Improving selection decisions with mating information by accounting for Mendelian sampling variances looking two generations ahead.

BACKGROUND: Breeding programs are judged by the genetic level of animals that are used to disseminate genetic progress. These animals are typically the best ones of the population. To maximise the genetic level of very good animals in the next generation, parents that are more likely to produce top performing offspring need to be selected. The ability of individuals to produce high-performing progeny differs because of differences in their breeding values and gametic variances. Differences in gametic variances among individuals are caused by differences in heterozygosity and linkage. The use of the gametic Mendelian sampling variance has been proposed before, for use in the usefulness criterion or Index5, and in this work, we extend existing approaches by not only considering the gametic Mendelian sampling variance of individuals, but also of their potential offspring. Thus, the criteria developed in this study plan one additional generation ahead. For simplicity, we assumed that the true quantitative trait loci (QTL) effects, genetic map and the haplotypes of all animals are known. RESULTS: In this study, we propose a new selection criterion, ExpBVSelGrOff, which describes the genetic level of selected grand-offspring that are produced by selected offspring of a particular mating. We compare our criterion with other published criteria in a stochastic simulation of an ongoing breeding program for 21 generations for proof of concept. ExpBVSelGrOff performed better than all other tested criteria, like the usefulness criterion or Index5 which have been proposed in the literature, without compromising short-term gains. After only five generations, when selection is strong (1%), selection based on ExpBVSelGrOff achieved 5.8% more commercial genetic gain and retained 25% more genetic variance without compromising inbreeding rate compared to selection based only on breeding values. CONCLUSIONS: Our proposed selection criterion offers a new tool to accelerate genetic progress for contemporary genomic breeding programs. It retains more genetic variance than previously published criteria that plan less far ahead. Considering future gametic Mendelian sampling variances in the selection process also seems promising for maintaining more genetic variance.

Definition of metafounders based on population structure analysis.

BACKGROUND: Limitations of the concept of identity by descent in the presence of stratification within a breeding population may lead to an incomplete formulation of the conventional numerator relationship matrix ( A ). Combining A with the genomic relationship matrix ( G ) in a single-step approach for genetic evaluation may cause inconsistencies that can be a source of bias in the resulting predictions. The objective of this study was to identify stratification using genomic data and to transfer this information to matrix A , to improve the compatibility of A and G . METHODS: Using software to detect population stratification (ADMIXTURE), we developed an iterative approach. First, we identified 2 to 40 strata ( k ) with ADMIXTURE, which we then introduced in a stepwise manner into matrix A , to generate matrix A Γ using the metafounder methodology. Improvements in consistency between matrix G and A Γ were evaluated by regression analysis and through the comparison of the overall mean and mean diagonal values of both matrices. The approach was tested on genotype and pedigree information of European and North American Brown Swiss animals (85,249). Analyses with ADMIXTURE were initially performed on the full set of genotypes (S1). In addition, we used an alternative dataset where we avoided sampling of closely related animals (S2). RESULTS: Results of the regression analyses of standard A on G were - 0.489, 0.780 and 0.647 for intercept, slope and fit of the regression. When analysing S1 data results of the regression for A Γ on G corresponding values were - 0.028, 1.087 and 0.807 for k =7, while there was no clear optimum k . Analyses of S2 gave a clear optimal k =24, with - 0.020, 0.998 and 0.817 as results of the regression. For this k differences in mean and mean diagonal values between both matrices were negligible. CONCLUSIONS: The derivation of hidden stratification information based on genotyped animals and its integration into A improved compatibility of the resulting A Γ and G considerably compared to the initial situation. In dairy breeding populations with large half-sib families as sub-structures it is necessary to balance the data when applying population structure analysis to obtain meaningful results.

Estimating genomic relationships of metafounders across and within breeds using maximum likelihood, pseudo-expectation-maximization maximum likelihood and increase of relationships.

