Pedigree Information Research Articles

Genealogical structure and genetic variability: A step towards conservation of white Morada Nova sheep in semi-arid region

Morada Nova breed has a low effective herd, and its white variety is in risk of extinction in Brazilian semi-arid region. This study aimed to evaluate white Morada Nova sheep’s genetic variability and population structure in four flocks. These are the only flocks in the world. The assessed parameters of pedigree integrity and a genealogy record of 219 animals. 44.74 % did not have pedigree information on their mother or father, and 50.47 % did not have available information on their grandparents. 52.97 % had a pedigree in their first ancestry (obtained through the average of known parents), 23.74 % in the second, 13.58 % in the third, and 5.33 % in the fourth. The effective size was 10.7, considering the complete equivalent generation. The effective number of founding animals (fe) and ancestors (fa) was 10, indicating the effective participation of all founding animals in the population over the generations, reducing losses of genetic variability. Out of all the ancestors, only 3 explained 50 % of the population’s genetic variability, reflecting the low values of fa and fe. The population’s average inbreeding and kinship coefficients were 2.61 and 4.54. The F statistics of Wright, Fis, Fst, and Fit, were −0.012, 0.016, and 0.003. The genetic conservation index (GCI) had an average of 2.01 ± 1.29, with minimum and maximum values of 1.0 and 6.38, respectively. Approximately, 71 % of the population had GCI below 2.0, while only 5.9 % of sheep had an GCI bigger than 5.0. This indicates the absence of sub-structures inf the population. There is no population subdivision, considering the genealogical structure of the evaluated flocks. The inbreeding and kinship coefficient values are controlled and serve as a starting point for establishing a future management plan for the genetic variability of the flock. It is recommended to use strategies to increase the effective population size, to meet the minimum number recommended by FAO and to promote the conservation and genetic improvement of the breed.

39 Using genetics and technology to improve swine robustness

Abstract Abstract Pig robustness has been an increasing concern in the global swine industry over the last 10 yr. This trend of increased mortality across all phases of production continues to worsen over time despite greater focus on research, management, and other production practices to control it. During this time, dramatic improvements in genetic progress have been realized through the selection of economically important traits. Historically, swine genetic companies have relied on data from their purebred animals reared in high-health and well-managed environments which has proven difficult to provide meaningful insight on variation in robustness traits. More recently, leading genetic companies have invested in large commercial test herds where crossbred pigs and breeding animals are individually identified with pedigree and genomic information. These pigs are reared under challenging and varying commercial conditions and mortality, removals, and reproductive efficiency data are gathered and used to generate crossbred breeding values. This type of data increases the accuracy of genetic estimates as well as creates new traits aimed at improving robustness and ease of management. Further investments have been made in precision livestock farming technologies such as computer vision which is quickly being developed due to the low cost of cameras and the ability to use edge computing to process images in real-time or to transfer images and data to the cloud. These developments are particularly compelling in the genetic improvement space when they can be paired with individual animal identification enabling novel traits to be measured in large populations more consistently and at a reduced cost compared with previous labor-intensive or cost-prohibitive methods. Early examples of this are the use of cameras to score feet and leg soundness in replacement gilts as lameness and associated feet and leg injuries are still one of the largest contributors to sow culls and mortality. This new digital feet and leg soundness scoring method has initially resulted in dramatically greater accuracy and heritability compared with conventional subjective human scoring methods. Other camera-based algorithms have been developed to track individual pigs and assess their daily behaviors and interactions. These developments are key to collecting new phenotypes for the selection of positive behavior traits for genetic selection compared with what was previously possible with human observer or scan sampling methods. Gene editing is another promising technology that has been used in human health and plant breeding but is now being widely researched in livestock. This technology has been used to create the first PRRS-resistant pigs to address one of the most costly diseases in the industry. New sources of data and technologies are key to creating and capturing existing and novel phenotypes on large populations of pigs in commercial environments to aid in the genetic improvement of non-conventional traits.

