Impact of genotypic errors with equal and unequal family contribution on accuracy of genomic prediction in aquaculture using simulation.

Genotypic errors, conflict between recorded genotype and the true genotype, can lead to false or biased population genetic parameters. Here, the effect of genotypic errors on accuracy of genomic predictions and genomic relationship matrix are investigated using a simulation study based on population and genomic structure comparable to black tiger prawn, Penaeus monodon. Fifty full-sib families across five generations with phenotypic and genotypic information on 53 K SNPs were simulated. Ten replicates of different scenarios with three heritability estimates, equal and unequal family contributions were generated. Within each scenario, four SNP densities and three genotypic error rates in each SNP density were implemented. Results showed that family contribution did not have a substantial impact on accuracy of predictions across different datasets. In the absence of genotypic errors, 3 K SNP density was found to be efficient in estimating the accuracy, whilst increasing the SNP density from 3 to 20 K resulted in a marginal increase in accuracy of genomic predictions using the current population and genomic parameters. In addition, results showed that the presence of even 10% errors in a 10 and 20 K SNP panel might not have a severe impact on accuracy of predictions. However, below 10 K marker density, even a 5% error can result in lower accuracy of predictions.

SNP discovery and population structure analysis in Lassi and Marecha camel breeds using a genotyping by sequencing method.

Pakistani camels have been classified socio-geographically into 20 breeds, but they have not yet been subjected to substantial selective pressures and the genetic basis for these breeds is not understood. However, it should be possible to distinguish them by use of molecular data. This study investigated the genetic diversity and population structure within and between two major Pakistani camel breeds, Marecha and Lassi. As no SNP array is currently available, we first identified 63 619 SNPs using a genotyping by sequencing approach. After quality control, a panel of 36 926 SNPs was used in the analysis. Population structure was investigated with a principal coordinate analysis as well as a cluster analysis using NetView, and multilocus heterozygosity analysis to explore between- and within-breed genetic variation. In addition, between-breed variation was explored using the fixation index, FST . We also compared relationship matrices computed using the VanRaden SNP-based method and a method developed specifically for genotyping by sequencing data. Among the two camel breeds, Lassi showed a lower level of genetic diversity whereas Marecha showed a higher level. As a genotyping platform has not yet been developed for the camel, the SNPs discovered in this study will be useful in future genetic studies in camels.

Copy number variation and variant discovery in Bullmastiff dogs.

Identification of genomic variants within dogs is important for understanding genetic factors contributing to breed diversity and phenotypic traits. This study aimed to identify sources of variation in the Bullmastiff using high-density signal intensity and whole-genome sequence data. Close to 3000 copy number variants (CNVs) were identified in Bullmastiff dogs using Canine HD BeadChip data. When CNVs were collated, 82 CNV regions (CNVRs) were detected, 50% in transcribed regions encompassing 432 genes. Fifty of the CNVRs detected have not been reported in other breeds and represent potential breed-specific variants. A proportion of the CNVR variants with predicted modifying effects on gene pathways may contribute to breed traits. Approximately 5 million putative variants per dog, inclusive of single nucleotide polymorphisms (SNPs), multi-nucleotide polymorphisms (MNPs) and insertion and deletions (INDELs), were identified from DNA sequence data on a small number of animals. Identification of genetic variants in the Bullmastiff highlights sources of variation in the breed and molecular markers that will assist in future trait and disease investigations in dogs.

Estimation of the health and economic burden of human brucellosis in India.

