scholarly journals PSXII-29 Partitioning of Inbreeding Depression using Pedigree and Genomic Approaches

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 247-248
Author(s):  
Pattarapol Sumreddee ◽  
Sajjad Toghiani ◽  
Elhamidi Hay ◽  
Samuel E Aggrey ◽  
Romdhane Rekaya
Keyword(s):  
Model Comparison ◽  
Common Ancestor ◽  
Growth Traits ◽  
Average Daily Gain ◽  
Recent Common Ancestor ◽  
Pedigree Information ◽  
Sources Of Information ◽  
Genomic Information ◽  
A Genome ◽  
Using Data

Abstract Understanding the accumulation of autozygosity over time in a genome could enhance the assessment of the effect of inbreeding and the mitigation of its harmful impact. To date, runs of homozygosity (ROH) have been commonly used to study inbreeding’s impact in livestock species, as an alternative to the pedigree-based approach. Although inbreeding caused by the mating of animals related through a recent common ancestor is reasonably expected to have more pronounced effects on traits, estimating these effects requires a clear definition of recent (new) and ancient (old) inbreeding. Several methods have been proposed to classify inbreeding using pedigree and genomic information. Unfortunately, these methods are largely based on heuristic criteria (e.g., number of generations from common ancestor and length of ROH segments). To mitigate these deficiencies, we developed a method to classify inbreeding into recent and ancient classes based on a grid search driven by the hypothesis that new inbreeding tends to have a more pronounced effect than old inbreeding. The proposed method was tested using data from Line-1 Hereford cattle population characterized by a deep complete pedigree. Genomic data consisted of 50K SNP genotypes. Effect of recent and ancient inbreeding was assessed on four growth traits (birth, weaning and yearling weights and average daily gain). Thresholds to classify inbreeding into recent and ancient classes varied across traits and sources of information. Using pedigree information, increased inbreeding in the last 10 to 11 generations was considered as recent. When genomic information was using, thresholds ranged between 4 to 7 indicating the ability of ROH segments to better characterize the harmful impact of inbreeding in shorter periods of time. Using several model comparison criteria (adjusted R-squared, AIC, and BIC), the proposed method was better than existing approaches. Furthermore, the method provided a more objective quantitative approach for the classification of inbreeding.

scholarly journals Grid search approach to discriminate between old and recent inbreeding using phenotypic, pedigree and genomic information

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Pattarapol Sumreddee ◽  
El Hamidi Hay ◽  
Sajjad Toghiani ◽  
Andrew Roberts ◽  
Samuel E. Aggrey ◽  
...  
Keyword(s):  
Common Ancestor ◽  
Growth Traits ◽  
Average Daily Gain ◽  
Recent Common Ancestor ◽  
Pedigree Information ◽  
Grid Search ◽  
Genomic Information ◽  
The Impact ◽  
Daily Gain ◽  
Harmful Effects

Abstract Background Although inbreeding caused by the mating of animals related through a recent common ancestor is expected to have more harmful effects on phenotypes than ancient inbreeding (old inbreeding), estimating these effects requires a clear definition of recent (new) and ancient (old) inbreeding. Several methods have been proposed to classify inbreeding using pedigree and genomic data. Unfortunately, these methods are largely based on heuristic criteria such as the number of generations from a common ancestor or length of runs of homozygosity (ROH) segments. To mitigate these deficiencies, this study aimed to develop a method to classify pedigree and genomic inbreeding into recent and ancient classes based on a grid search algorithm driven by the assumption that new inbreeding tends to have a more pronounced detrimental effect on traits. The proposed method was tested using a cattle population characterized by a deep pedigree. Results Effects of recent and ancient inbreeding were assessed on four growth traits (birth, weaning and yearling weights and average daily gain). Thresholds to classify inbreeding into recent and ancient classes were trait-specific and varied across traits and sources of information. Using pedigree information, inbreeding generated in the last 10 to 11 generations was considered as recent. When genomic information (ROH) was used, thresholds ranged between four to seven generations, indicating, in part, the ability of ROH segments to characterize the harmful effects of inbreeding in shorter periods of time. Nevertheless, using the proposed classification method, the discrimination between new and old inbreeding was less robust when ROH segments were used compared to pedigree. Using several model comparison criteria, the proposed approach was generally better than existing methods. Recent inbreeding appeared to be more harmful across the growth traits analyzed. However, both new and old inbreeding were found to be associated with decreased yearling weight and average daily gain. Conclusions The proposed method provided a more objective quantitative approach for the classification of inbreeding. The proposed method detected a clear divergence in the effects of old and recent inbreeding using pedigree data and it was superior to existing methods for all analyzed traits. Using ROH data, the discrimination between old and recent inbreeding was less clear and the proposed method was superior to existing approaches for two out of the four analyzed traits. Deleterious effects of recent inbreeding were detected sooner (fewer generations) using genomic information than pedigree. Difference in the results using genomic and pedigree information could be due to the dissimilarity in the number of generations to a common ancestor. Additionally, the uncertainty associated with the identification of ROH segments and associated inbreeding could have an effect on the results. Potential biases in the estimation of inbreeding effects may occur when new and old inbreeding are discriminated based on arbitrary thresholds. To minimize the impact of inbreeding, mating designs should take the different inbreeding origins into consideration.