Comparative Evaluation of Inbreeding Parameters in Korean Commercial Pig Breeds Using Genomic and Pedigree Information

Comparative Evaluation of Inbreeding Parameters in Korean Commercial Pig Breeds Using Genomic and Pedigree Information

Genetic characterization of a captive marmoset (Callithrix jacchus) colony using genotype-by-sequencing.

The marmoset is a fundamental nonhuman primate model for the study of aging, neurobiology, and many other topics. Genetic management of captive marmoset colonies is complicated by frequent chimerism in the blood and other tissues, a lack of tools to enable cost-effective, genome-wide interrogation of variation, and historic mergers and migrations of animals between colonies. We implemented genotype-by-sequencing (GBS) of hair follicle derived DNA (a minimally chimeric DNA source) of 82 marmosets housed at the Southwest National Primate Research Center (SNPRC). Our primary goals were the genetic characterization of our marmoset population for pedigree verification and colony management and to inform the scientific community of the functional genetic makeup of this valuable resource. We used the GBS data to reconstruct the genetic legacy of recent mergers between colonies, to identify genetically related animals whose relationships were previously unknown due to incomplete pedigree information, and to show that animals in the SNPRC colony appear to exhibit low levels of inbreeding. Of the >99,000 single-nucleotide variants (SNVs) that we characterized, >9800 are located within gene regions known to harbor pathogenic variants of clinical significance in humans. Overall, we show the combination of low-resolution (sparse) genotyping using hair follicle DNA is a powerful strategy for the genetic management of captive marmoset colonies and for identifying potential SNVs for the development of biomedical research models.

Accuracy of Genomic prediction for fleece traits in Inner Mongolia Cashmere goats

The fleece traits are important economic traits of goats. With the reduction of sequencing and genotyping cost and the improvement of related technologies, genomic selection for goats has become possible. The research collect pedigree, phenotype and genotype information of 2299 Inner Mongolia Cashmere goats (IMCGs) individuals. We estimate fixed effects, and compare the estimates of variance components, heritability and genomic predictive ability of fleece traits in IMCGs when using the pedigree based Best Linear Unbiased Prediction (ABLUP), Genomic BLUP (GBLUP) or single-step GBLUP (ssGBLUP). The fleece traits considered are cashmere production (CP), cashmere diameter (CD), cashmere length (CL) and fiber length (FL). It was found that year of production, sex, herd and individual ages had highly significant effects on the four fleece traits (P < 0.01). All of these factors should be considered when the genetic parameters of fleece traits in IMCGs are evaluated. The heritabilities of FL, CL, CP and CD with ABLUP, GBLUP and ssGBLUP methods were 0.26 ~ 0.31, 0.05 ~ 0.08, 0.15 ~ 0.20 and 0.22 ~ 0.28, respectively. Therefore, it can be inferred that the genetic progress of CL is relatively slow. The predictive ability of fleece traits in IMCGs with GBLUP (56.18% to 69.06%) and ssGBLUP methods (66.82% to 73.70%) was significantly higher than that of ABLUP (36.73% to 41.25%). For the ssGBLUP method is significantly (29% ~ 33%) higher than that with ABLUP, and which is slightly (4% ~ 14%) higher than that of GBLUP. The ssGBLUP will be as an superiors method for using genomic selection of fleece traits in Inner Mongolia Cashmere goats.

Pedigree-Based Genetic Diversity in the South African Boerboel Dog Breed.

