effects as random gave more accurate GEBV than treating breed as fixed. A simple GBLUP model where no breed effects were fitted gave the same accuracy (and correlations of GEBV very close to 1) as a model where GEBV for within-breed and the GEBV for (random) across-breed effects were included. When GEBV were predicted for herds with no data in the reference population, BayesR resulted in the highest accuracy, with 3% accuracy improvement averaged across traits, especially when the validation population was less related to the reference population. Estimates of heterosis from our models were in line with previous estimates from beef cattle. A method for estimating the number of effective breed comparisons for each breed combination accumulated across contemporary groups is presented.

CONCLUSIONS

When no pedigree is available, breed composition and heterosis for inclusion in multi-breed genomic evaluation can be estimated from genotypes. When GEBV were predicted for herds with no data in the reference population, BayesR resulted in the highest accuracy.

In it for the long run: perspectives on exploiting long-read sequencing in livestock for population scale studies of structural variants

Studies have demonstrated that structural variants (SV) play a substantial role in the evolution of species and have an impact on Mendelian traits in the genome. However, unlike small variants (< 50 bp), it has been challenging to accurately identify and genotype SV at the population scale using short-read sequencing. Long-read sequencing technologies are becoming competitively priced and can address several of the disadvantages of short-read sequencing for the discovery and genotyping of SV. In livestock species, analysis of SV at the population scale still faces challenges due to the lack of resources, high costs, technological barriers, and computational limitations. In this review, we summarize recent progress in the characterization of SV in the major livestock species, the obstacles that still need to be overcome, as well as the future directions in this growing field. It seems timely that research communities pool resources to build global population-scale long-read sequencing consortiums for the major livestock species for which the application of genomic tools has become cost-effective.

Adaptive sampling during sequencing reveals the origins of the bovine reproductive tract microbiome across reproductive stages and sexes

Cattle enterprises are one of the major livestock production systems globally and are forecasted to have stable growth in the next decade. To facilitate sustainable live weight production, optimal reproductive performance is essential. Microbial colonisation in the reproductive tract has been demonstrated as one of the factors contributing to bovine reproductive performance. Studies also implied that reproductive metagenomes are different at each stage of the estrous cycle. This study applied Oxford Nanopore Technologies’ adaptive long-read sequencing to profile the bovine reproductive microbiome collected from tropical cattle in northern Queensland, Australia. The microbiome samples were collected from cattle of different sexes, reproductive status and locations to provide a comprehensive view of the bovine reproductive microbiome in northern Australian cattle. Ascomycota, Firmicutes and Proteobacteria were abundant phyla identified in the bovine reproductive metagenomes of Australian cattle regardless of sexes, reproductive status and location. The species level taxonomical investigation suggested that gastrointestinal metagenome and the surrounding environment were potentially the origins of the bovine reproductive metagenome. Functional profiles further affirmed this implication, revealing that the reproductive metagenomes of the prepubertal and postpartum animals were dominated by microorganisms that catabolise dietary polysaccharides as an energy substrate while that of the pregnant animals had the function of harvesting energy from aromatic compounds. Bovine reproductive metagenome investigations can be employed to trace the origins of abnormal metagenomes, which is beneficial for disease prevention and control. Additionally, our results demonstrated different reproductive metagenome diversities between cattle from two different locations. The variation in diversity within one location can serve as the indicator of abnormal reproductive metagenome, but between locations inferences cannot be made. We suggest establishing localised metagenomic indices that can be used to infer abnormal reproductive metagenomes which contribute to abortion or sub-fertility.

Metagenomic Predictions: A Review 10 years on

Metagenomic predictions use variation in the metagenome (microbiome profile) to predict the unknown phenotype of the associated host. Metagenomic predictions were first developed 10 years ago, where they were used to predict which cattle would produce high or low levels of enteric methane. Since then, the approach has been applied to several traits and species including residual feed intake in cattle, and carcass traits, body mass index and disease state in pigs. Additionally, the method has been extended to include predictions based on other multi-dimensional data such as the metabolome, as well to combine genomic and metagenomic information. While there is still substantial optimisation required, the use of metagenomic predictions is expanding as DNA sequencing costs continue to fall and shows great promise particularly for traits heavily influenced by the microbiome such as feed efficiency and methane emissions.

Transcriptional changes in the peripheral blood leukocytes from Brangus cattle before and after tick challenge with Rhipicephalus australis

Background

Disease emergence and production loss caused by cattle tick infestations have focused attention on genetic selection strategies to breed beef cattle with increased tick resistance. However, the mechanisms behind host responses to tick infestation have not been fully characterised. Hence, this study examined gene expression profiles of peripheral blood leukocytes from tick-naive Brangus steers (Bos taurus x Bos indicus) at 0, 3, and 12 weeks following artificial tick challenge experiments with Rhipicephalus australis larvae. The aim of the study was to investigate the effect of tick infestation on host leukocyte response to explore genes associated with the expression of high and low host resistance to ticks.

Results

Animals with high (HR, n = 5) and low (LR, n = 5) host resistance were identified after repeated tick challenge. A total of 3644 unique differentially expressed genes (FDR < 0.05) were identified in the comparison of tick-exposed (both HR and LR) and tick-naive steers for the 3-week and 12-week infestation period. Enrichment analyses showed genes were involved in leukocyte chemotaxis, coagulation, and inflammatory response. The IL-17 signalling, and cytokine-cytokine interactions pathways appeared to be relevant in protection and immunopathology to tick challenge. Comparison of HR and LR phenotypes at timepoints of weeks 0, 3, and 12 showed there were 69, 8, and 4 differentially expressed genes, respectively. Most of these genes were related to immune, tissue remodelling, and angiogenesis functions, suggesting this is relevant in the development of resistance or susceptibility to tick challenge.

Conclusions

This study showed the effect of tick infestation on Brangus cattle with variable phenotypes of host resistance to R. australis ticks. Steers responded to infestation by expressing leukocyte genes related to chemotaxis, cytokine secretion, and inflammatory response. The altered expression of genes from the bovine MHC complex in highly resistant animals at pre- and post- infestation stages also supports the relevance of this genomic region for disease resilience. Overall, this study offers a resource of leukocyte gene expression data on matched tick-naive and tick-infested steers relevant for the improvement of tick resistance in composite cattle.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08686-3.

Environmental variation effects fertility in tropical beef cattle

The northern Australia beef cattle industry operates in harsh environmental conditions which consistently suppress female fertility. To better understand the environmental effect on cattle raised extensively in northern Australia, new environmental descriptors were defined for 54 commercial herds located across the region. Three fertility traits, based on the presence of a corpus luteum at 600 d of age, indicating puberty, (CL Presence, n = 25,176), heifer pregnancy (n = 20,989) and first lactation pregnancy (n = 10,072) were recorded. Temperature, humidity, and rainfall were obtained from publicly available data based on herd location. Being pubertal at 600 d (i.e. CL Presence) increased the likelihood of success at heifer pregnancy and first lactation pregnancy (P < 0.05), underscoring the importance of early puberty in reproductive success. A temperature humidity index (THI) of 65–70 had a significant (P < 0.05) negative effect on first lactation pregnancy rate, heifer pregnancy and puberty at 600 d of age. Area under the curve of daily THI was significant (P < 0.05) and reduced the likelihood of pregnancy at first lactation and puberty at 600 days. Deviation from long-term average rainfall was not significant (P < 0.05) for any trait. Average daily weight gain had a significant and positive relationship (P < 0.05) for heifer and first lactation pregnancy. The results indicate that chronic or cumulative heat load is more determinantal to reproductive performance than acute heat stress. The reason for the lack of a clear relationship between acute heat stress and reproductive performance is unclear but may be partially explained by peak THI and peak nutrition coinciding at the same time. Sufficient evidence was found to justify the use of average daily weight gain and chronic heat load as descriptors to define an environmental gradient.