BACKGROUND: The theory of "metafounders" proposes a unified framework for relationships across base populations within breeds (e.g. unknown parent groups), and base populations across breeds (crosses) together with a sensible compatibility with genomic relationships. Considering metafounders might be advantageous in pedigree best linear unbiased prediction (BLUP) or single-step genomic BLUP. Existing methods to estimate relationships across metafounders Γ are not well adapted to highly unbalanced data, genotyped individuals far from base populations, or many unknown parent groups (within breed per year of birth). METHODS: We derive likelihood methods to estimate Γ . For a single metafounder, summary statistics of pedigree and genomic relationships allow deriving a cubic equation with the real root being the maximum likelihood (ML) estimate of Γ . This equation is tested with Lacaune sheep data. For several metafounders, we split the first derivative of the complete likelihood in a term related to Γ , and a second term related to Mendelian sampling variances. Approximating the first derivative by its first term results in a pseudo-EM algorithm that iteratively updates the estimate of Γ by the corresponding block of the H-matrix. The method extends to complex situations with groups defined by year of birth, modelling the increase of Γ using estimates of the rate of increase of inbreeding ( Δ F ), resulting in an expanded Γ and in a pseudo-EM+ Δ F algorithm. We compare these methods with the generalized least squares (GLS) method using simulated data: complex crosses of two breeds in equal or unsymmetrical proportions; and in two breeds, with 10 groups per year of birth within breed. We simulate genotyping in all generations or in the last ones. RESULTS: For a single metafounder, the ML estimates of the Lacaune data corresponded to the maximum. For simulated data, when genotypes were spread across all generations, both GLS and pseudo-EM(+ Δ F ) methods were accurate. With genotypes only available in the most recent generations, the GLS method was biased, whereas the pseudo-EM(+ Δ F ) approach yielded more accurate and unbiased estimates. CONCLUSIONS: We derived ML, pseudo-EM and pseudo-EM+ Δ F methods to estimate Γ in many realistic settings. Estimates are accurate in real and simulated data and have a low computational cost.

Predictive ability of multi-population genomic prediction methods of phenotypes for reproduction traits in Chinese and Austrian pigs.

BACKGROUND: Multi-population genomic prediction can rapidly expand the size of the reference population and improve genomic prediction ability. Machine learning (ML) algorithms have shown advantages in single-population genomic prediction of phenotypes. However, few studies have explored the effectiveness of ML methods for multi-population genomic prediction. RESULTS: In this study, 3720 Yorkshire pigs from Austria and four breeding farms in China were used, and single-trait genomic best linear unbiased prediction (ST-GBLUP), multitrait GBLUP (MT-GBLUP), Bayesian Horseshoe (BayesHE), and three ML methods (support vector regression (SVR), kernel ridge regression (KRR) and AdaBoost.R2) were compared to explore the optimal method for joint genomic prediction of phenotypes of Chinese and Austrian pigs through 10 replicates of fivefold cross-validation. In this study, we tested the performance of different methods in two scenarios: (i) including only one Austrian population and one Chinese pig population that were genetically linked based on principal component analysis (PCA) (designated as the "two-population scenario") and (ii) adding reference populations that are unrelated based on PCA to the above two populations (designated as the "multi-population scenario"). Our results show that, the use of MT-GBLUP in the two-population scenario resulted in an improvement of 7.1% in predictive ability compared to ST-GBLUP, while the use of SVR and KKR yielded improvements in predictive ability of 4.5 and 5.3%, respectively, compared to MT-GBLUP. SVR and KRR also yielded lower mean square errors (MSE) in most population and trait combinations. In the multi-population scenario, improvements in predictive ability of 29.7, 24.4 and 11.1% were obtained compared to ST-GBLUP when using, respectively, SVR, KRR, and AdaBoost.R2. However, compared to MT-GBLUP, the potential of ML methods to improve predictive ability was not demonstrated. CONCLUSIONS: Our study demonstrates that ML algorithms can achieve better prediction performance than multitrait GBLUP models in multi-population genomic prediction of phenotypes when the populations have similar genetic backgrounds; however, when reference populations that are unrelated based on PCA are added, the ML methods did not show a benefit. When the number of populations increased, only MT-GBLUP improved predictive ability in both validation populations, while the other methods showed improvement in only one population.

Accuracy of genomic prediction using multiple Atlantic salmon populations.