The Boerboel dog breed (BBD) is indigenous to South Africa (SA) and plays an important role in safeguarding homes and farms. The Department of Agriculture, Land Reform, and Rural Development (DALRRD) classifies the BBD as a protected species, and it is valued for its intelligence, boldness, and strength, as well as for continually ensuring the safety of its owners. The aim of this study was to investigate genetic diversity within the BBD population using pedigree information. The original BBD data, which contained 87,808 records, were obtained from the Integrated Registration and Genetic Information System (INTERGIS). After editing, the pedigree data included 87,755 records of animals born between 1971 and 2019. Pedigree analyses were performed using PEDIG (Fortran 77 software) to determine the completeness, inbreeding coefficients, and genetic diversity as defined by the genetic contributions of the most important ancestors of the current animals. This study identified 91.2% inbred animals in the BBD population, with an average and maximum inbreeding of 7.5% and 50% of inbred animals, respectively. The estimated inbreeding rate per year was 0.20% with an effective population size of 83.1. The most influential ancestors explained 82.63% and 80.92% of the total genetic variation for males and females in the studied populations, respectively. Only 10 important ancestors explained more than 50% of the entire population's genetic diversity. The numbers of founders (f) were 348 and 356, and the effective numbers of founders (fe) were 57.4 and 60.1, respectively, for males and females. The numbers of founders were higher than the effective numbers of founders, implying a loss of genetic diversity due to unequal founder contributions. The BBD population was not critically endangered based on the inbreeding rates and effective population size; however, the population experienced a significant loss of genetic variability, unequal genetic contributions by founders, and a genetic bottleneck. Future breeding strategies could benefit from using equal proportions of parent stock and including new genetically distant breeds.

Genetic evaluations of dairy goats with few pedigree data: different approaches to use molecular information.

One of the limitations of implementing animal breeding programs in small-scale or extensive production systems is the lack of production records and genealogical records. In this context, molecular markers could help to gain information for the breeding program. This study addresses the inclusion of molecular data into traditional genetic evaluation models as a random effect by molecular pedigree reconstruction and as a fixed effect by Bayesian clustering. The methods were tested for lactation curve traits in 14 dairy goat herds with incomplete phenotypic data and pedigree information. The results showed an increment of 37.3% of the relationships regarding the originals with MOLCOAN and clustering into five genetic groups. Data leads to estimating additive variance, error variance, and heritability with four different models, including pedigree and molecular information. Deviance Information Criterion (DIC) values demonstrate a greater fitting of the models that include molecular information either as fixed (genetic clusters) or as random (molecular matrix) effects. The molecular information of simple markers can complement genetic improvement strategies in populations with little information.

Developing breeding values for shedding using industry data from New Zealand sheep

ABSTRACT Changes in wool prices, labour costs and animal welfare have sparked interest in several new sheep traits. Shedding, the ability of moulting or seasonal wool loss in sheep, is one of them. Here, we aimed to develop breeding values for shedding using existing data from New Zealand flocks. We used breeder-collected shedding scores, 0 = ‘no shedding on any part of the body’ to 10 = ‘wool shed fully from all the body’, for Wiltshire and Wiltshire-composite lambs born between 2003 and 2022. After QC, 20,653 phenotypic records from 25,066 animals with pedigree information (393 sires and 7439 dams from 12 flocks) were included in the analyses. Genetic parameters and breeding values were obtained using a genetic additive model with pedigree data (BLUP model), assuming shedding scores were quantitative. The genetic model incorporated the following variables: date of birth, sex, birth and rearing rank, age of dam and contemporary group. We found a high heritability for lamb shedding, 0.54 (0.02), and estimated a low-to-moderate prediction accuracy of breeding values (ranging from 0.09 to 0.36) using forward-validation. Our results confirmed that shedding can be subject to selection and that pedigree-based breeding values for this trait can be a useful tool for breeders.

Genomic inbreeding coefficients using imputation genotypes: Assessing the effect of ancestral genotyping in Holstein-Friesian dairy cows