High seroprevalence estimates of brucellosis in livestock species and humans in India suggest that the disease is a significant public health concern in the country. We developed an economic model and conducted an assessment of the impact of human brucellosis in India to describe the current situation to help formulate prevention and control strategies. Economic losses of human brucellosis were calculated based on the official records and the data from epidemiological surveys conducted in India. These data were used to estimate the disability adjusted life years (DALYs) due to human brucellosis. Uncertainty was incorporated in the model by applying probability distributions for certain input parameters. The analyses were further supplemented by conducting sensitivity analyses to determine which parameters had the biggest influence on the outcome of economic losses. The annual median losses due to human brucellosis were estimated to be Rs 627.5 million (uncertainty interval [95% UI] Rs 534.8-741.2 million; US $ 10.46 million) with a loss of Rs 442.3 million (95% UI 371.0-516.0; US $ 7.37 million) among adults and Rs 185.0 million (95% UI 124.0-255.0; US $ 3.08 million) among children. Human brucellosis in India caused a loss of 177 601 (95% UI 152 695-214 764) DALYs at the rate of 0.15 (95% UI 0.13-0.17) DALYs per thousand persons per year. The DALYs were found to be 0.29 (95% UI 0.08-0.70) per thousand persons per year in occupational and 0.13 (95% UI 0.06-0.18) in non-occupational adult population. This is the first systematic analysis of the health impact of human brucellosis in India and of indirect/production losses occurring due to human brucellosis anywhere in the world. The results indicate that brucellosis causes considerable economic losses and has a reasonable health impact, particularly among occupational groups. Intervention policies need to be strengthened to reduce the socio-economic impact of human brucellosis in India.

Estimation of the health and economic burden of neurocysticercosis in India.

Taenia solium is an endemic parasite in India which occurs in two forms in humans: cysticercosis (infection of soft tissues) and taeniosis (intestinal infection). Neurocysticercosis (NCC) is the most severe form of cysticercosis in which cysts develop in the central nervous system. This study was conducted to estimate health and economic impact due to human NCC-associated active epilepsy in India. Input data were sourced from published research literature, census data and other official records. Economic losses due to NCC-associated active epilepsy were estimated based on cost of treatment, hospitalisation and severe injury as well as loss of income. The disability-adjusted life years (DALYs) due to NCC were estimated by combining years of life lost due to early death and the number of years compromised due to disability taking the disease incidence into account. DALYs were estimated for five age groups, two genders and four regions, and then combined. To account for uncertainty, probability distributions were used for disease incidence data and other input parameters. In addition, sensitivity analyses were conducted to determine the impact of certain input parameters on health and economic estimates. It was estimated that in 2011, human NCC-associated active epilepsy caused an annual median loss of Rupees 12.03 billion (uncertainty interval [95% UI] Rs. 9.16-15.57 billion; US $ 185.14 million) with losses of Rs. 9.78 billion (95% UI Rs. 7.24-13.0 billion; US $ 150.56 million) from the North and Rs. 2.22 billion (95% UI Rs. 1.58-3.06 billion; US $ 34.14 million) from the South. The disease resulted in a total of 2.10 million (95% UI 0.99-4.10 million) DALYs per annum without age weighting and time discounting with 1.81 million (95% UI 0.84-3.57 million) DALYs from the North and 0.28 million (95% UI 0.13-0.55 million) from the South. The health burden per thousand persons per year was 1.73 DALYs (95% UI 0.82-3.39). The results indicate that human NCC causes significant health and economic impact in India. Programs for controlling the disease should be initiated to reduce the socio-economic impact of the disease in India.

Data and the associated R code used to estimate health and economic burden of neurocysticercosis in India.

This article contains epidemiological, demographic and other data used for estimating health and economic burden of neurocysticercosis (NCC)-associated active epilepsy in India [1]. Most of the data are embedded in the R-code used for analyses so that the reader is able to replicate the results or adapt the code to their own data. However, data used to conduct sensitivity analyses to evaluate the effect of changing important input values such as prevalence and per capita income on health and economic impact of NCC in India are included in tables. Results from sensitivity analyses are also presented in tables and figures. The paper also includes three scenarios with different age weighting (k) and time discounting (r) values used to estimate health and economic burden of NCC in India. The data for the scenario without any age weighting and time discounting are presented in "Estimation of the health and economic burden of neurocysticercosis in India" [1].

Additive and epistatic genome-wide association for growth and ultrasound scan measures of carcass-related traits in Brahman cattle.

