Dataset Information

Opportunities to Improve Resilience in Animal Breeding Programs.

ABSTRACT: Resilience is the capacity of an animal to be minimally affected by disturbances or to rapidly return to the state pertained before exposure to a disturbance. However, indicators for general resilience to environmental disturbances have not yet been defined, and perhaps therefore resilience is not yet included in breeding goals. The current developments on big data collection give opportunities to determine new resilience indicators based on longitudinal data, which can aid to incorporate resilience in animal breeding goals. The objectives of this paper were: (1) to define resilience indicator traits based on big data, (2) to define economic values for resilience, and (3) to show the potential to improve resilience of livestock through inclusion of resilience in breeding goals. Resilience might be measured based on deviations from expected production levels over a period of time. Suitable resilience indicators could be the variance of deviations, the autocorrelation of deviations, the skewness of deviations, and the slope of a reaction norm. These (new) resilience indicators provide opportunity to include resilience in breeding programs. Economic values of resilience indicators in the selection index can be calculated based on reduced costs due to labor and treatments. For example, when labor time is restricted, the economic value of resilience increases with an increasing number of animals per farm, and can become as large as the economic value of production. This shows the importance of including resilience in breeding goals. Two scenarios were described to show the additional benefit of including resilience in breeding programs. These examples showed that it is hard to improve resilience with only production traits in the selection index, but that it is possible to greatly improve resilience by including resilience indicators in the selection index. However, when health-related traits are already present in the selection index, the effect is smaller. Nevertheless, inclusion of resilience indicators in the selection index increases the response in the breeding goal and resilience, which results in less labor-demanding, and thus easier-to-manage livestock. Current developments on massive collection of data, and new phenotypes based on these data, offer exciting opportunities to breed for improved resilience of livestock.

SUBMITTER: Berghof TVL

PROVIDER: S-EPMC6339870 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Opportunities to Improve Resilience in Animal Breeding Programs.

Berghof Tom V L TVL Poppe Marieke M Mulder Han A HA

Frontiers in genetics 20190114

Resilience is the capacity of an animal to be minimally affected by disturbances or to rapidly return to the state pertained before exposure to a disturbance. However, indicators for general resilience to environmental disturbances have not yet been defined, and perhaps therefore resilience is not yet included in breeding goals. The current developments on big data collection give opportunities to determine new resilience indicators based on longitudinal data, which can aid to incorporate resili ...[more]

PMID: 30693014

Similar Datasets

Project description:Over the last few decades, the use of molecular markers has played an increasing role in rice breeding and genetics. Of the different types of molecular markers, microsatellites have been utilized most extensively, because they can be readily amplified by PCR and the large amount of allelic variation at each locus. Microsatellites are also known as simple sequence repeats (SSR), and they are typically composed of 1-6 nucleotide repeats. These markers are abundant, distributed throughout the genome and are highly polymorphic compared with other genetic markers, as well as being species-specific and co-dominant. For these reasons, they have become increasingly important genetic markers in rice breeding programs. The evolution of new biotypes of pests and diseases as well as the pressures of climate change pose serious challenges to rice breeders, who would like to increase rice production by introducing resistance to multiple biotic and abiotic stresses. Recent advances in rice genomics have now made it possible to identify and map a number of genes through linkage to existing DNA markers. Among the more noteworthy examples of genes that have been tightly linked to molecular markers in rice are those that confer resistance or tolerance to blast. Therefore, in combination with conventional breeding approaches, marker-assisted selection (MAS) can be used to monitor the presence or lack of these genes in breeding populations. For example, marker-assisted backcross breeding has been used to integrate important genes with significant biological effects into a number of commonly grown rice varieties. The use of cost-effective, finely mapped microsatellite markers and MAS strategies should provide opportunities for breeders to develop high-yield, blast resistance rice cultivars. The aim of this review is to summarize the current knowledge concerning the linkage of microsatellite markers to rice blast resistance genes, as well as to explore the use of MAS in rice breeding programs aimed at improving blast resistance in this species. We also discuss the various advantages, disadvantages and uses of microsatellite markers relative to other molecular marker types.