Extensive Variation in Gene Expression is Revealed in 13 Fertility-Related Genes Using RNA-Seq, ISO-Seq, and CAGE-Seq From Brahman Cattle

Fertility is a key driver of economic profitability in cattle production. A number of studies have identified genes associated with fertility using genome wide association studies and differential gene expression analysis; however, the genes themselves are poorly characterized in cattle. Here, we selected 13 genes from the literature which have previously been shown to have strong evidence for an association with fertility in Brahman cattle (Bos taurus indicus) or closely related breeds. We examine the expression variation of the 13 genes that are associated with cattle fertility using RNA-seq, CAGE-seq, and ISO-seq data from 11 different tissue samples from an adult Brahman cow and a Brahman fetus. Tissues examined include blood, liver, lung, kidney, muscle, spleen, ovary, and uterus from the cow and liver and lung from the fetus. The analysis revealed several novel isoforms, including seven from SERPINA7. The use of three expression characterization methodologies (5′ cap selected ISO-seq, CAGE-seq, and RNA-seq) allowed the identification of isoforms that varied in their length of 5′ and 3′ untranslated regions, variation otherwise undetectable (collapsed as degraded RNA) in generic isoform identification pipelines. The combinations of different sequencing technologies allowed us to overcome the limitations of relatively low sequence depth in the ISO-seq data. The lower sequence depth of the ISO-seq data was also reflected in the lack of observed expression of some genes that were observed in the CAGE-seq and RNA-seq data from the same tissue. We identified allele specific expression that was tissue-specific in AR, IGF1, SOX9, STAT3, and TAF9B. Finally, we characterized an exon of TAF9B as partially nested within the neighboring gene phosphoglycerate kinase 1. As this study only examined two animals, even more transcriptional variation may be present in a genetically diverse population. This analysis reveals the large amount of transcriptional variation within mammalian fertility genes and illuminates the fact that the transcriptional landscape cannot be fully characterized using a single technology alone.

Technical note: overcoming host contamination in bovine vaginal metagenomic samples with nanopore adaptive sequencing

Animal metagenomic studies, in which host-associated microbiomes are profiled, are an increasingly important contribution to our understanding of the physiological functions, health and susceptibility to diseases of livestock. One of the major challenges in these studies is host DNA contamination, which limits the sequencing capacity for metagenomic content and reduces the accuracy of metagenomic profiling. This is the first study comparing the effectiveness of different sequencing methods for profiling bovine vaginal metagenomic samples. We compared the new method of Oxford Nanopore Technologies (ONT) adaptive sequencing, which can be used to target or eliminate defined genetic sequences, to standard ONT sequencing, Illumina 16S rDNA amplicon sequencing, and Illumina shotgun sequencing. The efficiency of each method in recovering the metagenomic data and recalling the metagenomic profiles was assessed. ONT adaptive sequencing yielded a higher amount of metagenomic data than the other methods per 1 Gb of sequence data. The increased sequencing efficiency of ONT adaptive sequencing consequently reduced the amount of raw data needed to provide sufficient coverage for the metagenomic samples with high host-to-microbe DNA ratio. Additionally, the long reads generated by ONT adaptive sequencing retained the continuity of read information, which benefited the in-depth annotations for both taxonomical and functional profiles of the metagenome. The different methods resulted in the identification of different taxa. Genera Clostridium, which was identified at low abundances and categorized under Order "Unclassified Clostridiales" when using the 16S rDNA amplicon sequencing method, was identified to be the dominant genera in the sample when sequenced with the three other methods. Additionally, higher numbers of annotated genes were identified with ONT adaptive sequencing, which also produced high coverage on most of the commonly annotated genes. This study illustrates the advantages of ONT adaptive sequencing in improving the amount of metagenomic data derived from microbiome samples with high host-to-microbe DNA ratio and the advantage of long reads in preserving intact information for accurate annotations.

Genomic prediction using low-coverage portable Nanopore sequencing

Most traits in livestock, crops and humans are polygenic, that is, a large number of loci contribute to genetic variation. Effects at these loci lie along a continuum ranging from common low-effect to rare high-effect variants that cumulatively contribute to the overall phenotype. Statistical methods to calculate the effect of these loci have been developed and can be used to predict phenotypes in new individuals. In agriculture, these methods are used to select superior individuals using genomic breeding values; in humans these methods are used to quantitatively measure an individual’s disease risk, termed polygenic risk scores. Both fields typically use SNP array genotypes for the analysis. Recently, genotyping-by-sequencing has become popular, due to lower cost and greater genome coverage (including structural variants). Oxford Nanopore Technologies’ (ONT) portable sequencers have the potential to combine the benefits genotyping-by-sequencing with portability and decreased turn-around time. This introduces the potential for in-house clinical genetic disease risk screening in humans or calculating genomic breeding values on-farm in agriculture. Here we demonstrate the potential of the later by calculating genomic breeding values for four traits in cattle using low-coverage ONT sequence data and comparing these breeding values to breeding values calculated from SNP arrays. At sequencing coverages between 2X and 4X the correlation between ONT breeding values and SNP array-based breeding values was > 0.92 when imputation was used and > 0.88 when no imputation was used. With an average sequencing coverage of 0.5x the correlation between the two methods was between 0.85 and 0.92 using imputation, depending on the trait. This suggests that ONT sequencing has potential for in clinic or on-farm genomic prediction, however, further work to validate these findings in a larger population still remains.

Regional Anesthesia Use in Pediatric Burn Surgery: A Descriptive Retrospective Series

Pediatric burns are a common and often devastating injury. Treatment, reconstruction, and rehabilitation are painful experiences. For some, the experience triggers post-traumatic stress disorder and/or a chronic pain syndrome. Given the role pain plays as a major secondary disease, it must be addressed to achieve optimal healing. Regional anesthesia has been used extensively to manage postoperative pain and reduce the need for opioids following other surgical procedures in children. However, regional anesthesia is not widely used in pediatric burn care. We present a descriptive, retrospective case series of 15 pediatric burn patients who received regional anesthesia as part of their intra-operative pain management. In our patient population, we saw low levels of anesthetic as well as opioid usage with well-controlled pain. In this cohort, 93% of patients scored a 0/10 on the Face, Legs, Activity, Cry and Consolability (FLACC) scale for pain by post-anesthesia care unit (PACU) discharge, with an average PACU stay of 70 minutes. Thirty-three percent of patients received no opioids, with the average opioid dose being 0.06mg/kg morphine equivalents. This case series serves to make clinicians aware of the feasibility of use and benefits of regional anesthesia in pediatric burn patients requiring operative repair.

