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In plant breeding, heritability is often calculated (i) as a measure of precision of trials and/or (ii) to compute the response to selection. It is usually estimated on an entry-mean basis, since is usually an aggregated value, as genotypes are replicated in trials, which stands in contrast with animal breeding and human genetics. When this was first proposed, assumptions such as balanced data and independent genotypic effects were made that are often violated in modern plant breeding trials/analyses. Due to this, multiple alternative methods have been proposed, aiming to generalize heritability on an entry-mean basis. In this study, we propose an extension of the concept for heritability on an entry-mean to an entry-difference basis, which allows for more detailed insight and is more meaningful in the context of selection in plant breeding, because the correlation among entry means can be accounted for. We show that under certain circumstances our method reduces to other popular generalized methods for heritability estimation on an entry-mean basis. The approach is exemplified via four examples that show different levels of complexity, where we compare six methods for heritability estimation on an entry-mean basis to our approach (example codes: https://github.com/PaulSchmidtGit/Heritability). Results suggest that heritability on an entry-difference basis is a well-suited alternative for obtaining an overall heritability estimate, and in addition provides one heritability per genotype as well as one per difference between genotypes.

The dissection of complex traits of economic importance to the pig industry requires the availability of a significant number of genetic markers, such as single nucleotide polymorphisms (SNPs). This study was conducted to discover several hundreds of thousands of porcine SNPs using next generation sequencing technologies and use these SNPs, as well as others from different public sources, to design a high-density SNP genotyping assay. A total of 19 reduced representation libraries derived from four swine breeds (Duroc, Landrace, Large White, Pietrain) and a Wild Boar population and three restriction enzymes (AluI, HaeIII and MspI) were sequenced using Illumina's Genome Analyzer (GA). The SNP discovery effort resulted in the de novo identification of over 372K SNPs. More than 549K SNPs were used to design the Illumina Porcine 60K+SNP iSelect Beadchip, now commercially available as the PorcineSNP60. A total of 64,232 SNPs were included on the Beadchip. Results from genotyping the 158 individuals used for sequencing showed a high overall SNP call rate (97.5%). Of the 62,621 loci that could be reliably scored, 58,994 were polymorphic yielding a SNP conversion success rate of 94%. The average minor allele frequency (MAF) for all scorable SNPs was 0.274. Overall, the results of this study indicate the utility of using next generation sequencing technologies to identify large numbers of reliable SNPs. In addition, the validation of the PorcineSNP60 Beadchip demonstrated that the assay is an excellent tool that will likely be used in a variety of future studies in pigs.

The rate of annual yield increases for major staple crops must more than double relative to current levels in order to feed a predicted global population of 9 billion by 2050. Controlled hybridization and selective breeding have been used for centuries to adapt plant and animal species for human use. However, achieving higher, sustainable rates of improvement in yields in various species will require renewed genetic interventions and dramatic improvement of agricultural practices. Genomic prediction of breeding values has the potential to improve selection, reduce costs and provide a platform that unifies breeding approaches, biological discovery, and tools and methods. Here we compare and contrast some animal and plant breeding approaches to make a case for bringing the two together through the application of genomic selection. We propose a strategy for the use of genomic selection as a unifying approach to deliver innovative 'step changes' in the rate of genetic gain at scale.

Breed utilization, genetic improvement, and industry consolidation are predicted to have major impacts on the genetic composition of commercial chickens. Consequently, the question arises as to whether sufficient genetic diversity remains within industry stocks to address future needs. With the chicken genome sequence and more than 2.8 million single-nucleotide polymorphisms (SNPs), it is now possible to address biodiversity using a previously unattainable metric: missing alleles. To achieve this assessment, 2551 informative SNPs were genotyped on 2580 individuals, including 1440 commercial birds. The proportion of alleles lacking in commercial populations was assessed by (1) estimating the global SNP allele frequency distribution from a hypothetical ancestral population as a reference, then determining the portion of the distribution lost, and then (2) determining the relationship between allele loss and the inbreeding coefficient. The results indicate that 50% or more of the genetic diversity in ancestral breeds is absent in commercial pure lines. The missing genetic diversity resulted from the limited number of incorporated breeds. As such, hypothetically combining stocks within a company could recover only preexisting within-breed variability, but not more rare ancestral alleles. We establish that SNP weights act as sentinels of biodiversity and provide an objective assessment of the strains that are most valuable for preserving genetic diversity. This is the first experimental analysis investigating the extant genetic diversity of virtually an entire agricultural commodity. The methods presented are the first to characterize biodiversity in terms of allelic diversity and to objectively link rate of allele loss with the inbreeding coefficient.