BACKGROUND: The accuracy of genomic prediction is partly determined by the size of the reference population. In Atlantic salmon breeding programs, four parallel populations often exist, thus offering the opportunity to increase the size of the reference set by combining these populations. By allowing a reduction in the number of records per population, multi-population prediction can potentially reduce cost and welfare issues related to the recording of traits, particularly for diseases. In this study, we evaluated the accuracy of multi- and across-population prediction of breeding values for resistance to amoebic gill disease (AGD) using all single nucleotide polymorphisms (SNPs) on a 55K chip or a selected subset of SNPs based on the signs of allele substitution effect estimates across populations, using both linear and nonlinear genomic prediction (GP) models in Atlantic salmon populations. In addition, we investigated genetic distance, genetic correlation estimated based on genomic relationships, and persistency of linkage disequilibrium (LD) phase across these populations. RESULTS: The genetic distance between populations ranged from 0.03 to 0.07, while the genetic correlation ranged from 0.19 to 0.99. Nonetheless, compared to within-population prediction, there was limited or no impact of combining populations for multi-population prediction across the various models used or when using the selected subset of SNPs. The estimates of across-population prediction accuracy were low and to some extent proportional to the genetic correlation estimates. The persistency of LD phase between adjacent markers across populations using all SNP data ranged from 0.51 to 0.65, indicating that LD is poorly conserved across the studied populations. CONCLUSIONS: Our results show that a high genetic correlation and a high genetic relationship between populations do not guarantee a higher prediction accuracy from multi-population genomic prediction in Atlantic salmon.

Breeding for resilience in finishing pigs can decrease tail biting, lameness and mortality.

BACKGROUND: Previous research showed that deviations in longitudinal data are heritable and can be used as a proxy for pigs' general resilience. However, only a few studies investigated the relationship between these resilience traits and other traits related to resilience and welfare. Therefore, this study investigated the relationship between resilience traits derived from deviations in longitudinal data and traits related to animal resilience, health and welfare, such as tail and ear biting wounds, lameness and mortality. RESULTS: In our experiment, 1919 finishing pigs with known pedigree (133 Piétrain sires and 266 crossbred dams) were weighed every 2 weeks and scored for physical abnormalities, such as lameness and ear and tail biting wounds (17,066 records). Resilience was assessed via deviations in body weight, deviations in weighing order and deviations in observed activity during weighing. The association between these resilience traits and physical abnormality traits was investigated and genetic parameters were estimated. Deviations in body weight had moderate heritability estimates (h2 = 25.2 to 36.3%), whereas deviations in weighing order (h2 = 4.2%) and deviations in activity during weighing (h2 = 12.0%) had low heritability estimates. Moreover, deviations in body weight were positively associated and genetically correlated with tail biting wounds (rg = 0.22 to 0.30), lameness (rg = 0.15 to 0.31) and mortality (rg = 0.19 to 0.33). These results indicate that events of tail biting, lameness and mortality are associated with deviations in pigs' body weight evolution. This relationship was not found for deviations in weighing order and activity during weighing. Furthermore, individual body weight deviations were positively correlated with uniformity at the pen level, providing evidence that breeding for these resilience traits might increase both pigs' resilience and within-family uniformity. CONCLUSIONS: In summary, our findings show that breeding for resilience traits based on deviations in longitudinal weight data can decrease pigs' tail biting wounds, lameness and mortality while improving uniformity at the pen level. These findings are valuable for pig breeders, as they offer evidence that these resilience traits are an indication of animals' general health, welfare and resilience. Moreover, these results will stimulate the quantification of resilience via longitudinal body weights in other species.

Equivalence of variance components between standard and recursive genetic models using LDL' transformations.

BACKGROUND: Recursive models are a category of structural equation models that propose a causal relationship between traits. These models are more parameterized than multiple trait models, and they require imposing restrictions on the parameter space to ensure statistical identification. Nevertheless, in certain situations, the likelihood of recursive models and multiple trait models are equivalent. Consequently, the estimates of variance components derived from the multiple trait mixed model can be converted into estimates under several recursive models through LDL' or block-LDL' transformations. RESULTS: The procedure was employed on a dataset comprising five traits (birth weight-BW, weight at 90 days-W90, weight at 210 days-W210, cold carcass weight-CCW and conformation-CON) from the Pirenaica beef cattle breed. These phenotypic records were unequally distributed among 149,029 individuals and had a high percentage of missing data. The pedigree used consisted of 343,753 individuals. A Bayesian approach involving a multiple-trait mixed model was applied using a Gibbs sampler. The variance components obtained at each iteration of the Gibbs sampler were subsequently used to estimate the variance components within three distinct recursive models. CONCLUSIONS: The LDL' or block-LDL' transformations applied to the variance component estimates achieved from a multiple trait mixed model enabled inference across multiple sets of recursive models, with the sole prerequisite of being likelihood equivalent. Furthermore, the aforementioned transformations simplify the handling of missing data when conducting inference within the realm of recursive models.