Genome-wide association studies are routinely used to identify genomic regions associated with traits of interest. However, this ignores an important class of genomic associations, that of epistatic interactions. A genome-wide interaction analysis between single nucleotide polymorphisms (SNPs) using highly dense markers can detect epistatic interactions, but is a difficult task due to multiple testing and computational demand. However, It is important for revealing complex trait heredity. This study considers analytical methods that detect statistical interactions between pairs of loci. We investigated a three-stage modelling procedure: (i) a model without the SNP to estimate the variance components; (ii) a model with the SNP using variance component estimates from (i), thus avoiding iteration; and (iii) using the significant SNPs from (ii) for genome-wide epistasis analysis. We fitted these three-stage models to field data for growth and ultrasound measures for subcutaneous fat thickness in Brahman cattle. The study demonstrated the usefulness of modelling epistasis in the analysis of complex traits as it revealed extra sources of genetic variation and identified potential candidate genes affecting the concentration of insulin-like growth factor-1 and ultrasound scan measure of fat depth traits. Information about epistasis can add to our understanding of the complex genetic networks that form the fundamental basis of biological systems.

Predicting genetic merit for mastitis and fertility in dairy cattle using genome wide selection and high density SNP screens.

Two novel methods for genome wide selection (GWS) were examined for predicting the genetic merit of animals using SNP information alone. A panel of 1,546 dairy bulls with reliable EBVs was genotyped for 15,380 SNPs that spanned the whole bovine genome. Two complexity reduction methods were used, partial least squares (PLS) and regression using a genetic algorithm (GAR), to find optimal solutions of EBVs against SNP information. Extensive internal cross-validation was used tofind the best predictive models followed by external validation (without direct use of the pedigree or SNP location). Both PLS and GAR provided both accurate fit to the training data set for somatic cell count (SCC) (max r = 0.83) and fertility (max r = 0.88) and showed an accuracy of prediction of r = 0.47 for SCC, and r = 0.72 for fertility. This is the first empirical demonstration that genome wide selection can account for a very high proportion of additive genetic variation in fitness traits whilst exploiting only a small percentage of available SNP information, without use of pedigree or QTL mapping. PLS was computationally more efficient than GAR.

Genome-wide genetic diversity of Holstein Friesian cattle reveals new insights into Australian and global population variability, including impact of selection.

Past breeding strategies for dairy cattle have been very effective in producing rapid genetic gain to achieve industry targets and raise profitability. Such gains have been largely facilitated by intense selection of sires combined with the use of artificial insemination. However, this practice can potentially limit the level of genetic diversity through inbreeding and selection plateaus. The rate of inbreeding in Australia is increasing, primarily as a result of semen importation from a small number of prominent bulls from the USA. The effect of this genetic influx in the Australian dairy cattle population is poorly understood both in terms of diversity and local adaptation/divergence. This study uses 845 genome-wide SNP genetic markers and 431 bulls to characterize the level of genetic diversity and genetic divergence within the Australian and international Holstein Friesian dairy population. No significant differences in genetic diversity (as measured by heterozygosity [H(o)] and allelic richness [A]) were observed over the 25-year time period (1975-1999) for bulls used in Australia. The importation of foreign semen into Australia has increased the effective population size until it was in effect a sub-sample of the global population. Our data indicate that most individuals are equally closely related to one another, regardless of country of origin and year of birth. In effect, the global population can be considered as one single population unit. These results indicate that inbreeding, genetic drift and selection has had little effect at reducing genetic diversity and differentiating the Australian Holstein Friesian population at a genome-wide level.

Technical note: Whole-genome amplification of DNA extracted from cattle semen samples.

The bovine genome sequence project and the discovery of many thousands of bovine single nucleotide polymorphisms has opened the door for large-scale genotyping studies to identify genes that contribute to economically important traits with relevance to the beef and dairy industries. Large amounts of DNA will be required for these research projects. This study reports the use of the whole-genome amplification (WGA) method to create an unlimited supply of DNA for use in genotyping studies and long-term storage for future gene discovery projects. Two commercial WGA kits (GenomiPhi, Amersham Biosciences, Sydney, Australia, and REPLI-g, Qiagen, Doncaster, Australia) were used to amplify DNA from straws of bull semen, resulting in an average of 7.2 and 67 microg of DNA per reaction, respectively. The comparison of 3.5 kb of sequences from the amplified and unamplified DNA indicated no detectable DNA differences. Similarly, gene marker analysis conducted on genomic DNA and DNA after WGA indicated no difference in marker amplification or clarity and accuracy of scoring for approximately 10,000 single nucleotide polymorphism markers when compared with WGA samples genotyped in duplicate. These results illustrate that WGA is a suitable method for the amplification and recovery of DNA from bull semen samples for routine genomic investigations.