Lethal recessive alleles cause pre- or postnatal death in homozygous affected individuals, reducing fertility. Especially in small size domestic and wild populations, those alleles might be exposed by inbreeding, caused by matings between related parents that inherited the same recessive lethal allele from a common ancestor. In this study we report five relatively common (up to 13.4% carrier frequency) recessive lethal haplotypes in two commercial pig populations. The lethal haplotypes have a large effect on carrier-by-carrier matings, decreasing litter sizes by 15.1 to 21.6%. The causal mutations are of different type including two splice-site variants (affecting POLR1B and TADA2A genes), one frameshift (URB1), and one missense (PNKP) variant, resulting in a complete loss-of-function of these essential genes. The recessive lethal alleles affect up to 2.9% of the litters within a single population and are responsible for the death of 0.52% of the total population of embryos. Moreover, we provide compelling evidence that the identified embryonic lethal alleles contribute to the observed heterosis effect for fertility (i.e. larger litters in crossbred offspring). Together, this work marks specific recessive lethal variation describing its functional consequences at the molecular, phenotypic, and population level, providing a unique model to better understand fertility and heterosis in livestock.

Plant-derived protein sources are the most relevant substitutes for fishmeal in aquafeeds. Nevertheless, the effects of plant based diets on the intestinal microbiome especially of juvenile Rainbow trout (Oncorhynchus mykiss) are yet to be fully investigated. The present study demonstrates, based on 16S rDNA bacterial community profiling, that the intestinal microbiome of juvenile Rainbow trout is strongly affected by dietary plant protein inclusion levels. After first feeding of juveniles with either 0%, 50% or 97% of total dietary protein content derived from plants, statistically significant differences of the bacterial gut community for the three diet-types were detected, both at phylum and order level. The microbiome of juvenile fish consisted mainly of the phyla Proteobacteria, Firmicutes, Bacteroidetes, Fusobacteria and Actinobacteria, and thus fits the salmonid core microbiome suggested in previous studies. Dietary plant proteins significantly enhanced the relative abundance of the orders Lactobacillales, Bacillales and Pseudomonadales. Animal proteins in contrast significantly promoted Bacteroidales, Clostridiales, Vibrionales, Fusobacteriales and Alteromonadales. The overall alpha diversity significantly decreased with increasing plant protein inclusion levels and with age of experimental animals. In order to investigate permanent effects of the first feeding diet-type on the early development of the microbiome, a diet change was included in the study after 54 days, but no such effects could be detected. Instead, the microbiome of juvenile trout fry was highly dependent on the actual diet fed at the time of sampling.

Dietary protein sources can have profound effects on host-microbe interactions in the gut that are critically important for immune resilience. However more knowledge is needed to assess the impact of different protein sources on gut and animal health. Thirty-six wildtype male C57BL/6J mice of 35 d age (n = 6/group; mean ± SEM body weight 21.9 ± 0.25 g) were randomly assigned to groups fed for four weeks with semi synthetic diets prepared with one of the following protein sources containing (300 g/kg as fed basis): soybean meal (SBM), casein, partially delactosed whey powder, spray dried plasma protein, wheat gluten meal and yellow meal worm. At the end of the experiment, mice were sacrificed to collect ileal tissue to acquire gene expression data, and mammalian (mechanistic) target of rapamycin (mTOR) activity, ileal digesta to study changes in microbiota and serum to measure cytokines and chemokines. By genome-wide transcriptome analysis, we identified fourteen high level regulatory genes that are strongly affected in SBM-fed mice compared to the other experimental groups. They mostly related to the mTOR pathway. In addition, an increased (P < 0.05) concentration of granulocyte colony-stimulating factor was observed in serum of SBM-fed mice compared to other dietary groups. Moreover, by 16S rRNA sequencing, we observed that SBM-fed mice had higher (P < 0.05) abundances of Bacteroidales family S24-7, compared to the other dietary groups. We showed that measurements of genome-wide expression and microbiota composition in the mouse ileum reveal divergent responses to diets containing different protein sources, in particular for a diet based on SBM.