The objective of this study was to assess the effect of using or not the genotypes of the parents of a cow for imputing single nucleotide polymorphisms (SNP), on the estimation of genomic inbreeding coefficients of cows. Imputation (i.e., genotyped plus imputed) genotypes from 68,127 Italian Holstein dairy cows registered in the Italian National Association of Holstein, Brown and Jersey Breeders (ANAFIBJ) were analyzed. Cows were genotyped with the HD Illumina Infinium BovineHD BeadChip and GeneSeek Genomic Profiler HD-150K, and the MD GeneSeek Genomic Profiler 3, GeneSeek Genomic Profiler 4, GeneSeek MD and the Labogena MD. To assess differences among estimators genomic inbreeding coefficients were estimated with 4 PLINK v1.9 estimators (F, Fhat1, 2, 3), 2 genomic relationship matrix (grm) based estimators (Fgrm and Fgrm2; with the latter including also pedigree information) and one estimator of runs of homozygosity (ROH; FROH). Assuming that the correct genomic inbreeding coefficients should be those estimated from genotyped SNP, a comparison of the genomic inbreeding coefficients estimated either with the genotyped SNP or the SNP after imputation was made. Information on the presence or absence of genotypic information from sire, dam and maternal grandsire during the imputation was investigated. Genomic inbreeding coefficients estimated with genotyped SNP or SNP after imputation were consistent for F, Fhat3, Fgrm2 and FROH, when at least one of the parents was genotyped. Biased (mainly higher) genomic inbreeding coefficients of imputation SNP were observed in cows that were genotyped with MD SNP panels whose SNP were poorly represented in the selected imputation SNP data set and also did not have their parents genotyped compared with what expected based on actual genotype data. For cows genotyped with MD the estimators Fhat1, Fhat2 and Fgrm provided higher genomic inbreeding coefficients of imputation SNP even with both parents and the maternal grandsire genotyped. Overall, FROH was the most robust estimator, followed by F and Fhat3. Our findings suggest that SNP selection, parental genotyping and estimator should be considered for designing imputation strategies in dairy cattle for estimating genomic inbreeding with imputation SNP. For computing genomic inbreeding coefficients, it is recommendable to have at least one parent genotyped and use an ROH based estimator.

Establishment and application of multiplex microsatellite genotyping for parentage assignment in Manila clam Ruditapes philippinarum

The manila clam Ruditapes philippinarum has become an important bivalve species in worldwide aquaculture due to its delicious taste and high commercial value. With the rapid expansion of clam farming, there is an urgent need to obtain genetic improvement by selective breeding, such as family-based selection of improved varieties. In this study, 10 microsatellite loci were selected to establish four multiplex PCR groups using four different fluorescences (FAM, ROX, HEX, TAM). The accuracy of these loci was verified by the 100% success rate of parentage assignment in a full-sib family. Parentage assignment was carried out in the mixed-mating parents and their offspring with unknown pedigree information. The genotyping of ten microsatellite loci generated 90 alleles, having the observed heterozygosity (Ho) ranging from 0.333 to 0.729. The expected heterozygosity (He) varied from 0.358 to 0.794. The PIC ranged from 0.342 to 0.763, with a mean value of 0.620. The theoretical combined parentage exclusion (cEP) power for all ten microsatellites was 97% with known genotypes of one parent (P1) and 99% for given the genotypes of both parents (P2). The actual successful assignment rate reached 98% by using all four sets of multiplex microsatellites, serving as the effective method for parentage assignment in the clams. The development and application of multiplex microsatellite genotyping methods provide a cost-effective method for pedigree reconstruction, population genetics and selective breeding of the commercially important clams.

Optimal open nucleus breeding system for long-term genetic gain in the Pacific white shrimp using genomic selection