Project description:Cowpea is one of the most important grain legumes in sub-Saharan Africa (SSA). It provides strong support to the livelihood of small-scale farmers through its contributions to their nutritional security, income generation and soil fertility enhancement. Worldwide about 6.5 million metric tons of cowpea are produced annually on about 14.5 million hectares. The low productivity of cowpea is attributable to numerous abiotic and biotic constraints. The abiotic stress factors comprise drought, low soil fertility, and heat while biotic constraints include insects, diseases, parasitic weeds, and nematodes. Cowpea farmers also have limited access to quality seeds of improved varieties for planting. Some progress has been made through conventional breeding at international and national research institutions in the last three decades. Cowpea improvement could also benefit from modern breeding methods based on molecular genetic tools. A number of advances in cowpea genetic linkage maps, and quantitative trait loci associated with some desirable traits such as resistance to Striga, Macrophomina, Fusarium wilt, bacterial blight, root-knot nematodes, aphids, and foliar thrips have been reported. An improved consensus genetic linkage map has been developed and used to identify QTLs of additional traits. In order to take advantage of these developments single nucleotide polymorphism (SNP) genotyping is being streamlined to establish an efficient workflow supported by genotyping support service (GSS)-client interactions. About 1100 SNPs mapped on the cowpea genome were converted by LGC Genomics to KASP assays. Several cowpea breeding programs have been exploiting these resources to implement molecular breeding, especially for MARS and MABC, to accelerate cowpea variety improvement. The combination of conventional breeding and molecular breeding strategies, with workflow managed through the CGIAR breeding management system (BMS), promises an increase in the number of improved varieties available to farmers, thereby boosting cowpea production and productivity in SSA.

Project description:The American tropics are hotspots of wild and domesticated plant biodiversity, which is still underutilized by breeding programs despite being conserved at regional gene banks. The improvement of those programs depends on long-term public funds and the maintenance of specialized staff. Unfortunately, financial ups and downs complicate staff connectivity and their research impact. Between 2000 and 2010, Agrosavia (Corporación Colombiana de Investigación Agropecuaria) dramatically decreased its public financial support. In 2017, we surveyed all 52 researchers from Agrosavia involved in plant breeding and plant genetic resource programs to examine the effect of decimating funds in the last ten years. We hypothesized that the staff dedicated to plant breeding still suffer a strong fragmentation and low connectivity. As we expected, the social network among researchers is weak. The top ten central leaders are predominantly males with an M.Sc. degree but have significant experience in the area. The staff has experience in 31 tropical crops, and 17 are on the list of underutilized species. Moreover, although 26 of these crops are in the national germplasm bank, this has not been the primary source for their breeding programs. We proposed five principles to improve connectivity among teams and research impact: (1) The promotion of internal discussion about gender gaps and generation shifts to design indicators to monitor and decrease this disparity over time. (2) The construction of long-term initiatives and synergies with the Colombian government to support the local production of food security crops independent of market trends. (3) Better collaboration between the National Plant Germplasm Bank and plant breeding researchers. (4) A concerted priority list of species (especially those neglected or underutilized) and external institutions to better focus the collaborative efforts in research using public funds. (5) Better spaces for the design of projects among researchers and training programs in new technologies. These principles could also apply in other tropical countries with public plant breeding research programs facing similar challenges.

Project description:ObjectiveWe surveyed Orthopaedic Surgery Residency (OSR) programs to determine international opportunities by the academic institutional region within the United States, location of the international experience, duration, residency program year (PGY), funding source, and resident participation to date.DesignWe emailed a survey to all OSR programs in the United States to inquire about global opportunities in their residency programs. Further contact was made through an additional e-mail and up to three telephone calls. Data were analyzed using descriptive and chi-square statistics. This study was institutional review board exempt.SettingThis research study was conducted at the University of Nebraska Medical Center, a tertiary care facility in conjunction with the University of Nebraska Medical Center College of Medicine.ParticipantsThe participants of this research study included program directors and coordinators of all OSR programs (185) across the United States.ResultsA total of 102 OSR programs completed the survey (55% response rate). Notably, 50% of the responding programs offered a global health opportunity to their residents. Of the institutions that responded, those in the Midwest or South were more likely to offer the opportunity than institutions found in other US regions, although regional differences were not significant. Global experiences were most commonly: in Central or South America (41%); 1 to 2 weeks in duration (54%); and during PGY4 or PGY5 (71%). Furthermore, half of the programs provided full funding for the residents to participate in the global experience. In 33% of the programs, 10 or more residents had participated to date.ConclusionsInterest in global health among medical students is increasing. OSR programs have followed this trend, increasing their global health opportunities by 92% since 2015. Communicating the availability of and support for international opportunities to future residents may help interested students make informed decisions when applying to residency programs.