scholarly journals 209 Genomic selection for multiple maternal and growth traits in large white pigs using Single-Step GBLUP

2019 ◽  
Vol 97 (Supplement_3) ◽  
pp. 42-42
Author(s):  
Breno Fragomeni ◽  
Zulma Vitezica ◽  
Justine Liu ◽  
Yijian Huang ◽  
Kent Gray ◽  
...  
Keyword(s):  
Genetic Correlation ◽  
Growth Traits ◽  
Computing Time ◽  
Average Daily Gain ◽  
Genetic Correlations ◽  
Single Step ◽  
Genomic Information ◽  
Genomic Evaluation ◽  
Large White ◽  
Daily Gain

Abstract The objective of this study was to implement a multi-trait genomic evaluation for maternal and growth traits in a swine population. Phenotypes for preweaning mortality, litter size, weaning weight, and average daily gain were available for 282K Large White pigs. The pedigree included 314k individuals, of which 35,731 were genotyped for 45K SNPs. Variance components were estimated in a multi-trait animal model without genomic information by AIREMLF90. Genomic breeding values were estimated using the genomic information by single-step GBLUP. The algorithm for proven and young (APY) was used to reduce computing time. Genetic correlation between proportion and the total number of preweaning deaths was 0.95. A strong, positive genetic correlation was also observed between weaning weight and average daily gain (r = 0.94). Conversely, the genetic correlations between mortality and growth traits were negative, with an average of -0.7. To avoid computations by expensive threshold models, preweaning mortality was transformed from a binary trait to two linear dam traits: proportion and a total number of piglets dead before weaning. Because of the high genetic correlations within groups of traits, inclusion of only one growth and one mortality trait in the model decreases computing time and allows for the inclusion of other traits. Reduction in computing time for the evaluation using APY was up to 20x, and no differences in EPD ranking were observed. The algorithm for proven and young improves the efficiency of genomic evaluation in swine without harming the quality of predictions. For this population, a binary trait of mortality can be replaced by a linear trait of the dam, resulting in a similar ranking for the selection candidates.

THE EFFECT OF INBREEDING ON PREWEANING GROWTH OF YANKASA SHEEP

2021 ◽  
Vol 26 ◽  
pp. 6-10
Author(s):  
E. M. Awemu ◽  
B. Y. Abubakar ◽  
L. N. Nwakalor
Keyword(s):  
Birth Weight ◽  
Growth Traits ◽  
Average Daily Gain ◽  
Regression Coefficients ◽  
Breeding Period ◽  
Weaning Weight ◽  
Inbreeding Coefficients ◽  
Using Data ◽  
Inbreeding Level ◽  
Daily Gain

The accumulated and annual levels of inbreeding and their effects on growth traits of lambs were investigated using data collected over 11 years at the National Animal Production Research Institute Zaria. Inbreeding level averaged 1.313% per year, cumulating to 14.45% over the years. Average individuals inbreeding coefficients of offspring from sires used for more than one breeding period was 0.103% across the inbred individuals and 0.004% over all lambs. Regression coefficients of growth traits (everage values per year) on inbreeding levels by year were – 0.185kg ± 1.820g and -0.391kg for birth weight, preweaning average daily gain and weaning weight, respectively. All regression coefficients indicated that birth weight and weaning weight declined by 0.185kg and 0.391kg, respectively while preweaning average daily gain increased by 1.820g. Conscious efforts to reduce inbreeding level and its effects on growth traits will greatly lead to improved productivity

scholarly journals Genomic resources and toolkits for developmental study of whip spiders (Amblypygi) provide insights into arachnid genome evolution and antenniform leg patterning

