Biology subjects

Jenko, J.

Publications and source records attributed to Jenko, J..

7 recordsLinked to original sources

bioRxiv2022

The benefits and perils of import in small cattle breeding programs

Small breeding programs are limited in achieving competitive genetic gain and prone to high rates of inbreeding. Thus, they often import genetic material to increase genetic gain and to limit the loss of genetic variability. However, the benefit of import depends on the strength of genotype by environment interaction. It also also diminishes the relevance of domestic selection and the use of domestic breeding animals. Introduction of genomic selection has potentially execerbated this issue, but is also opening the potential for smaller breeding program. The aim of this paper was to determine when and to what extent do small breeding programs benefit from import. We simulated two cattle breeding programs differing in selection parameters representing a large foreign and a small domestic breeding program that differ in the initial genetic mean and annual genetic gain. We evaluated a control scenario without the use of foreign sires in the domestic breeding program and 20 scenarios that varied the percentage of domestic dams mated with foreign sires, the genetic correlation between the breeding programs (0.8 or 0.9), and the time of implementing genomic selection in the domestic compared to the foreign breeding program (concurrently or with a 10-year delay). We compared the scenarios based on the genetic gain and genic standard deviation. Finally, we partitioned breeding values and genetic trends of the scenarios to quantify the contribution of domestic selection and import to the domestic genetic gain. The simulation revealed that when both breeding programs implemented genomic selection simultaneously, the use of foreign sires increased domestic genetic gain only when genetic correlation was 0.9. In contrast, when the domestic breeding program implemented genomic selection with a 10-year delay, genetic correlation of 0.8 sufficed for a positive impact of import. In that scenario, domestic genetic gain increased with the increasing use of foreign sires but with a diminishing return. The partitioning analysis revealed that the contribution of import expectedly increased with the increased use of foreign sires. However, the increase did not depend on the genetic correlation and was not proportional to the increase in domestic genetic gain. This means that a small breeding program could be overly relying on import with diminishing returns for the genetic gain and marginal benefit for the genetic variability. The benefit of import depends on an interplay of genetic correlation, extent of using foreign sires, and a breeding scheme. It is therefore crucial that small breeding programs assess the possible benefits of import beyond domestic selection. The benefit of import should be weighted against the perils of decreased use of domestic sires and decreased contribution and value of domestic selection.

genetics↗

bioRxiv2020

Genomic selection for any dairy breeding program via optimized investment in phenotyping and genotyping

This paper evaluates the potential of maximizing genetic gain in dairy cattle breeding by optimizing investment into phenotyping and genotyping. Conventional breeding focuses on phenotyping selection candidates or their close relatives to maximize selection accuracy for breeders and quality assurance for producers. Genomic selection decoupled phenotyping and selection and through this increased genetic gain per year compared to the conventional selection. Although genomic selection is established in well-resourced breeding programs, small populations and developing countries still struggle with the implementation. The main issues include the lack of training animals and lack of financial resources. To address this, we simulated a case-study of a small dairy population with a number of scenarios with equal resources yet varied use of resources for phenotyping and genotyping. The conventional progeny testing scenario had 11 phenotype records per lactation. In genomic scenarios, we reduced phenotyping to between 10 and 1 phenotype records per lactation and invested the saved resources into genotyping. We tested these scenarios at different relative prices of phenotyping to genotyping and with or without an initial training population for genomic selection. Reallocating a part of phenotyping resources for repeated milk records to genotyping increased genetic gain compared to the conventional scenario regardless of the amount and relative cost of phenotyping, and the availability of an initial training population. Genetic gain increased by increasing genotyping, despite reduced phenotyping. High-genotyping scenarios even saved resources. Genomic scenarios expectedly increased accuracy for young non-phenotyped male and female candidates, but also cows. This study shows that breeding programs should optimize investment into phenotyping and genotyping to maximise return on investment. Our results suggest that any dairy breeding program using conventional progeny testing with repeated milk records can implement genomic selection without increasing the level of investment.

genomics↗

bioRxiv2019

Efficient use of genomic information for sustainable genetic improvement in small cattle populations

This paper compares genetic gain, genetic variation, and the efficiency of converting variation into gain under different genomic selection scenarios with truncation or optimum contribution selection in a small dairy population by simulation. Breeding programs have to maximize genetic gain but also ensure sustainability by maintaining genetic variation. Numerous studies showed that genomic selection increases genetic gain. Although genomic selection is a well-established method, small populations still struggle with choosing the most sustainable strategy to adopt this type of selection. We developed a simulator of a dairy population and simulated a model after the Slovenian Brown Swiss population with ~10,500 cows. We compared different truncation selection scenarios by varying i) the method of sire selection and their use on cows or bull-dams, and ii) selection intensity and the number of years a sire is in use. Furthermore, we compared different optimum contribution selection scenarios with optimization of sire selection and their usage. We compared the scenarios in terms of genetic gain, selection accuracy, generation interval, genetic and genic variance, the rate of coancestry, effective population size, and the conversion efficiency. The results show that early use of genomically tested sires increased genetic gain compared to progeny testing as expected from changes in selection accuracy and generation interval. A faster turnover of sires from year to year and higher intensity increased the genetic gain even further but increased the loss of genetic variation per year. While maximizing intensity gave the lowest conversion efficiency, a faster turn-over of sires gave an intermediate conversion efficiency. The largest conversion efficiency was achieved with the simultaneous use of genomically and progeny tested sires that were used over several years. Compared to truncation selection optimizing sire selection and their usage increased the conversion efficiency by either achieving comparable genetic gain for a smaller loss of genetic variation or achieving higher genetic gain for a comparable loss of genetic variation. Our results will help breeding organizations to implement sustainable genomic selection.

genomics↗

bioRxiv2018

Extending long-range phasing and haplotype library imputation algorithms to very large and heterogeneous datasets

BackgroundThis paper describes the latest improvements to the long-range phasing and haplotype library imputation algorithms that enable them to successfully phase both datasets with one million individuals and datasets genotyped using different sets of single nucleotide polymorphisms (SNPs). Previous publicly available implementations of long-range phasing could not phase large datasets due to the computational cost of defining surrogate parents by exhaustive all-against-all searches. Further, both long-range phasing and haplotype library imputation were not designed to deal with large amounts of missing data, which is inherent when using multiple SNP arrays.\n\nMethodsHere, we developed methods which avoid the need for all-against-all searches by performing long-range phasing on subsets of individuals and then combing results. We also extended long-range phasing and haplotype library imputation algorithms to enable them to use different sets of markers, including missing values, when determining surrogate parents and identifying haplotypes. We implemented and tested these extensions in an updated version of our phasing software AlphaPhase.\n\nResultsA simulated dataset with one million individuals genotyped with the same set of 6,711 SNP for a single chromosome took two days to phase. A larger dataset with one million individuals genotyped with 49,579 SNP for a single chromosome took 14 days to phase. The percentage of correctly phased alleles at heterozygous loci was respectively 90.5% and 90.0% for the two datasets, which is comparable to the accuracy achieved with previous versions of AlphaPhase on smaller datasets.\n\nThe phasing accuracy for datasets with different sets of markers was generally lower than that for datasets with one set of markers. For a simulated dataset with three sets of markers 2.8% of alleles at heterozygous positions were phased incorrectly whereas the equivalent figure with one set of markers was 0.6%.\n\nConclusionsThe improved long-range phasing and haplotype library imputation algorithms enable AlphaPhase to quickly and accurately phase very large and heterogeneous datasets. This will enable more powerful breeding and genetics research and application.

bioinformatics↗

bioRxiv2018

Analysis of a large data set reveals haplotypes carrying putatively recessive lethal alleles with pleiotropic effects on economically important traits in beef cattle