An Epigenetic Aging Clock for Cattle Using Portable Sequencing Technology

Extensively grazed cattle are often mustered only once a year. Therefore, birthdates are typically unknown or inaccurate. Birthdates would be useful for deriving important traits (growth rate; calving interval), breed registrations, and making management decisions. Epigenetic clocks use methylation of DNA to predict an individual's age. An epigenetic clock for cattle could provide a solution to the challenges of industry birthdate recording. Here we derived the first epigenetic clock for tropically adapted cattle using portable sequencing devices from tail hair, a tissue which is widely used in industry for genotyping. Cattle (n = 66) with ages ranging from 0.35 to 15.7 years were sequenced using Oxford Nanopore Technologies MinION and methylation was called at CpG sites across the genome. Sites were then filtered and used to calculate a covariance relationship matrix based on methylation state. Best linear unbiased prediction was used with 10-fold cross validation to predict age. A second methylation relationship matrix was also calculated that contained sites associated with genes used in the dog and human epigenetic clocks. The correlation between predicted age and actual age was 0.71 for all sites and 0.60 for dog and human gene epigenetic clock sites. The mean absolute deviation was 1.4 years for animals aged less than 3 years of age, and 1.5 years for animals aged 3-10 years. This is the first reported epigenetic clock using industry relevant samples in cattle.

A linkage disequilibrium-based approach to position unmapped SNPs in crop species

BACKGROUND

High-density SNP arrays are now available for a wide range of crop species. Despite the development of many tools for generating genetic maps, the genome position of many SNPs from these arrays is unknown. Here we propose a linkage disequilibrium (LD)-based algorithm to allocate unassigned SNPs to chromosome regions from sparse genetic maps. This algorithm was tested on sugarcane, wheat, and barley data sets. We calculated the algorithm's efficiency by masking SNPs with known locations, then assigning their position to the map with the algorithm, and finally comparing the assigned and true positions.

RESULTS

In the 20-fold cross-validation, the mean proportion of masked mapped SNPs that were placed by the algorithm to a chromosome was 89.53, 94.25, and 97.23% for sugarcane, wheat, and barley, respectively. Of the markers that were placed in the genome, 98.73, 96.45 and 98.53% of the SNPs were positioned on the correct chromosome. The mean correlations between known and new estimated SNP positions were 0.97, 0.98, and 0.97 for sugarcane, wheat, and barley. The LD-based algorithm was used to assign 5920 out of 21,251 unpositioned markers to the current Q208 sugarcane genetic map, representing the highest density genetic map for this species to date.

CONCLUSIONS

Our LD-based approach can be used to accurately assign unpositioned SNPs to existing genetic maps, improving genome-wide association studies and genomic prediction in crop species with fragmented and incomplete genome assemblies. This approach will facilitate genomic-assisted breeding for many orphan crops that lack genetic and genomic resources.

Piloting a New Curriculum: Guided At-Home Pediatric Regional Anesthesia Education Using a Portable Ultrasound

Ultrasound-guided regional anesthesia is the standard of care for most regional blocks in pediatric anesthesiology.Training programs must educate physicians to perform regional blocks safely and efficiently. Hands-on learning with simulation and live models is the gold standard. The coronavirus disease 2019 (COVID-19) pandemic has greatly hampered our ability to safely hold in-person workshops. We describe an at-home, guided virtual workshop using portable ultrasound to safely continue experiential trainee education.

The primary objective of this pilot virtual workshop was to develop an effective experiential learning program without the need for live child models. The main goal was to give trainees hands-on experience obtaining anatomical ultrasound images necessary for regional anesthesia blocks in a guided-virtual setting and to evaluate the effectiveness of skills acquisition. This workshop included two pediatric anesthesiology fellows and a pediatric anesthesiologist.

Trainees were instructed on ultrasound-guided regional block acquisition. For two weeks, trainees acquired images/movies of regional block anatomy at home using their own children. Virtual video assistance was available. Trainees then used acquired images/movies to discuss needle and local anesthetic placement with a pediatric regional anesthesiologist. Trainees completed pre- and post-workshop surveys assessing attitudes, perceived educational efficacy, and procedural skill acquisition. The faculty member also assessed trainees’ skills.

The virtual workshop was successful. Trainees expressed successful active learning and increased comfort in performing regional blocks on live patients. They correctly identified relevant anatomy of acquired images/movies, as well as needle and local anesthetic placement at the time of debriefing. Faculty were pleased with trainees’ initial performance of regional blocks.

Adapting an in-person workshop to an at-home guided experience is a safe, feasible, and well-received method for anesthesiology trainees to obtain experiential learning of ultrasound-guided regional anesthesia. This facilitated at-home learning experience allows for hands-on skill practice while preventing exposure of child models to the hospital setting during a pandemic.

Allelic Variation in Protein Tyrosine Phosphatase Receptor Type-C in Cattle Influences Erythrocyte, Leukocyte and Humoral Responses to Infestation With the Cattle Tick Rhipicephalus australis

The protein tyrosine phosphatase receptor type-C (PTPRC) gene encodes the common leukocyte antigen (CD45) receptor. CD45 affects cell adhesion, migration, cytokine signalling, cell development, and activation state. Four families of the gene have been identified in cattle: a taurine group (Family 1), two indicine groups (Families 2 and 4) and an African “taurindicine” group (Family 3). Host resistance in cattle to infestation with ticks is moderately heritable and primarily manifests as prevention of attachment and feeding by larvae. This study was conducted to describe the effects of PTPRC genotype on immune-response phenotypes in cattle that display a variable immune responsiveness to ticks. Thirty tick-naïve Santa-Gertrudis cattle (a stabilized composite of 5/8 taurine and 3/8 indicine) were artificially infested with ticks weekly for 13 weeks and ranked according to their tick counts. Blood samples were taken from control and tick-challenged cattle immediately before, then at 21 d after infestation and each subsequent week for 9 weeks. Assays included erythrocyte profiles, white blood cell counts, the percentage of cellular subsets comprising the peripheral blood mononuclear cell (PBMC) population, and the ability of PBMC to recognize and proliferate in response to stimulation with tick antigens in vitro. The cattle were PTPRC genotyped using a RFLP assay that differentiated Family 1 and 3 together (220 bp), from Family 2 (462 bp), and from Family 4 (486 bp). The PTPRC allele frequencies were Family 1/3 = 0.34; Family 2 = 0.47; Family 4 = 0.19. There was no significant association between PTPRC genotype and tick count. Each copy of the Family 1/3 allele significantly decreased total leucocyte count (WCC) and CD8⁺ cells. Increasing dosage of Family 2 alleles significantly increased red blood cell count (RCC), haematocrit (PCV), and haemoglobin (Hb) concentration in blood. Increasing dosage of the Family 4 allele was associated with increased WCC, reduced RCC, reduced PCV and reduced Hb. Homozygote Family 1/3 animals had consistently lower IgG1 in response to tick Ag than homozygote Family 2 animals. The PTPRC genotype influences the bovine immune response to ticks but was not associated with the observed variation in resistance to tick infestation in this study.

Improved genomic prediction of clonal performance in sugarcane by exploiting non-additive genetic effects

Non-additive genetic effects seem to play a substantial role in the expression of complex traits in sugarcane. Including non-additive effects in genomic prediction models significantly improves the prediction accuracy of clonal performance. In the recent decade, genetic progress has been slow in sugarcane. One reason might be that non-additive genetic effects contribute substantially to complex traits. Dense marker information provides the opportunity to exploit non-additive effects in genomic prediction. In this study, a series of genomic best linear unbiased prediction (GBLUP) models that account for additive and non-additive effects were assessed to improve the accuracy of clonal prediction. The reproducible kernel Hilbert space model, which captures non-additive genetic effects, was also tested. The models were compared using 3,006 genotyped elite clones measured for cane per hectare (TCH), commercial cane sugar (CCS), and Fibre content. Three forward prediction scenarios were considered to investigate the robustness of genomic prediction. By using a pseudo-diploid parameterization, we found significant non-additive effects that accounted for almost two-thirds of the total genetic variance for TCH. Average heterozygosity also had a major impact on TCH, indicating that directional dominance may be an important source of phenotypic variation for this trait. The extended-GBLUP model improved the prediction accuracies by at least 17% for TCH, but no improvement was observed for CCS and Fibre. Our results imply that non-additive genetic variance is important for complex traits in sugarcane, although further work is required to better understand the variance component partitioning in a highly polyploid context. Genomics-based breeding will likely benefit from exploiting non-additive genetic effects, especially in designing crossing schemes. These findings can help to improve clonal prediction, enabling a more accurate identification of variety candidates for the sugarcane industry.

