Performance of genetic imputation across commercial crop species

We show that accurate imputation can be carried out in three commercial plant species (maize, sugar beet and wheat) and that accurate imputation does not require a pedigree, although pedigree information can improve accuracy and speed. Our approach uses a hidden Markov model to build a haplotype library from individuals genotyped at high-density and then uses this library to impute low-density genotyped individuals to high-density. To build the library, we use founders when the pedigree is known, or a sample of progeny when the pedigree is unknown. Without a pedigree, and with 50 individuals genotyped at high-density and 100 low-density markers per chromosome, the median accuracies were 0.97 (maize), 0.96 (sugar beet), and 0.94 (wheat). We obtained similar accuracies with a pedigree. For biparental crosses with 100 markers per chromosome, median accuracies were 0.96 (maize), 0.96 (sugar beet) and 0.94 (wheat). For the imputation scenarios without a pedigree, we compared accuracies with those obtained by running Beagle 5.1. In all but one scenario, our method outperformed Beagle. We believe that plant breeders can effectively apply imputation in many crop species.

Linking Pedigree Information to the Gene Expression Phenotype to Understand Differential Family Survival Mechanisms in Highly Fecund Fish: A Case Study in the Larviculture of Pacific Bluefin Tuna

Mass spawning in fish culture often brings about a marked variance in family size, which can cause a reduction in effective population sizes in seed production for stock enhancement. This study reports an example of combined pedigree information and gene expression phenotypes to understand differential family survival mechanisms in early stages of Pacific bluefin tuna, Thunnus orientalis, in a mass culture tank. Initially, parentage was determined using the partial mitochondrial DNA control region sequence and 11 microsatellite loci at 1, 10, 15, and 40 days post-hatch (DPH). A dramatic proportional change in the families was observed at around 15 DPH; therefore, transcriptome analysis was conducted for the 15 DPH larvae using a previously developed oligonucleotide microarray. This analysis successfully addressed the family-specific gene expression phenotypes with 5739 differentially expressed genes and highlighted the importance of expression levels of gastric-function-related genes at the developmental stage for subsequent survival. This strategy demonstrated herein can be broadly applicable to species of interest in aquaculture to comprehend the molecular mechanism of parental effects on offspring survival, which will contribute to the optimization of breeding technologies.

Mining Single Nucleotide Polymorphism (SNP) Markers for Accurate Genotype Identification and Diversity Analysis of Chinese Jujube (Ziziphus jujuba Mill.) Germplasm

Chinese jujube (Ziziphus jujuba Mill.) is an economically important fruit tree with outstanding adaptability to marginal lands and a broad range of climate conditions. There are over 800 cultivars, mostly landraces from China. However, a high rate of mislabeling in Chinese jujube germplasm restricts the sharing of information and materials among jujube researchers and hampers the use of jujube germplasm in breeding. In the present study, we developed a large panel of single nucleotide polymorphism (SNP) markers and validated 288 SNPs by genotyping 114 accessions of Chinese jujube germplasm. The validation resulted in the designation of a set of 192 polymorphic SNP markers that revealed a high rate of synonymous mislabeling in the jujube germplasm collection in Ningxia, China. A total of 17 groups of duplicates were detected, encompassing 49 of the 114 Chinese jujube cultivars. Model-based population stratification revealed two germplasm groups, and the core members of the two groups showed a significant genetic differentiation (Fst = 0.16). The results supported the hypothesis that the cultivated Chinese jujube had multiple origins and multiple regions of domestication. The Neighbor-Joining dendrogram further revealed that this collection is comprised of multiple sub-groups, each including 1-13 closely related cultivars. Parentage analysis of cultivars with known pedigree information proved the efficacy of using these SNP markers for parentage verification. A subset of 96 SNPs with high information index was selected for future downstream application including gene bank management, verification of pedigrees in breeding programs, quality control for propagation of planting materials and support of the traceability and authentication of jujube products.

Correlation of Genomic and Pedigree Inbreeding Coefficients in Small Cattle Populations

This study aimed to identify inbreeding coefficient (F) estimators useful for improvement programs in a small Holstein population through the evaluation of different methodologies in the Mexican Holstein population. F was estimated as follows: (a) from pedigree information (Fped); (b) through runs of homozygosity (Froh); (c) from the number of observed and expected homozygotic SNP in the individuals (Fgeno); (d) through the genomic relationship matrix (Fmg). The study included information from 4277 animals with pedigree records and 100,806 SNP. The average and standard deviation values of F were 3.11 ± 2.30 for Fped, −0.02 ± 3.55 for Fgeno, 2.77 ± 0.71 for Froh and 3.03 ± 3.05 for Fmg. The correlations between coefficients varied from 0.30 between Fped and Froh, to 0.96 between Fgeno and Fmg. Differences in the level of inbreeding among the parent’s country of origin were found regardless of the method used. The correlations among genomic inbreeding coefficients were high; however, they were low with Fped, so further research on this topic is required.