Through centuries of both natural and artificial selection, a variety of local cattle populations arose with highly specific phenotypes. However, the intensification and expansion of scale in animal production systems led to the predominance of a few highly productive cattle breeds. The loss of local populations is often considered irreversible and with them specific qualities and rare variants could be lost as well. Over these last years, the interest in these local breeds has increased again leading to increasing efforts to conserve these breeds or even revive lost populations, e.g. through the use of crosses with similar breeds. However, the remaining populations are expected to contain crossbred individuals resulting from introgressions. They are likely to carry exogenous genes that affect the breed's authenticity on a genomic level. Using the revived Campine breed as a case study, 289 individuals registered as purebreds were genotyped on the Illumina BovineSNP50. In addition, genomic information on the Illumina BovineHD and Illumina BovineSNP50 of ten breeds was available to assess the current population structure, genetic diversity, and introgression with phenotypically similar and/or historically related breeds. Introgression with Holstein and beef cattle genotypes was limited to only a few farms. While the current population shows a substantial amount of within-breed variation, the majority of genotypes can be separated from other breeds in the study, supporting the re-establishment of the Campine breed. The majority of the population is genetically close to the Deep Red (NL), Improved Red (NL) and Eastern Belgium Red and White (BE) cattle, breeds known for their historical ties to the Campine breed. This would support an open herdbook policy, thereby increasing the population size and consequently providing a more secure future for the breed.

Utilizing the whole genomic variation of complex traits to predict the yet-to-be observed phenotypes or unobserved genetic values via whole genome prediction (WGP) and to infer the underlying genetic architecture via genome wide association study (GWAS) is an interesting and fast developing area in the context of human disease studies as well as in animal and plant breeding. Though thousands of significant loci for several species were detected via GWAS in the past decade, they were not used directly to improve WGP due to lack of proper models. Here, we propose a generalized way of building trait-specific genomic relationship matrices which can exploit GWAS results in WGP via a best linear unbiased prediction (BLUP) model for which we suggest the name BLUP|GA. Results from two illustrative examples show that using already existing GWAS results from public databases in BLUP|GA improved the accuracy of WGP for two out of the three model traits in a dairy cattle data set, and for nine out of the 11 traits in a rice diversity data set, compared to the reference methods GBLUP and BayesB. While BLUP|GA outperforms BayesB, its required computing time is comparable to GBLUP. Further simulation results suggest that accounting for publicly available GWAS results is potentially more useful for WGP utilizing smaller data sets and/or traits of low heritability, depending on the genetic architecture of the trait under consideration. To our knowledge, this is the first study incorporating public GWAS results formally into the standard GBLUP model and we think that the BLUP|GA approach deserves further investigations in animal breeding, plant breeding as well as human genetics.

Objectives were to evaluate breed, heterosis (HI), and maternal effects on wool production in Rambouillet (R x R), Targhee (T x T), and reciprocal-cross (R x T and T x R) 1-yr-old ewes. Greasy fleece weights (GFW) were obtained at shearing and mid-side, britch, and whole-fleece core wool samples were collected to quantify average (A-FD) and CV of fiber diameter (CV-FD). Laboratory scoured yield (LSY) was quantified on core samples and used to estimate clean fleece weight (CFW). Single-born ewes had greater GFW (3.48 kg), greater CFW (2.11 kg), and lower mid-side CV-FD (17.5%) than multiple-born ewes (3.18 kg, 1.95 kg, and 18.1%, respectively; P < 0.01). Rambouillet-sired ewes had greater LSY than T-sired ewes (60.6 vs. 60.0%; P < 0.01), but no breed effects were detected for GFW or CFW. A sire breed x dam breed interaction effect was detected for A-FD at all locations (P ≤ 0.05). Reciprocal-cross performance indicated unfavorable HI for A-FD within mid-side (+0.34 µm), britch (+0.97 µm), and core samples (+0.42 pm; P ≤ 0.05) compared to purebred average. Greater mid-side and britch A-FD in R x T (22.8 and 25.2 pm) than T x R ewes (21.2 and 23.5 pm; P < 0.01) implied a more favorable additive maternal effect for crossbred ewes gestated and reared by R compared to T dams. Future analyses will consider lifetime lamb and wool production of these breed types to evaluate the utility of finewool crossbred ewes in extensive production systems.