2020 ◽  
Author(s):  
Guilherme Gainett ◽  
Prashant P. Sharma
Keyword(s):  
Hox Genes ◽  
Common Ancestor ◽  
Genome Duplication ◽  
Expression Patterns ◽  
Recent Common Ancestor ◽  
Developmental Study ◽  
Genomic Resources ◽  
Most Recent Common Ancestor ◽  
Gap Genes ◽  
A Genome

AbstractBackgroundThe resurgence of interest in the comparative developmental study of chelicerates has led to important insights, such as the discovery of a genome duplication shared by spiders and scorpions, inferred to have occurred at the most recent common ancestor of Arachnopulmonata (a clade comprised of the five book lung-bearing arachnid orders). Nonetheless, several arachnid groups remain understudied in the context of development and genomics, such as the order Amblypygi (whip spiders). The phylogenetic position of Amblypygi in Arachnopulmonata posits them as an interesting group to test the incidence of the proposed genome duplication in the common ancestor of Arachnopulmonata, as well as the degree of retention of duplicates over 450 Myr. Moreover, whip spiders have their first pair of walking legs elongated and modified into sensory appendages (a convergence with the antenna of mandibulates), but the genetic patterning of these antenniform legs has never been investigated.ResultsWe established genomic resources and protocols for cultivation of embryos and gene expression assays by in situ hybridization to study the development of the whip spider Phrynus marginemaculatus. Using embryonic transcriptomes from three species of Amblypygi, we show that the ancestral whip spider exhibited duplications of all ten Hox genes. We deploy these resources to show that paralogs of the leg gap genes dachshund and homothorax retain arachnopulmonate-specific expression patterns in P. marginemaculatus. We characterize the expression of leg gap genes Distal-less, dachshund-1/2 and homothorax-1/2 in the embryonic antenniform leg and other appendages, and provide evidence that allometry, and by extension the antenniform leg fate, is specified early in embryogenesis.ConclusionThis study is the first step in establishing P. marginemaculatus as a model for modern chelicerate evolutionary developmental study, and provides the first resources sampling whip spiders for comparative genomics. Our results suggest that Amblypygi share a genome duplication with spiders and scorpions, and set up a framework to study the genetic specification of antenniform legs. Future efforts to study whip spider development must emphasize the development of tools for functional experiments in P. marginemaculatus.

scholarly journals Genomic prediction for growth using a low-density SNP panel in dromedary camels

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Morteza Bitaraf Sani ◽  
Javad Zare Harofte ◽  
Mohammad Hossein Banabazi ◽  
Saeid Esmaeilkhanian ◽  
Ali Shafei Naderi ◽  
...  
Keyword(s):  
Body Weight ◽  
Birth Weight ◽  
Sample Size ◽  
Genetic Improvement ◽  
Growth Traits ◽  
P Value ◽  
Dromedary Camels ◽  
Genome Wide ◽  
A Genome ◽  
Daily Gain

AbstractFor thousands of years, camels have produced meat, milk, and fiber in harsh desert conditions. For a sustainable development to provide protein resources from desert areas, it is necessary to pay attention to genetic improvement in camel breeding. By using genotyping-by-sequencing (GBS) method we produced over 14,500 genome wide markers to conduct a genome- wide association study (GWAS) for investigating the birth weight, daily gain, and body weight of 96 dromedaries in the Iranian central desert. A total of 99 SNPs were associated with birth weight, daily gain, and body weight (p-value < 0.002). Genomic breeding values (GEBVs) were estimated with the BGLR package using (i) all 14,522 SNPs and (ii) the 99 SNPs by GWAS. Twenty-eight SNPs were associated with birth weight, daily gain, and body weight (p-value < 0.001). Annotation of the genomic region (s) within ± 100 kb of the associated SNPs facilitated prediction of 36 candidate genes. The accuracy of GEBVs was more than 0.65 based on all 14,522 SNPs, but the regression coefficients for birth weight, daily gain, and body weight were 0.39, 0.20, and 0.23, respectively. Because of low sample size, the GEBVs were predicted using the associated SNPs from GWAS. The accuracy of GEBVs based on the 99 associated SNPs was 0.62, 0.82, and 0.57 for birth weight, daily gain, and body weight. This report is the first GWAS using GBS on dromedary camels and identifies markers associated with growth traits that could help to plan breeding program to genetic improvement. Further researches using larger sample size and collaboration of the camel farmers and more profound understanding will permit verification of the associated SNPs identified in this project. The preliminary results of study show that genomic selection could be the appropriate way to genetic improvement of body weight in dromedary camels, which is challenging due to a long generation interval, seasonal reproduction, and lack of records and pedigrees.

