Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.

Science.gov (United States)

Crossa, José; Pérez-Rodríguez, Paulino; Cuevas, Jaime; Montesinos-López, Osval; Jarquín, Diego; de Los Campos, Gustavo; Burgueño, Juan; González-Camacho, Juan M; Pérez-Elizalde, Sergio; Beyene, Yoseph; Dreisigacker, Susanne; Singh, Ravi; Zhang, Xuecai; Gowda, Manje; Roorkiwal, Manish; Rutkoski, Jessica; Varshney, Rajeev K

2017-11-01

Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. Copyright © 2017 Elsevier Ltd. All rights reserved.

Toward Genomics-Based Breeding in C3 Cool-Season Perennial Grasses

Science.gov (United States)

Talukder, Shyamal K.; Saha, Malay C.

2017-01-01

Most important food and feed crops in the world belong to the C3 grass family. The future of food security is highly reliant on achieving genetic gains of those grasses. Conventional breeding methods have already reached a plateau for improving major crops. Genomics tools and resources have opened an avenue to explore genome-wide variability and make use of the variation for enhancing genetic gains in breeding programs. Major C3 annual cereal breeding programs are well equipped with genomic tools; however, genomic research of C3 cool-season perennial grasses is lagging behind. In this review, we discuss the currently available genomics tools and approaches useful for C3 cool-season perennial grass breeding. Along with a general review, we emphasize the discussion focusing on forage grasses that were considered orphan and have little or no genetic information available. Transcriptome sequencing and genotype-by-sequencing technology for genome-wide marker detection using next-generation sequencing (NGS) are very promising as genomics tools. Most C3 cool-season perennial grass members have no prior genetic information; thus NGS technology will enhance collinear study with other C3 model grasses like Brachypodium and rice. Transcriptomics data can be used for identification of functional genes and molecular markers, i.e., polymorphism markers and simple sequence repeats (SSRs). Genome-wide association study with NGS-based markers will facilitate marker identification for marker-assisted selection. With limited genetic information, genomic selection holds great promise to breeders for attaining maximum genetic gain of the cool-season C3 perennial grasses. Application of all these tools can ensure better genetic gains, reduce length of selection cycles, and facilitate cultivar development to meet the future demand for food and fodder. PMID:28798766

Toward Genomics-Based Breeding in C3 Cool-Season Perennial Grasses

Directory of Open Access Journals (Sweden)

Shyamal K. Talukder

2017-07-01

Full Text Available Most important food and feed crops in the world belong to the C3 grass family. The future of food security is highly reliant on achieving genetic gains of those grasses. Conventional breeding methods have already reached a plateau for improving major crops. Genomics tools and resources have opened an avenue to explore genome-wide variability and make use of the variation for enhancing genetic gains in breeding programs. Major C3 annual cereal breeding programs are well equipped with genomic tools; however, genomic research of C3 cool-season perennial grasses is lagging behind. In this review, we discuss the currently available genomics tools and approaches useful for C3 cool-season perennial grass breeding. Along with a general review, we emphasize the discussion focusing on forage grasses that were considered orphan and have little or no genetic information available. Transcriptome sequencing and genotype-by-sequencing technology for genome-wide marker detection using next-generation sequencing (NGS are very promising as genomics tools. Most C3 cool-season perennial grass members have no prior genetic information; thus NGS technology will enhance collinear study with other C3 model grasses like Brachypodium and rice. Transcriptomics data can be used for identification of functional genes and molecular markers, i.e., polymorphism markers and simple sequence repeats (SSRs. Genome-wide association study with NGS-based markers will facilitate marker identification for marker-assisted selection. With limited genetic information, genomic selection holds great promise to breeders for attaining maximum genetic gain of the cool-season C3 perennial grasses. Application of all these tools can ensure better genetic gains, reduce length of selection cycles, and facilitate cultivar development to meet the future demand for food and fodder.

Impact of Genomic Technologies on Chickpea Breeding Strategies

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Rajeev K. Varshney

2012-08-01

Full Text Available The major abiotic and biotic stresses that adversely affect yield of chickpea (Cicer arietinum L. include drought, heat, fusarium wilt, ascochyta blight and pod borer. Excellent progress has been made in developing short-duration varieties with high resistance to fusarium wilt. The early maturity helps in escaping terminal drought and heat stresses and the adaptation of chickpea to short-season environments. Ascochyta blight continues to be a major challenge to chickpea productivity in areas where chickpea is exposed to cool and wet conditions. Limited variability for pod borer resistance has been a major bottleneck in the development of pod borer resistant cultivars. The use of genomics technologies in chickpea breeding programs has been limited, since available genomic resources were not adequate and limited polymorphism was observed in the cultivated chickpea for the available molecular markers. Remarkable progress has been made in the development of genetic and genomic resources in recent years and integration of genomic technologies in chickpea breeding has now started. Marker-assisted breeding is currently being used for improving drought tolerance and combining resistance to diseases. The integration of genomic technologies is expected to improve the precision and efficiency of chickpea breeding in the development of improved cultivars with enhanced resistance to abiotic and biotic stresses, better adaptation to existing and evolving agro-ecologies and traits preferred by farmers, industries and consumers.

Genomic-based-breeding tools for tropical maize improvement.

Science.gov (United States)

Chakradhar, Thammineni; Hindu, Vemuri; Reddy, Palakolanu Sudhakar

2017-12-01

Maize has traditionally been the main staple diet in the Southern Asia and Sub-Saharan Africa and widely grown by millions of resource poor small scale farmers. Approximately, 35.4 million hectares are sown to tropical maize, constituting around 59% of the developing worlds. Tropical maize encounters tremendous challenges besides poor agro-climatic situations with average yields recorded <3 tones/hectare that is far less than the average of developed countries. On the contrary to poor yields, the demand for maize as food, feed, and fuel is continuously increasing in these regions. Heterosis breeding introduced in early 90 s improved maize yields significantly, but genetic gains is still a mirage, particularly for crop growing under marginal environments. Application of molecular markers has accelerated the pace of maize breeding to some extent. The availability of array of sequencing and genotyping technologies offers unrivalled service to improve precision in maize-breeding programs through modern approaches such as genomic selection, genome-wide association studies, bulk segregant analysis-based sequencing approaches, etc. Superior alleles underlying complex traits can easily be identified and introgressed efficiently using these sequence-based approaches. Integration of genomic tools and techniques with advanced genetic resources such as nested association mapping and backcross nested association mapping could certainly address the genetic issues in maize improvement programs in developing countries. Huge diversity in tropical maize and its inherent capacity for doubled haploid technology offers advantage to apply the next generation genomic tools for accelerating production in marginal environments of tropical and subtropical world. Precision in phenotyping is the key for success of any molecular-breeding approach. This article reviews genomic technologies and their application to improve agronomic traits in tropical maize breeding has been reviewed in

Genomics for greater efficiency in pigeonpea hybrid breeding

Directory of Open Access Journals (Sweden)

Rachit K Saxena

2015-10-01

Full Text Available Cytoplasmic genic male sterility based hybrid technology has demonstrated its immense potential in increasing the productivity of various crops, including pigeonpea. This technology has shown promise for breaking the long-standing yield stagnation in pigeonpea. There are difficulties in commercial hybrid seed production due to non-availability of field-oriented technologies such as time-bound assessment of genetic purity of hybrid seeds. Besides this, there are other routine breeding activities which are labour oriented and need more resources. These include breeding and maintenance of new fertility restorers and maintainer lines, diversification of cytoplasm, and incorporation of biotic and abiotic stress resistances. The recent progress in genomics research could accelerate the existing traditional efforts to strengthen the hybrid breeding technology. Marker based seed purity assessment, identification of heterotic groups; selection of new fertility restorers are few areas which have already been initiated. In this paper efforts have been made to identify critical areas and opportunities where genomics can play a leading role and assist breeders in accelerating various activities related to breeding and commercialization of pigeonpea hybrids.

Accelerating the Switchgrass (Panicum virgatum L.) Breeding Cycle Using Genomic Selection Approaches

Science.gov (United States)

Lipka, Alexander E.; Lu, Fei; Cherney, Jerome H.; Buckler, Edward S.; Casler, Michael D.; Costich, Denise E.

2014-01-01

Switchgrass (Panicum virgatum L.) is a perennial grass undergoing development as a biofuel feedstock. One of the most important factors hindering breeding efforts in this species is the need for accurate measurement of biomass yield on a per-hectare basis. Genomic selection on simple-to-measure traits that approximate biomass yield has the potential to significantly speed up the breeding cycle. Recent advances in switchgrass genomic and phenotypic resources are now making it possible to evaluate the potential of genomic selection of such traits. We leveraged these resources to study the ability of three widely-used genomic selection models to predict phenotypic values of morphological and biomass quality traits in an association panel consisting of predominantly northern adapted upland germplasm. High prediction accuracies were obtained for most of the traits, with standability having the highest ten-fold cross validation prediction accuracy (0.52). Moreover, the morphological traits generally had higher prediction accuracies than the biomass quality traits. Nevertheless, our results suggest that the quality of current genomic and phenotypic resources available for switchgrass is sufficiently high for genomic selection to significantly impact breeding efforts for biomass yield. PMID:25390940

Advances and Challenges in Genomic Selection for Disease Resistance.

Science.gov (United States)

Poland, Jesse; Rutkoski, Jessica

2016-08-04

Breeding for disease resistance is a central focus of plant breeding programs, as any successful variety must have the complete package of high yield, disease resistance, agronomic performance, and end-use quality. With the need to accelerate the development of improved varieties, genomics-assisted breeding is becoming an important tool in breeding programs. With marker-assisted selection, there has been success in breeding for disease resistance; however, much of this work and research has focused on identifying, mapping, and selecting for major resistance genes that tend to be highly effective but vulnerable to breakdown with rapid changes in pathogen races. In contrast, breeding for minor-gene quantitative resistance tends to produce more durable varieties but is a more challenging breeding objective. As the genetic architecture of resistance shifts from single major R genes to a diffused architecture of many minor genes, the best approach for molecular breeding will shift from marker-assisted selection to genomic selection. Genomics-assisted breeding for quantitative resistance will therefore necessitate whole-genome prediction models and selection methodology as implemented for classical complex traits such as yield. Here, we examine multiple case studies testing whole-genome prediction models and genomic selection for disease resistance. In general, whole-genome models for disease resistance can produce prediction accuracy suitable for application in breeding. These models also largely outperform multiple linear regression as would be applied in marker-assisted selection. With the implementation of genomic selection for yield and other agronomic traits, whole-genome marker profiles will be available for the entire set of breeding lines, enabling genomic selection for disease at no additional direct cost. In this context, the scope of implementing genomics selection for disease resistance, and specifically for quantitative resistance and quarantined pathogens

Advances in genome editing for improved animal breeding: A review

Directory of Open Access Journals (Sweden)

Shakil Ahmad Bhat

2017-11-01

Full Text Available 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.

Application of Genomic Technologies to the Breeding of Trees.

Science.gov (United States)

Badenes, Maria L; Fernández I Martí, Angel; Ríos, Gabino; Rubio-Cabetas, María J

2016-01-01

The recent introduction of next generation sequencing (NGS) technologies represents a major revolution in providing new tools for identifying the genes and/or genomic intervals controlling important traits for selection in breeding programs. In perennial fruit trees with long generation times and large sizes of adult plants, the impact of these techniques is even more important. High-throughput DNA sequencing technologies have provided complete annotated sequences in many important tree species. Most of the high-throughput genotyping platforms described are being used for studies of genetic diversity and population structure. Dissection of complex traits became possible through the availability of genome sequences along with phenotypic variation data, which allow to elucidate the causative genetic differences that give rise to observed phenotypic variation. Association mapping facilitates the association between genetic markers and phenotype in unstructured and complex populations, identifying molecular markers for assisted selection and breeding. Also, genomic data provide in silico identification and characterization of genes and gene families related to important traits, enabling new tools for molecular marker assisted selection in tree breeding. Deep sequencing of transcriptomes is also a powerful tool for the analysis of precise expression levels of each gene in a sample. It consists in quantifying short cDNA reads, obtained by NGS technologies, in order to compare the entire transcriptomes between genotypes and environmental conditions. The miRNAs are non-coding short RNAs involved in the regulation of different physiological processes, which can be identified by high-throughput sequencing of RNA libraries obtained by reverse transcription of purified short RNAs, and by in silico comparison with known miRNAs from other species. All together, NGS techniques and their applications have increased the resources for plant breeding in tree species, closing the

Genomic selection needs to be carefully assessed to meet specific requirements in livestock breeding programs

Directory of Open Access Journals (Sweden)

Elisabeth eJonas

2015-02-01

Full Text Available Genomic selection is a promising development in agriculture, aiming improved production by exploiting molecular genetic markers to design novel breeding programs and to develop new markers-based models for genetic evaluation. It opens opportunities for research, as novel algorithms and lab methodologies are developed. Genomic selection can be applied in many breeds and species. Further research on the implementation of genomic selection in breeding programs is highly desirable not only for the common good, but also the private sector (breeding companies. It has been projected that this approach will improve selection routines, especially in species with long reproduction cycles, late or sex-limited or expensive trait recording and for complex traits. The task of integrating genomic selection into existing breeding programs is, however, not straightforward. Despite successful integration into breeding programs for dairy cattle, it has yet to be shown how much emphasis can be given to the genomic information and how much additional phenotypic information is needed from new selection candidates. Genomic selection is already part of future planning in many breeding companies of pigs and beef cattle among others, but further research is needed to fully estimate how effective the use of genomic information will be for the prediction of the performance of future breeding stock. Genomic prediction of production in crossbreeding and across-breed schemes, costs and choice of individuals for genotyping are reasons for a reluctance to fully rely on genomic information for selection decisions. Breeding objectives are highly dependent on the industry and the additional gain when using genomic information has to be considered carefully. This review synthesizes some of the suggested approaches in selected livestock species including cattle, pig, chicken and fish. It outlines tasks to help understanding possible consequences when applying genomic information in

Genomic analyses of modern dog breeds.

Science.gov (United States)

Parker, Heidi G

2012-02-01

A rose may be a rose by any other name, but when you call a dog a poodle it becomes a very different animal than if you call it a bulldog. Both the poodle and the bulldog are examples of dog breeds of which there are >400 recognized worldwide. Breed creation has played a significant role in shaping the modern dog from the length of his leg to the cadence of his bark. The selection and line-breeding required to maintain a breed has also reshaped the genome of the dog, resulting in a unique genetic pattern for each breed. The breed-based population structure combined with extensive morphologic variation and shared human environments have made the dog a popular model for mapping both simple and complex traits and diseases. In order to obtain the most benefit from the dog as a genetic system, it is necessary to understand the effect structured breeding has had on the genome of the species. That is best achieved by looking at genomic analyses of the breeds, their histories, and their relationships to each other.

An integrated approach for increasing breeding efficiency in apple and peach in Europe.

Science.gov (United States)

Laurens, Francois; Aranzana, Maria José; Arus, Pere; Bassi, Daniele; Bink, Marco; Bonany, Joan; Caprera, Andrea; Corelli-Grappadelli, Luca; Costes, Evelyne; Durel, Charles-Eric; Mauroux, Jehan-Baptiste; Muranty, Hélène; Nazzicari, Nelson; Pascal, Thierry; Patocchi, Andrea; Peil, Andreas; Quilot-Turion, Bénédicte; Rossini, Laura; Stella, Alessandra; Troggio, Michela; Velasco, Riccardo; van de Weg, Eric

2018-01-01

Despite the availability of whole genome sequences of apple and peach, there has been a considerable gap between genomics and breeding. To bridge the gap, the European Union funded the FruitBreedomics project (March 2011 to August 2015) involving 28 research institutes and private companies. Three complementary approaches were pursued: (i) tool and software development, (ii) deciphering genetic control of main horticultural traits taking into account allelic diversity and (iii) developing plant materials, tools and methodologies for breeders. Decisive breakthroughs were made including the making available of ready-to-go DNA diagnostic tests for Marker Assisted Breeding, development of new, dense SNP arrays in apple and peach, new phenotypic methods for some complex traits, software for gene/QTL discovery on breeding germplasm via Pedigree Based Analysis (PBA). This resulted in the discovery of highly predictive molecular markers for traits of horticultural interest via PBA and via Genome Wide Association Studies (GWAS) on several European genebank collections. FruitBreedomics also developed pre-breeding plant materials in which multiple sources of resistance were pyramided and software that can support breeders in their selection activities. Through FruitBreedomics, significant progresses were made in the field of apple and peach breeding, genetics, genomics and bioinformatics of which advantage will be made by breeders, germplasm curators and scientists. A major part of the data collected during the project has been stored in the FruitBreedomics database and has been made available to the public. This review covers the scientific discoveries made in this major endeavour, and perspective in the apple and peach breeding and genomics in Europe and beyond.

Marker-assisted selection in fish and shellfish breeding schemes

International Nuclear Information System (INIS)

Martinez, V.

2007-01-01

The main goals of breeding programmes for fish and shellfish are to increase the profitability and sustainability of aquaculture. Traditionally, these have been carried out successfully using pedigree information by selecting individuals based on breeding values predicted for traits measured on candidates using an 'animal model'. This methodology assumes that phenotypes are explained by a large number of genes with small effects and random environmental deviations. However, information on individual genes with medium or large effects cannot be used in this manner. In selective breeding programmes using pedigree information, molecular markers have been used primarily for parentage assignment when tagging individual fish is difficult and to avoid causing common environmental effects from rearing families in separate tanks. The use of these techniques in such conventional breeding programmes is discussed in detail. Exploiting the great biological diversity of many fish and shellfish species, different experimental designs may use either chromosomal manipulations or large family sizes to increase the likelihood of finding the loci affecting quantitative traits, the so-called QTL, by screening the segregation of molecular markers. Using information on identified loci in breeding schemes in aquaculture is expected to be cost-effective compared with traditional breeding methods only when the accuracy of predicting breeding values is rather low, e.g. for traits with low heritability such as disease resistance or carcass quality. One of the problems facing aquaculture is that some of the resources required to locate QTL accurately, such as dense linkage maps, are not yet available for the many species. Recently, however, information from expressed sequence tag (EST) databases has been used for developing molecular markers such as microsatellites and single nucleotide polymorphisms (SNPs). Marker-assisted selection (MAS) or genome-wide marker-assisted selection (G-MAS) using

Genomic selection needs to be carefully assessed to meet specific requirements in livestock breeding programs.

Science.gov (United States)

Jonas, Elisabeth; de Koning, Dirk-Jan

2015-01-01

Genomic selection is a promising development in agriculture, aiming improved production by exploiting molecular genetic markers to design novel breeding programs and to develop new markers-based models for genetic evaluation. It opens opportunities for research, as novel algorithms and lab methodologies are developed. Genomic selection can be applied in many breeds and species. Further research on the implementation of genomic selection (GS) in breeding programs is highly desirable not only for the common good, but also the private sector (breeding companies). It has been projected that this approach will improve selection routines, especially in species with long reproduction cycles, late or sex-limited or expensive trait recording and for complex traits. The task of integrating GS into existing breeding programs is, however, not straightforward. Despite successful integration into breeding programs for dairy cattle, it has yet to be shown how much emphasis can be given to the genomic information and how much additional phenotypic information is needed from new selection candidates. Genomic selection is already part of future planning in many breeding companies of pigs and beef cattle among others, but further research is needed to fully estimate how effective the use of genomic information will be for the prediction of the performance of future breeding stock. Genomic prediction of production in crossbreeding and across-breed schemes, costs and choice of individuals for genotyping are reasons for a reluctance to fully rely on genomic information for selection decisions. Breeding objectives are highly dependent on the industry and the additional gain when using genomic information has to be considered carefully. This review synthesizes some of the suggested approaches in selected livestock species including cattle, pig, chicken, and fish. It outlines tasks to help understanding possible consequences when applying genomic information in breeding scenarios.

Invited review: Breeding and ethical perspectives on genetically modified and genome edited cattle.

Science.gov (United States)

Eriksson, S; Jonas, E; Rydhmer, L; Röcklinsberg, H

2018-01-01

The hot topic of genetic modification and genome editing is sometimes presented as a rapid solution to various problems in the field of animal breeding and genetics. These technologies hold potential for future use in agriculture but we need to be aware of difficulties in large-scale application and integration in breeding schemes. In this review, we discuss applications of both classical genetic modifications (GM) using vectors and genome editing in dairy cattle breeding. We use an interdisciplinary approach considering both ethical and animal breeding perspectives. Decisions on how to make use of these techniques need to be made based not only on what is possible, but on what is reasonable to do. Principles of animal integrity, naturalness, risk perception, and animal welfare issues are examples of ethically relevant factors to consider. These factors also influence public perception and decisions about regulations by authorities. We need to acknowledge that we lack complete understanding of the genetic background of complex traits. It may be difficult, therefore, to predict the full effect of certain modifications in large-scale breeding programs. We present 2 potential applications: genome editing to dispense with dehorning, and insertion of human genes in bovine genomes to improve udder health as an example of classical GM. Both of these cases could be seen as beneficial for animal welfare but they differ in other aspects. In the former case, a genetic variant already present within the species is introduced, whereas in the latter case, transgenic animals are generated-this difference may influence how society regards the applications. We underline that the use of GM, as well as genome editing, of farm animals such as cattle is not independent of the context, and should be considered as part of an entire process, including, for example, the assisted reproduction technology that needs to be used. We propose that breeding organizations and breeding companies

Genotyping-by-sequencing (GBS), an ultimate marker-assisted selection (MAS) tool to accelerate plant breeding

OpenAIRE

He, Jiangfeng; Zhao, Xiaoqing; Laroche, André; Lu, Zhen-Xiang; Liu, HongKui; Li, Ziqin

2014-01-01

Marker-assisted selection (MAS) refers to the use of molecular markers to assist phenotypic selections in crop improvement. Several types of molecular markers, such as single nucleotide polymorphism (SNP), have been identified and effectively used in plant breeding. The application of next-generation sequencing (NGS) technologies has led to remarkable advances in whole genome sequencing, which provides ultra-throughput sequences to revolutionize plant genotyping and breeding. To further broad...

Genomic selection accuracy using multi-family prediction models in a wheat breeding program

Science.gov (United States)

Genomic selection (GS) uses genome-wide molecular marker data to predict the genetic value of selection candidates in breeding programs. In plant breeding, the ability to produce large numbers of progeny per cross allows GS to be conducted within each family. However, this approach requires phenotyp...

Allele coding in genomic evaluation

DEFF Research Database (Denmark)

Standen, Ismo; Christensen, Ole Fredslund

2011-01-01

Genomic data are used in animal breeding to assist genetic evaluation. Several models to estimate genomic breeding values have been studied. In general, two approaches have been used. One approach estimates the marker effects first and then, genomic breeding values are obtained by summing marker...... effects. In the second approach, genomic breeding values are estimated directly using an equivalent model with a genomic relationship matrix. Allele coding is the method chosen to assign values to the regression coefficients in the statistical model. A common allele coding is zero for the homozygous...... genotype of the first allele, one for the heterozygote, and two for the homozygous genotype for the other allele. Another common allele coding changes these regression coefficients by subtracting a value from each marker such that the mean of regression coefficients is zero within each marker. We call...

RosBREED: Enabling marker-assisted breeding in Rosaceae

NARCIS (Netherlands)

Iezzoni, A.F.; Weebadde, C.; Luby, J.; Yue, C.; Weg, van de W.E.; Fazio, G.; Main, D.; Peace, C.P.; Bassil, N.V.; McFerson, J.

2010-01-01

Genomics research has not yet been translated into routine practical application in breeding Rosaceae fruit crops (peach, apple, strawberry, cherry, apricot, pear, raspberry, etc.). Through dedicated efforts of many researchers worldwide, a wealth of genomics resources has accumulated, including EST

Genomics Assisted Ancestry Deconvolution in Grape

Science.gov (United States)

Sawler, Jason; Reisch, Bruce; Aradhya, Mallikarjuna K.; Prins, Bernard; Zhong, Gan-Yuan; Schwaninger, Heidi; Simon, Charles; Buckler, Edward; Myles, Sean

2013-01-01

The genus Vitis (the grapevine) is a group of highly diverse, diploid woody perennial vines consisting of approximately 60 species from across the northern hemisphere. It is the world’s most valuable horticultural crop with ~8 million hectares planted, most of which is processed into wine. To gain insights into the use of wild Vitis species during the past century of interspecific grape breeding and to provide a foundation for marker-assisted breeding programmes, we present a principal components analysis (PCA) based ancestry estimation method to calculate admixture proportions of hybrid grapes in the United States Department of Agriculture grape germplasm collection using genome-wide polymorphism data. We find that grape breeders have backcrossed to both the domesticated V. vinifera and wild Vitis species and that reasonably accurate genome-wide ancestry estimation can be performed on interspecific Vitis hybrids using a panel of fewer than 50 ancestry informative markers (AIMs). We compare measures of ancestry informativeness used in selecting SNP panels for two-way admixture estimation, and verify the accuracy of our method on simulated populations of admixed offspring. Our method of ancestry deconvolution provides a first step towards selection at the seed or seedling stage for desirable admixture profiles, which will facilitate marker-assisted breeding that aims to introgress traits from wild Vitis species while retaining the desirable characteristics of elite V. vinifera cultivars. PMID:24244717

Genomics assisted ancestry deconvolution in grape.

Directory of Open Access Journals (Sweden)

Jason Sawler

Full Text Available The genus Vitis (the grapevine is a group of highly diverse, diploid woody perennial vines consisting of approximately 60 species from across the northern hemisphere. It is the world's most valuable horticultural crop with ~8 million hectares planted, most of which is processed into wine. To gain insights into the use of wild Vitis species during the past century of interspecific grape breeding and to provide a foundation for marker-assisted breeding programmes, we present a principal components analysis (PCA based ancestry estimation method to calculate admixture proportions of hybrid grapes in the United States Department of Agriculture grape germplasm collection using genome-wide polymorphism data. We find that grape breeders have backcrossed to both the domesticated V. vinifera and wild Vitis species and that reasonably accurate genome-wide ancestry estimation can be performed on interspecific Vitis hybrids using a panel of fewer than 50 ancestry informative markers (AIMs. We compare measures of ancestry informativeness used in selecting SNP panels for two-way admixture estimation, and verify the accuracy of our method on simulated populations of admixed offspring. Our method of ancestry deconvolution provides a first step towards selection at the seed or seedling stage for desirable admixture profiles, which will facilitate marker-assisted breeding that aims to introgress traits from wild Vitis species while retaining the desirable characteristics of elite V. vinifera cultivars.

Localization of canine brachycephaly using an across breed mapping approach.

Directory of Open Access Journals (Sweden)

Danika Bannasch

2010-03-01

Full Text Available The domestic dog, Canis familiaris, exhibits profound phenotypic diversity and is an ideal model organism for the genetic dissection of simple and complex traits. However, some of the most interesting phenotypes are fixed in particular breeds and are therefore less tractable to genetic analysis using classical segregation-based mapping approaches. We implemented an across breed mapping approach using a moderately dense SNP array, a low number of animals and breeds carefully selected for the phenotypes of interest to identify genetic variants responsible for breed-defining characteristics. Using a modest number of affected (10-30 and control (20-60 samples from multiple breeds, the correct chromosomal assignment was identified in a proof of concept experiment using three previously defined loci; hyperuricosuria, white spotting and chondrodysplasia. Genome-wide association was performed in a similar manner for one of the most striking morphological traits in dogs: brachycephalic head type. Although candidate gene approaches based on comparable phenotypes in mice and humans have been utilized for this trait, the causative gene has remained elusive using this method. Samples from nine affected breeds and thirteen control breeds identified strong genome-wide associations for brachycephalic head type on Cfa 1. Two independent datasets identified the same genomic region. Levels of relative heterozygosity in the associated region indicate that it has been subjected to a selective sweep, consistent with it being a breed defining morphological characteristic. Genotyping additional dogs in the region confirmed the association. To date, the genetic structure of dog breeds has primarily been exploited for genome wide association for segregating traits. These results demonstrate that non-segregating traits under strong selection are equally tractable to genetic analysis using small sample numbers.

Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery.

Science.gov (United States)

Hickey, John M; Chiurugwi, Tinashe; Mackay, Ian; Powell, Wayne

2017-08-30

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

Genomic prediction across dairy cattle populations and breeds

DEFF Research Database (Denmark)

Zhou, Lei

Genomic prediction is successful in single breed genetic evaluation. However, there is no achievement in acoress breed prediction until now. This thesis investigated genomic prediction across populations and breeds using Chinese Holsterin, Nordic Holstein, Norwgian Red, and Nordic Red. Nordic Red...

Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery

DEFF Research Database (Denmark)

Hickey, John M.; Chiurugwi, Tinashe; Mackay, Ian

2017-01-01

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

Initiating genomic selection in tetraploid potato

DEFF Research Database (Denmark)

Sverrisdóttir, Elsa; Janss, Luc; Byrne, Stephen

Breeding for more space and resource efficient crops is important to feed the world’s increasing population. Potatoes produce approximately twice the amount of calories per hectare compared to cereals. The traditional “mate and phenotype” breeding approach is costly and time-consuming; however......, the completion of the genome sequence of potato has enabled the application of genomics-assisted breeding technologies. Genomic selection using genome-wide molecular markers is becoming increasingly applicable to crops as the genotyping costs continue to reduce and it is thus an attractive breeding alternative...... selection, can be obtained with good prediction accuracies in tetraploid potato....

Genomic dairy cattle breeding

DEFF Research Database (Denmark)

Mark, Thomas; Sandøe, Peter

2010-01-01

the thoughts of breeders and other stakeholders on how to best make use of genomic breeding in the future. Intensive breeding has played a major role in securing dramatic increases in milk yield since the Second World War. Until recently, the main focus in dairy cattle breeding was on production traits...... it less accountable to the concern of private farmers for the welfare of their animals. It is argued that there is a need to mobilise a wide range of stakeholders to monitor developments and maintain pressure on breeding companies so that they are aware of the need to take precautionary measures to avoid...

Next-Generation Sequencing Approaches in Genome-Wide Discovery of Single Nucleotide Polymorphism Markers Associated with Pungency and Disease Resistance in Pepper.

Science.gov (United States)

Manivannan, Abinaya; Kim, Jin-Hee; Yang, Eun-Young; Ahn, Yul-Kyun; Lee, Eun-Su; Choi, Sena; Kim, Do-Sun

2018-01-01

Pepper is an economically important horticultural plant that has been widely used for its pungency and spicy taste in worldwide cuisines. Therefore, the domestication of pepper has been carried out since antiquity. Owing to meet the growing demand for pepper with high quality, organoleptic property, nutraceutical contents, and disease tolerance, genomics assisted breeding techniques can be incorporated to develop novel pepper varieties with desired traits. The application of next-generation sequencing (NGS) approaches has reformed the plant breeding technology especially in the area of molecular marker assisted breeding. The availability of genomic information aids in the deeper understanding of several molecular mechanisms behind the vital physiological processes. In addition, the NGS methods facilitate the genome-wide discovery of DNA based markers linked to key genes involved in important biological phenomenon. Among the molecular markers, single nucleotide polymorphism (SNP) indulges various benefits in comparison with other existing DNA based markers. The present review concentrates on the impact of NGS approaches in the discovery of useful SNP markers associated with pungency and disease resistance in pepper. The information provided in the current endeavor can be utilized for the betterment of pepper breeding in future.

Next-Generation Sequencing Approaches in Genome-Wide Discovery of Single Nucleotide Polymorphism Markers Associated with Pungency and Disease Resistance in Pepper

Directory of Open Access Journals (Sweden)

Abinaya Manivannan

2018-01-01

Full Text Available Pepper is an economically important horticultural plant that has been widely used for its pungency and spicy taste in worldwide cuisines. Therefore, the domestication of pepper has been carried out since antiquity. Owing to meet the growing demand for pepper with high quality, organoleptic property, nutraceutical contents, and disease tolerance, genomics assisted breeding techniques can be incorporated to develop novel pepper varieties with desired traits. The application of next-generation sequencing (NGS approaches has reformed the plant breeding technology especially in the area of molecular marker assisted breeding. The availability of genomic information aids in the deeper understanding of several molecular mechanisms behind the vital physiological processes. In addition, the NGS methods facilitate the genome-wide discovery of DNA based markers linked to key genes involved in important biological phenomenon. Among the molecular markers, single nucleotide polymorphism (SNP indulges various benefits in comparison with other existing DNA based markers. The present review concentrates on the impact of NGS approaches in the discovery of useful SNP markers associated with pungency and disease resistance in pepper. The information provided in the current endeavor can be utilized for the betterment of pepper breeding in future.

Genomic breeding value prediction:methods and procedures

NARCIS (Netherlands)

Calus, M.P.L.

2010-01-01

Animal breeding faces one of the most significant changes of the past decades – the implementation of genomic selection. Genomic selection uses dense marker maps to predict the breeding value of animals with reported accuracies that are up to 0.31 higher than those of pedigree indexes, without the

Genomic Tools in Pea Breeding Programs: Status and Perspectives

Science.gov (United States)

Tayeh, Nadim; Aubert, Grégoire; Pilet-Nayel, Marie-Laure; Lejeune-Hénaut, Isabelle; Warkentin, Thomas D.; Burstin, Judith

2015-01-01

Pea (Pisum sativum L.) is an annual cool-season legume and one of the oldest domesticated crops. Dry pea seeds contain 22–25% protein, complex starch and fiber constituents, and a rich array of vitamins, minerals, and phytochemicals which make them a valuable source for human consumption and livestock feed. Dry pea ranks third to common bean and chickpea as the most widely grown pulse in the world with more than 11 million tons produced in 2013. Pea breeding has achieved great success since the time of Mendel's experiments in the mid-1800s. However, several traits still require significant improvement for better yield stability in a larger growing area. Key breeding objectives in pea include improving biotic and abiotic stress resistance and enhancing yield components and seed quality. Taking advantage of the diversity present in the pea genepool, many mapping populations have been constructed in the last decades and efforts have been deployed to identify loci involved in the control of target traits and further introgress them into elite breeding materials. Pea now benefits from next-generation sequencing and high-throughput genotyping technologies that are paving the way for genome-wide association studies and genomic selection approaches. This review covers the significant development and deployment of genomic tools for pea breeding in recent years. Future prospects are discussed especially in light of current progress toward deciphering the pea genome. PMID:26640470

Genomic tools in pea breeding programs: status and perspectives

Directory of Open Access Journals (Sweden)

Nadim eTAYEH

2015-11-01

Full Text Available Pea (Pisum sativum L. is an annual cool-season legume and one of the oldest domesticated crops. Dry pea seeds contain 22-25 percent protein, complex starch and fibre constituents and a rich array of vitamins, minerals, and phytochemicals which make them a valuable source for human consumption and livestock feed. Dry pea ranks third to common bean and chickpea as the most widely grown pulse in the world with more than 11 million tonnes produced in 2013. Pea breeding has achieved great success since the time of Mendel’s experiments in the mid-1800s. However, several traits still require significant improvement for better yield stability in a larger growing area. Key breeding objectives in pea include improving biotic and abiotic stress resistance and enhancing yield components and seed quality. Taking advantage of the diversity present in the pea genepool, many mapping populations have been constructed in the last decades and efforts have been deployed to identify loci involved in the control of target traits and further introgress them into elite breeding materials. Pea now benefits from next-generation sequencing and high-throughput genotyping technologies that are paving the way for genome-wide association studies and genomic selection approaches. This review covers the significant development and deployment of genomic tools for pea breeding in recent years. Future prospects are discussed especially in light of current progress towards deciphering the pea genome.

Application of Genomic Tools in Plant Breeding

OpenAIRE

Pérez-de-Castro, A.M.; Vilanova, S.; Cañizares, J.; Pascual, L.; Blanca, J.M.; Díez, M.J.; Prohens, J.; Picó, B.

2012-01-01

Plant breeding has been very successful in developing improved varieties using conventional tools and methodologies. Nowadays, the availability of genomic tools and resources is leading to a new revolution of plant breeding, as they facilitate the study of the genotype and its relationship with the phenotype, in particular for complex traits. Next Generation Sequencing (NGS) technologies are allowing the mass sequencing of genomes and transcriptomes, which is producing a vast array of genomic...

Evaluation of approaches for estimating the accuracy of genomic prediction in plant breeding.

Science.gov (United States)

Ould Estaghvirou, Sidi Boubacar; Ogutu, Joseph O; Schulz-Streeck, Torben; Knaak, Carsten; Ouzunova, Milena; Gordillo, Andres; Piepho, Hans-Peter

2013-12-06

In genomic prediction, an important measure of accuracy is the correlation between the predicted and the true breeding values. Direct computation of this quantity for real datasets is not possible, because the true breeding value is unknown. Instead, the correlation between the predicted breeding values and the observed phenotypic values, called predictive ability, is often computed. In order to indirectly estimate predictive accuracy, this latter correlation is usually divided by an estimate of the square root of heritability. In this study we use simulation to evaluate estimates of predictive accuracy for seven methods, four (1 to 4) of which use an estimate of heritability to divide predictive ability computed by cross-validation. Between them the seven methods cover balanced and unbalanced datasets as well as correlated and uncorrelated genotypes. We propose one new indirect method (4) and two direct methods (5 and 6) for estimating predictive accuracy and compare their performances and those of four other existing approaches (three indirect (1 to 3) and one direct (7)) with simulated true predictive accuracy as the benchmark and with each other. The size of the estimated genetic variance and hence heritability exerted the strongest influence on the variation in the estimated predictive accuracy. Increasing the number of genotypes considerably increases the time required to compute predictive accuracy by all the seven methods, most notably for the five methods that require cross-validation (Methods 1, 2, 3, 4 and 6). A new method that we propose (Method 5) and an existing method (Method 7) used in animal breeding programs were the fastest and gave the least biased, most precise and stable estimates of predictive accuracy. Of the methods that use cross-validation Methods 4 and 6 were often the best. The estimated genetic variance and the number of genotypes had the greatest influence on predictive accuracy. Methods 5 and 7 were the fastest and produced the least

Signatures of Selection in the Genomes of Commercial and Non-Commercial Chicken Breeds

Science.gov (United States)

Elferink, Martin G.; Megens, Hendrik-Jan; Vereijken, Addie; Hu, Xiaoxiang; Crooijmans, Richard P. M. A.; Groenen, Martien A. M.

2012-01-01

Identifying genomics regions that are affected by selection is important to understand the domestication and selection history of the domesticated chicken, as well as understanding molecular pathways underlying phenotypic traits and breeding goals. While whole-genome approaches, either high-density SNP chips or massively parallel sequencing, have been successfully applied to identify evidence for selective sweeps in chicken, it has been difficult to distinguish patterns of selection and stochastic and breed specific effects. Here we present a study to identify selective sweeps in a large number of chicken breeds (67 in total) using a high-density (58 K) SNP chip. We analyzed commercial chickens representing all major breeding goals. In addition, we analyzed non-commercial chicken diversity for almost all recognized traditional Dutch breeds and a selection of representative breeds from China. Based on their shared history or breeding goal we in silico grouped the breeds into 14 breed groups. We identified 396 chromosomal regions that show suggestive evidence of selection in at least one breed group with 26 of these regions showing strong evidence of selection. Of these 26 regions, 13 were previously described and 13 yield new candidate genes for performance traits in chicken. Our approach demonstrates the strength of including many different populations with similar, and breed groups with different selection histories to reduce stochastic effects based on single populations. PMID:22384281

High-throughput phenotyping and genomic selection: the frontiers of crop breeding converge.

Science.gov (United States)

Cabrera-Bosquet, Llorenç; Crossa, José; von Zitzewitz, Jarislav; Serret, María Dolors; Araus, José Luis

2012-05-01

Genomic selection (GS) and high-throughput phenotyping have recently been captivating the interest of the crop breeding community from both the public and private sectors world-wide. Both approaches promise to revolutionize the prediction of complex traits, including growth, yield and adaptation to stress. Whereas high-throughput phenotyping may help to improve understanding of crop physiology, most powerful techniques for high-throughput field phenotyping are empirical rather than analytical and comparable to genomic selection. Despite the fact that the two methodological approaches represent the extremes of what is understood as the breeding process (phenotype versus genome), they both consider the targeted traits (e.g. grain yield, growth, phenology, plant adaptation to stress) as a black box instead of dissecting them as a set of secondary traits (i.e. physiological) putatively related to the target trait. Both GS and high-throughput phenotyping have in common their empirical approach enabling breeders to use genome profile or phenotype without understanding the underlying biology. This short review discusses the main aspects of both approaches and focuses on the case of genomic selection of maize flowering traits and near-infrared spectroscopy (NIRS) and plant spectral reflectance as high-throughput field phenotyping methods for complex traits such as crop growth and yield. © 2012 Institute of Botany, Chinese Academy of Sciences.

Genomic Characterisation of the Indigenous Irish Kerry Cattle Breed

Science.gov (United States)

Browett, Sam; McHugo, Gillian; Richardson, Ian W.; Magee, David A.; Park, Stephen D. E.; Fahey, Alan G.; Kearney, John F.; Correia, Carolina N.; Randhawa, Imtiaz A. S.; MacHugh, David E.

2018-01-01

Kerry cattle are an endangered landrace heritage breed of cultural importance to Ireland. In the present study we have used genome-wide SNP array data to evaluate genomic diversity within the Kerry population and between Kerry cattle and other European breeds. Patterns of genetic differentiation and gene flow among breeds using phylogenetic trees with ancestry graphs highlighted historical gene flow from the British Shorthorn breed into the ancestral population of modern Kerry cattle. Principal component analysis (PCA) and genetic clustering emphasised the genetic distinctiveness of Kerry cattle relative to comparator British and European cattle breeds. Modelling of genetic effective population size (Ne) revealed a demographic trend of diminishing Ne over time and that recent estimated Ne values for the Kerry breed may be less than the threshold for sustainable genetic conservation. In addition, analysis of genome-wide autozygosity (FROH) showed that genomic inbreeding has increased significantly during the 20 years between 1992 and 2012. Finally, signatures of selection revealed genomic regions subject to natural and artificial selection as Kerry cattle adapted to the climate, physical geography and agro-ecology of southwest Ireland. PMID:29520297

Genomic Characterisation of the Indigenous Irish Kerry Cattle Breed

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Sam Browett

2018-02-01

Full Text Available Kerry cattle are an endangered landrace heritage breed of cultural importance to Ireland. In the present study we have used genome-wide SNP array data to evaluate genomic diversity within the Kerry population and between Kerry cattle and other European breeds. Patterns of genetic differentiation and gene flow among breeds using phylogenetic trees with ancestry graphs highlighted historical gene flow from the British Shorthorn breed into the ancestral population of modern Kerry cattle. Principal component analysis (PCA and genetic clustering emphasised the genetic distinctiveness of Kerry cattle relative to comparator British and European cattle breeds. Modelling of genetic effective population size (Ne revealed a demographic trend of diminishing Ne over time and that recent estimated Ne values for the Kerry breed may be less than the threshold for sustainable genetic conservation. In addition, analysis of genome-wide autozygosity (FROH showed that genomic inbreeding has increased significantly during the 20 years between 1992 and 2012. Finally, signatures of selection revealed genomic regions subject to natural and artificial selection as Kerry cattle adapted to the climate, physical geography and agro-ecology of southwest Ireland.

Integrating genomic selection into dairy cattle breeding programmes: a review.

Science.gov (United States)

Bouquet, A; Juga, J

2013-05-01

Extensive genetic progress has been achieved in dairy cattle populations on many traits of economic importance because of efficient breeding programmes. Success of these programmes has relied on progeny testing of the best young males to accurately assess their genetic merit and hence their potential for breeding. Over the last few years, the integration of dense genomic information into statistical tools used to make selection decisions, commonly referred to as genomic selection, has enabled gains in predicting accuracy of breeding values for young animals without own performance. The possibility to select animals at an early stage allows defining new breeding strategies aimed at boosting genetic progress while reducing costs. The first objective of this article was to review methods used to model and optimize breeding schemes integrating genomic selection and to discuss their relative advantages and limitations. The second objective was to summarize the main results and perspectives on the use of genomic selection in practical breeding schemes, on the basis of the example of dairy cattle populations. Two main designs of breeding programmes integrating genomic selection were studied in dairy cattle. Genomic selection can be used either for pre-selecting males to be progeny tested or for selecting males to be used as active sires in the population. The first option produces moderate genetic gains without changing the structure of breeding programmes. The second option leads to large genetic gains, up to double those of conventional schemes because of a major reduction in the mean generation interval, but it requires greater changes in breeding programme structure. The literature suggests that genomic selection becomes more attractive when it is coupled with embryo transfer technologies to further increase selection intensity on the dam-to-sire pathway. The use of genomic information also offers new opportunities to improve preservation of genetic variation. However

Breeding in peach, cherry and plum: from a tissue culture, genetic, transcriptomic and genomic perspective

Directory of Open Access Journals (Sweden)

Basilio Carrasco

2013-01-01

Full Text Available This review is an overview of traditional and modern breeding methodologies being used to develop new Prunus cultivars (stone fruits with major emphasis on peach, sweet cherry and Japanese plum. To this end, common breeding tools used to produce seedlings, including in vitro culture tools, are discussed. Additionally, the mechanisms of inheritance of many important agronomical traits are described. Recent advances in stone fruit transcriptomics and genomic resources are providing an understanding of the molecular basis of phenotypic variability as well as the identification of allelic variants and molecular markers. These have potential applications for understanding the genetic diversity of the Prunus species, molecular marker-assisted selection and transgenesis. Simple Sequence Repeat (SSR and Single Nucleotide Polymorphism (SNPs molecular markers are described as useful tools to describe genetic diversity in peach, sweet cherry and Japanese plum. Additionally, the recently sequenced peach genome and the public release of the sweet cherry genome are discussed in terms of their applicability to breeding programs

Next generation breeding.

Science.gov (United States)

Barabaschi, Delfina; Tondelli, Alessandro; Desiderio, Francesca; Volante, Andrea; Vaccino, Patrizia; Valè, Giampiero; Cattivelli, Luigi

2016-01-01

The genomic revolution of the past decade has greatly improved our understanding of the genetic make-up of living organisms. The sequencing of crop genomes has completely changed our vision and interpretation of genome organization and evolution. Re-sequencing allows the identification of an unlimited number of markers as well as the analysis of germplasm allelic diversity based on allele mining approaches. High throughput marker technologies coupled with advanced phenotyping platforms provide new opportunities for discovering marker-trait associations which can sustain genomic-assisted breeding. The availability of genome sequencing information is enabling genome editing (site-specific mutagenesis), to obtain gene sequences desired by breeders. This review illustrates how next generation sequencing-derived information can be used to tailor genomic tools for different breeders' needs to revolutionize crop improvement. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Evaluation of multiple approaches to identify genome-wide polymorphisms in closely related genotypes of sweet cherry (Prunus avium L.

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Seanna Hewitt

Full Text Available Identification of genetic polymorphisms and subsequent development of molecular markers is important for marker assisted breeding of superior cultivars of economically important species. Sweet cherry (Prunus avium L. is an economically important non-climacteric tree fruit crop in the Rosaceae family and has undergone a genetic bottleneck due to breeding, resulting in limited genetic diversity in the germplasm that is utilized for breeding new cultivars. Therefore, it is critical to recognize the best platforms for identifying genome-wide polymorphisms that can help identify, and consequently preserve, the diversity in a genetically constrained species. For the identification of polymorphisms in five closely related genotypes of sweet cherry, a gel-based approach (TRAP, reduced representation sequencing (TRAPseq, a 6k cherry SNParray, and whole genome sequencing (WGS approaches were evaluated in the identification of genome-wide polymorphisms in sweet cherry cultivars. All platforms facilitated detection of polymorphisms among the genotypes with variable efficiency. In assessing multiple SNP detection platforms, this study has demonstrated that a combination of appropriate approaches is necessary for efficient polymorphism identification, especially between closely related cultivars of a species. The information generated in this study provides a valuable resource for future genetic and genomic studies in sweet cherry, and the insights gained from the evaluation of multiple approaches can be utilized for other closely related species with limited genetic diversity in the breeding germplasm. Keywords: Polymorphisms, Prunus avium, Next-generation sequencing, Target region amplification polymorphism (TRAP, Genetic diversity, SNParray, Reduced representation sequencing, Whole genome sequencing (WGS

Genomic resources in mungbean for future breeding programs

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Sue K Kim

2015-08-01

Full Text Available Among the legume family, mungbean (Vigna radiata has become one of the important crops in Asia, showing a steady increase in global production. It provides a good source of protein and contains most notably folate and iron. Beyond the nutritional value of mungbean, certain features make it a well-suited model organism among legume plants because of its small genome size, short life-cycle, self-pollinating, and close genetic relationship to other legumes. In the past, there have been several efforts to develop molecular markers and linkage maps associated with agronomic traits for the genetic improvement of mungbean and, ultimately, breeding for cultivar development to increase the average yields of mungbean. The recent release of a reference genome of the cultivated mungbean (V. radiata var. radiata VC1973A and an additional de novo sequencing of a wild relative mungbean (V. radiata var. sublobata has provided a framework for mungbean genetic and genome research, that can further be used for genome-wide association and functional studies to identify genes related to specific agronomic traits. Moreover, the diverse gene pool of wild mungbean comprises valuable genetic resources of beneficial genes that may be helpful in widening the genetic diversity of cultivated mungbean. This review paper covers the research progress on molecular and genomics approaches and the current status of breeding programs that have developed to move toward the ultimate goal of mungbean improvement.

Across Breed QTL Detection and Genomic Prediction in French and Danish Dairy Cattle Breeds

DEFF Research Database (Denmark)

van den Berg, Irene; Guldbrandtsen, Bernt; Hozé, C

Our objective was to investigate the potential benefits of using sequence data to improve across breed genomic prediction, using data from five French and Danish dairy cattle breeds. First, QTL for protein yield were detected using high density genotypes. Part of the QTL detected within breed was...

Breeding of ozone resistant rice: Relevance, approaches and challenges

International Nuclear Information System (INIS)

Frei, Michael

2015-01-01

Tropospheric ozone concentrations have been rising across Asia, and will continue to rise during the 21st century. Ozone affects rice yields through reductions in spikelet number, spikelet fertility, and grain size. Moreover, ozone leads to changes in rice grain and straw quality. Therefore the breeding of ozone tolerant rice varieties is warranted. The mapping of quantitative trait loci (QTL) using bi-parental populations identified several tolerance QTL mitigating symptom formation, grain yield losses, or the degradation of straw quality. A genome-wide association study (GWAS) demonstrated substantial natural genotypic variation in ozone tolerance in rice, and revealed that the genetic architecture of ozone tolerance in rice is dominated by multiple medium and small effect loci. Transgenic approaches targeting tolerance mechanisms such as antioxidant capacity are also discussed. It is concluded that the breeding of ozone tolerant rice can contribute substantially to the global food security, and is feasible using different breeding approaches. - Highlights: • Tropospheric ozone affects millions of hectares of rice land. • Ozone affects rice yield and quality. • Breeding approaches to adapt rice to high ozone are discussed. • Challenges in the breeding of ozone resistant rice are discussed. - This review summarizes the effects of tropospheric ozone on rice and outlines approaches and challenges in the breeding of adapted varieties

Recurrent parent genome recovery analysis in a marker-assisted backcrossing program of rice (Oryza sativa L.).

Science.gov (United States)

Miah, Gous; Rafii, Mohd Y; Ismail, Mohd R; Puteh, Adam B; Rahim, Harun A; Latif, Mohammad A

2015-02-01

Backcross breeding is the most commonly used method for incorporating a blast resistance gene into a rice cultivar. Linkage between the resistance gene and undesirable units can persist for many generations of backcrossing. Marker-assisted backcrossing (MABC) along with marker-assisted selection (MAS) contributes immensely to overcome the main limitation of the conventional breeding and accelerates recurrent parent genome (RPG) recovery. The MABC approach was employed to incorporate (a) blast resistance gene(s) from the donor parent Pongsu Seribu 1, the blast-resistant local variety in Malaysia, into the genetic background of MR219, a popular high-yielding rice variety that is blast susceptible, to develop a blast-resistant MR219 improved variety. In this perspective, the recurrent parent genome recovery was analyzed in early generations of backcrossing using simple sequence repeat (SSR) markers. Out of 375 SSR markers, 70 markers were found polymorphic between the parents, and these markers were used to evaluate the plants in subsequent generations. Background analysis revealed that the extent of RPG recovery ranged from 75.40% to 91.3% and from 80.40% to 96.70% in BC1F1 and BC2F1 generations, respectively. In this study, the recurrent parent genome content in the selected BC2F2 lines ranged from 92.7% to 97.7%. The average proportion of the recurrent parent in the selected improved line was 95.98%. MAS allowed identification of the plants that are more similar to the recurrent parent for the loci evaluated in backcross generations. The application of MAS with the MABC breeding program accelerated the recovery of the RP genome, reducing the number of generations and the time for incorporating resistance against rice blast. Copyright © 2014 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Goals and hurdles for a successful implementation of genomic selection in breeding programme for selected annual and perennial crops.

Science.gov (United States)

Jonas, Elisabeth; de Koning, Dirk Jan

Genomic Selection is an important topic in quantitative genetics and breeding. Not only does it allow the full use of current molecular genetic technologies, it stimulates also the development of new methods and models. Genomic selection, if fully implemented in commercial farming, should have a major impact on the productivity of various agricultural systems. But suggested approaches need to be applicable in commercial breeding populations. Many of the published research studies focus on methodologies. We conclude from the reviewed publications, that a stronger focus on strategies for the implementation of genomic selection in advanced breeding lines, introduction of new varieties, hybrids or multi-line crosses is needed. Efforts to find solutions for a better prediction and integration of environmental influences need to continue within applied breeding schemes. Goals of the implementation of genomic selection into crop breeding should be carefully defined and crop breeders in the private sector will play a substantial part in the decision-making process. However, the lack of published results from studies within, or in collaboration with, private companies diminishes the knowledge on the status of genomic selection within applied breeding programmes. Studies on the implementation of genomic selection in plant breeding need to evaluate models and methods with an enhanced emphasis on population-specific requirements and production environments. Adaptation of methods to breeding schemes or changes to breeding programmes for a better integration of genomic selection strategies are needed across species. More openness with a continuous exchange will contribute to successes.

Genomic breeding value estimation using nonparametric additive regression models

Directory of Open Access Journals (Sweden)

Solberg Trygve

2009-01-01

Full Text Available Abstract Genomic selection refers to the use of genomewide dense markers for breeding value estimation and subsequently for selection. The main challenge of genomic breeding value estimation is the estimation of many effects from a limited number of observations. Bayesian methods have been proposed to successfully cope with these challenges. As an alternative class of models, non- and semiparametric models were recently introduced. The present study investigated the ability of nonparametric additive regression models to predict genomic breeding values. The genotypes were modelled for each marker or pair of flanking markers (i.e. the predictors separately. The nonparametric functions for the predictors were estimated simultaneously using additive model theory, applying a binomial kernel. The optimal degree of smoothing was determined by bootstrapping. A mutation-drift-balance simulation was carried out. The breeding values of the last generation (genotyped was predicted using data from the next last generation (genotyped and phenotyped. The results show moderate to high accuracies of the predicted breeding values. A determination of predictor specific degree of smoothing increased the accuracy.

Genomic tools in pearl millet breeding for drought tolerance: Status and prospects

Directory of Open Access Journals (Sweden)

Desalegn Debelo Serba

2016-11-01

Full Text Available Pearl millet (Penisetum glaucum (L R. Br. is a hardy cereal crop grown in the arid and semiarid tropics where other cereals are likely to fail to produce economic yields due to drought and heat stresses. Adaptive evolution, a form of natural selection shaped the crop to grow and yield satisfactorily with limited moisture supply or under periodic water deficits in the soil. Drought tolerance is a complex polygenic trait that various morphological and physiological responses are controlled by hundreds of genes and significantly influenced by the environment. The development of genomic tools will have enormous potential to improve the efficiency and precision of conventional breeding. The apparent independent domestication events, highly outcrossing nature and traditional cultivation in stressful environments maintained tremendous amount of polymorphism in pearl millet. This high polymorphism of the crop has been revealed by genome mapping that in turn stimulated the mapping and tagging of genomic regions controlling important traits such as drought tolerance. Mapping of a major QTL for terminal drought tolerance in independent populations envisaged the prospect for the development of molecular breeding in pearl millet. To accelerate genetic gains for drought tolerance targeted novel approaches such as establishment of marker-trait associations, genomic selection tools, genome sequence and genotyping-by-sequencing are still limited. Development and application of high throughput genomic tools need to be intensified to improve the breeding efficiency of pearl millet to minimize the impact of climate change on its production.

Integration of genomic information into sport horse breeding programs for optimization of accuracy of selection.

Science.gov (United States)

Haberland, A M; König von Borstel, U; Simianer, H; König, S

2012-09-01

Reliable selection criteria are required for young riding horses to increase genetic gain by increasing accuracy of selection and decreasing generation intervals. In this study, selection strategies incorporating genomic breeding values (GEBVs) were evaluated. Relevant stages of selection in sport horse breeding programs were analyzed by applying selection index theory. Results in terms of accuracies of indices (r(TI) ) and relative selection response indicated that information on single nucleotide polymorphism (SNP) genotypes considerably increases the accuracy of breeding values estimated for young horses without own or progeny performance. In a first scenario, the correlation between the breeding value estimated from the SNP genotype and the true breeding value (= accuracy of GEBV) was fixed to a relatively low value of r(mg) = 0.5. For a low heritability trait (h(2) = 0.15), and an index for a young horse based only on information from both parents, additional genomic information doubles r(TI) from 0.27 to 0.54. Including the conventional information source 'own performance' into the before mentioned index, additional SNP information increases r(TI) by 40%. Thus, particularly with regard to traits of low heritability, genomic information can provide a tool for well-founded selection decisions early in life. In a further approach, different sources of breeding values (e.g. GEBV and estimated breeding values (EBVs) from different countries) were combined into an overall index when altering accuracies of EBVs and correlations between traits. In summary, we showed that genomic selection strategies have the potential to contribute to a substantial reduction in generation intervals in horse breeding programs.

Genome-wide association mapping for yield and other agronomic traits in an elite breeding population of tropical rice (Oryza sativa).

Science.gov (United States)

Begum, Hasina; Spindel, Jennifer E; Lalusin, Antonio; Borromeo, Teresita; Gregorio, Glenn; Hernandez, Jose; Virk, Parminder; Collard, Bertrand; McCouch, Susan R

2015-01-01

Genome-wide association mapping studies (GWAS) are frequently used to detect QTL in diverse collections of crop germplasm, based on historic recombination events and linkage disequilibrium across the genome. Generally, diversity panels genotyped with high density SNP panels are utilized in order to assay a wide range of alleles and haplotypes and to monitor recombination breakpoints across the genome. By contrast, GWAS have not generally been performed in breeding populations. In this study we performed association mapping for 19 agronomic traits including yield and yield components in a breeding population of elite irrigated tropical rice breeding lines so that the results would be more directly applicable to breeding than those from a diversity panel. The population was genotyped with 71,710 SNPs using genotyping-by-sequencing (GBS), and GWAS performed with the explicit goal of expediting selection in the breeding program. Using this breeding panel we identified 52 QTL for 11 agronomic traits, including large effect QTLs for flowering time and grain length/grain width/grain-length-breadth ratio. We also identified haplotypes that can be used to select plants in our population for short stature (plant height), early flowering time, and high yield, and thus demonstrate the utility of association mapping in breeding populations for informing breeding decisions. We conclude by exploring how the newly identified significant SNPs and insights into the genetic architecture of these quantitative traits can be leveraged to build genomic-assisted selection models.

Accuracy of genomic selection in European maize elite breeding populations.

Science.gov (United States)

Zhao, Yusheng; Gowda, Manje; Liu, Wenxin; Würschum, Tobias; Maurer, Hans P; Longin, Friedrich H; Ranc, Nicolas; Reif, Jochen C

2012-03-01

Genomic selection is a promising breeding strategy for rapid improvement of complex traits. The objective of our study was to investigate the prediction accuracy of genomic breeding values through cross validation. The study was based on experimental data of six segregating populations from a half-diallel mating design with 788 testcross progenies from an elite maize breeding program. The plants were intensively phenotyped in multi-location field trials and fingerprinted with 960 SNP markers. We used random regression best linear unbiased prediction in combination with fivefold cross validation. The prediction accuracy across populations was higher for grain moisture (0.90) than for grain yield (0.58). The accuracy of genomic selection realized for grain yield corresponds to the precision of phenotyping at unreplicated field trials in 3-4 locations. As for maize up to three generations are feasible per year, selection gain per unit time is high and, consequently, genomic selection holds great promise for maize breeding programs.

Plant breeding with marker-assisted selection in Brazil

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Ney Sussumu Sakiyama

2014-03-01

Full Text Available Over the past three decades, molecular marker studies reached extraordinary advances, especially for sequencing and bioinformatics techniques. Marker-assisted selection became part of the breeding program routines of important seed companies, in order to accelerate and optimize the cultivar developing processes. Private seed companies increasingly use marker-assisted selection, especially for the species of great importance to the seed market, e.g. corn, soybean, cotton, and sunflower. In the Brazilian public institutions few breeding programs use it efficiently. The possible reasons are: lack of know-how, lack of appropriate laboratories, few validated markers, high cost, and lack of urgency in obtaining cultivars. In this article we analyze the use and the constraints of marker-assisted selection in plant breeding programs of Brazilian public institutes

Refining QTL with high-density SNP genotyping and whole genome sequence in three cattle breeds

DEFF Research Database (Denmark)

Sahana, Goutam; Guldbrandtsen, Bernt; Lund, Mogens Sandø

2012-01-01

Genome-wide association study was carried out in Nordic Holsteins, Nordic Red and Jersey breeds for functional traits using BovineHD Genotyping BreadChip (Illumina, San Diego, CA). The association analyses were carried out using both linear mixed model approach and a Bayesian variable selection...... method. Principal components were used to account for population structure. The QTL segregating in all three breeds were selected and a few of the most significant ones were followed in further analyses. The polymorphisms in the identified QTL regions were imputed using 90 whole genome sequences...

Reliabilities of genomic estimated breeding values in Danish Jersey

DEFF Research Database (Denmark)

Thomasen, Jørn Rind; Guldbrandtsen, Bernt; Su, Guosheng

2012-01-01

In order to optimize the use of genomic selection in breeding plans, it is essential to have reliable estimates of the genomic breeding values. This study investigated reliabilities of direct genomic values (DGVs) in the Jersey population estimated by three different methods. The validation methods...... were (i) fivefold cross-validation and (ii) validation on the most recent 3 years of bulls. The reliability of DGV was assessed using squared correlations between DGV and deregressed proofs (DRPs). In the recent 3-year validation model, estimated reliabilities were also used to assess the reliabilities...... of DGV. The data set consisted of 1003 Danish Jersey bulls with conventional estimated breeding values (EBVs) for 14 different traits included in the Nordic selection index. The bulls were genotyped for Single-nucleotide polymorphism (SNP) markers using the Illumina 54 K chip. A Bayesian method was used...

Genomic Prediction of Single Crosses in the Early Stages of a Maize Hybrid Breeding Pipeline

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Dnyaneshwar C. Kadam

2016-11-01

Full Text Available Prediction of single-cross performance has been a major goal of plant breeders since the beginning of hybrid breeding. Recently, genomic prediction has shown to be a promising approach, but only limited studies have examined the accuracy of predicting single-cross performance. Moreover, no studies have examined the potential of predicting single crosses among random inbreds derived from a series of biparental families, which resembles the structure of germplasm comprising the initial stages of a hybrid maize breeding pipeline. The main objectives of this study were to evaluate the potential of genomic prediction for identifying superior single crosses early in the hybrid breeding pipeline and optimize its application. To accomplish these objectives, we designed and analyzed a novel population of single crosses representing the Iowa Stiff Stalk synthetic/non-Stiff Stalk heterotic pattern commonly used in the development of North American commercial maize hybrids. The performance of single crosses was predicted using parental combining ability and covariance among single crosses. Prediction accuracies were estimated using cross-validation and ranged from 0.28 to 0.77 for grain yield, 0.53 to 0.91 for plant height, and 0.49 to 0.94 for staygreen, depending on the number of tested parents of the single cross and genomic prediction method used. The genomic estimated general and specific combining abilities showed an advantage over genomic covariances among single crosses when one or both parents of the single cross were untested. Overall, our results suggest that genomic prediction of single crosses in the early stages of a hybrid breeding pipeline holds great potential to redesign hybrid breeding and increase its efficiency.

Development of cost-effective Hordeum chilense DNA markers: molecular aids for marker-assisted cereal breeding.

Science.gov (United States)

Hernández, P; Dorado, G; Ramírez, M C; Laurie, D A; Snape, J W; Martín, A

2003-01-01

Hordeum chilense is a potential source of useful genes for wheat breeding. The use of this wild species to increase genetic variation in wheat will be greatly facilitated by marker-assisted introgression. In recent years, the search for the most suitable DNA marker system for tagging H. chilense genomic regions in a wheat background has lead to the development of RAPD and SCAR markers for this species. RAPDs represent an easy way of quickly generating suitable introgression markers, but their use is limited in heterogeneous wheat genetic backgrounds. SCARs are more specific assays, suitable for automatation or multiplexing. Direct sequencing of RAPD products is a cost-effective approach that reduces labour and costs for SCAR development. The use of SSR and STS primers originally developed for wheat and barley are additional sources of genetic markers. Practical applications of the different marker approaches for obtaining derived introgression products are described.

Exploiting Genomic Knowledge in Optimising Molecular Breeding Programmes: Algorithms from Evolutionary Computing

Science.gov (United States)

O'Hagan, Steve; Knowles, Joshua; Kell, Douglas B.

2012-01-01

Comparatively few studies have addressed directly the question of quantifying the benefits to be had from using molecular genetic markers in experimental breeding programmes (e.g. for improved crops and livestock), nor the question of which organisms should be mated with each other to best effect. We argue that this requires in silico modelling, an approach for which there is a large literature in the field of evolutionary computation (EC), but which has not really been applied in this way to experimental breeding programmes. EC seeks to optimise measurable outcomes (phenotypic fitnesses) by optimising in silico the mutation, recombination and selection regimes that are used. We review some of the approaches from EC, and compare experimentally, using a biologically relevant in silico landscape, some algorithms that have knowledge of where they are in the (genotypic) search space (G-algorithms) with some (albeit well-tuned ones) that do not (F-algorithms). For the present kinds of landscapes, F- and G-algorithms were broadly comparable in quality and effectiveness, although we recognise that the G-algorithms were not equipped with any ‘prior knowledge’ of epistatic pathway interactions. This use of algorithms based on machine learning has important implications for the optimisation of experimental breeding programmes in the post-genomic era when we shall potentially have access to the full genome sequence of every organism in a breeding population. The non-proprietary code that we have used is made freely available (via Supplementary information). PMID:23185279

Development of Highly Informative Genome-Wide Single Sequence Repeat Markers for Breeding Applications in Sesame and Construction of a Web Resource: SisatBase

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Komivi Dossa

2017-08-01

Full Text Available The sequencing of the full nuclear genome of sesame (Sesamum indicum L. provides the platform for functional analyses of genome components and their application in breeding programs. Although the importance of microsatellites markers or simple sequence repeats (SSR in crop genotyping, genetics, and breeding applications is well established, only a little information exist concerning SSRs at the whole genome level in sesame. In addition, SSRs represent a suitable marker type for sesame molecular breeding in developing countries where it is mainly grown. In this study, we identified 138,194 genome-wide SSRs of which 76.5% were physically mapped onto the 13 pseudo-chromosomes. Among these SSRs, up to three primers pairs were supplied for 101,930 SSRs and used to in silico amplify the reference genome together with two newly sequenced sesame accessions. A total of 79,957 SSRs (78% were polymorphic between the three genomes thereby suggesting their promising use in different genomics-assisted breeding applications. From these polymorphic SSRs, 23 were selected and validated to have high polymorphic potential in 48 sesame accessions from different growing areas of Africa. Furthermore, we have developed an online user-friendly database, SisatBase (http://www.sesame-bioinfo.org/SisatBase/, which provides free access to SSRs data as well as an integrated platform for functional analyses. Altogether, the reference SSR and SisatBase would serve as useful resources for genetic assessment, genomic studies, and breeding advancement in sesame, especially in developing countries.

Genomic prediction in contrast to a genome-wide association study in explaining heritable variation of complex growth traits in breeding populations of Eucalyptus.

Science.gov (United States)

Müller, Bárbara S F; Neves, Leandro G; de Almeida Filho, Janeo E; Resende, Márcio F R; Muñoz, Patricio R; Dos Santos, Paulo E T; Filho, Estefano Paludzyszyn; Kirst, Matias; Grattapaglia, Dario

2017-07-11

capture large proportions of trait heritability and predict growth traits in trees with accuracies equal or better than those attainable by phenotypic selection. Additionally, our results document the superiority of the whole-genome regression approach in accounting for large proportions of the heritability of complex traits such as growth in contrast to the limited value of the local GWAS approach toward breeding applications in forest trees.

Genome-wide identification of breed-informative single-nucleotide ...

African Journals Online (AJOL)

This is because the SNPs on BovineSNP50 and GGP-80K assays were ascertained as being common in European taurine breeds. Lower MAF and SNP informativeness observed in this study limits the application of these assays in breed assignment, and could have other implications for genome-wide studies in South ...

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

KAUST Repository

Liu, Guozheng

2016-07-06

Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat.

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Guozheng Liu

Full Text Available Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1 examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2 explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3 investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L. and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs, but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

KAUST Repository

Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

2016-01-01

Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

Science.gov (United States)

Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

2016-01-01

Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population. PMID:27383841

Allele coding in genomic evaluation

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Christensen Ole F

2011-06-01

Full Text Available Abstract Background Genomic data are used in animal breeding to assist genetic evaluation. Several models to estimate genomic breeding values have been studied. In general, two approaches have been used. One approach estimates the marker effects first and then, genomic breeding values are obtained by summing marker effects. In the second approach, genomic breeding values are estimated directly using an equivalent model with a genomic relationship matrix. Allele coding is the method chosen to assign values to the regression coefficients in the statistical model. A common allele coding is zero for the homozygous genotype of the first allele, one for the heterozygote, and two for the homozygous genotype for the other allele. Another common allele coding changes these regression coefficients by subtracting a value from each marker such that the mean of regression coefficients is zero within each marker. We call this centered allele coding. This study considered effects of different allele coding methods on inference. Both marker-based and equivalent models were considered, and restricted maximum likelihood and Bayesian methods were used in inference. Results Theoretical derivations showed that parameter estimates and estimated marker effects in marker-based models are the same irrespective of the allele coding, provided that the model has a fixed general mean. For the equivalent models, the same results hold, even though different allele coding methods lead to different genomic relationship matrices. Calculated genomic breeding values are independent of allele coding when the estimate of the general mean is included into the values. Reliabilities of estimated genomic breeding values calculated using elements of the inverse of the coefficient matrix depend on the allele coding because different allele coding methods imply different models. Finally, allele coding affects the mixing of Markov chain Monte Carlo algorithms, with the centered coding being

Genome-Wide Specific Selection in Three Domestic Sheep Breeds.

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Huihua Wang

Full Text Available Commercial sheep raised for mutton grow faster than traditional Chinese sheep breeds. Here, we aimed to evaluate genetic selection among three different types of sheep breed: two well-known commercial mutton breeds and one indigenous Chinese breed.We first combined locus-specific branch lengths and di statistical methods to detect candidate regions targeted by selection in the three different populations. The results showed that the genetic distances reached at least medium divergence for each pairwise combination. We found these two methods were highly correlated, and identified many growth-related candidate genes undergoing artificial selection. For production traits, APOBR and FTO are associated with body mass index. For meat traits, ALDOA, STK32B and FAM190A are related to marbling. For reproduction traits, CCNB2 and SLC8A3 affect oocyte development. We also found two well-known genes, GHR (which affects meat production and quality and EDAR (associated with hair thickness were associated with German mutton merino sheep. Furthermore, four genes (POL, RPL7, MSL1 and SHISA9 were associated with pre-weaning gain in our previous genome-wide association study.Our results indicated that combine locus-specific branch lengths and di statistical approaches can reduce the searching ranges for specific selection. And we got many credible candidate genes which not only confirm the results of previous reports, but also provide a suite of novel candidate genes in defined breeds to guide hybridization breeding.

Genome-Wide Specific Selection in Three Domestic Sheep Breeds.

Science.gov (United States)

Wang, Huihua; Zhang, Li; Cao, Jiaxve; Wu, Mingming; Ma, Xiaomeng; Liu, Zhen; Liu, Ruizao; Zhao, Fuping; Wei, Caihong; Du, Lixin

2015-01-01

Commercial sheep raised for mutton grow faster than traditional Chinese sheep breeds. Here, we aimed to evaluate genetic selection among three different types of sheep breed: two well-known commercial mutton breeds and one indigenous Chinese breed. We first combined locus-specific branch lengths and di statistical methods to detect candidate regions targeted by selection in the three different populations. The results showed that the genetic distances reached at least medium divergence for each pairwise combination. We found these two methods were highly correlated, and identified many growth-related candidate genes undergoing artificial selection. For production traits, APOBR and FTO are associated with body mass index. For meat traits, ALDOA, STK32B and FAM190A are related to marbling. For reproduction traits, CCNB2 and SLC8A3 affect oocyte development. We also found two well-known genes, GHR (which affects meat production and quality) and EDAR (associated with hair thickness) were associated with German mutton merino sheep. Furthermore, four genes (POL, RPL7, MSL1 and SHISA9) were associated with pre-weaning gain in our previous genome-wide association study. Our results indicated that combine locus-specific branch lengths and di statistical approaches can reduce the searching ranges for specific selection. And we got many credible candidate genes which not only confirm the results of previous reports, but also provide a suite of novel candidate genes in defined breeds to guide hybridization breeding.

Whole-genome sequence, SNP chips and pedigree structure: building demographic profiles in domestic dog breeds to optimize genetic-trait mapping

Science.gov (United States)

Dreger, Dayna L.; Rimbault, Maud; Davis, Brian W.; Bhatnagar, Adrienne; Parker, Heidi G.

2016-01-01

ABSTRACT In the decade following publication of the draft genome sequence of the domestic dog, extraordinary advances with application to several fields have been credited to the canine genetic system. Taking advantage of closed breeding populations and the subsequent selection for aesthetic and behavioral characteristics, researchers have leveraged the dog as an effective natural model for the study of complex traits, such as disease susceptibility, behavior and morphology, generating unique contributions to human health and biology. When designing genetic studies using purebred dogs, it is essential to consider the unique demography of each population, including estimation of effective population size and timing of population bottlenecks. The analytical design approach for genome-wide association studies (GWAS) and analysis of whole-genome sequence (WGS) experiments are inextricable from demographic data. We have performed a comprehensive study of genomic homozygosity, using high-depth WGS data for 90 individuals, and Illumina HD SNP data from 800 individuals representing 80 breeds. These data were coupled with extensive pedigree data analyses for 11 breeds that, together, allowed us to compute breed structure, demography, and molecular measures of genome diversity. Our comparative analyses characterize the extent, formation and implication of breed-specific diversity as it relates to population structure. These data demonstrate the relationship between breed-specific genome dynamics and population architecture, and provide important considerations influencing the technological and cohort design of association and other genomic studies. PMID:27874836

Genome-editing technologies and their potential application in horticultural crop breeding

Science.gov (United States)

Xiong, Jin-Song; Ding, Jing; Li, Yi

2015-01-01

Plant breeding, one of the oldest agricultural activities, parallels human civilization. Many crops have been domesticated to satisfy human's food and aesthetical needs, including numerous specialty horticultural crops such as fruits, vegetables, ornamental flowers, shrubs, and trees. Crop varieties originated through selection during early human civilization. Other technologies, such as various forms of hybridization, mutation, and transgenics, have also been invented and applied to crop breeding over the past centuries. The progress made in these breeding technologies, especially the modern biotechnology-based breeding technologies, has had a great impact on crop breeding as well as on our lives. Here, we first review the developmental process and applications of these technologies in horticultural crop breeding. Then, we mainly describe the principles of the latest genome-editing technologies and discuss their potential applications in the genetic improvement of horticultural crops. The advantages and challenges of genome-editing technologies in horticultural crop breeding are also discussed. PMID:26504570

Enhancing genetic gain in the era of molecular breeding.

Science.gov (United States)

Xu, Yunbi; Li, Ping; Zou, Cheng; Lu, Yanli; Xie, Chuanxiao; Zhang, Xuecai; Prasanna, Boddupalli M; Olsen, Michael S

2017-05-17

As one of the important concepts in conventional quantitative genetics and breeding, genetic gain can be defined as the amount of increase in performance that is achieved annually through artificial selection. To develop pro ducts that meet the increasing demand of mankind, especially for food and feed, in addition to various industrial uses, breeders are challenged to enhance the potential of genetic gain continuously, at ever higher rates, while they close the gaps that remain between the yield potential in breeders' demonstration trials and the actual yield in farmers' fields. Factors affecting genetic gain include genetic variation available in breeding materials, heritability for traits of interest, selection intensity, and the time required to complete a breeding cycle. Genetic gain can be improved through enhancing the potential and closing the gaps, which has been evolving and complemented with modern breeding techniques and platforms, mainly driven by molecular and genomic tools, combined with improved agronomic practice. Several key strategies are reviewed in this article. Favorable genetic variation can be unlocked and created through molecular and genomic approaches including mutation, gene mapping and discovery, and transgene and genome editing. Estimation of heritability can be improved by refining field experiments through well-controlled and precisely assayed environmental factors or envirotyping, particularly for understanding and controlling spatial heterogeneity at the field level. Selection intensity can be significantly heightened through improvements in the scale and precision of genotyping and phenotyping. The breeding cycle time can be shortened by accelerating breeding procedures through integrated breeding approaches such as marker-assisted selection and doubled haploid development. All the strategies can be integrated with other widely used conventional approaches in breeding programs to enhance genetic gain. More transdisciplinary

Population Structure and Genomic Breed Composition in an Angus-Brahman Crossbred Cattle Population.

Science.gov (United States)

Gobena, Mesfin; Elzo, Mauricio A; Mateescu, Raluca G

2018-01-01

Crossbreeding is a common strategy used in tropical and subtropical regions to enhance beef production, and having accurate knowledge of breed composition is essential for the success of a crossbreeding program. Although pedigree records have been traditionally used to obtain the breed composition of crossbred cattle, the accuracy of pedigree-based breed composition can be reduced by inaccurate and/or incomplete records and Mendelian sampling. Breed composition estimation from genomic data has multiple advantages including higher accuracy without being affected by missing, incomplete, or inaccurate records and the ability to be used as independent authentication of breed in breed-labeled beef products. The present study was conducted with 676 Angus-Brahman crossbred cattle with genotype and pedigree information to evaluate the feasibility and accuracy of using genomic data to determine breed composition. We used genomic data in parametric and non-parametric methods to detect population structure due to differences in breed composition while accounting for the confounding effect of close familial relationships. By applying principal component analysis (PCA) and the maximum likelihood method of ADMIXTURE to genomic data, it was possible to successfully characterize population structure resulting from heterogeneous breed ancestry, while accounting for close familial relationships. PCA results offered additional insight into the different hierarchies of genetic variation structuring. The first principal component was strongly correlated with Angus-Brahman proportions, and the second represented variation within animals that have a relatively more extended Brangus lineage-indicating the presence of a distinct pattern of genetic variation in these cattle. Although there was strong agreement between breed proportions estimated from pedigree and genetic information, there were significant discrepancies between these two methods for certain animals. This was most likely due

Population Structure and Genomic Breed Composition in an Angus–Brahman Crossbred Cattle Population

Directory of Open Access Journals (Sweden)

Mesfin Gobena

2018-03-01

Full Text Available Crossbreeding is a common strategy used in tropical and subtropical regions to enhance beef production, and having accurate knowledge of breed composition is essential for the success of a crossbreeding program. Although pedigree records have been traditionally used to obtain the breed composition of crossbred cattle, the accuracy of pedigree-based breed composition can be reduced by inaccurate and/or incomplete records and Mendelian sampling. Breed composition estimation from genomic data has multiple advantages including higher accuracy without being affected by missing, incomplete, or inaccurate records and the ability to be used as independent authentication of breed in breed-labeled beef products. The present study was conducted with 676 Angus–Brahman crossbred cattle with genotype and pedigree information to evaluate the feasibility and accuracy of using genomic data to determine breed composition. We used genomic data in parametric and non-parametric methods to detect population structure due to differences in breed composition while accounting for the confounding effect of close familial relationships. By applying principal component analysis (PCA and the maximum likelihood method of ADMIXTURE to genomic data, it was possible to successfully characterize population structure resulting from heterogeneous breed ancestry, while accounting for close familial relationships. PCA results offered additional insight into the different hierarchies of genetic variation structuring. The first principal component was strongly correlated with Angus–Brahman proportions, and the second represented variation within animals that have a relatively more extended Brangus lineage—indicating the presence of a distinct pattern of genetic variation in these cattle. Although there was strong agreement between breed proportions estimated from pedigree and genetic information, there were significant discrepancies between these two methods for certain animals

Review. Promises, pitfalls and challenges of genomic selection in breeding programs

Energy Technology Data Exchange (ETDEWEB)

Ibanez-Escriche, N.; Gonzalez-Recio, O.

2011-07-01

The aim of this work was to review the main challenges and pitfalls of the implementation of genomic selection in the breeding programs of different livestock species. Genomic selection is now one of the main challenges in animal breeding and genetics. Its application could considerably increase the genetic gain in traits of interest. However, the success of its practical implementation depends on the selection scheme characteristics, and these must be studied for each particular case. In dairy cattle, especially in Holsteins, genomic selection is a reality. However, in other livestock species (beef cattle, small ruminants, monogastrics and fish) genomic selection has mainly been used experimentally. The main limitation for its implementation in the mentioned livestock species is the high geno typing costs compared to the low selection value of the candidate. Nevertheless, nowadays the possibility of using single-nucleotide polymorphism (SNP) chips of low density to make genomic selection applications economically feasible is under study. Economic studies may optimize the benefits of genomic selection (GS) to include new traits in the breeding goals. It is evident that genomic selection offers great potential; however, a suitable geno typing strategy and recording system for each case is needed in order to properly exploit it. (Author) 50 refs.

Mitigation of inbreeding while preserving genetic gain in genomic breeding programs for outbred plants.

Science.gov (United States)

Lin, Zibei; Shi, Fan; Hayes, Ben J; Daetwyler, Hans D

2017-05-01

Heuristic genomic inbreeding controls reduce inbreeding in genomic breeding schemes without reducing genetic gain. Genomic selection is increasingly being implemented in plant breeding programs to accelerate genetic gain of economically important traits. However, it may cause significant loss of genetic diversity when compared with traditional schemes using phenotypic selection. We propose heuristic strategies to control the rate of inbreeding in outbred plants, which can be categorised into three types: controls during mate allocation, during selection, and simultaneous selection and mate allocation. The proposed mate allocation measure GminF allocates two or more parents for mating in mating groups that minimise coancestry using a genomic relationship matrix. Two types of relationship-adjusted genomic breeding values for parent selection candidates ([Formula: see text]) and potential offspring ([Formula: see text]) are devised to control inbreeding during selection and even enabling simultaneous selection and mate allocation. These strategies were tested in a case study using a simulated perennial ryegrass breeding scheme. As compared to the genomic selection scheme without controls, all proposed strategies could significantly decrease inbreeding while achieving comparable genetic gain. In particular, the scenario using [Formula: see text] in simultaneous selection and mate allocation reduced inbreeding to one-third of the original genomic selection scheme. The proposed strategies are readily applicable in any outbred plant breeding program.

Domestic estimated breeding values and genomic enhanced breeding values of bulls in comparison with their foreign genomic enhanced breeding values.

Science.gov (United States)

Přibyl, J; Bauer, J; Čermák, V; Pešek, P; Přibylová, J; Šplíchal, J; Vostrá-Vydrová, H; Vostrý, L; Zavadilová, L

2015-10-01

Estimated breeding values (EBVs) and genomic enhanced breeding values (GEBVs) for milk production of young genotyped Holstein bulls were predicted using a conventional BLUP - Animal Model, a method fitting regression coefficients for loci (RRBLUP), a method utilizing the realized genomic relationship matrix (GBLUP), by a single-step procedure (ssGBLUP) and by a one-step blending procedure. Information sources for prediction were the nation-wide database of domestic Czech production records in the first lactation combined with deregressed proofs (DRP) from Interbull files (August 2013) and domestic test-day (TD) records for the first three lactations. Data from 2627 genotyped bulls were used, of which 2189 were already proven under domestic conditions. Analyses were run that used Interbull values for genotyped bulls only or that used Interbull values for all available sires. Resultant predictions were compared with GEBV of 96 young foreign bulls evaluated abroad and whose proofs were from Interbull method GMACE (August 2013) on the Czech scale. Correlations of predictions with GMACE values of foreign bulls ranged from 0.33 to 0.75. Combining domestic data with Interbull EBVs improved prediction of both EBV and GEBV. Predictions by Animal Model (traditional EBV) using only domestic first lactation records and GMACE values were correlated by only 0.33. Combining the nation-wide domestic database with all available DRP for genotyped and un-genotyped sires from Interbull resulted in an EBV correlation of 0.60, compared with 0.47 when only Interbull data were used. In all cases, GEBVs had higher correlations than traditional EBVs, and the highest correlations were for predictions from the ssGBLUP procedure using combined data (0.75), or with all available DRP from Interbull records only (one-step blending approach, 0.69). The ssGBLUP predictions using the first three domestic lactation records in the TD model were correlated with GMACE predictions by 0.69, 0.64 and 0

Prospects for genomic selection in cassava breeding

Science.gov (United States)

Cassava (Manihot esculenta Crantz) is a clonally propagated staple food crop in the tropics. Genomic selection (GS) has been implemented at three breeding institutions in Africa in order to reduce cycle times. Initial studies provided promising estimates of predictive abilities. Here, we expand on p...

Genome-wide association study, genomic prediction and marker-assisted selection for seed weight in soybean (Glycine max).

Science.gov (United States)

Zhang, Jiaoping; Song, Qijian; Cregan, Perry B; Jiang, Guo-Liang

2016-01-01

Twenty-two loci for soybean SW and candidate genes conditioning seed development were identified; and prediction accuracies of GS and MAS were estimated through cross-validation and validation with unrelated populations. Soybean (Glycine max) is a major crop for plant protein and oil production, and seed weight (SW) is important for yield and quality in food/vegetable uses of soybean. However, our knowledge of genes controlling SW remains limited. To better understand the molecular mechanism underlying the trait and explore marker-based breeding approaches, we conducted a genome-wide association study in a population of 309 soybean germplasm accessions using 31,045 single nucleotide polymorphisms (SNPs), and estimated the prediction accuracy of genomic selection (GS) and marker-assisted selection (MAS) for SW. Twenty-two loci of minor effect associated with SW were identified, including hotspots on Gm04 and Gm19. The mixed model containing these loci explained 83.4% of phenotypic variation. Candidate genes with Arabidopsis orthologs conditioning SW were also proposed. The prediction accuracies of GS and MAS by cross-validation were 0.75-0.87 and 0.62-0.75, respectively, depending on the number of SNPs used and the size of training population. GS also outperformed MAS when the validation was performed using unrelated panels across a wide range of maturities, with an average prediction accuracy of 0.74 versus 0.53. This study convincingly demonstrated that soybean SW is controlled by numerous minor-effect loci. It greatly enhances our understanding of the genetic basis of SW in soybean and facilitates the identification of genes controlling the trait. It also suggests that GS holds promise for accelerating soybean breeding progress. The results are helpful for genetic improvement and genomic prediction of yield in soybean.

Genomic selection for crossbred performance accounting for breed-specific effects.

Science.gov (United States)

Lopes, Marcos S; Bovenhuis, Henk; Hidalgo, André M; van Arendonk, Johan A M; Knol, Egbert F; Bastiaansen, John W M

2017-06-26

Breed-specific effects are observed when the same allele of a given genetic marker has a different effect depending on its breed origin, which results in different allele substitution effects across breeds. In such a case, single-breed breeding values may not be the most accurate predictors of crossbred performance. Our aim was to estimate the contribution of alleles from each parental breed to the genetic variance of traits that are measured in crossbred offspring, and to compare the prediction accuracies of estimated direct genomic values (DGV) from a traditional genomic selection model (GS) that are trained on purebred or crossbred data, with accuracies of DGV from a model that accounts for breed-specific effects (BS), trained on purebred or crossbred data. The final dataset was composed of 924 Large White, 924 Landrace and 924 two-way cross (F1) genotyped and phenotyped animals. The traits evaluated were litter size (LS) and gestation length (GL) in pigs. The genetic correlation between purebred and crossbred performance was higher than 0.88 for both LS and GL. For both traits, the additive genetic variance was larger for alleles inherited from the Large White breed compared to alleles inherited from the Landrace breed (0.74 and 0.56 for LS, and 0.42 and 0.40 for GL, respectively). The highest prediction accuracies of crossbred performance were obtained when training was done on crossbred data. For LS, prediction accuracies were the same for GS and BS DGV (0.23), while for GL, prediction accuracy for BS DGV was similar to the accuracy of GS DGV (0.53 and 0.52, respectively). In this study, training on crossbred data resulted in higher prediction accuracy than training on purebred data and evidence of breed-specific effects for LS and GL was demonstrated. However, when training was done on crossbred data, both GS and BS models resulted in similar prediction accuracies. In future studies, traits with a lower genetic correlation between purebred and crossbred

Strategies for use of reproductive technologies in genomic dairy cattle breeding programs

DEFF Research Database (Denmark)

Thomasen, Jørn Rind; Sørensen, Anders Christian

A simulation study was performed for testing the effect of using reproductive technologies in a genomic dairy cattle young bull breeding scheme. The breeding scheme parameters: 1) number of donors, 2) number of progeny per donor, 3) age of the donor, 4) number of sires, and 5) reliability...... of genomic breeding values. The breeding schemes were evaluated according to genetic gain and rate of inbreeding. The relative gain by use of reproductive technologies is 11 to 84 percent points depending on the choice of other breeding scheme parameters. A large donor program with high selection intensity...... of sires provides the highest genetic gain. A relatively higher genetic gain is obtained for higher reliability of GEBV. Extending the donor program and number of selected bulls has a major effect of reducing the rate of inbreeding without compromising genetic gain....

Genomic Selection in the Era of Next Generation Sequencing for Complex Traits in Plant Breeding.

Science.gov (United States)

Bhat, Javaid A; Ali, Sajad; Salgotra, Romesh K; Mir, Zahoor A; Dutta, Sutapa; Jadon, Vasudha; Tyagi, Anshika; Mushtaq, Muntazir; Jain, Neelu; Singh, Pradeep K; Singh, Gyanendra P; Prabhu, K V

2016-01-01

Genomic selection (GS) is a promising approach exploiting molecular genetic markers to design novel breeding programs and to develop new markers-based models for genetic evaluation. In plant breeding, it provides opportunities to increase genetic gain of complex traits per unit time and cost. The cost-benefit balance was an important consideration for GS to work in crop plants. Availability of genome-wide high-throughput, cost-effective and flexible markers, having low ascertainment bias, suitable for large population size as well for both model and non-model crop species with or without the reference genome sequence was the most important factor for its successful and effective implementation in crop species. These factors were the major limitations to earlier marker systems viz., SSR and array-based, and was unimaginable before the availability of next-generation sequencing (NGS) technologies which have provided novel SNP genotyping platforms especially the genotyping by sequencing. These marker technologies have changed the entire scenario of marker applications and made the use of GS a routine work for crop improvement in both model and non-model crop species. The NGS-based genotyping have increased genomic-estimated breeding value prediction accuracies over other established marker platform in cereals and other crop species, and made the dream of GS true in crop breeding. But to harness the true benefits from GS, these marker technologies will be combined with high-throughput phenotyping for achieving the valuable genetic gain from complex traits. Moreover, the continuous decline in sequencing cost will make the WGS feasible and cost effective for GS in near future. Till that time matures the targeted sequencing seems to be more cost-effective option for large scale marker discovery and GS, particularly in case of large and un-decoded genomes.

Genome-enabled prediction models for yield related traits in chickpea

Science.gov (United States)

Genomic selection (GS) unlike marker-assisted backcrossing (MABC) predicts breeding values of lines using genome-wide marker profiling and allows selection of lines prior to field-phenotyping, thereby shortening the breeding cycle. A collection of 320 elite breeding lines was selected and phenotyped...

Accuracy of genomic breeding value prediction for intramuscular fat using different genomic relationship matrices in Hanwoo (Korean cattle).

Science.gov (United States)

Choi, Taejeong; Lim, Dajeong; Park, Byoungho; Sharma, Aditi; Kim, Jong-Joo; Kim, Sidong; Lee, Seung Hwan

2017-07-01

Intramuscular fat is one of the meat quality traits that is considered in the selection strategies for Hanwoo (Korean cattle). Different methods are used to estimate the breeding value of selection candidates. In the present work we focused on accuracy of different genotype relationship matrices as described by forni and pedigree based relationship matrix. The data set included a total of 778 animals that were genotyped for BovineSNP50 BeadChip. Among these 778 animals, 72 animals were sires for 706 reference animals and were used as a validation dataset. Single trait animal model (best linear unbiased prediction and genomic best linear unbiased prediction) was used to estimate the breeding values from genomic and pedigree information. The diagonal elements for the pedigree based coefficients were slightly higher for the genomic relationship matrices (GRM) based coefficients while off diagonal elements were considerably low for GRM based coefficients. The accuracy of breeding value for the pedigree based relationship matrix (A) was 13% while for GRM (GOF, G05, and Yang) it was 0.37, 0.45, and 0.38, respectively. Accuracy of GRM was 1.5 times higher than A in this study. Therefore, genomic information will be more beneficial than pedigree information in the Hanwoo breeding program.

Genetic diversity analysis of two commercial breeds of pigs using genomic and pedigree data.

Science.gov (United States)

Zanella, Ricardo; Peixoto, Jane O; Cardoso, Fernando F; Cardoso, Leandro L; Biegelmeyer, Patrícia; Cantão, Maurício E; Otaviano, Antonio; Freitas, Marcelo S; Caetano, Alexandre R; Ledur, Mônica C

2016-03-30

Genetic improvement in livestock populations can be achieved without significantly affecting genetic diversity if mating systems and selection decisions take genetic relationships among individuals into consideration. The objective of this study was to examine the genetic diversity of two commercial breeds of pigs. Genotypes from 1168 Landrace (LA) and 1094 Large White (LW) animals from a commercial breeding program in Brazil were obtained using the Illumina PorcineSNP60 Beadchip. Inbreeding estimates based on pedigree (F x) and genomic information using runs of homozygosity (F ROH) and the single nucleotide polymorphisms (SNP) by SNP inbreeding coefficient (F SNP) were obtained. Linkage disequilibrium (LD), correlation of linkage phase (r) and effective population size (N e ) were also estimated. Estimates of inbreeding obtained with pedigree information were lower than those obtained with genomic data in both breeds. We observed that the extent of LD was slightly larger at shorter distances between SNPs in the LW population than in the LA population, which indicates that the LW population was derived from a smaller N e . Estimates of N e based on genomic data were equal to 53 and 40 for the current populations of LA and LW, respectively. The correlation of linkage phase between the two breeds was equal to 0.77 at distances up to 50 kb, which suggests that genome-wide association and selection should be performed within breed. Although selection intensities have been stronger in the LA breed than in the LW breed, levels of genomic and pedigree inbreeding were lower for the LA than for the LW breed. The use of genomic data to evaluate population diversity in livestock animals can provide new and more precise insights about the effects of intense selection for production traits. Resulting information and knowledge can be used to effectively increase response to selection by appropriately managing the rate of inbreeding, minimizing negative effects of inbreeding

Genomic Tools in Cowpea Breeding Programs: Status and Perspectives

Science.gov (United States)

Boukar, Ousmane; Fatokun, Christian A.; Huynh, Bao-Lam; Roberts, Philip A.; Close, Timothy J.

2016-01-01

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

Genomic tools in cowpea breeding programs: status and perspectives

Directory of Open Access Journals (Sweden)

Ousmane eBoukar

2016-06-01

Full Text Available 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

Alfalfa breeding benefits from genomics of Medicago truncatula

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Žilije Bernadet

2010-01-01

Full Text Available International programs aim at developing knowledge and tools in the model species Medicago truncatula. Genetic resources, DNA sequences, markers, genetic and physical maps are now publicly available. These efforts contribute to improve breeding schemes of crop species such as alfalfa. However, transfer of information from M. truncatula to alfalfa is not straightforward. The article reviews the gain given by the model species to better analyze genetic determinism of breeding traits in alfalfa. It also shows that investments in alfalfa genomics (DNA sequences, SNP development are needed to benefit from the model species.

Genomic Prediction of Seed Quality Traits Using Advanced Barley Breeding Lines

Science.gov (United States)

Nielsen, Nanna Hellum; Jahoor, Ahmed; Jensen, Jens Due; Orabi, Jihad; Cericola, Fabio; Edriss, Vahid; Jensen, Just

2016-01-01

Genomic selection was recently introduced in plant breeding. The objective of this study was to develop genomic prediction for important seed quality parameters in spring barley. The aim was to predict breeding values without expensive phenotyping of large sets of lines. A total number of 309 advanced spring barley lines tested at two locations each with three replicates were phenotyped and each line was genotyped by Illumina iSelect 9Kbarley chip. The population originated from two different breeding sets, which were phenotyped in two different years. Phenotypic measurements considered were: seed size, protein content, protein yield, test weight and ergosterol content. A leave-one-out cross-validation strategy revealed high prediction accuracies ranging between 0.40 and 0.83. Prediction across breeding sets resulted in reduced accuracies compared to the leave-one-out strategy. Furthermore, predicting across full and half-sib-families resulted in reduced prediction accuracies. Additionally, predictions were performed using reduced marker sets and reduced training population sets. In conclusion, using less than 200 lines in the training set can result in low prediction accuracy, and the accuracy will then be highly dependent on the family structure of the selected training set. However, the results also indicate that relatively small training sets (200 lines) are sufficient for genomic prediction in commercial barley breeding. In addition, our results indicate a minimum marker set of 1,000 to decrease the risk of low prediction accuracy for some traits or some families. PMID:27783639

Genomic Prediction of Seed Quality Traits Using Advanced Barley Breeding Lines.

Directory of Open Access Journals (Sweden)

Nanna Hellum Nielsen

Full Text Available Genomic selection was recently introduced in plant breeding. The objective of this study was to develop genomic prediction for important seed quality parameters in spring barley. The aim was to predict breeding values without expensive phenotyping of large sets of lines. A total number of 309 advanced spring barley lines tested at two locations each with three replicates were phenotyped and each line was genotyped by Illumina iSelect 9Kbarley chip. The population originated from two different breeding sets, which were phenotyped in two different years. Phenotypic measurements considered were: seed size, protein content, protein yield, test weight and ergosterol content. A leave-one-out cross-validation strategy revealed high prediction accuracies ranging between 0.40 and 0.83. Prediction across breeding sets resulted in reduced accuracies compared to the leave-one-out strategy. Furthermore, predicting across full and half-sib-families resulted in reduced prediction accuracies. Additionally, predictions were performed using reduced marker sets and reduced training population sets. In conclusion, using less than 200 lines in the training set can result in low prediction accuracy, and the accuracy will then be highly dependent on the family structure of the selected training set. However, the results also indicate that relatively small training sets (200 lines are sufficient for genomic prediction in commercial barley breeding. In addition, our results indicate a minimum marker set of 1,000 to decrease the risk of low prediction accuracy for some traits or some families.

Development of Genomic Resources in the Species of Trifolium L. and Its Application in Forage Legume Breeding

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Leif Skøt

2012-05-01

Full Text Available Clovers (genus Trifolium are a large and widespread genus of legumes. A number of clovers are of agricultural importance as forage crops in grassland agriculture, particularly temperate areas. White clover (Trifolium repens L. is used in grazed pasture and red clover (T. pratense L. is widely cut and conserved as a winter feed. For the diploid red clover, genetic and genomic tools and resources have developed rapidly over the last five years including genetic and physical maps, BAC (bacterial artificial chromosome end sequence and transcriptome sequence information. This has paved the way for the use of genome wide selection and high throughput phenotyping in germplasm development. For the allotetraploid white clover progress has been slower although marker assisted selection is in use and relatively robust genetic maps and QTL (quantitative trait locus information now exist. For both species the sequencing of the model legume Medicago truncatula gene space is an important development to aid genomic, biological and evolutionary studies. The first genetic maps of another species, subterranean clover (Trifolium subterraneum L. have also been published and its comparative genomics with red clover and M. truncatula conducted. Next generation sequencing brings the potential to revolutionize clover genomics, but international consortia and effective use of germplasm, novel population structures and phenomics will be required to carry out effective translation into breeding. Another avenue for clover genomic and genetic improvement is interspecific hybridization. This approach has considerable potential with regard to crop improvement but also opens windows of opportunity for studies of biological and evolutionary processes.

Structuring an Efficient Organic Wheat Breeding Program

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P. Stephen Baenziger

2011-08-01

Full Text Available Our long-term goal is to develop wheat cultivars that will improve the profitability and competitiveness of organic producers in Nebraska and the Northern Great Plains. Our approach is to select in early generations for highly heritable traits that are needed for both organic and conventional production (another breeding goal, followed by a targeted organic breeding effort with testing at two organic locations (each in a different ecological region beginning with the F6 generation. Yield analyses from replicated trials at two organic breeding sites and 7 conventional breeding sites from F6 through F12 nurseries revealed, using analyses of variance, biplots, and comparisons of selected lines that it is inappropriate to use data from conventional testing for making germplasm selections for organic production. Selecting and testing lines under organic production practices in different ecological regions was also needed and cultivar selections for organic production were different than those for conventional production. Modifications to this breeding protocol may include growing early generation bulks in an organic cropping system. In the future, our selection efforts should also focus on using state-of-the-art, non-transgenic breeding technologies (genomic selection, marker-assisted breeding, and high throughput phenotyping to synergistically improve organic and conventional wheat breeding.

Comparisons of single-stage and two-stage approaches to genomic selection.

Science.gov (United States)

Schulz-Streeck, Torben; Ogutu, Joseph O; Piepho, Hans-Peter

2013-01-01

Genomic selection (GS) is a method for predicting breeding values of plants or animals using many molecular markers that is commonly implemented in two stages. In plant breeding the first stage usually involves computation of adjusted means for genotypes which are then used to predict genomic breeding values in the second stage. We compared two classical stage-wise approaches, which either ignore or approximate correlations among the means by a diagonal matrix, and a new method, to a single-stage analysis for GS using ridge regression best linear unbiased prediction (RR-BLUP). The new stage-wise method rotates (orthogonalizes) the adjusted means from the first stage before submitting them to the second stage. This makes the errors approximately independently and identically normally distributed, which is a prerequisite for many procedures that are potentially useful for GS such as machine learning methods (e.g. boosting) and regularized regression methods (e.g. lasso). This is illustrated in this paper using componentwise boosting. The componentwise boosting method minimizes squared error loss using least squares and iteratively and automatically selects markers that are most predictive of genomic breeding values. Results are compared with those of RR-BLUP using fivefold cross-validation. The new stage-wise approach with rotated means was slightly more similar to the single-stage analysis than the classical two-stage approaches based on non-rotated means for two unbalanced datasets. This suggests that rotation is a worthwhile pre-processing step in GS for the two-stage approaches for unbalanced datasets. Moreover, the predictive accuracy of stage-wise RR-BLUP was higher (5.0-6.1%) than that of componentwise boosting.

Genomic selection in plant breeding: from theory to practice.

Science.gov (United States)

Jannink, Jean-Luc; Lorenz, Aaron J; Iwata, Hiroyoshi

2010-03-01

We intuitively believe that the dramatic drop in the cost of DNA marker information we have experienced should have immediate benefits in accelerating the delivery of crop varieties with improved yield, quality and biotic and abiotic stress tolerance. But these traits are complex and affected by many genes, each with small effect. Traditional marker-assisted selection has been ineffective for such traits. The introduction of genomic selection (GS), however, has shifted that paradigm. Rather than seeking to identify individual loci significantly associated with a trait, GS uses all marker data as predictors of performance and consequently delivers more accurate predictions. Selection can be based on GS predictions, potentially leading to more rapid and lower cost gains from breeding. The objectives of this article are to review essential aspects of GS and summarize the important take-home messages from recent theoretical, simulation and empirical studies. We then look forward and consider research needs surrounding methodological questions and the implications of GS for long-term selection.

Overlap in genomic variation associated with milk fat composition in Holstein Friesian and Dutch native dual-purpose breeds.

Science.gov (United States)

Maurice-Van Eijndhoven, M H T; Bovenhuis, H; Veerkamp, R F; Calus, M P L

2015-09-01

The aim of this study was to identify if genomic variations associated with fatty acid (FA) composition are similar between the Holstein-Friesian (HF) and native dual-purpose breeds used in the Dutch dairy industry. Phenotypic and genotypic information were available for the breeds Meuse-Rhine-Yssel (MRY), Dutch Friesian (DF), Groningen White Headed (GWH), and HF. First, the reliability of genomic breeding values of the native Dutch dual-purpose cattle breeds MRY, DF, and GWH was evaluated using single nucleotide polymorphism (SNP) effects estimated in HF, including all SNP or subsets with stronger associations in HF. Second, the genomic variation of the regions associated with FA composition in HF (regions on Bos taurus autosome 5, 14, and 26), were studied in the different breeds. Finally, similarities in genotype and allele frequencies between MRY, DF, GWH, and HF breeds were assessed for specific regions associated with FA composition. On average across the traits, the highest reliabilities of genomic prediction were estimated for GWH (0.158) and DF (0.116) when the 8 to 22 SNP with the strongest association in HF were included. With the same set of SNP, GEBV for MRY were the least reliable (0.022). This indicates that on average only 2 (MRY) to 16% (GWH) of the genomic variation in HF is shared with the native Dutch dual-purpose breeds. The comparison of predicted variances of different regions associated with milk and milk fat composition showed that breeds clearly differed in genomic variation within these regions. Finally, the correlations of allele frequencies between breeds across the 8 to 22 SNP with the strongest association in HF were around 0.8 between the Dutch native dual-purpose breeds, whereas the correlations between the native breeds and HF were clearly lower and around 0.5. There was no consistent relationship between the reliabilities of genomic prediction for a specific breed and the correlation between the allele frequencies of this breed

Biotechnology Assisted Wheat Breeding for Organic Agriculture

DEFF Research Database (Denmark)

Steffan, Philipp Matthias

model identified two novel QTL for common bunt resistance located on wheat chromosomes 2B and 7 A. The identification of new resistance loci may help to broaden our understanding of common bunt resistance in wheat, and QTL may potentially be exploited by marker assisted selection in plant breeding. QTL...... markers for common bunt resistance may potentially help to speed up resistance breeding by shortening the long time required for phenotypic disease screening. Here, we report the results of 1. an association mapping study for common bunt resistance, 2. a QTL mapping study for the localization of common...

Whole-genome sequencing reveals mutational landscape underlying phenotypic differences between two widespread Chinese cattle breeds

OpenAIRE

Xu, Yao; Jiang, Yu; Shi, Tao; Cai, Hanfang; Lan, Xianyong; Zhao, Xin; Plath, Martin; Chen, Hong

2017-01-01

Whole-genome sequencing provides a powerful tool to obtain more genetic variability that could produce a range of benefits for cattle breeding industry. Nanyang (Bos indicus) and Qinchuan (Bos taurus) are two important Chinese indigenous cattle breeds with distinct phenotypes. To identify the genetic characteristics responsible for variation in phenotypes between the two breeds, in the present study, we for the first time sequenced the genomes of four Nanyang and four Qinchuan cattle with 10 ...

GAAP: Genome-organization-framework-Assisted Assembly Pipeline for prokaryotic genomes.

Science.gov (United States)

Yuan, Lina; Yu, Yang; Zhu, Yanmin; Li, Yulai; Li, Changqing; Li, Rujiao; Ma, Qin; Siu, Gilman Kit-Hang; Yu, Jun; Jiang, Taijiao; Xiao, Jingfa; Kang, Yu

2017-01-25

Next-generation sequencing (NGS) technologies have greatly promoted the genomic study of prokaryotes. However, highly fragmented assemblies due to short reads from NGS are still a limiting factor in gaining insights into the genome biology. Reference-assisted tools are promising in genome assembly, but tend to result in false assembly when the assigned reference has extensive rearrangements. Herein, we present GAAP, a genome assembly pipeline for scaffolding based on core-gene-defined Genome Organizational Framework (cGOF) described in our previous study. Instead of assigning references, we use the multiple-reference-derived cGOFs as indexes to assist in order and orientation of the scaffolds and build a skeleton structure, and then use read pairs to extend scaffolds, called local scaffolding, and distinguish between true and chimeric adjacencies in the scaffolds. In our performance tests using both empirical and simulated data of 15 genomes in six species with diverse genome size, complexity, and all three categories of cGOFs, GAAP outcompetes or achieves comparable results when compared to three other reference-assisted programs, AlignGraph, Ragout and MeDuSa. GAAP uses both cGOF and pair-end reads to create assemblies in genomic scale, and performs better than the currently available reference-assisted assembly tools as it recovers more assemblies and makes fewer false locations, especially for species with extensive rearranged genomes. Our method is a promising solution for reconstruction of genome sequence from short reads of NGS.

Identification of genomic regions associated with phenotypic variation between dog breeds using selection mapping.

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Amaury Vaysse

2011-10-01

Full Text Available The extraordinary phenotypic diversity of dog breeds has been sculpted by a unique population history accompanied by selection for novel and desirable traits. Here we perform a comprehensive analysis using multiple test statistics to identify regions under selection in 509 dogs from 46 diverse breeds using a newly developed high-density genotyping array consisting of >170,000 evenly spaced SNPs. We first identify 44 genomic regions exhibiting extreme differentiation across multiple breeds. Genetic variation in these regions correlates with variation in several phenotypic traits that vary between breeds, and we identify novel associations with both morphological and behavioral traits. We next scan the genome for signatures of selective sweeps in single breeds, characterized by long regions of reduced heterozygosity and fixation of extended haplotypes. These scans identify hundreds of regions, including 22 blocks of homozygosity longer than one megabase in certain breeds. Candidate selection loci are strongly enriched for developmental genes. We chose one highly differentiated region, associated with body size and ear morphology, and characterized it using high-throughput sequencing to provide a list of variants that may directly affect these traits. This study provides a catalogue of genomic regions showing extreme reduction in genetic variation or population differentiation in dogs, including many linked to phenotypic variation. The many blocks of reduced haplotype diversity observed across the genome in dog breeds are the result of both selection and genetic drift, but extended blocks of homozygosity on a megabase scale appear to be best explained by selection. Further elucidation of the variants under selection will help to uncover the genetic basis of complex traits and disease.

The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes.

Science.gov (United States)

Clark, Samuel A; Hickey, John M; Daetwyler, Hans D; van der Werf, Julius H J

2012-02-09

The theory of genomic selection is based on the prediction of the effects of genetic markers in linkage disequilibrium with quantitative trait loci. However, genomic selection also relies on relationships between individuals to accurately predict genetic value. This study aimed to examine the importance of information on relatives versus that of unrelated or more distantly related individuals on the estimation of genomic breeding values. Simulated and real data were used to examine the effects of various degrees of relationship on the accuracy of genomic selection. Genomic Best Linear Unbiased Prediction (gBLUP) was compared to two pedigree based BLUP methods, one with a shallow one generation pedigree and the other with a deep ten generation pedigree. The accuracy of estimated breeding values for different groups of selection candidates that had varying degrees of relationships to a reference data set of 1750 animals was investigated. The gBLUP method predicted breeding values more accurately than BLUP. The most accurate breeding values were estimated using gBLUP for closely related animals. Similarly, the pedigree based BLUP methods were also accurate for closely related animals, however when the pedigree based BLUP methods were used to predict unrelated animals, the accuracy was close to zero. In contrast, gBLUP breeding values, for animals that had no pedigree relationship with animals in the reference data set, allowed substantial accuracy. An animal's relationship to the reference data set is an important factor for the accuracy of genomic predictions. Animals that share a close relationship to the reference data set had the highest accuracy from genomic predictions. However a baseline accuracy that is driven by the reference data set size and the overall population effective population size enables gBLUP to estimate a breeding value for unrelated animals within a population (breed), using information previously ignored by pedigree based BLUP methods.

Biotechnology and apple breeding in Japan

Science.gov (United States)

Igarashi, Megumi; Hatsuyama, Yoshimichi; Harada, Takeo; Fukasawa-Akada, Tomoko

2016-01-01

Apple is a fruit crop of significant economic importance, and breeders world wide continue to develop novel cultivars with improved characteristics. The lengthy juvenile period and the large field space required to grow apple populations have imposed major limitations on breeding. Various molecular biological techniques have been employed to make apple breeding easier. Transgenic technology has facilitated the development of apples with resistance to fungal or bacterial diseases, improved fruit quality, or root stocks with better rooting or dwarfing ability. DNA markers for disease resistance (scab, powdery mildew, fire-blight, Alternaria blotch) and fruit skin color have also been developed, and marker-assisted selection (MAS) has been employed in breeding programs. In the last decade, genomic sequences and chromosome maps of various cultivars have become available, allowing the development of large SNP arrays, enabling efficient QTL mapping and genomic selection (GS). In recent years, new technologies for genetic improvement, such as trans-grafting, virus vectors, and genome-editing, have emerged. Using these techniques, no foreign genes are present in the final product, and some of them show considerable promise for application to apple breeding. PMID:27069388

Whole-genome regression and prediction methods applied to plant and animal breeding

NARCIS (Netherlands)

Los Campos, De G.; Hickey, J.M.; Pong-Wong, R.; Daetwyler, H.D.; Calus, M.P.L.

2013-01-01

Genomic-enabled prediction is becoming increasingly important in animal and plant breeding, and is also receiving attention in human genetics. Deriving accurate predictions of complex traits requires implementing whole-genome regression (WGR) models where phenotypes are regressed on thousands of

Be-Breeder – an application for analysis of genomic data in plant breeding

Directory of Open Access Journals (Sweden)

Filipe Inácio Matias

2016-12-01

Full Text Available Be-Breeder is an application directed toward genetic breeding of plants, developed through the Shiny package of the R software, which allows different phenotype and molecular (marker analysis to be undertaken. The section for analysis of molecular data of the Be-Breeder application makes it possible to achieve quality control of genotyping data, to obtain genomic kinship matrices, and to analyze genomic selection, genome association, and genetic diversity in a simple manner on line. This application is available for use in a network through the site of the Allogamous Plant Breeding Laboratory of ESALQ-USP (http://www.genetica.esalq.usp.br/alogamas/R.html.

Genomic tools and and prospects for new breeding techniques in flower bulb crops

Science.gov (United States)

For many of the new breeding techniques, sequence information is of the utmost importance. In addition to current breeding techniques, such as marker-assisted selection (MAS) and genetic modification (GM), new breeding techniques such as zinc finger nucleases, oligonucleotide-mediated mutagenesis, R...

Possibilities for marker-assisted selection in aquaculture breeding schemes

International Nuclear Information System (INIS)

Sonesson, A.K.

2007-01-01

FAO estimates that there are around 200 species in aquaculture. However, only a few species have ongoing selective breeding programmes. Marker-assisted selection (MAS) is not used in any aquaculture breeding scheme today. The aim of this chapter, therefore, is to review briefly the current status of aquaculture breeding schemes and to evaluate the possibilities for MAS of aquaculture species. Genetic marker maps have been published for some species in culture. The marker density of these maps is, in general, rather low and the maps are composed of many amplified fragment length polymorphism (AFLP) markers anchored to few microsatellites. Some quantitative trait loci (QTL) have been identified for economically important traits, but they are not yet mapped at a high density. Computer simulations of within-family MAS schemes show a very high increase in genetic gain compared with conventional family-based breeding schemes, mainly due to the large family sizes that are typical for aquaculture breeding schemes. The use of genetic markers to identify individuals and their implications for breeding schemes with control of inbreeding are discussed. (author)

A two step Bayesian approach for genomic prediction of breeding values.

Science.gov (United States)

Shariati, Mohammad M; Sørensen, Peter; Janss, Luc

2012-05-21

In genomic models that assign an individual variance to each marker, the contribution of one marker to the posterior distribution of the marker variance is only one degree of freedom (df), which introduces many variance parameters with only little information per variance parameter. A better alternative could be to form clusters of markers with similar effects where markers in a cluster have a common variance. Therefore, the influence of each marker group of size p on the posterior distribution of the marker variances will be p df. The simulated data from the 15th QTL-MAS workshop were analyzed such that SNP markers were ranked based on their effects and markers with similar estimated effects were grouped together. In step 1, all markers with minor allele frequency more than 0.01 were included in a SNP-BLUP prediction model. In step 2, markers were ranked based on their estimated variance on the trait in step 1 and each 150 markers were assigned to one group with a common variance. In further analyses, subsets of 1500 and 450 markers with largest effects in step 2 were kept in the prediction model. Grouping markers outperformed SNP-BLUP model in terms of accuracy of predicted breeding values. However, the accuracies of predicted breeding values were lower than Bayesian methods with marker specific variances. Grouping markers is less flexible than allowing each marker to have a specific marker variance but, by grouping, the power to estimate marker variances increases. A prior knowledge of the genetic architecture of the trait is necessary for clustering markers and appropriate prior parameterization.

Expanding Possibilities for Intervention against Small Ruminant Lentiviruses through Genetic Marker-Assisted Selective Breeding

Directory of Open Access Journals (Sweden)

Donald P. Knowles

2013-06-01

Full Text Available Small ruminant lentiviruses include members that infect sheep (ovine lentivirus [OvLV]; also known as ovine progressive pneumonia virus/maedi-visna virus and goats (caprine arthritis encephalitis virus [CAEV]. Breed differences in seroprevalence and proviral concentration of OvLV had suggested a strong genetic component in susceptibility to infection by OvLV in sheep. A genetic marker test for susceptibility to OvLV has been developed recently based on the TMEM154 gene with validation data from over 2,800 sheep representing nine cohorts. While no single genotype has been shown to have complete resistance to OvLV, consistent association in thousands of sheep from multiple breeds and management conditions highlight a new strategy for intervention by selective breeding. This genetic marker-assisted selection (MAS has the potential to be a useful addition to existing viral control measures. Further, the discovery of multiple additional genomic regions associated with susceptibility to or control of OvLV suggests that additional genetic marker tests may be developed to extend the reach of MAS in the future. This review will cover the strengths and limitations of existing data from host genetics as an intervention and outline additional questions for future genetic research in sheep, goats, small ruminant lentiviruses, and their host-pathogen interactions.

Expanding Possibilities for Intervention against Small Ruminant Lentiviruses through Genetic Marker-Assisted Selective Breeding

Science.gov (United States)

White, Stephen N.; Knowles, Donald P.

2013-01-01

Small ruminant lentiviruses include members that infect sheep (ovine lentivirus [OvLV]; also known as ovine progressive pneumonia virus/maedi-visna virus) and goats (caprine arthritis encephalitis virus [CAEV]). Breed differences in seroprevalence and proviral concentration of OvLV had suggested a strong genetic component in susceptibility to infection by OvLV in sheep. A genetic marker test for susceptibility to OvLV has been developed recently based on the TMEM154 gene with validation data from over 2,800 sheep representing nine cohorts. While no single genotype has been shown to have complete resistance to OvLV, consistent association in thousands of sheep from multiple breeds and management conditions highlight a new strategy for intervention by selective breeding. This genetic marker-assisted selection (MAS) has the potential to be a useful addition to existing viral control measures. Further, the discovery of multiple additional genomic regions associated with susceptibility to or control of OvLV suggests that additional genetic marker tests may be developed to extend the reach of MAS in the future. This review will cover the strengths and limitations of existing data from host genetics as an intervention and outline additional questions for future genetic research in sheep, goats, small ruminant lentiviruses, and their host-pathogen interactions. PMID:23771240

Characterization of the complete mitochondrial genome of the king pigeon (Columba livia breed king).

Science.gov (United States)

Zhang, Rui-Hua; He, Wen-Xiao; Xu, Tong

2015-06-01

The king pigeon is a breed of pigeon developed over many years of selective breeding primarily as a utility breed. In the present work, we report the complete mitochondrial genome sequence of king pigeon for the first time. The total length of the mitogenome was 17,221 bp with the base composition of 30.14% for A, 24.05% for T, 31.82% for C, and 13.99% for G and an A-T (54.22 %)-rich feature was detected. It harbored 13 protein-coding genes, two ribosomal RNA genes, 22 transfer RNA genes, and one non-coding control region (D-loop region). The arrangement of all genes was identical to the typical mitochondrial genomes of pigeon. The complete mitochondrial genome sequence of king pigeon would serve as an important data set of the germplasm resources for further study.

The complete mitochondrial genome of the Jacobin pigeon (Columba livia breed Jacobin).

Science.gov (United States)

He, Wen-Xiao; Jia, Jin-Feng

2015-06-01

The Jacobin is a breed of fancy pigeon developed over many years of selective breeding that originated in Asia. In the present work, we report the complete mitochondrial genome sequence of Jacobin pigeon for the first time. The total length of the mitogenome was 17,245 bp with the base composition of 30.18% for A, 23.98% for T, 31.88% for C, and 13.96% for G and an A-T (54.17 %)-rich feature was detected. It harbored 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes and 1 non-coding control region. The arrangement of all genes was identical to the typical mitochondrial genomes of pigeon. The complete mitochondrial genome sequence of Jacobin pigeon would serve as an important data set of the germplasm resources for further study.

Whole-Genome Regression and Prediction Methods Applied to Plant and Animal Breeding

Science.gov (United States)

de los Campos, Gustavo; Hickey, John M.; Pong-Wong, Ricardo; Daetwyler, Hans D.; Calus, Mario P. L.

2013-01-01

Genomic-enabled prediction is becoming increasingly important in animal and plant breeding and is also receiving attention in human genetics. Deriving accurate predictions of complex traits requires implementing whole-genome regression (WGR) models where phenotypes are regressed on thousands of markers concurrently. Methods exist that allow implementing these large-p with small-n regressions, and genome-enabled selection (GS) is being implemented in several plant and animal breeding programs. The list of available methods is long, and the relationships between them have not been fully addressed. In this article we provide an overview of available methods for implementing parametric WGR models, discuss selected topics that emerge in applications, and present a general discussion of lessons learned from simulation and empirical data analysis in the last decade. PMID:22745228

Progress in the molecular and genetic modification breeding of beef cattle in China.

Science.gov (United States)

Tong, Bin; Zhang, Li; Li, Guang-Peng

2017-11-20

The studies of beef cattle breeding in China have been greatly improved with the rapid development of the international beef cattle industrialization. The beef cattle breeding technologies have rapidly transformed from traditional breeding to molecular marker-assisted breeding, genomic selection and genetic modification breeding. Hundreds of candidate genes and molecular markers associated with growth, meat quality, reproduction performance and diseases resistance have been identified, and some of them have already been used in cattle breeding. Genes and molecular markers associated with growth and development are focused on the growth hormone, muscle regulatory factors, myostatin and insulin-like growth factors. Meat quality is mediated by fatty acid transport and deposition related signals, calpains and calpain system, muscle regulatory factors and muscle growth regulation pathways. Reproduction performance is regulated by GnRH-FSH-LH, growth differentiation factor 9, prolactin receptor and forkhead box protein O1. Disease resistance is modulated by the major histocompatibility complex gene family, toll-like receptors, mannose-binding lectin and interferon gene signals. In this review, we summarize the most recent progress in beef cattle breeding in marker-assisted selection, genome-wide selection and genetic modification breeding, aiming to provide a reference for further genetic breeding research of beef cattle in China.

Accuracy of Genomic Prediction in a Commercial Perennial Ryegrass Breeding Program

Directory of Open Access Journals (Sweden)

Dario Fè

2016-11-01

Full Text Available The implementation of genomic selection (GS in plant breeding, so far, has been mainly evaluated in crops farmed as homogeneous varieties, and the results have been generally positive. Fewer results are available for species, such as forage grasses, that are grown as heterogenous families (developed from multiparent crosses in which the control of the genetic variation is far more complex. Here we test the potential for implementing GS in the breeding of perennial ryegrass ( L. using empirical data from a commercial forage breeding program. Biparental F and multiparental synthetic (SYN families of diploid perennial ryegrass were genotyped using genotyping-by-sequencing, and phenotypes for five different traits were analyzed. Genotypes were expressed as family allele frequencies, and phenotypes were recorded as family means. Different models for genomic prediction were compared by using practically relevant cross-validation strategies. All traits showed a highly significant level of genetic variance, which could be traced using the genotyping assay. While there was significant genotype × environment (G × E interaction for some traits, accuracies were high among F families and between biparental F and multiparental SYN families. We have demonstrated that the implementation of GS in grass breeding is now possible and presents an opportunity to make significant gains for various traits.

Arbitrarily amplified DNA: New molecular approaches to plant breeding, ecology and evolution

Energy Technology Data Exchange (ETDEWEB)

Caetano-Anolles, G [Department of Biology, University of Oslo, Oslo (Norway)

2001-11-01

Several DNA fingerprinting techniques that use arbitrary primers to characterize, scan and tag genomic DNA were optimized and used to study plants and microbial pathogens. The generated arbitrarily amplified DNA (AAD) profiles could be tailored in their complexity and polymorphic content, allowing analysis of closely related organisms, such as vegetatively-propagated horticultural crops or clonal fungal populations. AAD markers were used in cultivar and strain identification, map-based cloning, and marker-assisted breeding, sometimes as sequence-tagged sites. Phenetic analysis using parsimony, cluster, and numerical methods was applied successfully to the identification of genetic relationships in turfgrass species such as bermudagrass, woody plants such as dogwoods, and floricultural species such as petunia and chrysanthemum. AAD profiles were used to measure for the first time a genome-wide mutation rate, directly in a plant. Mutation rates in vegetatively propagated bermudagrass were comparable to those in human, mice, fruit flies, and worms. In combination with established tools used in molecular systematics (e.g. rDNA sequence analysis), AAD markers tracked the introduction of exotic dogwood anthracnose-causing fungi in North America. As part of a breeding effort to combat dogwood diseases, AAD was used in pseudo-testcross mapping of the tree at the intra-specific level. Markers were efficiently generated despite the close relatedness of parental dogwood material. Finally, DNA markers and tags were also generated in soybean, and were used to construct high density maps and walk towards defined genomic regions in the positional cloning of the supernodulation nts-1 symbiotic gene. (author)

Arbitrarily amplified DNA: New molecular approaches to plant breeding, ecology and evolution

International Nuclear Information System (INIS)

Caetano-Anolles, G.

2001-01-01

Several DNA fingerprinting techniques that use arbitrary primers to characterize, scan and tag genomic DNA were optimized and used to study plants and microbial pathogens. The generated arbitrarily amplified DNA (AAD) profiles could be tailored in their complexity and polymorphic content, allowing analysis of closely related organisms, such as vegetatively-propagated horticultural crops or clonal fungal populations. AAD markers were used in cultivar and strain identification, map-based cloning, and marker-assisted breeding, sometimes as sequence-tagged sites. Phenetic analysis using parsimony, cluster, and numerical methods was applied successfully to the identification of genetic relationships in turfgrass species such as bermudagrass, woody plants such as dogwoods, and floricultural species such as petunia and chrysanthemum. AAD profiles were used to measure for the first time a genome-wide mutation rate, directly in a plant. Mutation rates in vegetatively propagated bermudagrass were comparable to those in human, mice, fruit flies, and worms. In combination with established tools used in molecular systematics (e.g. rDNA sequence analysis), AAD markers tracked the introduction of exotic dogwood anthracnose-causing fungi in North America. As part of a breeding effort to combat dogwood diseases, AAD was used in pseudo-testcross mapping of the tree at the intra-specific level. Markers were efficiently generated despite the close relatedness of parental dogwood material. Finally, DNA markers and tags were also generated in soybean, and were used to construct high density maps and walk towards defined genomic regions in the positional cloning of the supernodulation nts-1 symbiotic gene. (author)

The complete mitochondrial genome of the ice pigeon (Columba livia breed ice).

Science.gov (United States)

Zhang, Rui-Hua; He, Wen-Xiao

2015-02-01

The ice pigeon is a breed of fancy pigeon developed over many years of selective breeding. In the present work, we report the complete mitochondrial genome sequence of ice pigeon for the first time. The total length of the mitogenome was 17,236 bp with the base composition of 30.2% for A, 24.0% for T, 31.9% for C, and 13.9% for G and an A-T (54.2 %)-rich feature was detected. It harbored 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes and 1 non-coding control region (D-loop region). The arrangement of all genes was identical to the typical mitochondrial genomes of pigeon. The complete mitochondrial genome sequence of ice pigeon would serve as an important data set of the germplasm resources for further study.

Assisted reproductive techniques for cattle breeding in developing countries: a critical appraisal of their value and limitations.

Science.gov (United States)

Rodriguez-Martinez, H

2012-01-01

Commercialization of animal biotechnologies, including those related to reproduction [also known as assisted reproductive techniques (ARTS)], is an increasing reality in developing countries, following the enormous flow of information around us and the increasing global commercial interests in areas where cattle production has its major assets. The present review discusses the achievements of various biotechnological tools for reproduction in cattle including semen handling for artificial insemination (AI), superovulation and embryo transfer (MOET), in vitro handling of oocytes and production of embryos, reproductive cloning and emerging technologies (sex selection, gene targeting and nuclear transfer for livestock transgenesis, genomics for marker-assisted selection, etc.). The application of these technologies for cattle breeding is critically discussed in relation to their impact in the improvement of the efficiency of dairy and beef production in developed and - particularly - in developing countries, which ultimately rule the possibilities of a competitive and sound production of food for human consumption. Despite the remarkable progress made and the punctual importance of some of the above-mentioned technologies, AI remains the most important assisted reproductive technology (ART) in developing countries. Any attempt to gain widespread of any other ART under the predominant economical conditions in developing countries ought to match the simplicity and the success of AI as a breeding tool. © 2012 Blackwell Verlag GmbH.

A fast EM algorithm for BayesA-like prediction of genomic breeding values.

Directory of Open Access Journals (Sweden)

Xiaochen Sun

Full Text Available Prediction accuracies of estimated breeding values for economically important traits are expected to benefit from genomic information. Single nucleotide polymorphism (SNP panels used in genomic prediction are increasing in density, but the Markov Chain Monte Carlo (MCMC estimation of SNP effects can be quite time consuming or slow to converge when a large number of SNPs are fitted simultaneously in a linear mixed model. Here we present an EM algorithm (termed "fastBayesA" without MCMC. This fastBayesA approach treats the variances of SNP effects as missing data and uses a joint posterior mode of effects compared to the commonly used BayesA which bases predictions on posterior means of effects. In each EM iteration, SNP effects are predicted as a linear combination of best linear unbiased predictions of breeding values from a mixed linear animal model that incorporates a weighted marker-based realized relationship matrix. Method fastBayesA converges after a few iterations to a joint posterior mode of SNP effects under the BayesA model. When applied to simulated quantitative traits with a range of genetic architectures, fastBayesA is shown to predict GEBV as accurately as BayesA but with less computing effort per SNP than BayesA. Method fastBayesA can be used as a computationally efficient substitute for BayesA, especially when an increasing number of markers bring unreasonable computational burden or slow convergence to MCMC approaches.

Analysis of Genome-Wide Copy Number Variations in Chinese Indigenous and Western Pig Breeds by 60 K SNP Genotyping Arrays

Science.gov (United States)

Sun, Yaqi; Wang, Hongyang; Wang, Chao; Yu, Shaobo; Liu, Jing; Zhang, Yu; Fan, Bin; Li, Kui; Liu, Bang

2014-01-01

Copy number variations (CNVs) represent a substantial source of structural variants in mammals and contribute to both normal phenotypic variability and disease susceptibility. Although low-resolution CNV maps are produced in many domestic animals, and several reports have been published about the CNVs of porcine genome, the differences between Chinese and western pigs still remain to be elucidated. In this study, we used Porcine SNP60 BeadChip and PennCNV algorithm to perform a genome-wide CNV detection in 302 individuals from six Chinese indigenous breeds (Tongcheng, Laiwu, Luchuan, Bama, Wuzhishan and Ningxiang pigs), three western breeds (Yorkshire, Landrace and Duroc) and one hybrid (Tongcheng×Duroc). A total of 348 CNV Regions (CNVRs) across genome were identified, covering 150.49 Mb of the pig genome or 6.14% of the autosomal genome sequence. In these CNVRs, 213 CNVRs were found to exist only in the six Chinese indigenous breeds, and 60 CNVRs only in the three western breeds. The characters of CNVs in four Chinese normal size breeds (Luchuan, Tongcheng and Laiwu pigs) and two minipig breeds (Bama and Wuzhishan pigs) were also analyzed in this study. Functional annotation suggested that these CNVRs possess a great variety of molecular function and may play important roles in phenotypic and production traits between Chinese and western breeds. Our results are important complementary to the CNV map in pig genome, which provide new information about the diversity of Chinese and western pig breeds, and facilitate further research on porcine genome CNVs. PMID:25198154

Factors affecting the accuracy of genomic selection for growth and wood quality traits in an advanced-breeding population of black spruce (Picea mariana).

Science.gov (United States)

Lenz, Patrick R N; Beaulieu, Jean; Mansfield, Shawn D; Clément, Sébastien; Desponts, Mireille; Bousquet, Jean

2017-04-28

Genomic selection (GS) uses information from genomic signatures consisting of thousands of genetic markers to predict complex traits. As such, GS represents a promising approach to accelerate tree breeding, which is especially relevant for the genetic improvement of boreal conifers characterized by long breeding cycles. In the present study, we tested GS in an advanced-breeding population of the boreal black spruce (Picea mariana [Mill.] BSP) for growth and wood quality traits, and concurrently examined factors affecting GS model accuracy. The study relied on 734 25-year-old trees belonging to 34 full-sib families derived from 27 parents and that were established on two contrasting sites. Genomic profiles were obtained from 4993 Single Nucleotide Polymorphisms (SNPs) representative of as many gene loci distributed among the 12 linkage groups common to spruce. GS models were obtained for four growth and wood traits. Validation using independent sets of trees showed that GS model accuracy was high, related to trait heritability and equivalent to that of conventional pedigree-based models. In forward selection, gains per unit of time were three times higher with the GS approach than with conventional selection. In addition, models were also accurate across sites, indicating little genotype-by-environment interaction in the area investigated. Using information from half-sibs instead of full-sibs led to a significant reduction in model accuracy, indicating that the inclusion of relatedness in the model contributed to its higher accuracies. About 500 to 1000 markers were sufficient to obtain GS model accuracy almost equivalent to that obtained with all markers, whether they were well spread across the genome or from a single linkage group, further confirming the implication of relatedness and potential long-range linkage disequilibrium (LD) in the high accuracy estimates obtained. Only slightly higher model accuracy was obtained when using marker subsets that were

Establishing the basis for Genomic Prediction in Perennial Ryegrass

DEFF Research Database (Denmark)

Fé, Dario

2015-01-01

Genomic Selection (GS) is a relatively new technology, which has already revolutionized animal breeding and which is expected to have a high impact on plant breeding. In contrast to traditional marker assisted breeding, which only focuses on specific genes. GS estimates the genetic value...

Be-Breeder - an application for analysis of genomic data in plant breeding

OpenAIRE

Matias,Filipe Inácio; Granato,Italo Stefanine Correa; Dequigiovanni,Gabriel; Fritsche-Neto,Roberto

2017-01-01

Abstract Be-Breeder is an application directed toward genetic breeding of plants, developed through the Shiny package of the R software, which allows different phenotype and molecular (marker) analysis to be undertaken. The section for analysis of molecular data of the Be-Breeder application makes it possible to achieve quality control of genotyping data, to obtain genomic kinship matrices, and to analyze genome selection, genome association, and genetic diversity in a simple manner on line. ...