Project description:Red clover is a highly valuable crop for the ruminant industry in the temperate regions worldwide. It also provides multiple environmental services, such as contribution to increased soil fertility and reduced soil erosion. This study used 661 single nucleotide polymorphism (SNP) markers via targeted sequencing using seqSNP, to describe genetic diversity and population structure in 382 red clover accessions. The accessions were selected from NordGen representing red clover germplasm from Norway, Sweden, Finland and Denmark as well as from Lantmännen, a Swedish seed company. Each accession was represented by 10 individuals, which was sequenced as a pool. The mean Nei's standard genetic distance between the accessions and genetic variation within accessions were 0.032 and 0.18, respectively. The majority of the accessions had negative Tajima's D, suggesting that they contain significant proportions of rare alleles. A pairwise FST revealed high genetic similarity between the different cultivated types, while the wild populations were divergent. Unlike wild populations, which exhibited genetic differentiation, there was no clear differentiation among all cultivated types. A principal coordinate analysis revealed that the first principal coordinate, distinguished most of the wild populations from the cultivated types, in agreement with the results obtained using a discriminant analysis of principal components and cluster analysis. Accessions of wild populations and landraces collected from southern and central Scandinavia showed a higher genetic similarity to Lantmännen accessios. It is therefore possible to link the diversity of the environments where wild populations were collected to the genetic diversity of the cultivated and wild gene pools. Additionally, least absolute shrinkage and selection operator (LASSO) models revealed associations between variation in temperature and precipitation and SNPs within genes controlling stomatal opening. Temperature was also related to kinase proteins, which are known to regulate plant response to temperature stress. Furthermore, the variation between wild populations and cultivars was correlated with SNPs within genes regulating root development. Overall, this study comprehensively investigated Nordic European red clover germplasm, and the results provide forage breeders with valuable information for further selection and development of red clover cultivars.

Project description:BackgroundBreeders and geneticists use statistical models to separate genetic and environmental effects on phenotype. A common way to separate these effects is to model a descriptor of an environment, a contemporary group or herd, and account for genetic relationship between animals across environments. However, separating the genetic and environmental effects in smallholder systems is challenging due to small herd sizes and weak genetic connectedness across herds. We hypothesised that accounting for spatial relationships between nearby herds can improve genetic evaluation in smallholder systems. Furthermore, geographically referenced environmental covariates are increasingly available and could model underlying sources of spatial relationships. The objective of this study was therefore, to evaluate the potential of spatial modelling to improve genetic evaluation in dairy cattle smallholder systems.MethodsWe performed simulations and real dairy cattle data analysis to test our hypothesis. We modelled environmental variation by estimating herd and spatial effects. Herd effects were considered independent, whereas spatial effects had distance-based covariance between herds. We compared these models using pedigree or genomic data.ResultsThe results show that in smallholder systems (i) standard models do not separate genetic and environmental effects accurately, (ii) spatial modelling increases the accuracy of genetic evaluation for phenotyped and non-phenotyped animals, (iii) environmental covariates do not substantially improve the accuracy of genetic evaluation beyond simple distance-based relationships between herds, (iv) the benefit of spatial modelling was largest when separating the genetic and environmental effects was challenging, and (v) spatial modelling was beneficial when using either pedigree or genomic data.ConclusionsWe have demonstrated the potential of spatial modelling to improve genetic evaluation in smallholder systems. This improvement is driven by establishing environmental connectedness between herds, which enhances separation of genetic and environmental effects. We suggest routine spatial modelling in genetic evaluations, particularly for smallholder systems. Spatial modelling could also have a major impact in studies of human and wild populations.

Dataset Information

Opportunities to Improve Resilience in Animal Breeding Programs.

Publications

Opportunities to Improve Resilience in Animal Breeding Programs.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets