A short critical history of the application of genomics to animal breeding

Advancing Dairy and Beef Genetics Through Genomic Technologies

The US beef and dairy industries have made remarkable advances in sustainability and productivity through technological advancements, including selective breeding. Yet, challenges persist due to the complex nature of quantitative traits. While the beef industry has progressed in adopting genomic technologies, the availability of phenotypic data remains an obstacle. To meet the need for sustainable production systems, novel traits are being targeted for selection. Additionally, emerging approaches such as genome editing and high-throughput phenotyping hold promise for further genetic progress. Future research should address the challenges of translating functional genomic findings into practical applications, while simultaneously harnessing analytical methods.

Two novel SNPs identified in STAT1 gene adjoining a QTL for milk production in Holstein Friesian crossbreds of Kerala

We analyzed the effect of a single nucleotide polymorphism, g. C3141T in the 3' UTR of Signal transducer and activator of transcription-1 gene (STAT1) on milk production traits in the Holstein Friesian crossbred cattle of Kerala (n = 144) by association analysis and expression study. The population was genotyped by restriction fragment length polymorphism using Pag1. Association study using the General Linear Model-Analysis of Variance revealed that none of the yield or composition traits analyzed were significantly differed. The expression profile of STAT1 gene in leucocytes of animals bearing homozygous genotypes was compared by quantitative real time PCR using SYBR green chemistry with and relative expression was not found to be significantly differed. The second stage of the study, the STAT1 mRNA spanning 3213 bp was amplified from leucocytes and sequenced (GenBank: MT459802.1). Two novel SNPs were identified; one synonymous mutation in the coding region (g.A1212G) and the other in the 3'UTR (g.T3042C). The novel SNPs might contribute to STAT1 gene regulation mediated by alternate spicing or binding sites for regulatory molecules. The results reiterate the importance of extensive studies of STAT1 gene variants to substantiate the presence of a quantitative trait loci for dairy traits in the vicinity of STAT1 gene.

Assessment of Genetic and Health Management of Tunisian Holstein Dairy Herds with a Focus on Longevity

In Tunisia, the recognition of the possibility of including longevity and disease resistance in dairy cattle selection objectives has been hypothesized as a useful strategy by both researchers and producers. However, in this paper, the state of the art, with a focus on health and longevity, is reviewed. Along the same lines, the heritability for the milk traits, fertility traits, and longevity of Tunisian Holstein dairy cows complies with the literature. Therefore, the influence of genetics on some diseases of the dairy cow was investigated. In addition, a decreasing efficiency in cow fertility has been observed over the last few years. The results showed that the risk of culling increased with common diseases. When analyzed with the Weibull model, functional lifespan was strongly influenced by milk yield; therefore, the risk increased with a reduced milk yield. In her first three lactations, the relative risk of selection increased gradually with lactation. Thus, the risk of thinning is highest at the beginning and end of the first feeding and the end of her second feeding. In conclusion, the risk of culling was reduced in parity. The factors that influence the life of the herd, such as health, husbandry, environmental conditions, and management, are often ignored when evaluating longevity.

Fitting Genomic Prediction Models with Different Marker Effects among Prefectures to Carcass Traits in Japanese Black Cattle

We fitted statistical models, which assumed single-nucleotide polymorphism (SNP) marker effects differing across the fattened steers marketed into different prefectures, to the records for cold carcass weight (CW) and marbling score (MS) of 1036, 733, and 279 Japanese Black fattened steers marketed into Tottori, Hiroshima, and Hyogo prefectures in Japan, respectively. Genotype data on 33,059 SNPs was used. Five models that assume only common SNP effects to all the steers (model 1), common effects plus SNP effects differing between the steers marketed into Hyogo prefecture and others (model 2), only the SNP effects differing between Hyogo steers and others (model 3), common effects plus SNP effects specific to each prefecture (model 4), and only the effects specific to each prefecture (model 5) were exploited. For both traits, slightly lower values of residual variance than that of model 1 were estimated when fitting all other models. Estimated genetic correlation among the prefectures in models 2 and 4 ranged to 0.53 to 0.71, all <0.8. These results might support that the SNP effects differ among the prefectures to some degree, although we discussed the necessity of careful consideration to interpret the current results.

