Retrieval analysis of ceramic-coated metal-on-polyethylene total hip replacements

PURPOSE: Ceramic coatings have been used in metal-on-polyethylene (MOP) hips to reduce the risk of wear and also infection; the clinical efficacy of this remains unclear. This retrieval study sought to better understand the performance of coated bearing surfaces. METHODS: Forty-three coated MOP components were analysed post-retrieval for evidence of coating loss and gross polyethylene wear. Coating loss was graded using a visual semi-quantitative protocol. Evidence of gross polyethylene wear was determined by radiographic analysis and visual inspection of the retrieved implants. RESULTS: All components with gross polyethylene wear (n = 10) were revised due to a malfunctioning acetabular component; 35 % (n = 15) of implants exhibited visible coating loss and the incidence of polyethylene wear in samples with coating loss was 54 %, significantly (p = 0.02) elevated compared to samples with intact coatings (14 %). CONCLUSIONS: In this study we found evidence of coating loss on metal femoral heads which was associated with increased wear of the corresponding polyethylene acetabular cups

Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example

© The Author(s) 2017 This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Most agronomic traits of interest for crop improvement (including seed yield) are highly complex quantitative traits controlled by numerous genetic loci, which brings challenges for comprehensively capturing associated markers/ genes. We propose that multiple trait interactions underlie complex traits such as seed yield, and that considering these component traits and their interactions can dissect individual quantitative trait loci (QTL) effects more effectively and improve yield predictions. Using a segregating rapeseed (Brassica napus) population, we analyzed a large set of trait data generated in 19 independent experiments to investigate correlations between seed yield and other complex traits, and further identified QTL in this population with a SNP-based genetic bin map. A total of 1904 consensus QTL accounting for 22 traits, including 80 QTL directly affecting seed yield, were anchored to the B. napus reference sequence. Through trait association analysis and QTL meta-analysis, we identified a total of 525 indivisible QTL that either directly or indirectly contributed to seed yield, of which 295 QTL were detected across multiple environments. A majority (81.5%) of the 525 QTL were pleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrasting genetic effects, as well as 31 QTL with minor complementary effects. Implementation of the 525 QTL in genomic prediction models improved seed yield prediction accuracy. Dissecting the genetic and phenotypic interrelationships underlying complex quantitative traits using this method will provide valuable insights for genomics-based crop improvement.Peer reviewedFinal Published versio

Agricultural and socioeconomic factors associated with farmer household dietary diversity in India: A comparative study of Visakhapatnam and Sonipat

This is the final version. Available on open access from MDPI via the DOI in this record. Data Availability Statement: The datasets used and/or analyzed during the current study are available with CCDC, and can be obtained from Sailesh Mohan (co-author) on reasonable request.Using primary data from 479 farmer households, this study examined the associations between agricultural and socioeconomic factors and farmer household dietary diversity in Visakhapatnam and Sonipat. Cropping intensity was positively associated with farmers’ household dietary diversity score (HDDS), suggesting that higher cropping intensity may expand the gross cropped area and improve food security among subsistence farmers. Distance to food markets was also significantly associated with farmer HDDS, which suggests that market integration with rural households can improve farmer HDDS in Visakhapatnam. In Sonipat, wealth index had a positive association with farmer HDDS, targeting the income pathway by improving farmer HDDS in this region. Considering the relative contribution of these factors, distance to food markets, cropping intensity, and crop diversity were the three most important factors affecting farmer HDDS in Visakhapatnam, whereas wealth index, cropping intensity, and distance to food markets emerged as the top three important factors contributing to farmer HDDS in Sonipat. Our study concludes that the associations between agricultural and socioeconomic factors and farmer HDDS are complex but context- and location-specific; therefore, considering the site- and context-specific circumstances, different connections to HDDS in India can be found to better support policy priorities on the ground.Wellcome Trus

Assignment of chromosomal locations for unassigned SNPs/scaffolds based on pair-wise linkage disequilibrium estimates