Strategies and considerations for implementing genomic selection to improve traits with additive and non-additive genetic architectures in sugarcane breeding

Simulations highlight the potential of genomic selection to substantially increase genetic gain for complex traits in sugarcane. The success rate depends on the trait genetic architecture and the implementation strategy. Genomic selection (GS) has the potential to increase the rate of genetic gain in sugarcane beyond the levels achieved by conventional phenotypic selection (PS). To assess different implementation strategies, we simulated two different GS-based breeding strategies and compared genetic gain and genetic variance over five breeding cycles to standard PS. GS scheme 1 followed similar routines like conventional PS but included three rapid recurrent genomic selection (RRGS) steps. GS scheme 2 also included three RRGS steps but did not include a progeny assessment stage and therefore differed more fundamentally from PS. Under an additive trait model, both simulated GS schemes achieved annual genetic gains of 2.6-2.7% which were 1.9 times higher compared to standard phenotypic selection (1.4%). For a complex non-additive trait model, the expected annual rates of genetic gain were lower for all breeding schemes; however, the rates for the GS schemes (1.5-1.6%) were still greater than PS (1.1%). Investigating cost-benefit ratios with regard to numbers of genotyped clones showed that substantial benefits could be achieved when only 1500 clones were genotyped per 10-year breeding cycle for the additive genetic model. Our results show that under a complex non-additive genetic model, the success rate of GS depends on the implementation strategy, the number of genotyped clones and the stage of the breeding program, likely reflecting how changes in QTL allele frequencies change additive genetic variance and therefore the efficiency of selection. These results are encouraging and motivate further work to facilitate the adoption of GS in sugarcane breeding.

Accuracy of genomic prediction of complex traits in sugarcane

Complex traits in sugarcane can be accurately predicted using genome-wide DNA markers. Genomic single-step prediction is an attractive method for genomic selection in commercial breeding programs. Sugarcane breeding programs have achieved up to 1% genetic gain in key traits such as tonnes of cane per hectare (TCH), commercial cane sugar (CCS) and Fibre content over the past decades. Here, we assess the potential of genomic selection to increase the rate of genetic gain for these traits by deriving genomic estimated breeding values (GEBVs) from a reference population of 3984 clones genotyped for 26 K SNP. We evaluated the three different genomic prediction approaches GBLUP, genomic single step (GenomicSS), and BayesR. GenomicSS combining pedigree and SNP information from historic and recent breeding programs achieved the most accurate predictions for most traits (0.3-0.44). This method is attractive for routine genetic evaluation because it requires relatively little modification to the existing evaluation and results in breeding value estimates for all individuals, not only those genotyped. Adding information from early-stage trials added up to 5% accuracy for CCS and Fibre, but 0% for TCH, reflecting the importance of competition effects for TCH. These GEBV accuracies are sufficiently high that, combined with the right breeding strategy, a doubling of the rate of genetic gain could be achieved. We also assessed the flowering traits days to flowering, gender and pollen viability and found high heritabilities of 0.57, 0.78 and 0.72, respectively. The GEBV accuracies indicated that genomic selection could be used to improve these traits. This could open new avenues for breeders to manage their breeding programs, for example, by synchronising flowering time and selecting males with high pollen viability.

Variants at the ASIP locus contribute to coat color darkening in Nellore cattle

BACKGROUND

Nellore cattle (Bos indicus) are well-known for their adaptation to warm and humid environments. Hair length and coat color may impact heat tolerance. The Nellore breed has been strongly selected for white coat, but bulls generally exhibit darker hair ranging from light grey to black on the head, neck, hump, and knees. Given the potential contribution of coat color variation to the adaptation of cattle populations to tropical and sub-tropical environments, our aim was to map positional and functional candidate genetic variants associated with darkness of hair coat (DHC) in Nellore bulls.

RESULTS

We performed a genome-wide association study (GWAS) for DHC using data from 432 Nellore bulls that were genotyped for more than 777 k single nucleotide polymorphism (SNP) markers. A single major association signal was detected in the vicinity of the agouti signaling protein gene (ASIP). The analysis of whole-genome sequence (WGS) data from 21 bulls revealed functional variants that are associated with DHC, including a structural rearrangement involving ASIP (ASIP-SV1). We further characterized this structural variant using Oxford Nanopore sequencing data from 13 Australian Brahman heifers, which share ancestry with Nellore cattle; we found that this variant originates from a 1155-bp deletion followed by an insertion of a transposable element of more than 150 bp that may impact the recruitment of ASIP non-coding exons.

CONCLUSIONS

Our results indicate that the variant ASIP sequence causes darker coat pigmentation on specific parts of the body, most likely through a decreased expression of ASIP and consequently an increased production of eumelanin.

The Future of Livestock Management: A Review of Real-Time Portable Sequencing Applied to Livestock

Oxford Nanopore Technologies' MinION has proven to be a valuable tool within human and microbial genetics. Its capacity to produce long reads in real time has opened up unique applications for portable sequencing. Examples include tracking the recent African swine fever outbreak in China and providing a diagnostic tool for disease in the cassava plant in Eastern Africa. Here we review the current applications of Oxford Nanopore sequencing in livestock, then focus on proposed applications in livestock agriculture for rapid diagnostics, base modification detection, reference genome assembly and genomic prediction. In particular, we propose a future application: 'crush-side genotyping' for real-time on-farm genotyping for extensive industries such as northern Australian beef production. An initial in silico experiment to assess the feasibility of crush-side genotyping demonstrated promising results. SNPs were called from simulated Nanopore data, that included the relatively high base call error rate that is characteristic of the data, and calling parameters were varied to understand the feasibility of SNP calling at low coverages in a heterozygous population. With optimised genotype calling parameters, over 85% of the 10,000 simulated SNPs were able to be correctly called with coverages as low as 6×. These results provide preliminary evidence that Oxford Nanopore sequencing has potential to be used for real-time SNP genotyping in extensive livestock operations.

Genomic predictions for enteric methane production are improved by metabolome and microbiome data in sheep (Ovis aries)

Methane production from rumen methanogenesis contributes approximately 71% of greenhouse gas emissions from the agricultural sector. This study has performed genomic predictions for methane production from 99 sheep across 3 yr using a residual methane phenotype that is log methane yield corrected for live weight, rumen volume, and feed intake. Using genomic relationships, the prediction accuracies (as determined by the correlation between predicted and observed residual methane production) ranged from 0.058 to 0.220 depending on the time point being predicted. The best linear unbiased prediction algorithm was then applied to relationships between animals that were built on the rumen metabolome and microbiome. Prediction accuracies for the metabolome-based relationships for the two available time points were 0.254 and 0.132; the prediction accuracy for the first microbiome time point was 0.142. The second microbiome time point could not successfully predict residual methane production. When the metabolomic relationships were added to the genomic relationships, the accuracy of predictions increased to 0.274 (from 0.201 when only the genomic relationship was used) and 0.158 (from 0.081 when only the genomic relationship was used) for the two time points, respectively. When the microbiome relationships from the first time point were added to the genomic relationships, the maximum prediction accuracy increased to 0.247 (from 0.216 when only the genomic relationship was used), which was achieved by giving the genomic relationships 10 times more weighting than the microbiome relationships. These accuracies were higher than the genomic, metabolomic, and microbiome relationship matrixes achieved alone when identical sets of animals were used.