The prediction accuracies of linear-type traits in Czech Holstein cattle when using ssGBLUP or wssGBLUP

The aim of this study was to assess the contribution of the weighted single-step genomic best linear unbiased prediction (wssGBLUP) method compared to the single-step genomic best linear unbiased prediction (ssGBLUP) method for genomic evaluation of 25 linear-type traits in the Czech Holstein cattle population. The nationwide database of linear-type traits with 6,99,681 records combined with deregressed proofs from Interbull (MACE method) was used as the input data. Genomic breeding values (GEBVs) were predicted based on these phenotypes using ssGBLUP and wssGBLUP methods using the BLUPF90 software. The bull validation test was employed which was based on comparing GEBVs of young bulls (N = 334) with no progeny in 2016. A minimum of 50 daughters with their own performance in 2020 was chosen to verify the contribution to the GEBV prediction, GEBV reliability, validation reliabilities (R2), and regression coefficients (b1). The results showed that the differences between the two methods were negligible. The low benefit of wssGBLUP may be due to the inclusion of a small number of SNPs; therefore, most predictions rely on polygenic relationships between animals. Nevertheless, the benefits of wssGBLUP analysis should be assessed with respect to specific population structures and given traits.

Trajectory of livestock genomics in South Asia: A comprehensive review

Livestock plays a central role in sustaining human livelihood in South Asia. There are numerous and distinct livestock species in South Asian countries. Several of them have experienced genetic development in recent years due to the application of genomic technologies and effective breeding programs. This review discusses genomic studies on cattle, buffalo, sheep, goat, pig, horse, camel, yak, mithun, and poultry. The frontiers covered in this review are genetic diversity, admixture studies, selection signature research, QTL discovery, genome-wide association studies (GWAS), and genomic selection. The review concludes with recommendations for South Asian livestock systems to increasingly leverage genomic technologies, based on the lessons learned from the numerous case studies. This paper aims to present a comprehensive analysis of the dichotomy in the South Asian livestock sector and argues that a realistic approach to genomics in livestock can ensure long-term genetic advancements.

Improvement of Genomic Predictions in Small Breeds by Construction of Genomic Relationship Matrix Through Variable Selection

Genomic selection has been increasingly implemented in the animal breeding industry, and it is becoming a routine method in many livestock breeding contexts. However, its use is still limited in several small-population local breeds, which are, nonetheless, an important source of genetic variability of great economic value. A major roadblock for their genomic selection is accuracy when population size is limited: to improve breeding value accuracy, variable selection models that assume heterogenous variance have been proposed over the last few years. However, while these models might outperform traditional and genomic predictions in terms of accuracy, they also carry a proportional increase of breeding value bias and dispersion. These mutual increases are especially striking when genomic selection is performed with a low number of phenotypes and high shrinkage value—which is precisely the situation that happens with small local breeds. In our study, we tested several alternative methods to improve the accuracy of genomic selection in a small population. First, we investigated the impact of using only a subset of informative markers regarding prediction accuracy, bias, and dispersion. We used different algorithms to select them, such as recursive feature eliminations, penalized regression, and XGBoost. We compared our results with the predictions of pedigree-based BLUP, single-step genomic BLUP, and weighted single-step genomic BLUP in different simulated populations obtained by combining various parameters in terms of number of QTLs and effective population size. We also investigated these approaches on a real data set belonging to the small local Rendena breed. Our results show that the accuracy of GBLUP in small-sized populations increased when performed with SNPs selected via variable selection methods both in simulated and real data sets. In addition, the use of variable selection models—especially those using XGBoost—in our real data set did not impact bias and the dispersion of estimated breeding values. We have discussed possible explanations for our results and how our study can help estimate breeding values for future genomic selection in small breeds.

Development of the First Microsatellite Multiplex PCR Panel for Meagre (Argyrosomus regius), a Commercial Aquaculture Species

In this study, a microsatellite-based multiplex PCR panel for meagre (Argyrosomus regius) was developed as a useful and single tool in parental assignment and population studies. Twenty-one specific and interspecific microsatellites from different aquaculture species of meagre (Argyrosomus regius), Japanese meagre (A. japonicus), red drum (Sciaenops ocellatus) and yellow meagre (Acoupa weakfish) were assessed for genetic variability, allelic range and genotype reliability. Finally, a SuperMultiplex for Argyrosomus regius (SMAr) was designed with only the best eight microsatellite markers. The panel assessment was performed using a batch of brood stock from one company and a sample of 616 offspring. It was possible to assign 95% of the offspring to a single pair of parents using the exclusion method. It is therefore considered an easy procedure, and a powerful and low-cost tool for parental assignment to support companies’ breeding programs and to exchange information between research groups.