The open nucleus breeding system (ONBS) has been widely employed in livestock breeding and has demonstrated a desirable genetic gain compared to the traditional closed nucleus breeding system (CNBS). However, no related study and application for ONBS exist on aquatic animal breeding. The present investigation simulates the family-based ONBS with different proportions of introduced multiplier individuals used as parents of the nucleus population (NP) and CNBS schemes for the harvest body weight of the Pacific white shrimp (Litopenaeus vannamei). The multiplier population (MP) comprised progenies from eight families with high estimated breeding value (EBV) or genomic EBV (GEBV) of NP of the previous generation. ONBS was assigned three proportions (10%, 30%, and 50%) of the introduced MP individuals. The short-term selection (G0 to G10) and long-term selection (G0 to G20) were performed for CNBS and ONBS schemes using pedigree-based best linear unbiased prediction (PBLUP) with the A relationship matrix from the pedigree or single-step genomic BLUP (ssGBLUP) with the H relationship matrix integrating SNP markers and pedigree. The genetic gain of body weight and inbreeding coefficient of NP for eight breeding schemes with CNBS_PBLUP (CP), CNBS_ssGLUP (CS), ONBS_PBLUP (OP10, OP30, OP50), and ONBS_ssGBLUP (OS10, OS30, OS50) with three proportions of the introduced MP individuals were calculated. Compared to CP, genetic gains for the three OP schemes increased by 7.68 to 11.27% after short-term selection, and by 2.51 to 5.79% after long-term selection. In comparison to CS, genetic gains for the three OS schemes increased by 8.21 to 8.96% after short-term selection, and from 4.46 to 5.87% after long-term selection. The ONBS schemes achieved higher genetic gains than the corresponding CNBS schemes whether using genomic or pedigree information. The advantage of ONBS over CNBS is reduced after long-term selection. Genetic gains for the three OS schemes increased by 9.77 to 14.06% after long-term selection compared with the corresponding OP schemes. Furthermore, no significant difference (P > 0.05) in genetic gain was revealed among the ONBS schemes after either pedigree-based or genomic selection. Inbreeding coefficients for the three OP schemes increased from 59.45 to 70.98% compared with CP, whereas inbreeding coefficients for the three OS schemes increased from 24.72 to 32.22% compared with CS. Besides, after long-term selection, inbreeding coefficients for the three OS schemes decreased from 13.13 to 14.79% compared with the corresponding OP schemes. In a nutshell, ONBS using introduced MP individuals has great promise in the selective breeding program of L. vannamei. Genomic information has more potential to improve selection response and control inbreeding level than pedigree information when applying ONBS.

Mother of all bonds: Influences on spatial association across the lifespan in capuchins.

In humans, being more socially integrated is associated with better physical and mental health and/or with lower mortality. This link between sociality and health may have ancient roots: sociality also predicts survival or reproduction in other mammals, such as rats, dolphins, and non-human primates. A key question, therefore, is which factors influence the degree of sociality over the life course. Longitudinal data can provide valuable insight into how environmental variability drives individual differences in sociality and associated outcomes. The first year of life-when long-lived mammals are the most reliant on others for nourishment and protection-is likely to play an important role in how individuals learn to integrate into groups. Using behavioral, demographic, and pedigree information on 376 wild capuchin monkeys (Cebus imitator) across 20 years, we address how changes in group composition influence spatial association. We further try to determine the extent to which early maternal social environments have downstream effects on sociality across the juvenile and (sub)adult stages. We find a positive effect of early maternal spatial association, where female infants whose mothers spent more time around others also later spent more time around others as juveniles and subadults. Our results also highlight the importance of kin availability and other aspects of group composition (e.g., group size) in dynamically influencing spatial association across developmental stages. We bring attention to the importance of-and difficulty in-determining the social versus genetic influences that parents have on offspring phenotypes. RESEARCH HIGHLIGHTS: Having more maternal kin (mother and siblings) is associated with spending more time near others across developmental stages in both male and female capuchins. Having more offspring as a subadult or adult female is additionally associated with spending more time near others. A mother's average sociality (time near others) is predictive of how social her daughters (but not sons) become as juveniles and subadults (a between-mother effect). Additional variation within sibling sets in this same maternal phenotype is not predictive of how social they become later relative to each other (no within-mother effect).

