Accuracy of 54K to HD gebotype imputation in Brown Swiss cattle

Imputation of genotypes can be used to reduce the implementation costs of genomic selection. In this study, we evaluated the accuracy of genotype imputation from Illumina 54k to Illumina High Density (HD) in Brown Swiss cattle. Genotype data comprised 6,106 54k and 880 HD genotyped bulls and cows of Brown Swiss and Original Braunvieh cattle. Genotype data was checked for parentage conflicts and SNP were excluded if MAF was below 0.5% and SNP call rate was lower than 90%. The final data set included 39,004 SNP for the 54k and 627,306 SNP for the HD chip. HD genotypes of animals born between 2004 and 2008 (n=365) were masked to mimic animals genotyped with the 54k chip. Methods used for imputation were FImpute and Findhap V2. Both programs use pedigree information for imputation. The accuracy of imputation was assessed by the correlation (r) between true and imputed genotypes, the percentage of correctly and incorrectly imputed genotypes. Both programs gave high imputation accuracy with FImpute outperforming Findhap. Accuracy of imputation increased with increasing relationship between the HD genotyped reference population and 54k genotyped imputation candidates. Average r for FImpute and Findhap were 0.992 and 0.988 when both parents of the 54k genotyped candidate were HD genotyped, respectively. Correlations were lower when no direct relatives were HD genotyped (0.971 and 0.918 for FImpute and Findhap, respectively). Accuracy of imputation highly depended on MAF of the imputed SNP. For FImpute, average r ranged between 0.89 (MAF <0.025) and 0.99 (MAF between 0.4 and 0.5)

Genome-wide association study for 13 udder traits from linear type classification in cattle

Udder conformation traits are known to correlate with the incidence of clinical mastitis and the length of productive life. The results of a genome-wide association study based on imputed high-density genotypes of 1,637 -Brown Swiss sires and de-regressed breeding values for 13 udder traits are presented here. For seven traits significant signals could be observed in five regions on BTA3, BTA5, BTA6, BTA17, and BTA25. For fore udder length and teats diameter significant SNPs were found in a known region around 90 Mb on BTA6. For the trait rear udder height significant SNPs are positioned in the coding region of the SNX29gene. Several significant SNPs around 62 Mb on BTA17 are associated with the traits rear udder width, frontteat placement and rear teat placement. The function of potential candidate genes and the influence of substructure will be addressed as next steps

Small molecule inhibitors of Late SV40 Factor (LSF) abrogate hepatocellular carcinoma (HCC): evaluation using an endogenous HCC model

Hepatocellular carcinoma (HCC) is a lethal malignancy with high mortality and poor prognosis. Oncogenic transcription factor Late SV40 Factor (LSF) plays an important role in promoting HCC. A small molecule inhibitor of LSF, Factor Quinolinone Inhibitor 1 (FQI1), significantly inhibited human HCC xenografts in nude mice without harming normal cells. Here we evaluated the efficacy of FQI1 and another inhibitor, FQI2, in inhibiting endogenous hepatocarcinogenesis. HCC was induced in a transgenic mouse with hepatocyte-specific overexpression of c-myc (Alb/c-myc) by injecting N-nitrosodiethylamine (DEN) followed by FQI1 or FQI2 treatment after tumor development. LSF inhibitors markedly decreased tumor burden in Alb/c-myc mice with a corresponding decrease in proliferation and angiogenesis. Interestingly, in vitro treatment of human HCC cells with LSF inhibitors resulted in mitotic arrest with an accompanying increase in CyclinB1. Inhibition of CyclinB1 induction by Cycloheximide or CDK1 activity by Roscovitine significantly prevented FQI-induced mitotic arrest. A significant induction of apoptosis was also observed upon treatment with FQI. These effects of LSF inhibition, mitotic arrest and induction of apoptosis by FQI1s provide multiple avenues by which these inhibitors eliminate HCC cells. LSF inhibitors might be highly potent and effective therapeutics for HCC either alone or in combination with currently existing therapies.The present study was supported in part by grants from The James S. McDonnell Foundation, National Cancer Institute Grant R01 CA138540-01A1 (DS), National Institutes of Health Grant R01 CA134721 (PBF), the Samuel Waxman Cancer Research Foundation (SWCRF) (DS and PBF), National Institutes of Health Grants R01 GM078240 and P50 GM67041 (SES), the Johnson and Johnson Clinical Innovation Award (UH), and the Boston University Ignition Award (UH). JLSW was supported by Alnylam Pharmaceuticals, Inc. DS is the Harrison Endowed Scholar in Cancer Research and Blick scholar. PBF holds the Thelma Newmeyer Corman Chair in Cancer Research. The authors acknowledge Dr. Lauren E. Brown (Dept. Chemistry, Boston University) for the synthesis of FQI1 and FQI2, and Lucy Flynn (Dept. Biology, Boston University) for initially identifying G2/M effects caused by FQI1. (James S. McDonnell Foundation; R01 CA138540-01A1 - National Cancer Institute; R01 CA134721 - National Institutes of Health; R01 GM078240 - National Institutes of Health; P50 GM67041 - National Institutes of Health; Samuel Waxman Cancer Research Foundation (SWCRF); Johnson and Johnson Clinical Innovation Award; Boston University Ignition Award; Alnylam Pharmaceuticals, Inc.)Published versio