Genetic parameters for novel climatic resilience indicators derived from automatically-recorded vaginal temperature in lactating sows under heat stress conditions.

BACKGROUND: Longitudinal records of automatically-recorded vaginal temperature (TV) could be a key source of data for deriving novel indicators of climatic resilience (CR) for breeding more resilient pigs, especially during lactation when sows are at an increased risk of suffering from heat stress (HS). Therefore, we derived 15 CR indicators based on the variability in TV in lactating sows and estimated their genetic parameters. We also investigated their genetic relationship with sows' key reproductive traits. RESULTS: The heritability estimates of the CR traits ranged from 0.000 ± 0.000 for slope for decreased rate of TV (SlopeDe) to 0.291 ± 0.047 for sum of TV values below the HS threshold (HSUB). Moderate to high genetic correlations (from 0.508 ± 0.056 to 0.998 ± 0.137) and Spearman rank correlations (from 0.431 to 1.000) between genomic estimated breeding values (GEBV) were observed for five CR indicators, i.e. HS duration (HSD), the normalized median multiplied by normalized variance (Nor_medvar), the highest TV value of each measurement day for each individual (MaxTv), and the sum of the TV values above (HSUA) and below (HSUB) the HS threshold. These five CR indicators were lowly to moderately genetically correlated with shoulder skin surface temperature (from 0.139 ± 0.008 to 0.478 ± 0.048) and respiration rate (from 0.079 ± 0.011 to 0.502 ± 0.098). The genetic correlations between these five selected CR indicators and sow reproductive performance traits ranged from - 0.733 to - 0.175 for total number of piglets born alive, from - 0.733 to - 0.175 for total number of piglets born, and from - 0.434 to - 0.169 for number of pigs weaned. The individuals with the highest GEBV (most climate-sensitive) had higher mean skin surface temperature, respiration rate (RR), panting score (PS), and hair density, but had lower mean body condition scores compared to those with the lowest GEBV (most climate-resilient). CONCLUSIONS: Most of the CR indicators evaluated are heritable with substantial additive genetic variance. Five of them, i.e. HSD, MaxTv, HSUA, HSUB, and Nor_medvar share similar underlying genetic mechanisms. In addition, individuals with higher CR indicators are more likely to exhibit better HS-related physiological responses, higher body condition scores, and improved reproductive performance under hot conditions. These findings highlight the potential benefits of genetically selecting more heat-tolerant individuals based on CR indicators.

MATRILINEAL, a sperm-specific phospholipase, triggers maize haploid induction.

Sexual reproduction in flowering plants involves double fertilization, the union of two sperm from pollen with two sex cells in the female embryo sac. Modern plant breeders increasingly seek to circumvent this process to produce doubled haploid individuals, which derive from the chromosome-doubled cells of the haploid gametophyte. Doubled haploid production fixes recombinant haploid genomes in inbred lines, shaving years off the breeding process. Costly, genotype-dependent tissue culture methods are used in many crops, while seed-based in vivo doubled haploid systems are rare in nature and difficult to manage in breeding programmes. The multi-billion-dollar maize hybrid seed business, however, is supported by industrial doubled haploid pipelines using intraspecific crosses to in vivo haploid inducer males derived from Stock 6, first reported in 1959 (ref. 5), followed by colchicine treatment. Despite decades of use, the mode of action remains controversial. Here we establish, through fine mapping, genome sequencing, genetic complementation, and gene editing, that haploid induction in maize (Zea mays) is triggered by a frame-shift mutation in MATRILINEAL (MTL), a pollen-specific phospholipase, and that novel edits in MTL lead to a 6.7% haploid induction rate (the percentage of haploid progeny versus total progeny). Wild-type MTL protein localizes exclusively to sperm cytoplasm, and pollen RNA-sequence profiling identifies a suite of pollen-specific genes overexpressed during haploid induction, some of which may mediate the formation of haploid seed. These findings highlight the importance of male gamete cytoplasmic components to reproductive success and male genome transmittance. Given the conservation of MTL in the cereals, this discovery may enable development of in vivo haploid induction systems to accelerate breeding in crop plants.

Genetic analysis of the modern Australian labradoodle dog breed reveals an excess of the poodle genome.

The genomic diversity of the domestic dog is an invaluable resource for advancing understanding of mammalian biology, evolutionary biology, morphologic variation, and behavior. There are approximately 350 recognized breeds in the world today, many established through hybridization and selection followed by intense breeding programs aimed at retaining or enhancing specific traits. As a result, many breeds suffer from an excess of particular diseases, one of many factors leading to the recent trend of "designer breed" development, i.e. crossing purebred dogs from existing breeds in the hope that offspring will be enriched for desired traits and characteristics of the parental breeds. We used a dense panel of 150,106 SNPs to analyze the population structure of the Australian labradoodle (ALBD), to understand how such breeds are developed. Haplotype and admixture analyses show that breeds other than the poodle (POOD) and Labrador retriever (LAB) contributed to ALBD formation, but that the breed is, at the genetic level, predominantly POOD, with all small and large varieties contributing to its construction. Allele frequency analysis reveals that the breed is enhanced for variants associated with a poodle-like coat, which is perceived by breeders to have an association with hypoallergenicity. We observed little enhancement for LAB-specific alleles. This study provides a blueprint for understanding how dog breeds are formed, highlighting the limited scope of desired traits in defining new breeds.

Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock.

Genome-Wide Association Studies (GWAS) in large human cohorts have identified thousands of loci associated with complex traits and diseases. For identifying the genes and gene-associated variants that underlie complex traits in livestock, especially where sample sizes are limiting, it may help to integrate the results of GWAS for equivalent traits in humans as prior information. In this study, we sought to investigate the usefulness of results from a GWAS on human height as prior information for identifying the genes and gene-associated variants that affect stature in cattle, using GWAS summary data on samples sizes of 700,000 and 58,265 for humans and cattle, respectively. Using Fisher's exact test, we observed a significant proportion of cattle stature-associated genes (30/77) that are also associated with human height (odds ratio = 5.1, p = 3.1e-10). Result of randomized sampling tests showed that cattle orthologs of human height-associated genes, hereafter referred to as candidate genes (C-genes), were more enriched for cattle stature GWAS signals than random samples of genes in the cattle genome (p = 0.01). Randomly sampled SNPs within the C-genes also tend to explain more genetic variance for cattle stature (up to 13.2%) than randomly sampled SNPs within random cattle genes (p = 0.09). The most significant SNPs from a cattle GWAS for stature within the C-genes did not explain more genetic variance for cattle stature than the most significant SNPs within random cattle genes (p = 0.87). Altogether, our findings support previous studies that suggest a similarity in the genetic regulation of height across mammalian species. However, with the availability of a powerful GWAS for stature that combined data from 8 cattle breeds, prior information from human-height GWAS does not seem to provide any additional benefit with respect to the identification of genes and gene-associated variants that affect stature in cattle.

Cost, risk, and avoidance of inbreeding in a cooperatively breeding bird.

Inbreeding is often avoided in natural populations by passive processes such as sex-biased dispersal. But, in many social animals, opposite-sexed adult relatives are spatially clustered, generating a risk of incest and hence selection for active inbreeding avoidance. Here we show that, in long-tailed tits (Aegithalos caudatus), a cooperative breeder that risks inbreeding by living alongside opposite-sex relatives, inbreeding carries fitness costs and is avoided by active kin discrimination during mate choice. First, we identified a positive association between heterozygosity and fitness, indicating that inbreeding is costly. We then compared relatedness within breeding pairs to that expected under multiple mate-choice models, finding that pair relatedness is consistent with avoidance of first-order kin as partners. Finally, we show that the similarity of vocal cues offers a plausible mechanism for discrimination against first-order kin during mate choice. Long-tailed tits are known to discriminate between the calls of close kin and nonkin, and they favor first-order kin in cooperative contexts, so we conclude that long-tailed tits use the same kin discrimination rule to avoid inbreeding as they do to direct help toward kin.

Inducing a summer brood break increases the efficacy of oxalic acid vaporization for Varroa destructor (Mesostigmata: Varroidae) control in Apis mellifera (Hymenoptera: Apidae) colonies.