<p>Abstract</p> <p>Background</p> <p>Recent developments of high-density SNP chips across a number of species require accurate genetic maps. Despite rapid advances in genome sequence assembly and availability of a number of tools for creating genetic maps, the exact genome location for a number of SNPs from these SNP chips still remains unknown. We have developed a locus ordering procedure based on linkage disequilibrium (LODE) which provides estimation of the chromosomal positions of unaligned SNPs and scaffolds. It also provides an alternative means for verification of genetic maps. We exemplified LODE in cattle.</p> <p>Results</p> <p>The utility of the LODE procedure was demonstrated using data from 1,943 bulls genotyped for 73,569 SNPs across three different SNP chips. First, the utility of the procedure was tested by analysing the masked positions of 1,500 randomly-chosen SNPs with known locations (50 from each chromosome), representing three classes of minor allele frequencies (MAF), namely >0.05, 0.01<MAF ≤ 0.05 and 0.001<MAF ≤ 0.01. The efficiency (percentage of masked SNPs that could be assigned a location) was 96.7%, 30.6% and 2.0%; with an accuracy (the percentage of SNPs assigned correctly) of 99.9%, 98.9% and 33.3% in the three classes of MAF, respectively. The average precision for placement of the SNPs was 914, 3,137 and 6,853 kb, respectively. Secondly, 4,688 of 5,314 SNPs unpositioned in the Btau4.0 assembly were positioned using the LODE procedure. Based on these results, the positions of 485 unordered scaffolds were determined. The procedure was also used to validate the genome positions of 53,068 SNPs placed on Btau4.0 bovine assembly, resulting in identification of problem areas in the assembly. Finally, the accuracy of the LODE procedure was independently validated by comparative mapping on the hg18 human assembly.</p> <p>Conclusion</p> <p>The LODE procedure described in this study is an efficient and accurate method for positioning SNPs (MAF>0.05), for validating and checking the quality of a genome assembly, and offers a means for positioning of unordered scaffolds containing SNPs. The LODE procedure will be helpful in refining genome sequence assemblies, especially those being created from next-generation sequencing where high-throughput SNP discovery and genotyping platforms are integrated components of genome analysis.</p

Food insecurity and its determinants among adults in North and South India.

This is the final version. Available from BMC via the DOI in this record. Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.BACKGROUND: Food insecurity is a major public health problem worldwide. In India, there are limited food insecurity assessment studies using a conventionally accepted method like the Food Insecurity Experience Scale (FIES), developed by the Food and Agricultural Organization (FAO). This study aims to measure food insecurity using the FIES and explore its determinants and association with body mass index (BMI) among Indian adults.  METHODS: In a cross-sectional study, we used FIES to measure food security in a sample of 9005 adults residing in North and South India. Using questionnaires, socio-demographic factors, dietary intake and food security data were collected. The dietary diversity scores (FAO-IDDS) and food insecurity scores (FAO-FIES) were calculated. Body size was measured and BMI was calculated.  RESULTS: The mean age of the study participants was 52.4 years (± 11.7); half were women and half resided in rural areas. Around 10% of the participants reported having experienced (mild or moderate or severe) food insecurity between October 2018 and February 2019. Dietary diversity (measured by FAO's Individual Dietary Diversity Scores, IDDS) was low and half of the participants consumed ≤ 3 food groups/day. The mean BMI was 24.7 kg/m2. In the multivariate analysis, a lower IDDS and BMI were associated with a higher FIES. The place of residence, gender and wealth index were important determinants of FIES, with those residing in South India, women and those belonging to the poorest wealth index reporting higher food insecurity. CONCLUSION: Food security is understudied in India. Our study adds important evidence to the literature. Despite having marginal food insecurity, high prevalence of low diet quality, especially among women, is disconcerting. Similar studies at the national level are warranted to determine the food insecurity situation comprehensively in India and plan appropriate policy actions to address it effectively, to attain the key Sustainable Development Goals (SDG).Wellcome TrustEli Lille

Estimating genetic diversity across the neutral genome with the use of dense marker maps

<p>Abstract</p> <p>Background</p> <p>With the advent of high throughput DNA typing, dense marker maps have become available to investigate genetic diversity on specific regions of the genome. The aim of this paper was to compare two marker based estimates of the genetic diversity in specific genomic regions lying in between markers: IBD-based genetic diversity and heterozygosity.</p> <p>Methods</p> <p>A computer simulated population was set up with individuals containing a single 1-Morgan chromosome and 1665 SNP markers and from this one, an additional population was produced with a lower marker density i.e. 166 SNP markers. For each marker interval based on adjacent markers, the genetic diversity was estimated either by IBD probabilities or heterozygosity. Estimates were compared to each other and to the true genetic diversity. The latter was calculated for a marker in the middle of each marker interval that was not used to estimate genetic diversity.</p> <p>Results</p> <p>The simulated population had an average minor allele frequency of 0.28 and an LD (r²) of 0.26, comparable to those of real livestock populations. Genetic diversities estimated by IBD probabilities and by heterozygosity were positively correlated, and correlations with the true genetic diversity were quite similar for the simulated population with a high marker density, both for specific regions (r = 0.19-0.20) and large regions (r = 0.61-0.64) over the genome. For the population with a lower marker density, the correlation with the true genetic diversity turned out to be higher for the IBD-based genetic diversity.</p> <p>Conclusions</p> <p>Genetic diversities of ungenotyped regions of the genome (i.e. between markers) estimated by IBD-based methods and heterozygosity give similar results for the simulated population with a high marker density. However, for a population with a lower marker density, the IBD-based method gives a better prediction, since variation and recombination between markers are missed with heterozygosity.</p