scholarly journals Emerging issues in genomic selection

2021 ◽  
Author(s):  
I Misztal ◽  
I Aguilar ◽  
D Lourenco ◽  
L Ma ◽  
J Steibel ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Sparse Matrices ◽  
Large Datasets ◽  
Single Step ◽  
Genomic Information ◽  
Long Term Effects ◽  
Additive Variance ◽  
Recent Developments ◽  
Emerging Issues ◽  
Using Data

Abstract Genomic selection is now practiced successfully across many species. However, many questions remain such as long-term effects, estimations of genomic parameters, robustness of GWAS with small and large datasets, and stability of genomic predictions. This study summarizes presentations from at the 2020 ASAS symposium. The focus of many studies until now is on linkage disequilibrium (LD) between two loci. Ignoring higher level equilibrium may lead to phantom dominance and epistasis. The Bulmer effect leads to a reduction of the additive variance; however, selection for increased recombination rate can release anew genetic variance. With genomic information, estimates of genetic parameters may be biased by genomic preselection, but costs of estimation can increase drastically due to the dense form of the genomic information. To make computation of estimates feasible, genotypes could be retained only for the most important animals, and methods of estimation should use algorithms that can recognize dense blocks in sparse matrices. GWAS studies using small genomic datasets frequently find many marker-trait associations whereas studies using much bigger datasets find only a few. Most current tools use very simple models for GWAS, possibly causing artifacts. These models are adequate for large datasets where pseudo-phenotypes such as deregressed proofs indirectly account for important effects for traits of interest. Artifacts arising in GWAS with small datasets can be minimized by using data from all animals (whether genotyped or not), realistic models, and methods that account for population structure. Recent developments permit computation of p-values from GBLUP, where models can be arbitrarily complex but restricted to genotyped animals only, and to single-step GBLUP that also uses phenotypes from ungenotyped animals. Stability was an important part of nongenomic evaluations, where genetic predictions were stable in the absence of new data even with low prediction accuracies. Unfortunately, genomic evaluations for such animals change because all animals with genotypes are connected. A top ranked animal can easily drop in the next evaluation, causing a crisis of confidence in genomic evaluations. While correlations between consecutive genomic evaluations are high, outliers can have differences as high as one SD. A solution to fluctuating genomic evaluations is to base selection decisions on groups of animals. While many issues in genomic selection have been solved, many new issues that require additional research continue to surface.

scholarly journals Allelic Genealogies in Sporophytic Self-Incompatibility Systems in Plants

Genetics ◽  
1998 ◽  
Vol 150 (3) ◽  
pp. 1187-1198 ◽  
Author(s):  
Mikkel H Schierup ◽  
Xavier Vekemans ◽  
Freddy B Christiansen
Keyword(s):  
Dominance Hierarchy ◽  
Common Ancestor ◽  
Recent Common Ancestor ◽  
Self Incompatibility ◽  
Most Recent Common Ancestor ◽  
Dominance Interactions ◽  
Turnover Process ◽  
Neutral Gene ◽  
Interspecific Comparisons ◽  
Coalescence Times

Abstract Expectations for the time scale and structure of allelic genealogies in finite populations are formed under three models of sporophytic self-incompatibility. The models differ in the dominance interactions among the alleles that determine the self-incompatibility phenotype: In the SSIcod model, alleles act codominantly in both pollen and style, in the SSIdom model, alleles form a dominance hierarchy, and in SSIdomcod, alleles are codominant in the style and show a dominance hierarchy in the pollen. Coalescence times of alleles rarely differ more than threefold from those under gametophytic self-incompatibility, and transspecific polymorphism is therefore expected to be equally common. The previously reported directional turnover process of alleles in the SSIdomcod model results in coalescence times lower and substitution rates higher than those in the other models. The SSIdom model assumes strong asymmetries in allelic action, and the most recessive extant allele is likely to be the most recent common ancestor. Despite these asymmetries, the expected shape of the allele genealogies does not deviate markedly from the shape of a neutral gene genealogy. The application of the results to sequence surveys of alleles, including interspecific comparisons, is discussed.

scholarly journals Molecular epidemiological characteristics of echovirus 6 in mainland China: extensive circulation of genotype F from 2007 to 2018