The ectoparasitic mite, Varroa destructor (Anderson and Trueman), is the leading cause of western honey bee colony, Apis mellifera (L.), mortality in the United States. Due to mounting evidence of resistance to certain approved miticides, beekeepers are struggling to keep their colonies alive. To date, there are varied but limited approved options for V. destructor control. Vaporized oxalic acid (OA) has proven to be an effective treatment against the dispersal phase of V. destructor but has its limitations since the vapor cannot penetrate the protective wax cap of honey bee pupal cells where V. destructor reproduces. In the Southeastern United States, honey bee colonies often maintain brood throughout the year, limiting the usefulness of OA. Prior studies have shown that even repeated applications of OA while brood is present are ineffective at decreasing mite populations. In the summer of 2021, we studied whether incorporating a forced brood break while vaporizing with OA would be an effective treatment against V. destructor. Ninety experimental colonies were divided into 2 blocks, one with a brood break and the other with no brood break. Within the blocks, each colony was randomly assigned 1 of 3 treatments: no OA, 2 g OA, or 3 g OA. The combination of vaporizing with OA and a forced brood break increased mite mortality by 5× and reduced mite populations significantly. These results give beekeepers in mild climates an additional integrated pest management method for controlling V. destructor during the summer season.

Role of Melatonin in Bovine Reproductive Biotechnology.

Melatonin has profound antioxidant activity and numerous functions in humans as well as in livestock and poultry. Additionally, melatonin plays an important role in regulating the biological rhythms of animals. Combining melatonin with scientific breeding management has considerable potential for optimizing animal physiological functions, but this idea still faces significant challenges. In this review, we summarized the beneficial effects of melatonin supplementation on physiology and reproductive processes in cattle, including granulosa cells, oocytes, circadian rhythm, stress, inflammation, testicular function, spermatogenesis, and semen cryopreservation. There is much emerging evidence that melatonin can profoundly affect cattle. In the future, we hope that melatonin can not only be applied to cattle, but can also be used to safely and effectively improve the efficiency of animal husbandry.

Application and prospect of gene chip in genetic breeding of livestock and poultry.

Gene chip is a high-throughput technique for detecting specific DNA sequences by DNA or DNA-RNA complementary hybridization, among which SNP genotyping chips have been widely employed in the animal genetics and breeding, and have made great achievements in cattle (Bos taurus), pigs (Sus scrofa), sheep (Caprinae), chickens (Gallus gallus) and other livestock. However, genomic selection applied in production merely uses genomic information and cannot fully explain the molecular mechanism of complex traits genetics, which limits the accuracy of genomic selection. With the continuous progresses in epigenetic research, the development of commercial methylation chips and the application of the epigenome-wide association study (EWAS), DNA methylation has been extensively used to draw the causal connections between genetics and phenotypes. In the future, it is hopefully expected to develop methylation chips customized for livestock and poultry and explore methylation sites significantly related to economic traits of livestock and poultry through EWAS thereby extending the understanding of causal variation of complex traits. Combining methylation chips and SNP chips, we can capture the epigenomic and genomic information of livestock and poultry, interpret genetic variation more precisely, improve the accuracy of genome selection, and promote the fine evolution of molecular genetic breeding of livestock and poultry. In this review, we summarize the application of SNP chips and depict the prospects of the application of methylation chips in livestock and poultry. This review will provide valuable insights for further application of gene chips in farm animal breeding.

Artificial seawater based long-term culture of colonial ascidians.

Tunicates are highly diverse marine invertebrate filter-feeders that are vertebrates' closest relatives. These organisms, despite a drastically different body plan during their adulthood, have a tissue complexity related to that of vertebrates. Ascidians, which compose most of the Tunicata, are benthic sessile hermaphrodites that reproduce sexually through a motile tadpole larval stage. Over half of the known ascidians species are able to reproduce asexually by budding, typically leading to the formation of colonies where animals, called zooids, are interconnected through an external vascular system. In addition, colonial ascidians are established models for important biological processes including allorecognition, immunobiology, aging, angiogenesis and whole-body regeneration. However, the current paucity in breeding infrastructures limits the study of these animals to coastal regions. To promote a wider scientific spreading and popularity of colonial ascidians, we have developed a flexible recirculating husbandry setup for their long-term in-lab culture. Our system is inspired both by the flow-through aquariums used by coastal ascidian labs, as well as by the recirculating in-lab systems used for zebrafish research. Our hybrid system thus combines colony breeding, water filtering and food culturing in a semi-automated system where specimens develop on hanging microscopy glass slides. Temperature, light/dark cycles, flow speed and feeding rates can be controlled independently in four different breeding environments to provide room for species-specific optimization as well as for running experiments. This setup is complemented with a quarantine for the acclimatization of wild isolates. Herein we present our success in breeding Botrylloides diegensis, a species of colonial ascidians, for more than 3 years in recirculating artificial seawater over 600 â€‹km away from their natural habitat. We show that colonies adapt well to in-lab culturing provided that a suitable marine microbiome is present, and that a specific strain can be isolated, propagated and efficiently used for research over prolonged periods of time. The flexible and modular structure of our system can be scaled and adapted to the needs of specific species, such as Botryllus schlosseri, as well as of particular laboratory spaces. Overall, we show that Botrylloides diegensis can be proficiently bred in-land and suggest that our results can be extended to other species of colonial ascidians to promote research on these fascinating animals.