Measuring the learning effectiveness of serious gaming for training of complex manufacturing tasks

© 2017, © The Author(s) 2017. Background. Training new workers on complex manufacturing tasks has long been a challenge for high value manufacturing companies. Equipment downtime, costly instructors, and dangerous working environments are some of the impediments of hands-on training. To overcome these hurdles, a traditional manufacturing paper manual was transformed into a serious game through capturing and embedding expert knowledge. Aim. This article investigates the learning effectiveness of learning via a serious game (Training Game) compared with the tradition learning method (Paper Manual) through a user study. Method. Twenty employees took part in a randomised controlled trial. They were assigned to one of two conditions: Training Game (experimental condition), or Paper Manual (control condition). Participants spent a maximum of 30 minutes to study manufacturing instructions before completing two tests to evaluate the amount of learning achieved. Results. The results show that the Training Game was more effective for learning procedu ral knowledge than the Paper Manual. Regarding factual knowledge, no significant difference was identified between the two conditions. In terms of motivation, increased engagement levels were reported in the Training Game condition. Conclusions. This user study shows evidence that the serious TG being evaluated is an effective method for training procedural knowledge in a complex manufacturing scenario

Optimizing Selection of the Reference Population for Genotype Imputation From Array to Sequence Variants

Imputation of high-density genotypes to whole-genome sequences (WGS) is a cost-effective method to increase the density of available markers within a population. Imputed genotypes have been successfully used for genomic selection and discovery of variants associated with traits of interest for the population. To allow for the use of imputed genotypes for genomic analyses, accuracy of imputation must be high. Accuracy of imputation is influenced by multiple factors, such as size and composition of the reference group, and the allele frequency of variants included. Understanding the use of imputed WGSs prior to the generation of the reference population is important, as accurate imputation might be more focused, for instance, on common or on rare variants. The aim of this study was to present and evaluate new methods to select animals for sequencing relying on a previously genotyped population. The Genetic Diversity Index method optimizes the number of unique haplotypes in the future reference population, while the Highly Segregating Haplotype selection method targets haplotype alleles found throughout the majority of the population of interest. First the WGSs of a dairy cattle population were simulated. The simulated sequences mimicked the linkage disequilibrium level and the variants’ frequency distribution observed in currently available Holstein sequences. Then, reference populations of different sizes, in which animals were selected using both novel methods proposed here as well as two other methods presented in previous studies, were created. Finally, accuracies of imputation obtained with different reference populations were compared against each other. The novel methods were found to have overall accuracies of imputation of more than 0.85. Accuracies of imputation of rare variants reached values above 0.50. In conclusion, if imputed sequences are to be used for discovery of novel associations between variants and traits of interest in the population, animals carrying novel information should be selected and, consequently, the Genetic Diversity Index method proposed here may be used. If sequences are to be used to impute the overall genotyped population, a reference population consisting of common haplotypes carriers selected using the proposed Highly Segregating Haplotype method is recommended