2021 ◽  
Author(s):  
Wenjun Cheng ◽  
Tianjiao Ji ◽  
Shuaifeng Zhou ◽  
Yong Shi ◽  
Lili Jiang ◽  
...  
Keyword(s):  
Common Ancestor ◽  
Mainland China ◽  
Recent Common Ancestor ◽  
Genetic Characteristics ◽  
Most Recent Common Ancestor ◽  
Significant Difference ◽  
Echovirus 6 ◽  
Epidemiological Characteristics ◽  
Highest Posterior Density ◽  
Genotype F

AbstractEchovirus 6 (E6) is associated with various clinical diseases and is frequently detected in environmental sewage. Despite its high prevalence in humans and the environment, little is known about its molecular phylogeography in mainland China. In this study, 114 of 21,539 (0.53%) clinical specimens from hand, foot, and mouth disease (HFMD) cases collected between 2007 and 2018 were positive for E6. The complete VP1 sequences of 87 representative E6 strains, including 24 strains from this study, were used to investigate the evolutionary genetic characteristics and geographical spread of E6 strains. Phylogenetic analysis based on VP1 nucleotide sequence divergence showed that, globally, E6 strains can be grouped into six genotypes, designated A to F. Chinese E6 strains collected between 1988 and 2018 were found to belong to genotypes C, E, and F, with genotype F being predominant from 2007 to 2018. There was no significant difference in the geographical distribution of each genotype. The evolutionary rate of E6 was estimated to be 3.631 × 10-3 substitutions site-1 year-1 (95% highest posterior density [HPD]: 3.2406 × 10-3-4.031 × 10-3 substitutions site-1 year-1) by Bayesian MCMC analysis. The most recent common ancestor of the E6 genotypes was traced back to 1863, whereas their common ancestor in China was traced back to around 1962. A small genetic shift was detected in the Chinese E6 population size in 2009 according to Bayesian skyline analysis, which indicated that there might have been an epidemic around that year.

scholarly journals Comparison of models for missing pedigree in single-step genomic prediction

2021 ◽  
Vol 99 (2) ◽  
Author(s):  
Yutaka Masuda ◽  
Shogo Tsuruta ◽  
Matias Bermann ◽  
Heather L Bradford ◽  
Ignacy Misztal
Keyword(s):  
Density Function ◽  
Single Step ◽  
Joint Density ◽  
Pedigree Information ◽  
Relationship Matrix ◽  
Genomic Information ◽  
Breeding Values ◽  
Joint Density Function ◽  
Information Updates ◽  
Genetic Trends

Abstract Pedigree information is often missing for some animals in a breeding program. Unknown-parent groups (UPGs) are assigned to the missing parents to avoid biased genetic evaluations. Although the use of UPGs is well established for the pedigree model, it is unclear how UPGs are integrated into the inverse of the unified relationship matrix (H-inverse) required for single-step genomic best linear unbiased prediction. A generalization of the UPG model is the metafounder (MF) model. The objectives of this study were to derive 3 H-inverses and to compare genetic trends among models with UPG and MF H-inverses using a simulated purebred population. All inverses were derived using the joint density function of the random breeding values and genetic groups. The breeding values of genotyped animals (u2) were assumed to be adjusted for UPG effects (g) using matrix Q2 as u2∗=u2+Q2g before incorporating genomic information. The Quaas–Pollak-transformed (QP) H-inverse was derived using a joint density function of u2∗ and g updated with genomic information and assuming nonzero cov(u2∗,g′). The modified QP (altered) H-inverse also assumes that the genomic information updates u2∗ and g, but cov(u2∗,g′)=0. The UPG-encapsulated (EUPG) H-inverse assumed genomic information updates the distribution of u2∗. The EUPG H-inverse had the same structure as the MF H-inverse. Fifty percent of the genotyped females in the simulation had a missing dam, and missing parents were replaced with UPGs by generation. The simulation study indicated that u2∗ and g in models using the QP and altered H-inverses may be inseparable leading to potential biases in genetic trends. Models using the EUPG and MF H-inverses showed no genetic trend biases. These 2 H-inverses yielded the same genomic EBV (GEBV). The predictive ability and inflation of GEBVs from young genotyped animals were nearly identical among models using the QP, altered, EUPG, and MF H-inverses. Although the choice of H-inverse in real applications with enough data may not result in biased genetic trends, the EUPG and MF H-inverses are to be preferred because of theoretical justification and possibility to reduce biases.

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