Potential of Genome Editing to Improve Aquaculture Breeding and Production.

Aquaculture is the fastest growing food production sector and is rapidly becoming the primary source of seafood for human diets. Selective breeding programs are enabling genetic improvement of production traits, such as disease resistance, but progress is limited by the heritability of the trait and generation interval of the species. New breeding technologies, such as genome editing using CRISPR/Cas9 have the potential to expedite sustainable genetic improvement in aquaculture. Genome editing can rapidly introduce favorable changes to the genome, such as fixing alleles at existing trait loci, creating de novo alleles, or introducing alleles from other strains or species. The high fecundity and external fertilization of most aquaculture species can facilitate genome editing for research and application at a scale that is not possible in farmed terrestrial animals.

pathDIP 4: an extended pathway annotations and enrichment analysis resource for human, model organisms and domesticated species.

PathDIP was introduced to increase proteome coverage of literature-curated human pathway databases. PathDIP 4 now integrates 24 major databases. To further reduce the number of proteins with no curated pathway annotation, pathDIP integrates pathways with physical protein-protein interactions (PPIs) to predict significant physical associations between proteins and curated pathways. For human, it provides pathway annotations for 5366 pathway orphans. Integrated pathway annotation now includes six model organisms and ten domesticated animals. A total of 6401 core and ortholog pathways have been curated from the literature or by annotating orthologs of human proteins in the literature-curated pathways. Extended pathways are the result of combining these pathways with protein-pathway associations that are predicted using organism-specific PPIs. Extended pathways expand proteome coverage from 81 088 to 120 621 proteins, making pathDIP 4 the largest publicly available pathway database for these organisms and providing a necessary platform for comprehensive pathway-enrichment analysis. PathDIP 4 users can customize their search and analysis by selecting organism, identifier and subset of pathways. Enrichment results and detailed annotations for input list can be obtained in different formats and views. To support automated bioinformatics workflows, Java, R and Python APIs are available for batch pathway annotation and enrichment analysis. PathDIP 4 is publicly available at http://ophid.utoronto.ca/pathDIP.

Selection signatures in goats reveal copy number variants underlying breed-defining coat color phenotypes.

Domestication and human selection have formed diverse goat breeds with characteristic phenotypes. This process correlated with the fixation of causative genetic variants controlling breed-specific traits within regions of reduced genetic diversity, so called selection signatures or selective sweeps. Using whole genome sequencing of DNA pools (pool-seq) from 20 genetically diverse modern goat breeds and bezoars, we identified 2,239 putative selection signatures. In two Pakistani goat breeds, Pak Angora and Barbari, we found selection signatures in a region harboring KIT, a gene involved in melanoblast development, migration, and survival. The search for candidate causative variants responsible for these selective sweeps revealed two different copy number variants (CNVs) downstream of KIT that were exclusively present in white Pak Angora and white-spotted Barbari goats. Several Swiss goat breeds selected for specific coat colors showed selection signatures at the ASIP locus encoding the agouti signaling protein. Analysis of these selective sweeps revealed four different CNVs associated with the white or tan (AWt), Swiss markings (Asm), badgerface (Ab), and the newly proposed peacock (Apc) allele. RNA-seq analyses on skin samples from goats with the different CNV alleles suggest that the identified structural variants lead to an altered expression of ASIP between eumelanistic and pheomelanistic body areas. Our study yields novel insights into the genetic control of pigmentation by identifying six functionally relevant CNVs. It illustrates how structural changes of the genome have contributed to phenotypic evolution in domestic goats.