Inbreeding Calculated with Runs of Homozygosity Suggests Chromosome-Specific Inbreeding Depression Regions in Line 1 Hereford

The goal of this study was to evaluate inbreeding in a closed beef cattle population and assess phenotype prediction accuracy using inbreeding information. Effects of inbreeding on average daily gain phenotype in the Line 1 Hereford cattle population were assessed in this study. Genomic data were used to calculate inbreeding based on runs of homozygosity (ROH), and pedigree information was used to calculate the probability of an allele being identical by descent. Prediction ability of phenotypes using inbreeding coefficients calculated based on pedigree information and runs of homozygosity over the whole genome was close to 0, even in the case of significant inbreeding coefficient effects. On the other hand, inbreeding calculated per individual chromosomes’ ROH yielded higher accuracies of prediction. Additionally, including only ROH from chromosomes with higher predicting ability further increased prediction accuracy. Phenotype prediction accuracy, inbreeding depression, and the effects of chromosome-specific ROHs varied widely across the genome. The results of this study suggest that inbreeding should be evaluated per individual regions of the genome. Moreover, mating schemes to avoid inbreeding depression should focus more on specific ROH with negative effects. Finally, using ROH as added information may increase prediction of the genetic merit of animals in a genomic selection program.

VIKING II, a Worldwide Observational Cohort of Volunteers with Northern Isles Ancestry

Introduction: The purpose of VIKING II is to create an observational cohort of volunteers with ancestry from the Northern Isles of Scotland, primarily for identifying genetic variants influencing disease. The new online protocol is separate to, but follows on from, earlier genetic epidemiological clinic-based studies in the isolated populations of Orkney and Shetland. These populations are favourable for the study of rarer genetic variants due to genetic drift, the large number of relatives, and availability of pedigree information. Methods and Analysis: Online methods are being used to recruit ~4,000 people who have Northern Isles ancestry, living anywhere in the world. The option for participants to have actionable genetic results returned is offered. Broad consent will be taken electronically. Data will be collected at baseline through an online questionnaire and longitudinally through linkage to NHS data in the electronic health record. The questionnaire collects a variety of phenotypes including personal and family health. DNA will be extracted from saliva samples then genome-wide genotyped and exome sequenced. VIKING II aims to capitalise on the special features of the Northern Isles populations to create a research cohort that will facilitate the analysis of genetic variants associated with a broad range of traits and disease endpoints. Ethics and Dissemination The South East Scotland Research Ethics Committee gave the study a favourable opinion. VIKING II is sponsored by the University of Edinburgh and NHS Lothian. Summary research findings will be disseminated to participants and funding bodies, presented at conferences and reported in peer-reviewed publications.

Heritability and genetic variance estimation of Osteosarcoma (OSA) in Irish Wolfhound, using deep pedigree information

Background Osteosarcoma (OSA) is a devastating disease that is common in the Irish Wolfhound breed. The aim of this study was to use a pedigree-based approach to determine the heritability of OSA in the Irish Wolfhound using data from a large publically available database. Results The pedigree used for this study included 5110 pure-bred Irish Wolfhounds, including 332 dogs diagnosed with OSA and 360 control dogs; dogs were considered controls if they lived over 10 years of age and were not reported to have developed OSA. The estimated heritability of OSA in the Irish Wolfhound was 0.65. Conclusion The results of this study indicate that OSA in the Irish Wolfhound is highly heritable, and support the need for future research investigating associated genetic mutations.

PSXV-9 Transgenerational epigenetic variance for production and reproduction traits in maternal-line pigs