Impact of inbreeding on production, fertility, and health traits in German Holstein dairy cattle utilizing various inbreeding estimators

In dairy cattle production, it is important to understand how inbreeding affects production, fertility, and health traits. However, there is still limited use of genomic information to estimate inbreeding, despite advancements in genotyping technologies. To address this gap, we investigated the impact of inbreeding on German Holstein dairy cattle using both pedigree-based and genomic-based inbreeding estimators. We employed one method based on pedigree information (Fped) together with 6 genomic-based methods, including 3 GCTA estimators (Fhat1, Fhat2, Fhat3), VanRaden's first method (FVR1, with observed allele frequencies and FVR0.5 when allele frequencies are set to 0.5), and one based on runs of homozygosity (Froh). Data from 24,489 cows with both phenotypes and genotypes were used, with a pedigree including 232,780 animals born between 1970 and 2018. We analyzed the effects of inbreeding depression on production, fertility, and health traits separately, using single-trait linear animal models as well as threshold models to account for the binary nature of the health traits. For the health traits, we transformed solutions from the liability scale to a probability scale for easier interpretation. Our results showed that the mean inbreeding coefficients from all estimators ranged from -0.003 to 0.243, with negative values observed for most genomic-based methods. We found out that a 1% increase in inbreeding caused a depression ranging from 25.94 kg (Fhat1) to 40.62 kg (Fhat3), 1.18 kg (Fhat2) to 1.70 kg (Fhat3), 0.90 kg (Fhat2) to 1.45 kg (Froh and Fhat3), 0.19 (Fped) to 0.34 d (Fhat3) for 305 d milk yield, fat, protein, and calving interval respectively. The health traits showed slight changes when inbreeding was gradually increased by 5% with digital dermatitis showing rather a contrasting trend to that of mastitis which reduced the more an animal was inbred. Overall, our study highlights the importance of considering both pedigree-based and genomic-based inbreeding estimators when assessing the impact on inbreeding, emphasizing that not all inbreeding is harmful.

Inbreeding depression and runs of homozygosity islands in Asturiana de los Valles cattle breed after 30 years of selection.

Inbreeding depression results in a decrease in the average phenotypic values of affected traits. It has been traditionally estimated from pedigree-based inbreeding coefficients. However, with the development of single-nucleotide polymorphism arrays, novel methods were developed for calculating the inbreeding coefficient, and consequently, inbreeding depression. The aim of the study was to analyse inbreeding depression in 6 growth and 2 reproductive traits in the Asturiana de los Valles cattle breed using both genealogical and molecular information. The pedigree group comprised 225,848 records and an average equivalent number of complete generations of 2.3. The molecular data comprised genotypes of 2693 animals using the Affymetrix medium-density chip. Using the pedigree information, three different inbreeding coefficients were estimated for the genotyped animals: the full pedigree coefficient (FPED ), and the recent and ancient inbreeding coefficients based on the information of the last three generations (FPED<3G ) and until the last three generations (FPED>3G ), respectively. Using the molecular data, seven inbreeding coefficients were calculated. Four of them were estimated based on runs of homozygosity (ROH), considering (1) the total length (FROH ), (2) segments shorter than 4 megabases (FROH<4 ), (3) between 4 and 17 megabases (FROH4-17 ), and (4) longer than 17 Mb (FROH>17 ). Additionally, the three inbreeding coefficients implemented in the Plink software (FHAT1-3 ) were estimated. Inbreeding depression was estimated using linear mixed-effects model with inbreeding coefficients used as covariates. All analysed traits (birth weight, preweaning average daily gain, weaning weight adjusted at 180 days, carcass weight, calving ease, age at first calving, calving interval) showed a statistically significant non-zero effect of inbreeding depression estimated from the pedigree group, except for the Postweaning Average Daily Gain trait. When inbreeding coefficients were based on the genomic group, statistically significant inbreeding depression was observed for two traits, Preweaning Average Daily Gain and Weaning Weight based on FROH , FROH>17 , and FHAT3 inbreeding coefficients. Nevertheless, similar to inbreeding depression estimated based on pedigree information, estimates of inbreeding depression based on genomic information had no relevant economic impact. Despite this, from a long-term perspective, genotyped data could be included to maximize genetic progress in genetic programs following an optimal genetic contribution strategy and to consider individual inbreeding load instead global inbreeding. ROH islands were identified on chromosomes 2, 3, 8, 10, and 16. Such regions contain several candidate genes for growth development, intramuscular fat, body weight and lipid metabolism that are related to production traits selected in Asturiana de los Valles breed.