Use of whole-genome sequence data and novel genomic selection strategies to improve selection for age at puberty in tropically-adapted beef heifers

Background

In tropically-adapted beef heifers, application of genomic prediction for age at puberty has been limited due to low prediction accuracies. Our aim was to investigate novel methods of pre-selecting whole-genome sequence (WGS) variants and alternative analysis methodologies; including genomic best linear unbiased prediction (GBLUP) with multiple genomic relationship matrices (MGRM) and Bayesian (BayesR) analyses, to determine if prediction accuracy for age at puberty can be improved.

Methods

Genotypes and phenotypes were obtained from two research herds. In total, 868 Brahman and 960 Tropical Composite heifers were recorded in the first population and 3695 Brahman, Santa Gertrudis and Droughtmaster heifers were recorded in the second population. Genotypes were imputed to 23 million whole-genome sequence variants. Eight strategies were used to pre-select variants from genome-wide association study (GWAS) results using conditional or joint (COJO) analyses. Pre-selected variants were included in three models, GBLUP with a single genomic relationship matrix (SGRM), GBLUP MGRM and BayesR. Five-way cross-validation was used to test the effect of marker panel density (6 K, 50 K and 800 K), analysis model, and inclusion of pre-selected WGS variants on prediction accuracy.

Results

In all tested scenarios, prediction accuracies for age at puberty were highest in BayesR analyses. The addition of pre-selected WGS variants had little effect on the accuracy of prediction when BayesR was used. The inclusion of WGS variants that were pre-selected using a meta-analysis with COJO analyses by chromosome, fitted in a MGRM model, had the highest prediction accuracies in the GBLUP analyses, regardless of marker density. When the low-density (6 K) panel was used, the prediction accuracy of GBLUP was equal (0.42) to that with the high-density panel when only six additional sequence variants (identified using meta-analysis COJO by chromosome) were included.

Conclusions

While BayesR consistently outperforms other methods in terms of prediction accuracies, reasonable improvements in accuracy can be achieved when using GBLUP and low-density panels with the inclusion of a relatively small number of highly relevant WGS variants.

Characterization of the poll allele in Brahman cattle using long-read Oxford Nanopore sequencing

Brahman cattle (Bos indicus) are well adapted to thrive in tropical environments. Since their introduction to Australia in 1933, Brahman's ability to grow and reproduce on marginal lands has proven their value in the tropical beef industry. The poll phenotype, which describes the absence of horns, has become desirable in the cattle industry for animal welfare and handler safety concerns. The poll locus has been mapped to chromosome one. Four alleles, each a copy number variant, have been reported across this locus in B. indicus and Bos taurus. However, the causative mutation in Brahman cattle has not been fully characterized. Oxford Nanopore Technologies' minION sequencer was used to sequence four homozygous poll (PcPc), four homozygous horned (pp), and three heterozygous (Pcp) Brahmans to characterize the poll allele in Brahman cattle. A total of 98 Gb were sequenced and an average coverage of 3.33X was achieved. Read N50 scores ranged from 9.9 to 19 kb. Examination of the mapped reads across the poll locus revealed insertions approximately 200 bp in length in the poll animals that were absent in the horned animals. These results are consistent with the Celtic poll allele, a 212-bp duplication that replaces 10 bp. This provides direct evidence that the Celtic poll allele is segregating in the Australian Brahman population.

Metagenomics of rumen bacteriophage from thirteen lactating dairy cattle

BACKGROUND

The bovine rumen hosts a diverse and complex community of Eukarya, Bacteria, Archea and viruses (including bacteriophage). The rumen viral population (the rumen virome) has received little attention compared to the rumen microbial population (the rumen microbiome). We used massively parallel sequencing of virus like particles to investigate the diversity of the rumen virome in thirteen lactating Australian Holstein dairy cattle all housed in the same location, 12 of which were sampled on the same day.

RESULTS

Fourteen putative viral sequence fragments over 30 Kbp in length were assembled and annotated. Many of the putative genes in the assembled contigs showed no homology to previously annotated genes, highlighting the large amount of work still required to fully annotate the functions encoded in viral genomes. The abundance of the contig sequences varied widely between animals, even though the cattle were of the same age, stage of lactation and fed the same diets. Additionally the twelve animals which were co-habited shared a number of their dominant viral contigs. We compared the functional characteristics of our bovine viromes with that of other viromes, as well as rumen microbiomes. At the functional level, we found strong similarities between all of the viral samples, which were highly distinct from the rumen microbiome samples.

CONCLUSIONS

Our findings suggest a large amount of between animal variation in the bovine rumen virome and that co-habiting animals may have more similar viromes than non co-habited animals. We report the deepest sequencing to date of the rumen virome. This work highlights the enormous amount of novelty and variation present in the rumen virome.

Comparison of total 12-lead QRS voltage in a variety of cardiac conditions and its usefulness in predicting increased cardiac mass

Echocardiography provides a more accurate method to determine increased cardiac mass than does electrocardiography. Nevertheless, most offices of physicians do not possess echocardiographic machines, but many possess electrocardiographic machines. Many electrocardiographic criteria have been used to determine increased cardiac mass, but few of the criteria have been measured against cardiac weight determined at necropsy or after cardiac transplantation. Such was the purpose of the present study. Cardiac weight at necropsy or after transplantation was determined in 359 patients with 11 different cardiac conditions, and total 12-lead electrocardiographic QRS voltage (from the peak of the R wave to the nadir of either the Q or the S wave, whichever was deeper) was measured in each patient. Even in hearts with massively increased cardiac mass (>1,000 g), the total 12-lead QRS voltage was clearly increased (>175 mm) in only 94%, but this criterion was superior to that of previously described electrocardiographic criteria for "left ventricular hypertrophy." Hearts with excessive adipose tissue infrequently had increased total 12-lead QRS voltage despite increased cardiac weight. Likewise, patients with fatal cardiac amyloidosis had hearts of increased weight but quite low total 12-lead QRS voltage. In conclusion, 12-lead QRS voltage is useful in predicting increased cardiac mass, but that predictability is dependent in part on the cause of the increased cardiac mass.

Metagenomic predictions: from microbiome to complex health and environmental phenotypes in humans and cattle

Mammals have a large cohort of endo- and ecto- symbiotic microorganisms (the microbiome) that potentially influence host phenotypes. There have been numerous exploratory studies of these symbiotic organisms in humans and other animals, often with the aim of relating the microbiome to a complex phenotype such as body mass index (BMI) or disease state. Here, we describe an efficient methodology for predicting complex traits from quantitative microbiome profiles. The method was demonstrated by predicting inflammatory bowel disease (IBD) status and BMI from human microbiome data, and enteric greenhouse gas production from dairy cattle rumen microbiome profiles. The method uses unassembled massively parallel sequencing (MPS) data to form metagenomic relationship matrices (analogous to genomic relationship matrices used in genomic predictions) to predict IBD, BMI and methane production phenotypes with useful accuracies (r = 0.423, 0.422 and 0.466 respectively). Our results show that microbiome profiles derived from MPS can be used to predict complex phenotypes of the host. Although the number of biological replicates used here limits the accuracy that can be achieved, preliminary results suggest this approach may surpass current prediction accuracies that are based on the host genome. This is especially likely for traits that are largely influenced by the gut microbiota, for example digestive tract disorders or metabolic functions such as enteric methane production in cattle.