Modeling epigenetic factors impacting phenotypic expression of economically important traits has become a hot-topic in the field of animal breeding due to the variability in genetic expression caused by environmental stressors (e.g., heat stress). This variability may be due, in part, to in-utero epigenomic remodeling, which has been reported to be passed from parent to offspring. We aimed to estimate transgenerational epigenetic variance for various production and reproduction traits measured in a maternal-line pig population, using a Bayesian approach. The phenotypes for production [n = 10,862; i.e., weaning weight (WW), birth weight (BW) and ultrasound-backfat thickness (BF)] and reproduction [n = 5,235, i.e., number of piglets born alive (NBA) and total number of piglets born (TB)] traits from a purebred Landrace population were provided by Smithfield Premium Genetics (NC, USA). The pedigree information traced back to 10 generations. Single-trait genetic analyses were performed using mixed models that included additive genetic, common environmental, and epigenetic random effects. The Gibbs sampler algorithm based on Markov chain Monte Carlo was used to estimate the variance components. The epigenetic relationship matrix was constructed using a recursive parameter (λ) related to the transmissibility coefficient of epigenetic markers. A grid search approach was used to define the optimal λ value (λ values ranged from 0.1 to 0.5, with an interval of 0.1). The optimal λ value was determined based on the deviance information criterion, and it was used to estimate the additive and epigenetic variances. For instance, based on preliminary results, the optimal λ value estimated for TB was 0.3 with an additive genetic variance of 0.94 (0.19 PSD) and epigenetic variance of 0.67 (0.18 PSD). The additive genetic heritability was 0.076 (0.015 PSD) and the estimated epigenetic heritability was 0.053 (0.015 PSD). This preliminary result suggests that epigenetics contribute to the non-Mendelian variability in pigs.

33 Impact of Including the Cause of Missing Records on Genetic Evaluations for Growth in Commercial Pigs

It is of interest to evaluate crossbred pigs for hot carcass weight (HCW) and birth weight (BW); however, obtaining a HCW record is dependent on livability (LIV) and retained tag (RT). The purpose of this study is to analyze how HCW evaluations are affected when herd removal and missing identification are included in the model and examine if accounting for the reasons for missing traits improves the accuracy of predicting breeding values. Pedigree information was available for 1,965,077 purebred and crossbred animals. Records for 503,716 commercial three-way crossbred terminal animals from 2014 to 2019 were provided by Smithfield Premium Genetics. Two pedigree-based models were compared; model 1 (M1) was a threshold-linear model with all four traits (BW, HCW, RT, and LIV), and model 2 (M2) was a linear model including only BW and HCW. The fixed effects used in the model were contemporary group, sex, age at harvest (for HCW only), and dam parity. The random effects included direct additive genetic and random litter effects. Accuracy, dispersion, bias, and Pearson correlations were estimated using the linear regression method. The heritabilities were 0.11, 0.07, 0.02, and 0.04 for BW, HCW, RT, and LIV, respectively, with standard errors less than 0.01. No difference was observed in heritabilities or accuracies for BW and HCW between M1 and M2. Accuracies were 0.33, 0.37, 0.19, and 0.23 for BW, HCW, RT, and LIV respectively. The genetic correlation between BW and RT was 0.34 ± 0.03, and between BW and LIV was 0.56 ± 0.03. The positive and moderate genetic correlations between BW and other traits imply a heavier BW resulted in a higher probability of surviving to harvest. Despite the heritable and correlated aspects of RT and LIV, results imply no major differences between M1 and M2; hence, it is unnecessary to include these traits in classical models for BW and HCW.

PSXVI-17 Estimation of inbreeding in local sheep breeds of west Asian and central Asian origin based on high-density SNP-genotypes

Maintaining high levels of genetic diversity is a key factor of successful breeding of resilient, resistant to diseases and productive sheep. Prevention of inbreeding is of special importance in the mountainous hard-to-get habitats where gene flow is limited or absent. An assessment of inbreeding coefficients based only on pedigree information is not always correct. In addition, pedigree information is often missing for flocks of native sheep. In this regard, we performed a genomic assessment of inbreeding in 15 local sheep breeds inhabiting severe environments of Russia and neighboring Asian countries based on estimations of standardized multilocus heterozygosity (sMLH) and runs of homozygosity [F(ROH)]. For this study, we used SNP genotypes of twelve Russian local breeds (n = 316) and three Kyrgyz local breeds (n = 68), which were generated using Ovine Infinium® HD SNP BeadChip (Illumina, CA, USA). The sMLH values were calculated using R package inbreedR and visualized in R package ggplot2. The F(ROH) values were calculated using the R package detectRUNS by applying the consecutive runs method. Mean sMLH values were varied from 0.962 ± 0.006 in the Andean breed to 1.031 ± 0.002 in the Buryat breed and averaged to 1.001± 0.004. The least mean F(ROH) value was detected in the Mongolian breed (0.0043 ± 0.0009) while the greatest ones were observed in the Alai and Andean breeds (0.0364 ± 0.0049 and 0.0357 ± 0.0061, respectively). The strong negative correlations between sMLH and F(ROH) were detected for all of studied breeds (r2 = –0.8496, CI = –0.8752… –0.8192). The obtained data is relevant for control of inbreeding level in the populations and for future sustainable management of native fat-tailed sheep breeds. The study was funded by RSF No. 19-16-00070.