Comparison of variant calling methods for whole genome sequencing data in dairy cattle

Accurate identification of SNPs from next-generation sequencing data is crucial for high-quality downstream analysis. Whole genome sequence data of 65 key ancestors of genotyped Swiss dairy populations were available for investigation (24 billion reads, 96.8% mapped to UMD31, 12x coverage). Four publically available variant calling programmes were assessed and different levels of pre-calling handling for each method were tested and compared. SNP concordance was examined with Illumina’s BovineHD Genotyping BeadChip®. Depending on variant calling software used, between 16,894,054 and 22,048,382 SNP were identified (multi-sample calling). A total of 14,644,310 SNP were identified by all four variant callers (multi-sample calling). InDel counts ranged from 1,997,791 to 2,857,754; 1,708,649 InDels were identified by all four variant callers. A minimum of pre-calling data handling resulted in the highest non-reference sensitivity and the lowest non-reference discrepancy rates

Re-Livestock facilitating innovations for resilient livestock farming systems

Comunicación oral presentada en: 2023 ICAR Conference. Breeding for Resilience: Transitioning Diverse Livestock Farming Systems into the Future. Toledo, España, 21-26 mayo (2023

Novel genetic parameters for genetic residual feed intake in dairy cattle using time series data from multiple parities and countries in North America and Europe.

Residual feed intake is viewed as an important trait in breeding programs that could be used to enhance genetic progress in feed efficiency. In particular, improving feed efficiency could improve both economic and environmental sustainability in the dairy cattle industry. However, data remain sparse, limiting the development of reliable genomic evaluations across lactation and parity for residual feed intake. Here, we estimated novel genetic parameters for genetic residual feed intake (gRFI) across the first, second, and third parity, using a random regression model. Research data on the measured feed intake, milk production, and body weight of 7,379 cows (271,080 records) from 6 countries in 2 continents were shared through the Horizon 2020 project GenTORE and Resilient Dairy Genome Project. The countries included Canada (1,053 cows with 47,130 weekly records), Denmark (1,045 cows with 72,760 weekly records), France (329 cows with 16,888 weekly records), Germany (938 cows with 32,614 weekly records), the Netherlands (2,051 cows with 57,830 weekly records), and United States (1,963 cows with 43,858 weekly records). Each trait had variance components estimated from first to third parity, using a random regression model across countries. Genetic residual feed intake was found to be heritable in all 3 parities, with first parity being predominant (range: 22-34%). Genetic residual feed intake was highly correlated across parities for mid- to late lactation; however, genetic correlation across parities was lower during early lactation, especially when comparing first and third parity. We estimated a genetic correlation of 0.77 ± 0.37 between North America and Europe for dry matter intake at first parity. Published literature on genetic correlations between high input countries/continents for dry matter intake support a high genetic correlation for dry matter intake. In conclusion, our results demonstrate the feasibility of estimating variance components for gRFI across parities, and the value of sharing data on scarce phenotypes across countries. These results can potentially be implemented in genetic evaluations for gRFI in dairy cattle

A game prototype for understanding the safety issues of a lifeboat launch

© 2018 The Author(s) Novel, advanced game techniques provide us with new possibilities to mimic a complicated training process, with the added benefit of enhanced safety. In this paper, we design and implement a 3D game with the support of virtual reality equipment which imitates the process of a lifeboat launch, involving both tractor manoeuvres and boat operations. It is a complex but vital process which can save lives at sea but also has many potential hazards. The primary objective of the game is to allow novices to better understand the sequence of the operations and manage the potential risks which may occur during the launch process. Additionally, the game has been promoted to the general public for educational purposes and to raise awareness of the safety issues involved. The key modules of the game are designed based on physical simulations to give the players enhanced plausible cognition and enjoyable interaction. We conducted two case studies for the two purposes of the games: one for training with volunteers without launching experience and the other for public awareness of the potential hazards with young children. The game is proven to be very promising for future professional training, and it serves the educational purpose of awareness of the safety issues for general public while being entertaining

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