Reproductive traits in Pura Raza Española mares manifest inbreeding depression from low levels of homozygosity.

Inbreeding depression is a genetic phenomenon associated with the loss of fitness and mean phenotypic performance due to mating between relatives. Historically, inbreeding coefficients have been estimated from pedigree information. However, the onset of genomic selection programs provides large datasets of individuals genotyped using SNP arrays, enabling more precise assessment of an individual's genomic-level inbreeding using genomic data. One of the traits most sensitive to issues stemming from increased inbreeding is reproduction. This is particularly important in equine, in which fertility is only moderate compared to other livestock species. To explore this further, we evaluated the effect of inbreeding on five reproductive traits (age at first foaling (AFF), average interval between foalings (AIF), total number of foalings (NF), productive life (PL) and reproductive efficiency (RE)) in Pura Raza Español mares using genomic data. Residual predicted phenotypes were obtained by purging these traits through the REML (wgResidual ) and ssGREML (gResidual ) approaches in reproductive data of 29,847 PRE mares using the BLUPF90+ program. Next, we used pedigree-based (Fped ) and ROH-based genomic (FROH ) inbreeding coefficients derived from 1018 animals genotyped with 61,271 SNPs to estimate the inbreeding depression (linear regression). Our results indicated significant levels of inbreeding depression for all reproductive traits, with the exception of the AIF trait when Fped was used. However, all traits were negatively affected by the increase in genomic inbreeding, and FROH was found to capture more inbreeding depression than Fped . Likewise, REML models (ssGREML) using genomic data for estimated predicted residual phenotypes resulted in higher variance explained by the model compared with the models not using genomics (REML). Finally, a segmented regression analysis was conducted to evaluate the effect of inbreeding depression, revealing that the levels of genealogical and genomic homozygosity do not manifest uniformly in reproductive traits. In contrast, the levels of inbreeding depression ranged from low to high as homozygosity increased. This analysis also showed that reproductive traits are very sensitive to inbreeding depression, even with relatively low levels of homozygosity.

Toward a Standard Data Architecture for Additive Manufacturing

To advance additive manufacturing (AM), a scalable architecture is needed to structure, curate and access the data from AM R&D projects that are conducted to evaluate new materials, processes and technologies. Effective project metadata management enables the sharing of AM domain knowledge. This work introduces an AM data modeling architecture to capture pedigree information from AM projects which enables the traceability of the material. This overall AM model includes five modules covering information about (1) project management, (2) feedstock materials, (3) AM building and post processing, (4) microstructure and properties measurements and (5) computer simulations. The objective of this design is to ease the integration of the heterogeneous datasets from different sources and allow for extensions, for example, to incorporate sub-models from other efforts. As a proof of concept, the material and process models defined in the paper capture the major metadata elements for laser powder bed fusion AM. To demonstrate the effectiveness of the architecture, the models are implemented using extensible markup language and preliminarily tested using the project data from America Makes. Additional data sub-models can be integrated in this architecture without affecting the existing structure.

Prediction of response to truncated selection based on BLUP of breeding values and its prediction accuracy.

Three methods of predicting the response to truncated selection based on BLUP of breeding values (BVs) were compared under conditions in which the phenotypic values for the progenies of selected animals were not available. The following methods were used to predict the response to selection: (1) based on the mean of estimated breeding values (EBV) in the candidate population for selection ( ), (2) based on the variance of EBV in the candidate population for selection ( ), and (3) based on diagonal elements of the inverse matrix on the left-hand side of the mixed model equation ( ). The deviation of the average BV of the selected animals from the average BV of the candidate population for selection was taken as the true response to selection. The pedigree information and phenotypic values used for comparison were generated by Monte Carlo computer simulation. The results showed that had the smallest absolute mean error and had the smallest root-mean-square error. We concluded that it is desirable to use or to predict the response to truncated selection based on BLUP of BVs. However, in the population where selection is ongoing, the prediction accuracy of selection response is likely to be affected by the distortion of the distribution and the Bulmer effect for .