Accuracy of direct genomic values in Holstein bulls and cows using subsets of SNP markers

Background: At the current price, the use of high-density single nucleotide polymorphisms (SNP) genotyping assays in genomic selection of dairy cattle is limited to applications involving elite sires and dams. The objective of this study was to evaluate the use of low-density assays to predict direct genomic value (DGV) on five milk production traits, an overall conformation trait, a survival index, and two profit index traits (APR, ASI). Methods. Dense SNP genotypes were available for 42,576 SNP for 2,114 Holstein bulls and 510 cows. A subset of 1,847 bulls born between 1955 and 2004 was used as a training set to fit models with various sets of pre-selected SNP. A group of 297 bulls born between 2001 and 2004 and all cows born between 1992 and 2004 were used to evaluate the accuracy of DGV prediction. Ridge regression (RR) and partial least squares regression (PLSR) were used to derive prediction equations and to rank SNP based on the absolute value of the regression coefficients. Four alternative strategies were applied to select subset of SNP, namely: subsets of the highest ranked SNP for each individual trait, or a single subset of evenly spaced SNP, where SNP were selected based on their rank for ASI, APR or minor allele frequency within intervals of approximately equal length. Results: RR and PLSR performed very similarly to predict DGV, with PLSR performing better for low-density assays and RR for higher-density SNP sets. When using all SNP, DGV predictions for production traits, which have a higher heritability, were more accurate (0.52-0.64) than for survival (0.19-0.20), which has a low heritability. The gain in accuracy using subsets that included the highest ranked SNP for each trait was marginal (5-6%) over a common set of evenly spaced SNP when at least 3,000 SNP were used. Subsets containing 3,000 SNP provided more than 90% of the accuracy that could be achieved with a high-density assay for cows, and 80% of the high-density assay for young bulls. Conclusions: Accurate genomic evaluation of the broader bull and cow population can be achieved with a single genotyping assays containing ∼ 3,000 to 5,000 evenly spaced SNP

Commercial chicken breeds exhibit highly divergent patterns of linkage disequilibrium

The analysis of linkage disequilibrium (LD) underpins the development of effective genotyping technologies, trait mapping and understanding of biological mechanisms such as those driving recombination and the impact of selection. We apply the Malécot-Morton model of LD to create additive LD maps that describe the high-resolution LD landscape of commercial chickens. We investigated LD in chickens (Gallus gallus) at the highest resolution to date for broiler, white egg and brown egg layer commercial lines. There is minimal concordance between breeds of fine-scale LD patterns (correlation coefficient &lt;0.21), and even between discrete broiler lines. Regions of LD breakdown, which may align with recombination hot spots, are enriched near CpG islands and transcription start sites (P&lt;2.2 × 10?16), consistent with recent evidence described in finches, but concordance in hot spot locations between commercial breeds is only marginally greater than random. As in other birds, functional elements in the chicken genome are associated with recombination but, unlike evidence from other bird species, the LD landscape is not stable in the populations studied. The development of optimal genotyping panels for genome-led selection programmes will depend on careful analysis of the LD structure of each line of interest. Further study is required to fully elucidate the mechanisms underlying highly divergent LD patterns found in commercial chickens

A high density linkage map of the bovine genome

<p>Abstract</p> <p>Background</p> <p>Recent technological advances have made it possible to efficiently genotype large numbers of single nucleotide polymorphisms (SNPs) in livestock species, allowing the production of high-density linkage maps. Such maps can be used for quality control of other SNPs and for fine mapping of quantitative trait loci (QTL) via linkage disequilibrium (LD).</p> <p>Results</p> <p>A high-density bovine linkage map was constructed using three types of markers. The genotypic information was obtained from 294 microsatellites, three milk protein haplotypes and 6769 SNPs. The map was constructed by combining genetic (linkage) and physical information in an iterative mapping process. Markers were mapped to 3,155 unique positions; the 6,924 autosomal markers were mapped to 3,078 unique positions and the 123 non-pseudoautosomal and 19 pseudoautosomal sex chromosome markers were mapped to 62 and 15 unique positions, respectively. The linkage map had a total length of 3,249 cM. For the autosomes the average genetic distance between adjacent markers was 0.449 cM, the genetic distance between unique map positions was 1.01 cM and the average genetic distance (cM) per Mb was 1.25.</p> <p>Conclusion</p> <p>There is a high concordance between the order of the SNPs in our linkage map and their physical positions on the most recent bovine genome sequence assembly (Btau 4.0). The linkage maps provide support for fine mapping projects and LD studies in bovine populations. Additionally, the linkage map may help to resolve positions of unassigned portions of the bovine genome.</p