Development and evaluation of the nutrition component of the Rapid Eating and Activity Assessment for Patients (REAP): a new tool for primary care providers

OBJECTIVES

1. To describe the development of a dietary assessment tool (Rapid Eating and Activity Assessment for Patients [REAP]) that quickly assesses a patient's diet and physical activity and facilitates brief counselling by a primary care provider, and 2. To describe the evaluation of the REAP in terms of its reliability, validity, and ease of use by primary care providers.

DESIGN, SETTING AND PARTICIPANTS

The evaluation of REAP included: 1) an implementation feasibility study conducted with 61 medical students and practicing physicians in practice settings at various medical schools; 2) a calibration study with 44 Brown University Medical School students; 3) cognitive assessment testing with 31 consumers in Rhode Island; and 4) a reliability and calibration study of the revised tool with 94 consumers in Rhode Island and Massachusetts.

RESULTS

The feasibility study revealed moderately high rankings on usefulness, ease, practicality, and helpfulness. The calibration studies demonstrated that REAP has excellent test-retest reliability (r = 0.86, P < .0001), is correlated with the Healthy Eating Index score (r = 0.49, P = .0007), and is significantly associated with intake of most nutrients studied.

CONCLUSIONS AND IMPLICATIONS

REAP has adequate reliability and validity to be used in primary care practices for nutrition assessment and counselling, and is also user-friendly for providers.

Human herpesviruses-6 and -7 each cause significant neurological morbidity in Britain and Ireland

BACKGROUND

Primary human herpesvirus-6 and -7 (HHV-6/-7) infections cause febrile illness sometimes complicated by convulsions and rarely encephalopathy.

AIMS

To explore the extent of such HHV-6 and -7 induced disease in young children.

METHODS

In a three year prospective study in Britain and Ireland, 205 children (2-35 months old) hospitalised with suspected encephalitis and/or severe illness with fever and convulsions were reported via the British Paediatric Surveillance Unit network. Blood samples were tested for primary HHV-6 and -7 infections.

RESULTS

26/156 (17%) of children aged 2-23 months had primary infection (11 HHV-6; 13 HHV-7; two with both viruses) coinciding with the acute illness; this was much higher than the about three cases expected by chance. All 26 were pyrexial; 25 had convulsions (18 status epilepticus), 11 requiring ventilation. Median hospital stay was 7.5 days. For HHV-6 primary infection the median age was 53 weeks (range 42-94) and the distribution differed from that of uninfected children; for HHV-7, the median was 60 weeks (range 17-102) and the distribution did not differ for the uninfected. Fewer (5/15) children with primary HHV-7 infection had previously been infected with HHV-6 than expected.

CONCLUSIONS

Primary HHV-6 and HHV-7 infections accounted for a significant proportion of cases in those <2 years old of severe illness with fever and convulsions requiring hospital admission; each virus contributed equally. Predisposing factors are age for HHV-6 and no previous infection with HHV-6 for HHV-7. Children with such neurological disease should be investigated for primary HHV-6/-7 infections, especially in rare cases coinciding by chance with immunisation to exclude misdiagnosis as vaccine reactions.

Evaluation and treatment of iron deficiency in adults

Iron deficiency is prevalent in populations seen in primary practices. It is easily evaluated and treated, but often undiagnosed. Iron deficiency can lead not only to anemia but to decreased work capacity, abnormal neurotransmitter function, and altered immunologic and inflammatory defenses. Risk for iron deficiency is a function of iron loss, iron intake, iron absorption, and physiologic demands. Women of child-bearing age are at especially high risk for iron deficiency due to ongoing menstrual blood losses. This article presents and describes a simple algorithm incorporating dietary considerations for evaluation and treatment of iron deficiency in primary care settings.

Talking to patients about food insecurity

Food insecurity is highly prevalent in the United States. Even in the best of times, some 10% of the U.S. population self-reports food insecurity in the U.S. annual census instrument, and some 23.3 million Americans use the community-based emergency food system. Unemployed or underemployed individuals, the elderly, single parents, substance abusers, and uninsured or underinsured individuals with medical illnesses are at increased risk for food insecurity. This article discusses clinical approaches to food-insecure individuals. Measurement tools developed to define and document the extent of hunger and food insecurity in the U.S. population are presented as templates for discussion between doctor or dietitian and patient. Information is provided to help clinicians guide patients with food insecurity to appropriate resources.

RGSZ1 and Ret RGS: two of several splice variants from the gene RGS20

RGSZ1 and Ret RGS, members of the regulator of G-protein signaling (RGS) family, are GTPase-activating proteins (GAPs) with high selectivity for G alpha(z). We show here that RGSZ1 and Ret RGSZ1 are products of two of several splice variants of one gene, RGS20. RGS20 spans approximately 107 kb and contains at least seven exons. Five exons account for RGSZ1, including a single exon distinct to RGSZ1 that encodes a newly identified amino-terminal region. The previously described open reading frame (ORF) and 3' untranslated region are encoded by four downstream exons that also encode about half of Ret RGS. The 5' end of the RGSZ1 ORF contains several in-frame ATG codons (3-5 depending on the species), and multiple translational start sites may help explain the molecular weight heterogeneity of purified bovine brain RGSZ. Ret RGS replaces the 24 N-terminal amino acid residues of RGSZ1 with a large, N-terminal region that initially distinguished the bovine Ret RGS from human and mouse RGSZ1. This N-terminal domain is encoded by two distinct 5' exons that are variably combined with the four downstream exons shared with RGSZ1 to produce at least six mRNAs. They encode proteins with N termini that vary in size, hydrophobicity, and the presence of a cysteine string. At least two mRNAs that include the exon that encodes the N-terminal region unique to RGSZ1 were found in brain and a few other tissues, but not retina. RGS20 thus can account for multiple G(z)-selective GAPs in different tissues.

Binding of regulator of G protein signaling (RGS) proteins to phospholipid bilayers. Contribution of location and/or orientation to Gtpase-activating protein activity

Regulator of G protein signaling (RGS) proteins must bind membranes in an orientation that permits the protein-protein interactions necessary for regulatory activity. RGS4 binds to phospholipid surfaces in a slow, multistep process that leads to maximal GTPase-activating protein (GAP) activity. When RGS4 is added to phospholipid vesicles that contain m2 or m1 muscarinic receptor and G(i), G(z), or G(q), GAP activity increases approximately 3-fold over 4 h at 30 degrees C and more slowly at 20 degrees C. This increase in GAP activity is preceded by several other events that suggest that, after binding, optimal interaction with G protein and receptor requires reorientation of RGS4 on the membrane surface, a conformational change, or both. Binding of RGS4 is initially reversible but becomes irreversible within 5 min. Onset of irreversibility parallels initial quenching of tryptophan fluorescence (t(12) approximately 30 s). Further quenching occurs after binding has become irreversible (t(12) approximately 6 min) but is complete well before maximal GAP activity is attained. These processes all appear to be energetically driven by the amphipathic N-terminal domain of RGS4 and are accelerated by palmitoylation of cysteine residues in this region. The RGS4 N-terminal domain confers similar membrane binding behavior on the RGS domains of either RGS10 or RGSZ1.