Discrepancies in University of California Fig Breeding Records

A 1975 fig crop reference chapter written by W.B. Storey contains pedigree information involving 30 cultivars from the University of California breeding program and early California. The data were compared with the records from the US Department of Agriculture and statements from two other sources. Graphical representations were used to determine differences among the authors. All data are supplied in this article and supplemental materials. An estimate of correct parentage is presented in the final graph.

Aleutian disease: Risk factors and ImmunAD strategy for genetic improvement of tolerance in American mink (Neogale vison).

Aleutian disease (AD) is a devastating infectious disease in American mink (Neogale vison) industry caused by Aleutian mink disease virus (AMDV). Two crucial steps toward controlling infectious diseases in farm animals are: (i) assessment of the infection risk factors to minimize the likelihood of infection and (ii) selection of animals with superior immune responses against pathogens to build tolerant farms. This study aimed to investigate AD risk factors and evaluate a novel "ImmunAD" approach for genetic improvement of AD tolerance. Phenotypic records and pedigree information of 1,366 and 24,633 animals were included in this study. The risk of animal's age, sex, color type, and year of sampling on AMDV infection was assessed using a logistic regression model and counter immune-electrophoresis (CIEP) test results. ImmunAD phenotype was calculated based on AMDVG enzyme-linked immunosorbent assay (ELISA) and CIEP test results, and breeding values for ImmunAD were estimated using an animal model. Animals were classified into high-coordinated (HCIR), average-coordinated (ACIR), and low-coordinated immune responders (LCIR) using ImmunAD's breeding values, and the impact of selection of HCIR on live grade of pelt quality (PQ), harvest weight (HW), and harvest length (HL) breeding values were evaluated. Age of > 1 year, male sex, and year of sampling were identified as significant risk factors of AD (p < 0.05). A moderate-to-high heritability (0.55±0.07) was estimated for ImmunAD, while a higher heritability was observed among the CIEP-positive animals (0.76±0.06). Significantly higher breeding values were observed for PQ and HL among HCIR than those for LCIR and ACIR (p < 0.05). Our findings indicate the critical role of male breeders in AD distribution within mink farms. Regular screening of AD in male breeders before pairing them with females during breeding seasons can help disease control. ImmunAD strategy can be applied to genetic improvement of AD tolerance, with favorable impacts on some growth and production traits. Higher genetic gains can be achieved in populations with higher AD seroprevalences.

Construction of a strawberry breeding core collection to capture and exploit genetic variation

BackgroundGenetic diversity is crucial for the success of plant breeding programs and core collections are important resources to capture this diversity. Many core collections have already been constructed by gene banks, whose main goal is to obtain a panel of a limited number of genotypes to simplify management practices and to improve shareability while retaining as much diversity as possible. However, as gene banks have a different composition and goal than plant breeding programs, constructing a core collection for a plant breeding program should consider different aspects.ResultsIn this study, we present a novel approach for constructing a core collection by integrating both genomic and pedigree information to maximize the representation of the breeding germplasm in a minimum subset of genotypes while accounting for future genetic variation within a strawberry breeding program. Our stepwise approach starts with selecting the most important crossing parents of advanced selections and genotypes included for specific traits, to represent also future genetic variation. We then use pedigree-genomic-based relationship coefficients combined with the ‘accession to nearest entry’ criterion to complement the core collection and maximize its representativeness of the current breeding program. Combined pedigree-genomic-based relationship coefficients allow for accurate relationship estimation without the need to genotype every individual in the breeding program.ConclusionsThis stepwise construction of a core collection in a strawberry breeding program can be applied in other plant breeding programs to construct core collections for various purposes.