BackgroundDeleterious recessive alleles can result in reduced economic performance in livestock in multiple ways in homozygous individuals: from early embryonic death, death soon after birth, to being non-lethal but causing reduced viability. While death is an easy phenotype to score, reduced viability is not as easy to identify. However, it can sometimes be observed as reduced artificial insemination (AI) conception rates, longer calving intervals, or higher hazard for live born animals.\n\nMethodsIn this paper, we searched for haplotypes carrying putatively recessive lethal alleles in 132,725 genotyped Irish beef cattle from five breeds: Aberdeen Angus, Charolais, Hereford, Limousin, and Simmental. We phased the genotypes in sliding windows along the genome and used five tests to identify haplotypes with absence of or reduced homozygosity. We then corroborated the identified haplotypes with reproduction records, indicating early embryonic death, and postnatal survival records. Finally, we assessed haplotype pleiotropy by estimating substitution effects on national estimates of breeding values for 15 economically important traits in beef production.\n\nResultsWe found support for three haplotypes with carrying putatively recessive lethal alleles. The haplotypes were located on chromosome 14 in Aberdeen Angus, chromosome 19 in Charolais and chromosome 16 in Simmental. Their population frequencies is 15.2%, 14.4%, and 8.8%, respectively. All of the haplotypes showed pleiotropic effects on economically important traits for beef production. Their allele substitution effects are {euro}3.23, {euro}1.47, and {euro}2.30 for the terminal index and -{euro}3.15, -{euro}0.75, and {euro}1.12 for the replacement index, where one standard deviations are {euro}18.32, {euro}22.54, and {euro}22.33 for terminal index and {euro}29.52, {euro}35.62, and {euro}30.97 for the replacement index. We identified ZFAT as the candidate gene for lethality in Aberdeen Angus, several candidate genes for the Simmental haplotype, and no candidate genes for the Charolais haplotype.\n\nConclusionsWe analysed genotype, reproduction, survival, and production data to discover haplotypes carrying putatively recessive lethal alleles in Irish beef cattle. We found support for three haplotypes. All three haplotypes have pleiotropic effects on economically important traits in beef production.

genetics↗

bioRxiv2018

Removal of alleles by genome editing -- RAGE against the deleterious load

BackgroundIn this paper, we simulate deleterious load in an animal breeding program, and compare the efficiency of genome editing and selection for decreasing load. Deleterious variants can be identified by bioinformatics screening methods that use sequence conservation and biological prior information about protein function. Once deleterious variants have been identified, how can they be used in breeding?\n\nResultsWe simulated a closed animal breeding population subject to both natural selection against deleterious load and artificial selection for a quantitative trait representing the breeding goal. Deleterious load was polygenic and due to either codominant or recessive variants. We compared strategies for removal of deleterious alleles by genome editing (RAGE) to selection against carriers. Each strategy varied in how animals and variants were prioritized for editing or selection.\n\nConclusionsGenome editing of deleterious alleles reduces deleterious load, but requires simultaneous editing of multiple deleterious variants in the same sire to be effective when deleterious variants are recessive. In the short term, selection against carriers is a possible alternative to genome editing when variants are recessive. The dominance of deleterious variants affects both the efficiency of genome editing and selection against carriers, and which variant prioritization strategy is the most efficient. Our results suggest that in the future, there is the potential to use RAGE against deleterious load in animal breeding.

genetics↗

bioRxiv2017

A strategy to exploit surrogate sire technology in livestock breeding programs

In this work, we performed simulations to develop and test a strategy for exploiting surrogate sire technology in animal breeding programs. Surrogate sire technology allows the creation of males that lack their own germline cells, but have transplanted spermatogonial stem cells from donor males. With this technology, a single elite male donor could give rise to huge numbers of progeny, potentially as much as all the production animals in a particular time period.\n\nOne hundred replicates of various scenarios were performed. Scenarios followed a common overall structure but differed in the strategy used to identify elite donors and how these donors were used in the product development part.\n\nThe results of this study showed that using surrogate sire technology would significantly increase the genetic merit of commercial sires, by as much as 6.5 to 9.2 years worth of genetic gain compared to a conventional breeding program. The simulations suggested that a strategy involving three stages (an initial genomic test followed by two subsequent progeny tests) was the most effective of all the strategies tested.\n\nThe use of one or a handful of elite donors to generate the production animals would be very different to current practice. While the results demonstrate the great potential of surrogate sire technology there are considerable risks but also other opportunities. Practical implementation of surrogate sire technology would need to account for these.

genetics↗