GTPase-activating proteins for heterotrimeric G proteins: regulators of G protein signaling (RGS) and RGS-like proteins

GTPase-activating proteins (GAPs) regulate heterotrimeric G proteins by increasing the rates at which their subunits hydrolyze bound GTP and thus return to the inactive state. G protein GAPs act allosterically on G subunits, in contrast to GAPs for the Ras-like monomeric GTP-binding proteins. Although they do not contribute directly to the chemistry of GTP hydrolysis, G protein GAPs can accelerate hydrolysis >2000-fold. G protein GAPs include both effector proteins (phospholipase C-¿, p115RhoGEF) and a growing family of regulators of G protein signaling (RGS proteins) that are found throughout the animal and fungal kingdoms. GAP activity can sharpen the termination of a signal upon removal of stimulus, attenuate a signal either as a feedback inhibitor or in response to a second input, promote regulatory association of other proteins, or redirect signaling within a G protein signaling network. GAPs are regulated by various controls of their cellular concentrations, by complex interactions with G¿ or with G¿5 through an endogenous G-like domain, and by interaction with multiple other proteins.

Palmitoylation of a conserved cysteine in the regulator of G protein signaling (RGS) domain modulates the GTPase-activating activity of RGS4 and RGS10

RGS4 and RGS10 expressed in Sf9 cells are palmitoylated at a conserved Cys residue (Cys(95) in RGS4, Cys(66) in RGS10) in the regulator of G protein signaling (RGS) domain that is also autopalmitoylated when the purified proteins are incubated with palmitoyl-CoA. RGS4 also autopalmitoylates at a previously identified cellular palmitoylation site, either Cys(2) or Cys(12). The C2A/C12A mutation essentially eliminates both autopalmitoylation and cellular [(3)H]palmitate labeling of Cys(95). Membrane-bound RGS4 is palmitoylated both at Cys(95) and Cys(2/12), but cytosolic RGS4 is not palmitoylated. RGS4 and RGS10 are GTPase-activating proteins (GAPs) for the G(i) and G(q) families of G proteins. Palmitoylation of Cys(95) on RGS4 or Cys(66) on RGS10 inhibits GAP activity 80-100% toward either Galpha(i) or Galpha(z) in a single-turnover, solution-based assay. In contrast, when GAP activity was assayed as acceleration of steady-state GTPase in receptor-G protein proteoliposomes, palmitoylation of RGS10 potentiated GAP activity >/=20-fold. Palmitoylation near the N terminus of C95V RGS4 did not alter GAP activity toward soluble Galpha(z) and increased G(z) GAP activity about 2-fold in the vesicle-based assay. Dual palmitoylation of wild-type RGS4 remained inhibitory. RGS protein palmitoylation is thus multi-site, complex in its control, and either inhibitory or stimulatory depending on the RGS protein and its sites of palmitoylation.

Reciprocal signaling between heterotrimeric G proteins and the p21-stimulated protein kinase

p21-activated protein kinase (PAK)-1 phosphorylated Galpha(z), a member of the Galpha(i) family that is found in the brain, platelets, and adrenal medulla. Phosphorylation approached 1 mol of phosphate/mol of Galpha(z) in vitro. In transfected cells, Galpha(z) was phosphorylated both by wild-type PAK1 when stimulated by the GTP-binding protein Rac1 and by constitutively active PAK1 mutants. In vitro, phosphorylation occurred only at Ser(16), one of two Ser residues that are the major substrate sites for protein kinase C (PKC). PAK1 did not phosphorylate other Galpha subunits (i1, i2, i3, o, s, or q). PAK1-phosphorylated Galpha(z) was resistant both to RGSZ1, a G(z)-selective GTPase-activating protein (GAP), and to RGS4, a relatively nonselective GAP for the G(i) and G(q) families of G proteins. Phosphorylation of Ser(27) by PKC did not alter sensitivity to either GAP. The previously described inhibition of G(z) GAPs by PKC is therefore mediated by phosphorylation of Ser(16). Phosphorylation of either Ser(16) by PAK1 or Ser(27) by PKC decreased the affinity of Galpha(z) for Gbetagamma; phosphorylation of both residues by PKC caused no further effect. PAK1 thus regulates Galpha(z) function by attenuating the inhibitory effects of both GAPs and Gbetagamma. In this context, the kinase activity of PAK1 toward several protein substrates was directly inhibited by Gbetagamma, suggesting that PAK1 acts as a Gbetagamma-regulated effector protein. This inhibition of mammalian PAK1 by Gbetagamma contrasts with the stimulation of the PAK homolog Ste20p in Saccharomyces cerevisiae by the Gbetagamma homolog Ste4p/Ste18p.

Rapid GTP binding and hydrolysis by G(q) promoted by receptor and GTPase-activating proteins

Receptor-promoted GTP binding and GTPase-activating protein (GAP)-promoted GTP hydrolysis determine the onset and termination of G protein signaling; they coordinately control signal amplitude. The mechanisms whereby cells independently regulate signal kinetics and signal amplitude are therefore central to understanding G protein function. We have used quench-flow kinetic methods to measure the rates of the individual reactions of the agonist-stimulated GTPase cycle for G(q) during steady-state signaling. G(q) and m1 muscarinic cholinergic receptor were co-reconstituted into proteoliposomes with one of two GAPs: phospholipase C (PLC)-beta1, the major G(q)-regulated effector protein, and RGS4, a GAP commonly thought to be an inhibitor of G(q) signaling. In this system, the rate constant for GAP-stimulated hydrolysis of Galpha(q)-bound GTP at 30 degrees C was 9-12 s(-1) for PLC-beta1 and 22-27 s(-1) for RGS4. These rates are 1,000- to 2,000-fold faster than in the absence of a GAP and far faster than measured previously. G(q) can thus hydrolyze bound GTP with deactivation half-times of 25-75 ms at 30 degrees C, commensurate with physiological rates of signal termination. GDP/GTP exchange, which reactivates G(q), was the principal rate-limiting step for the GTPase cycle and was also faster than previously thought. At physiological concentrations of GTP, exchange was limited by the rate of dissociation of GDP from the receptor-G(q) complex, with a maximal rate of 1.8 s(-1) at 30 degrees C. Comparison of activation and deactivation rates help explain how GDP/GTP exchange balance rapid GTP hydrolysis to maintain steady-state signal amplitude.

Individualizing therapy to prevent long-term consequences of estrogen deficiency in postmenopausal women

BACKGROUND

Alendronate sodium and raloxifene hydrochloride were recently approved for the prevention of postmenopausal osteoporosis, but data on their clinical efficacy are limited. We compared these drugs with hormone replacement therapy (HRT) to help women and physicians guide postmenopausal treatment decisions.

OBJECTIVE

To help physicians understand how they can best help women choose the most beneficial therapy after menopause based on their individual risk profile.

METHODS

We developed a decision analytic Markov model to compare the effects of alendronate therapy, raloxifene therapy, and HRT on risks of hip fracture, coronary heart disease (CHD), breast cancer, and life expectancy. Regression models linked individual risk factors to future disease risks and were modified by drug effects on bone density, lipid levels, and associated breast cancer effects.