Genomic Prediction in Local Breeds: The Rendena Cattle as a Case Study

Simple Summary

Although genomic selection is being used in many livestock species, it has not yet been considered in local breeds due to the lower population size and the potential less effective impact on the genetic evaluation of these breeds. The current research aims to investigate how genomic data can impact the accuracy of genetic predictions for beef traits in Rendena, a small local cattle breed of the North-East of Italy selected for a dual purpose. Classical animal models using only phenotypic information were compared with two models that integrated genomic data with pedigree information. The genomic models presented better accuracy in estimated breeding values of the animals than the ‘classical’ animal model, especially the ‘simpler’ one assuming homogeneous variances of single nucleotide polymorphisms. Our results show that the inclusion of genomic information can be successfully applied to breeding selection scenarios even in small local cattle breeds such as Rendena.

Abstract

The maintenance of local cattle breeds is key to selecting for efficient food production, landscape protection, and conservation of biodiversity and local cultural heritage. Rendena is an indigenous cattle breed from the alpine North-East of Italy, selected for dual purpose, but with lesser emphasis given to beef traits. In this situation, increasing accuracy for beef traits could prevent detrimental effects due to the antagonism with milk production. Our study assessed the impact of genomic information on estimated breeding values (EBVs) in Rendena performance-tested bulls. Traits considered were average daily gain, in vivo EUROP score, and in vivo estimate of dressing percentage. The final dataset contained 1691 individuals with phenotypes and 8372 animals in pedigree, 1743 of which were genotyped. Using the cross-validation method, three models were compared: (i) Pedigree-BLUP (PBLUP); (ii) single-step GBLUP (ssGBLUP), and (iii) weighted single-step GBLUP (WssGBLUP). Models including genomic information presented higher accuracy, especially WssGBLUP. However, the model with the best overall properties was the ssGBLUP, showing higher accuracy than PBLUP and optimal values of bias and dispersion parameters. Our study demonstrated that integrating phenotypes for beef traits with genomic data can be helpful to estimate EBVs, even in a small local breed.

Toward Genome-Based Selection in Asian Seabass: What Can We Learn From Other Food Fishes and Farm Animals?

Due to the steadily increasing need for seafood and the plateauing output of fisheries, more fish need to be produced by aquaculture production. In parallel with the improvement of farming methods, elite food fish lines with superior traits for production must be generated by selection programs that utilize cutting-edge tools of genomics. The purpose of this review is to provide a historical overview and status report of a selection program performed on a catadromous predator, the Asian seabass (Lates calcarifer, Bloch 1790) that can change its sex during its lifetime. We describe the practices of wet lab, farm and lab in detail by focusing onto the foundations and achievements of the program. In addition to the approaches used for selection, our review also provides an inventory of genetic/genomic platforms and technologies developed to (i) provide current and future support for the selection process; and (ii) improve our understanding of the biology of the species. Approaches used for the improvement of terrestrial farm animals are used as examples and references, as those processes are far ahead of the ones used in aquaculture and thus they might help those working on fish to select the best possible options and avoid potential pitfalls.

Genetic Improvement in South African Livestock: Can Genomics Bridge the Gap Between the Developed and Developing Sectors?

South Africa (SA) holds a unique position on the African continent with a rich diversity in terms of available livestock resources, vegetation, climatic regions and cultures. The livestock sector has been characterized by a dual system of a highly developed commercial sector using modern technology vs. a developing sector including emerging and smallholder farmers. Emerging farmers typically aim to join the commercial sector, but lag behind with regard to the use of modern genetic technologies, while smallholder farmers use traditional practices aimed at subsistence. Several factors influence potential application of genomics by the livestock industries, which include available research funding, socio-economic constraints and extension services. State funded Beef and Dairy genomic programs have been established with the aim of building reference populations for genomic selection with most of the potential beneficiaries in the well-developed commercial sector. The structure of the beef, dairy and small stock industries is fragmented and the outcomes of selection strategies are not perceived as an advantage by the processing industry or the consumer. The indigenous and local composites represent approximately 40% of the total beef and sheep populations and present valuable genetic resources. Genomic research has mostly provided insight on genetic biodiversity of these resources, with limited attention to novel phenotypes associated with adaptation or disease tolerance. Genetic improvement of livestock through genomic technology needs to address the role of adapted breeds in challenging environments, increasing reproductive and growth efficiency. National animal recording schemes contributed significantly to progress in the developed sector with regard to genetic evaluations and estimated breeding values (EBV) as a selection tool over the past three decades. The challenge remains on moving the focus to novel traits for increasing efficiency and addressing welfare and environmental issues. Genetic research programs are required that will be directed to bridge the gap between the elite breeders and the developing livestock sector. The aim of this review was to provide a perspective on the dichotomy in the South African livestock sector arguing that a realistic approach to the use of genomics in beef, dairy and small stock is required to ensure sustainable long term genetic progress.

TRIENNIAL GROWTH AND DEVELOPMENT SYMPOSIUM: Genetics and breeding for intramuscular fat and oleic acid content in pigs

The intramuscular fat (IMF) and oleic acid (OL) content have been favorably related to pork quality and human health. This influences the purchasing behavior of consumers and, therefore, also shifts the attention of breeding companies toward whether these traits are included into the breeding goal of the lines producing for high-valued markets. Because IMF and OL are unfavorably associated with lean content, a key economic trait, the real challenge for the industry is not simply to increase IMF and OL, but rather to come up with the right trade-off between them and lean content. In this paper we review the efforts performed to genetically improve IMF and OL, with particular reference to the research we conducted in a Duroc line aimed at producing high quality fresh and dry-cured pork products. Based on this research, we conclude that there are selection strategies that lead to response scenarios where IMF, OL, and lean content can be simultaneously improved. Such scenarios involve regular recording of IMF and OL, so that developing a cost-efficient phenotyping system for these traits is paramount. With the economic benefits of genomic selection needing further assessment in pigs, selection on a combination of pedigree-connected phenotypes and genotypes from a panel of selected genetic markers is presented as a suitable alternative. Evidence is provided supporting that at least a polymorphism in the leptin receptor and another in the stearoyl-CoA desaturase genes should be in that panel. Selection for IMF and OL results in an opportunity cost on lean growth. The extent to which it is affordable relies on the consumers' willingness to pay for premium products and on the cost to benefit ratio of alternative management strategies, such as specific dietary manipulations. How the genotype can influence the effect of the diet on IMF and OL remains a topic for further research.

Advances in genome editing for improved animal breeding: A review

Since centuries, the traits for production and disease resistance are being targeted while improving the genetic merit of domestic animals, using conventional breeding programs such as inbreeding, outbreeding, or introduction of marker-assisted selection. The arrival of new scientific concepts, such as cloning and genome engineering, has added a new and promising research dimension to the existing animal breeding programs. Development of genome editing technologies such as transcription activator-like effector nuclease, zinc finger nuclease, and clustered regularly interspaced short palindromic repeats systems begun a fresh era of genome editing, through which any change in the genome, including specific DNA sequence or indels, can be made with unprecedented precision and specificity. Furthermore, it offers an opportunity of intensification in the frequency of desirable alleles in an animal population through gene-edited individuals more rapidly than conventional breeding. The specific research is evolving swiftly with a focus on improvement of economically important animal species or their traits all of which form an important subject of this review. It also discusses the hurdles to commercialization of these techniques despite several patent applications owing to the ambiguous legal status of genome-editing methods on account of their disputed classification. Nonetheless, barring ethical concerns gene-editing entailing economically important genes offers a tremendous potential for breeding animals with desirable traits.

Peptide biomarkers used for the selective breeding of a complex polygenic trait in honey bees

We present a novel way to select for highly polygenic traits. For millennia, humans have used observable phenotypes to selectively breed stronger or more productive livestock and crops. Selection on genotype, using single-nucleotide polymorphisms (SNPs) and genome profiling, is also now applied broadly in livestock breeding programs; however, selection on protein/peptide or mRNA expression markers has not yet been proven useful. Here we demonstrate the utility of protein markers to select for disease-resistant hygienic behavior in the European honey bee (Apis mellifera L.). Robust, mechanistically-linked protein expression markers, by integrating cis- and trans- effects from many genomic loci, may overcome limitations of genomic markers to allow for selection. After three generations of selection, the resulting marker-selected stock outperformed an unselected benchmark stock in terms of hygienic behavior, and had improved survival when challenged with a bacterial disease or a parasitic mite, similar to bees selected using a phenotype-based assessment for this trait. This is the first demonstration of the efficacy of protein markers for industrial selective breeding in any agricultural species, plant or animal.

Genetic Marker Discovery in Complex Traits: A Field Example on Fat Content and Composition in Pigs

Among the large number of attributes that define pork quality, fat content and composition have attracted the attention of breeders in the recent years due to their interaction with human health and technological and sensorial properties of meat. In livestock species, fat accumulates in different depots following a temporal pattern that is also recognized in humans. Intramuscular fat deposition rate and fatty acid composition change with life. Despite indication that it might be possible to select for intramuscular fat without affecting other fat depots, to date only one depot-specific genetic marker (PCK1 c.2456C>A) has been reported. In contrast, identification of polymorphisms related to fat composition has been more successful. For instance, our group has described a variant in the stearoyl-coA desaturase (SCD) gene that improves the desaturation index of fat without affecting overall fatness or growth. Identification of mutations in candidate genes can be a tedious and costly process. Genome-wide association studies can help in narrowing down the number of candidate genes by highlighting those which contribute most to the genetic variation of the trait. Results from our group and others indicate that fat content and composition are highly polygenic and that very few genes explain more than 5% of the variance of the trait. Moreover, as the complexity of the genome emerges, the role of non-coding genes and regulatory elements cannot be disregarded. Prediction of breeding values from genomic data is discussed in comparison with conventional best linear predictors of breeding values. An example based on real data is given, and the implications in phenotype prediction are discussed in detail. The benefits and limitations of using large SNP sets versus a few very informative markers as predictors of genetic merit of breeding candidates are evaluated using field data as an example.

Inter- and intra-genetic diversity in the Polish Konik horse: implications for the conservation program

The main objective of the study was to determine the genetic diversity in the Polish Konik (PK) population in the context of a currently conducted conservation program. A total of 94 horses of 16 PK dam lines currently distinguished by breeders were considered. Pedigree analyses were carried out for the whole population of PK registered in the studbook. Basic molecular parameters were estimated. The average group linkage clustering method was used based on the Euclidean similarity measurements between the lines. The allele frequency of 17 microsatellites was used to determine Euclidean distances. Inbreeding coefficients were extracted from the additive relationship matrix. Moreover, some pedigree parameters were estimated. The observed heterozygosity ranged from 0.48 to 0.76. The expected heterozygosity estimated for the dam lines was higher. PIC values were higher than 0.6 in all the lines. Fis ranged from –0.19 to 0.28, whereas Fit and Fst varied between 0.12 and 0.41 and 0.12 and 0.29, respectively. Minor dissimilarity distances existed for some dam lines. The inbreeding level was 9.3%. The average number of discrete generation equivalents reached 6.85. The majority of the dam lines are not genetically differentiated. Hence, a revision of the breeding strategy seems to be necessary.

What can livestock breeders learn from conservation genetics and vice versa?

The management of livestock breeds and threatened natural population share common challenges, including small effective population sizes, high risk of inbreeding, and the potential benefits and costs associated with mixing disparate gene pools. Here, we consider what has been learnt about these issues, the ways in which the knowledge gained from one area might be applied to the other, and the potential of genomics to provide new insights. Although there are key differences stemming from the importance of artificial versus natural selection and the decreased level of environmental heterogeneity experienced by many livestock populations, we suspect that information from genetic rescue in natural populations could be usefully applied to livestock. This includes an increased emphasis on maintaining substantial population sizes at the expense of genetic uniqueness in ensuring future adaptability, and on emphasizing the way that environmental changes can influence the relative fitness of deleterious alleles and genotypes in small populations. We also suspect that information gained from cross-breeding and the maintenance of unique breeds will be increasingly important for the preservation of genetic variation in small natural populations. In particular, selected genes identified in domestic populations provide genetic markers for exploring adaptive evolution in threatened natural populations. Genomic technologies in the two disciplines will be important in the future in realizing genetic gains in livestock and maximizing adaptive capacity in wildlife, and particularly in understanding how parts of the genome may respond differently when exposed to population processes and selection.

One hundred years of statistical developments in animal breeding

Statistical methodology has played a key role in scientific animal breeding. Approximately one hundred years of statistical developments in animal breeding are reviewed. Some of the scientific foundations of the field are discussed, and many milestones are examined from historical and critical perspectives. The review concludes with a discussion of some future challenges and opportunities arising from the massive amount of data generated by livestock, plant, and human genome projects.