RESULTS

Hormone replacement therapy, alendronate therapy, and raloxifene therapy have similar predicted efficacies in preventing hip fractures (estimated relative risk, 0.57, 0.54, and 0.58, respectively). Hormone replacement therapy should be more than 10 times more effective than raloxifene therapy in preventing CHD, but raloxifene therapy may not induce breast cancer. Women at low risk for hip fracture, CHD, and breast cancer do not benefit significantly from any treatment. Among women at average risk, HRT was preferred unless raloxifene therapy could reduce the risk of breast cancer by at least 66%, compared with a 47% increase for HRT. Women at high risk for CHD benefit most from HRT; women at high risk for breast cancer but low risk for CHD benefit most from raloxifene therapy, but only if it lowers the risk of breast cancer.

CONCLUSION

Because of significant differences in the impact of these drugs, treatment choice depends on an individual woman's risk for hip fracture, CHD, and breast cancer.

Phospholipase C-beta1 directly accelerates GTP hydrolysis by Galphaq and acceleration is inhibited by Gbeta gamma subunits

Phospholipase C-beta, the principal effector protein regulated by Galphaq, has been shown to increase the agonist-stimulated, steady-state GTPase activity of Gq in proteoliposomes that contain both heterotrimeric Gq and m1 muscarinic receptor. We now use a moderately stable complex of R183C Galphaq bound to GTP to show that PLC-beta1 acts directly as a GTPase-activating protein (GAP) for isolated Galphaq in a membrane-free system. PLC-beta1 accelerated the hydrolysis of GalphaqR183C.GTP up to 20-fold. The Km was 1.5 nM, which is similar both to the EC50 with which R183C and wild type Galphaq activate PLC-beta1 and to the EC50 with which PLC-beta1 acts as a Gq GAP in the vesicle-based assay. The Galphaq GAP activity of RGS4 can also be quantitated by this assay; it accelerated hydrolysis of bound GTP about 100-fold. The Gq GAP activities of both PLC-beta1 and RGS4 are blocked by Gbeta gamma subunits, probably by a competitive mechanism. These data suggest either that the Gbeta gamma subunits are not continuously required for receptor-catalyzed GDP/GTP exchange during steady-state GTP hydrolysis or that GAPs, either PLC-beta or RGS proteins, can substitute for Gbeta gamma in this set of reactions.

Kinetic control of guanine nucleotide binding to soluble Galpha(q)

Binding of guanine nucleotides to heterotrimeric G proteins is controlled primarily by kinetic factors, such as the release of bound GDP, rather than by affinity alone. Detergent-solubilized Galpha(q) displays unusual guanine nucleotide binding properties in comparison with other G protein alpha subunits. Under conditions where most G proteins bind nearly stoichiometric GTPgammaS in 5-30 min at micromolar nucleotide concentrations, GTPgammaS binding to Galpha(q) is slow (>1 hr to completion), markedly substoichiometric, and dependent upon high concentrations of nucleotide (0.1 to 0.2 mM). Although the latter two properties suggest low affinity, GTPgammaS dissociation is immeasurably slow under commonly used conditions. We found that purified Galpha(q) can bind stoichiometric GTPgammaS, but that binding is controlled kinetically by a combination of factors. GDP (or IDP) dissociated slowly from Galpha(q), but the dissociation rate increased linearly with the concentration of (NH4)2SO4 up to 0.75 M (approximately 20-fold acceleration). The resulting GDP-free Galpha(q) was labile to rapid and irreversible denaturation, however (rate constant > or = 1 min(-1) at 20 degrees). Denaturation competed kinetically with relatively slow GTPgammaS association, such that stoichiometric binding was only attained at 100 microM GTPgammaS. These findings reconcile the slowly reversible binding of GTPgammaS to Galpha(q) with the other behaviors that suggested lower affinity, and point out that events subsequent to GDP dissociation can markedly influence the rates and extents of guanine nucleotide binding to G protein alpha subunits. Understanding these interactions allowed the direct, accurate quantitation of active Galpha(q) by a simple GTPgammaS binding assay in the presence of (NH4)2SO4, and similarly can prevent underestimation of the concentrations of other G proteins.

Modulation of the affinity and selectivity of RGS protein interaction with G alpha subunits by a conserved asparagine/serine residue

The crystal structure of the complex between a G protein alpha subunit (Gi alpha 1) and its GTPase-activating protein (RGS4) demonstrated that RGS4 acts predominantly by stabilization of the transition state for GTP hydrolysis [Tesmer, J. J., et al. (1997) Cell 89, 251]. However, attention was called to a conserved Asn residue (Asn128) that could play a catalytic role by interacting, directly or indirectly, with the hydrolytic water molecule. We have analyzed the effects of several disparate substitutions for Asn128 on the GAP activity of RGS4 toward four G alpha substrates (Go, Gi, Gq, and Gz) using two assay formats. The results substantiate the importance of this residue but indicate that it is largely involved in substrate binding and that its function may vary with different G alpha targets. Various mutations decreased the apparent affinity of RGS4 for substrate G alpha proteins by several orders of magnitude, but had variable and modest effects on maximal rates of GTP hydrolysis when tested with different G alpha subunits. One mutation, N128F, that differentially decreased the GAP activity toward G alpha i compared with that toward G alpha q could be partially suppressed by mutation of the nearby residue in G alpha i to that found in G alpha q (K180P). Detection of GAP activities of the mutants was enhanced in sensitivity up to 100-fold by assay at steady state in proteoliposomes that contain heterotrimeric G protein and receptor.

Fitting nutrition into the medical model: the role of decision analytic cost-effectiveness techniques

Physicians are accustomed to making decisions based on information regarding the prevalence of disease, symptoms, physical signs, laboratory test results, and the risks and benefits of alternative treatments. If nutritional assessment and therapeutics are to become more common components of medical practice, significant barriers in each of these areas must be overcome. Even rudimentary dietary assessment is often missing from physician education. Dietary assessment tools that are readily available and that have demonstrated usefulness are largely unknown. In addition, many nutritional interventions have not been formally investigated in randomized, controlled trials, and thus their cost-effectiveness remains unknown. We present one approach to these issues by discussing the construction of a decision model examining strategies for vitamin D and calcium screening. The application of medical decision making techniques to problems in clinical nutrition illustrates how findings from research studies may be used to determine the risks, benefits and costs of alternative population based health related nutrition policies which can then be applied by physicians in their daily interactions with patients.

The N-terminal domain of RGS4 confers receptor-selective inhibition of G protein signaling

Regulators of heterotrimeric G protein signaling (RGS) proteins are GTPase-activating proteins (GAPs) that accelerate GTP hydrolysis by Gq and Gi alpha subunits, thus attenuating signaling. Mechanisms that provide more precise regulatory specificity have been elusive. We report here that an N-terminal domain of RGS4 discriminated among receptor signaling complexes coupled via Gq. Accordingly, deletion of the N-terminal domain of RGS4 eliminated receptor selectivity and reduced potency by 10(4)-fold. Receptor selectivity and potency of inhibition were partially restored when the RGS4 box was added together with an N-terminal peptide. In vitro reconstitution experiments also indicated that sequences flanking the RGS4 box were essential for high potency GAP activity. Thus, RGS4 regulates Gq class signaling by the combined action of two domains: 1) the RGS box accelerates GTP hydrolysis by Galphaq and 2) the N terminus conveys high affinity and receptor-selective inhibition. These activities are each required for receptor selectivity and high potency inhibition of receptor-coupled Gq signaling.