Implementation of genomic prediction in Lolium perenne (L. breeding populations

Directory of Open Access Journals (Sweden)

Nastasiya F Grinberg

2016-02-01

Full Text Available Perennial ryegrass (Lolium perenne L. is one of the most widely grown forage grasses in temperate agriculture. In order to maintain and increase its usage as forage in livestock agriculture, there is a continued need for improvement in biomass yield, quality, disease resistance and seed yield. Genetic gain for traits such as biomass yield has been relatively modest. This has been attributed to its long breeding cycle, and the necessity to use population based breeding methods. Thanks to recent advances in genotyping techniques there is increasing interest in genomic selection from which genomically estimated breeding values (GEBV are derived. In this paper we compare the classical RRBLUP model with state-of-the-art machine learning (ML techniques that should yield themselves easily to use in GS and demonstrate their application to predicting quantitative traits in a breeding population of L. perenne. Prediction accuracies varied from 0 to 0.59 depending on trait, prediction model and composition of the training population. The BLUP model produced the highest prediction accuracies for most traits and training populations. Forage quality traits had the highest accuracies compared to yield related traits. There appeared to be no clear pattern to the effect of the training population composition on the prediction accuracies. The heritability of the forage quality traits was generally higher than for the yield related traits, and could partly explain the difference in accuracy. Some population structure was evident in the breeding populations, and probably contributed to the varying effects of training population on the predictions. The average linkage disequilibrium (LD between adjacent markers ranged from 0.121 to 0.215. Higher marker density and larger training population closely related with the test population are likely to improve the prediction accuracy.

Genetic Gain and Inbreeding from Genomic Selection in a Simulated Commercial Breeding Program for Perennial Ryegrass

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Zibei Lin

2016-03-01

Full Text Available Genomic selection (GS provides an attractive option for accelerating genetic gain in perennial ryegrass ( improvement given the long cycle times of most current breeding programs. The present study used simulation to investigate the level of genetic gain and inbreeding obtained from GS breeding strategies compared with traditional breeding strategies for key traits (persistency, yield, and flowering time. Base population genomes were simulated through random mating for 60,000 generations at an effective population size of 10,000. The degree of linkage disequilibrium (LD in the resulting population was compared with that obtained from empirical studies. Initial parental varieties were simulated to match diversity of current commercial cultivars. Genomic selection was designed to fit into a company breeding program at two selection points in the breeding cycle (spaced plants and miniplot. Genomic estimated breeding values (GEBVs for productivity traits were trained with phenotypes and genotypes from plots. Accuracy of GEBVs was 0.24 for persistency and 0.36 for yield for single plants, while for plots it was lower (0.17 and 0.19, respectively. Higher accuracy of GEBVs was obtained for flowering time (up to 0.7, partially as a result of the larger reference population size that was available from the clonal row stage. The availability of GEBVs permit a 4-yr reduction in cycle time, which led to at least a doubling and trebling genetic gain for persistency and yield, respectively, than the traditional program. However, a higher rate of inbreeding per cycle among varieties was also observed for the GS strategy.

Genetic Gain and Inbreeding from Genomic Selection in a Simulated Commercial Breeding Program for Perennial Ryegrass.

Science.gov (United States)

Lin, Zibei; Cogan, Noel O I; Pembleton, Luke W; Spangenberg, German C; Forster, John W; Hayes, Ben J; Daetwyler, Hans D

2016-03-01

Genomic selection (GS) provides an attractive option for accelerating genetic gain in perennial ryegrass () improvement given the long cycle times of most current breeding programs. The present study used simulation to investigate the level of genetic gain and inbreeding obtained from GS breeding strategies compared with traditional breeding strategies for key traits (persistency, yield, and flowering time). Base population genomes were simulated through random mating for 60,000 generations at an effective population size of 10,000. The degree of linkage disequilibrium (LD) in the resulting population was compared with that obtained from empirical studies. Initial parental varieties were simulated to match diversity of current commercial cultivars. Genomic selection was designed to fit into a company breeding program at two selection points in the breeding cycle (spaced plants and miniplot). Genomic estimated breeding values (GEBVs) for productivity traits were trained with phenotypes and genotypes from plots. Accuracy of GEBVs was 0.24 for persistency and 0.36 for yield for single plants, while for plots it was lower (0.17 and 0.19, respectively). Higher accuracy of GEBVs was obtained for flowering time (up to 0.7), partially as a result of the larger reference population size that was available from the clonal row stage. The availability of GEBVs permit a 4-yr reduction in cycle time, which led to at least a doubling and trebling genetic gain for persistency and yield, respectively, than the traditional program. However, a higher rate of inbreeding per cycle among varieties was also observed for the GS strategy. Copyright © 2016 Crop Science Society of America.

Genotyping cows for the reference increase reliability of genomic prediction in a small breed

DEFF Research Database (Denmark)

Thomasen, Jørn Rind; Sørensen, Anders Christian; Lund, Mogens Sandø

2013-01-01

We hypothesized that adding cows to the reference population in a breed with a small number of reference bulls would increase reliabilities of genomic breeding values and genetic gain. We tested this premise by comparing two strategies for maintaining the reference population for genetic gain......, inbreeding and reliabilities of genomic predictions: 1) Adding 60 progeny tested bulls each year (B), and 2) in addition to 60 progeny tested bulls, adding 2,000 genotyped cows per year (C). Two breeding schemes were tested: 1) A turbo scheme (T) with only genotyped young bulls used intensively, and 2...... compared to the H-B, at the same level of ∆F. T-C yielded 15% higher ∆G compared t o T-B. Changing the breeding scheme from H-B to H-C increased ∆G by 5.5%. The lowest ∆F was observed with genotyping of cows. Reliabilities of GEBV in the C schemes showed a steep increase in reliability during the first...

Genomic Footprints in Selected and Unselected Beef Cattle Breeds in Korea.

Directory of Open Access Journals (Sweden)

Dajeong Lim

Full Text Available Korean Hanwoo cattle have been subjected to intensive artificial selection over the past four decades to improve meat production traits. Another three cattle varieties very closely related to Hanwoo reside in Korea (Jeju Black and Brindle and in China (Yanbian. These breeds have not been part of a breeding scheme to improve production traits. Here, we compare the selected Hanwoo against these similar but presumed to be unselected populations to identify genomic regions that have been under recent selection pressure due to the breeding program. Rsb statistics were used to contrast the genomes of Hanwoo versus a pooled sample of the three unselected population (UN. We identified 37 significant SNPs (FDR corrected in the HW/UN comparison and 21 known protein coding genes were within 1 MB to the identified SNPs. These genes were previously reported to affect traits important for meat production (14 genes, reproduction including mammary gland development (3 genes, coat color (2 genes, and genes affecting behavioral traits in a broader sense (2 genes. We subsequently sequenced (Illumina HiSeq 2000 platform 10 individuals of the brown Hanwoo and the Chinese Yanbian to identify SNPs within the candidate genomic regions. Based on allele frequency differences, haplotype structures, and literature research, we singled out one non-synonymous SNP in the APP gene (APP: c.569C>T, Ala199Val and predicted the mutational effect on the protein structure. We found that protein-protein interactions might be impaired due to increased exposed hydrophobic surfaces of the mutated protein. The APP gene has also been reported to affect meat tenderness in pigs and obesity in humans. Meat tenderness has been linked to intramuscular fat content, which is one of the main breeding goals for brown Hanwoo, potentially supporting a causal influence of the herein described nsSNP in the APP gene.

Genomic Footprints in Selected and Unselected Beef Cattle Breeds in Korea.

Science.gov (United States)

Lim, Dajeong; Strucken, Eva M; Choi, Bong Hwan; Chai, Han Ha; Cho, Yong Min; Jang, Gul Won; Kim, Tae-Hun; Gondro, Cedric; Lee, Seung Hwan

2016-01-01

Korean Hanwoo cattle have been subjected to intensive artificial selection over the past four decades to improve meat production traits. Another three cattle varieties very closely related to Hanwoo reside in Korea (Jeju Black and Brindle) and in China (Yanbian). These breeds have not been part of a breeding scheme to improve production traits. Here, we compare the selected Hanwoo against these similar but presumed to be unselected populations to identify genomic regions that have been under recent selection pressure due to the breeding program. Rsb statistics were used to contrast the genomes of Hanwoo versus a pooled sample of the three unselected population (UN). We identified 37 significant SNPs (FDR corrected) in the HW/UN comparison and 21 known protein coding genes were within 1 MB to the identified SNPs. These genes were previously reported to affect traits important for meat production (14 genes), reproduction including mammary gland development (3 genes), coat color (2 genes), and genes affecting behavioral traits in a broader sense (2 genes). We subsequently sequenced (Illumina HiSeq 2000 platform) 10 individuals of the brown Hanwoo and the Chinese Yanbian to identify SNPs within the candidate genomic regions. Based on allele frequency differences, haplotype structures, and literature research, we singled out one non-synonymous SNP in the APP gene (APP: c.569C>T, Ala199Val) and predicted the mutational effect on the protein structure. We found that protein-protein interactions might be impaired due to increased exposed hydrophobic surfaces of the mutated protein. The APP gene has also been reported to affect meat tenderness in pigs and obesity in humans. Meat tenderness has been linked to intramuscular fat content, which is one of the main breeding goals for brown Hanwoo, potentially supporting a causal influence of the herein described nsSNP in the APP gene.

A genome wide survey of SNP variation reveals the genetic structure of sheep breeds.

Directory of Open Access Journals (Sweden)

James W Kijas

Full Text Available The genetic structure of sheep reflects their domestication and subsequent formation into discrete breeds. Understanding genetic structure is essential for achieving genetic improvement through genome-wide association studies, genomic selection and the dissection of quantitative traits. After identifying the first genome-wide set of SNP for sheep, we report on levels of genetic variability both within and between a diverse sample of ovine populations. Then, using cluster analysis and the partitioning of genetic variation, we demonstrate sheep are characterised by weak phylogeographic structure, overlapping genetic similarity and generally low differentiation which is consistent with their short evolutionary history. The degree of population substructure was, however, sufficient to cluster individuals based on geographic origin and known breed history. Specifically, African and Asian populations clustered separately from breeds of European origin sampled from Australia, New Zealand, Europe and North America. Furthermore, we demonstrate the presence of stratification within some, but not all, ovine breeds. The results emphasize that careful documentation of genetic structure will be an essential prerequisite when mapping the genetic basis of complex traits. Furthermore, the identification of a subset of SNP able to assign individuals into broad groupings demonstrates even a small panel of markers may be suitable for applications such as traceability.

Breeding Jatropha curcas by genomic selection: A pilot assessment of the accuracy of predictive models.

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Azevedo Peixoto, Leonardo de; Laviola, Bruno Galvêas; Alves, Alexandre Alonso; Rosado, Tatiana Barbosa; Bhering, Leonardo Lopes

2017-01-01

Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY) and the weight of 100 seeds (W100S) using restricted maximum likelihood (REML); to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.

Breeding Jatropha curcas by genomic selection: A pilot assessment of the accuracy of predictive models.

Directory of Open Access Journals (Sweden)

Leonardo de Azevedo Peixoto

Full Text Available Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY and the weight of 100 seeds (W100S using restricted maximum likelihood (REML; to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.

Applications of population genetics to animal breeding, from wright, fisher and lush to genomic prediction.

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Hill, William G

2014-01-01

Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives' performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher's infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with "genomic selection" is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas.

Harvesting Legume Genomes: Plant Genetic Resources

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Genomics and high through-put phenotyping are ushering in a new era of accessing genetic diversity held in plant genetic resources, the cornerstone of both traditional and genomics-assisted breeding efforts of food legume crops. Acknowledged or not, yield plateaus must be broken given the daunting ...

Whole genome sequencing of Gyeongbuk Araucana, a newly developed blue-egg laying chicken breed, reveals its origin and genetic characteristics.

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Jeong, Hyeonsoo; Kim, Kwondo; Caetano-Anollés, Kelsey; Kim, Heebal; Kim, Byung-Ki; Yi, Jun-Koo; Ha, Jae-Jung; Cho, Seoae; Oh, Dong Yep

2016-05-24

Chicken, Gallus gallus, is a valuable species both as a food source and as a model organism for scientific research. Here, we sequenced the genome of Gyeongbuk Araucana, a rare chicken breed with unique phenotypic characteristics including flight ability, large body size, and laying blue-shelled eggs, to identify its genomic features. We generated genomes of Gyeongbuk Araucana, Leghorn, and Korean Native Chicken at a total of 33.5, 35.82, and 33.23 coverage depth, respectively. Along with the genomes of 12 Chinese breeds, we identified genomic variants of 16.3 million SNVs and 2.3 million InDels in mapped regions. Additionally, through assembly of unmapped reads and selective sweep, we identified candidate genes that fall into heart, vasculature and muscle development and body growth categories, which provided insight into Gyeongbuk Araucana's phenotypic traits. Finally, genetic variation based on the transposable element insertion pattern was investigated to elucidate the features of transposable elements related to blue egg shell formation. This study presents results of the first genomic study on the Gyeongbuk Araucana breed; it has potential to serve as an invaluable resource for future research on the genomic characteristics of this chicken breed as well as others.

Persistence of accuracy of genomic estimated breeding values over generations in layer chickens

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Fernando Rohan

2011-06-01

Full Text Available Abstract Background The predictive ability of genomic estimated breeding values (GEBV originates both from associations between high-density markers and QTL (Quantitative Trait Loci and from pedigree information. Thus, GEBV are expected to provide more persistent accuracy over successive generations than breeding values estimated using pedigree-based methods. The objective of this study was to evaluate the accuracy of GEBV in a closed population of layer chickens and to quantify their persistence over five successive generations using marker or pedigree information. Methods The training data consisted of 16 traits and 777 genotyped animals from two generations of a brown-egg layer breeding line, 295 of which had individual phenotype records, while others had phenotypes on 2,738 non-genotyped relatives, or similar data accumulated over up to five generations. Validation data included phenotyped and genotyped birds from five subsequent generations (on average 306 birds/generation. Birds were genotyped for 23,356 segregating SNP. Animal models using genomic or pedigree relationship matrices and Bayesian model averaging methods were used for training analyses. Accuracy was evaluated as the correlation between EBV and phenotype in validation divided by the square root of trait heritability. Results Pedigree relationships in outbred populations are reduced by 50% at each meiosis, therefore accuracy is expected to decrease by the square root of 0.5 every generation, as observed for pedigree-based EBV (Estimated Breeding Values. In contrast the GEBV accuracy was more persistent, although the drop in accuracy was substantial in the first generation. Traits that were considered to be influenced by fewer QTL and to have a higher heritability maintained a higher GEBV accuracy over generations. In conclusion, GEBV capture information beyond pedigree relationships, but retraining every generation is recommended for genomic selection in closed breeding

Updates to the Cool Season Food Legume Genome Database: Resources for pea, lentil, faba bean and chickpea genetics, genomics and breeding

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The Cool Season Food Legume Genome database (CSFL, www.coolseasonfoodlegume.org) is an online resource for genomics, genetics, and breeding research for chickpea, lentil,pea, and faba bean. The user-friendly and curated website allows for all publicly available map,marker,trait, gene,transcript, ger...

Pea (Pisum sativum L. in the Genomic Era

Directory of Open Access Journals (Sweden)

Robert J. Redden

2012-04-01

Full Text Available Pea (Pisum sativum L. was the original model organism used in Mendel’s discovery (1866 of the laws of inheritance, making it the foundation of modern plant genetics. However, subsequent progress in pea genomics has lagged behind many other plant species. Although the size and repetitive nature of the pea genome has so far restricted its sequencing, comprehensive genomic and post genomic resources already exist. These include BAC libraries, several types of molecular marker sets, both transcriptome and proteome datasets and mutant populations for reverse genetics. The availability of the full genome sequences of three legume species has offered significant opportunities for genome wide comparison revealing synteny and co-linearity to pea. A combination of a candidate gene and colinearity approach has successfully led to the identification of genes underlying agronomically important traits including virus resistances and plant architecture. Some of this knowledge has already been applied to marker assisted selection (MAS programs, increasing precision and shortening the breeding cycle. Yet, complete translation of marker discovery to pea breeding is still to be achieved. Molecular analysis of pea collections has shown that although substantial variation is present within the cultivated genepool, wild material offers the possibility to incorporate novel traits that may have been inadvertently eliminated. Association mapping analysis of diverse pea germplasm promises to identify genetic variation related to desirable agronomic traits, which are historically difficult to breed for in a traditional manner. The availability of high throughput ‘omics’ methodologies offers great promise for the development of novel, highly accurate selective breeding tools for improved pea genotypes that are sustainable under current and future climates and farming systems.

Genome-wide scan for visceral leishmaniasis in mixed-breed dogs identifies candidate genes involved in T helper cells and macrophage signaling

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We conducted a genome-wide scan for visceral leishmaniasis in mixed-breed dogs from a highly endemic area in Brazil using 149,648 single nucleotide polymorphism (SNP) markers genotyped in 20 cases and 28 controls. Using a mixed model approach, we found two candidate loci on canine autosomes 1 and 2....

Commonalities in Development of Pure Breeds and Population Isolates Revealed in the Genome of the Sardinian Fonni's Dog

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Dreger, Dayna L.; Davis, Brian W.; Cocco, Raffaella; Sechi, Sara; Di Cerbo, Alessandro; Parker, Heidi G.; Polli, Michele; Marelli, Stefano P.; Crepaldi, Paola; Ostrander, Elaine A.

2016-01-01

The island inhabitants of Sardinia have long been a focus for studies of complex human traits due to their unique ancestral background and population isolation reflecting geographic and cultural restriction. Population isolates share decreased genomic diversity, increased linkage disequilibrium, and increased inbreeding coefficients. In many regions, dogs and humans have been exposed to the same natural and artificial forces of environment, growth, and migration. Distinct dog breeds have arisen through human-driven selection of characteristics to meet an ideal standard of appearance and function. The Fonni’s Dog, an endemic dog population on Sardinia, has not been subjected to an intensive system of artificial selection, but rather has developed alongside the human population of Sardinia, influenced by geographic isolation and unregulated selection based on its environmental adaptation and aptitude for owner-desired behaviors. Through analysis of 28 dog breeds, represented with whole-genome sequences from 13 dogs and ∼170,000 genome-wide single nucleotide variants from 155 dogs, we have produced a genomic illustration of the Fonni’s Dog. Genomic patterns confirm within-breed similarity, while population and demographic analyses provide spatial identity of Fonni’s Dog to other Mediterranean breeds. Investigation of admixture and fixation indices reveals insights into the involvement of Fonni’s Dogs in breed development throughout the Mediterranean. We describe how characteristics of population isolates are reflected in dog breeds that have undergone artificial selection, and are mirrored in the Fonni’s Dog through traditional isolating factors that affect human populations. Lastly, we show that the genetic history of Fonni’s Dog parallels demographic events in local human populations. PMID:27519604

Breeding schemes for the implementation of genomic selection in wheat (Triticum spp.).

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Bassi, Filippo M; Bentley, Alison R; Charmet, Gilles; Ortiz, Rodomiro; Crossa, Jose

2016-01-01

In the last decade the breeding technology referred to as 'genomic selection' (GS) has been implemented in a variety of species, with particular success in animal breeding. Recent research shows the potential of GS to reshape wheat breeding. Many authors have concluded that the estimated genetic gain per year applying GS is several times that of conventional breeding. GS is, however, a new technology for wheat breeding and many programs worldwide are still struggling to identify the best strategy for its implementation. This article provides practical guidelines on the key considerations when implementing GS. A review of the existing GS literature for a range of species is provided and used to prime breeder-oriented considerations on the practical applications of GS. Furthermore, this article discusses potential breeding schemes for GS, genotyping considerations, and methods for effective training population design. The components of selection intensity, progress toward inbreeding in half- or full-sibs recurrent schemes, and the generation of selection are also presented. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

A computational approach to animal breeding.

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Berger-Wolf, Tanya Y; Moore, Cristopher; Saia, Jared

2007-02-07

We propose a computational model of mating strategies for controlled animal breeding programs. A mating strategy in a controlled breeding program is a heuristic with some optimization criteria as a goal. Thus, it is appropriate to use the computational tools available for analysis of optimization heuristics. In this paper, we propose the first discrete model of the controlled animal breeding problem and analyse heuristics for two possible objectives: (1) breeding for maximum diversity and (2) breeding a target individual. These two goals are representative of conservation biology and agricultural livestock management, respectively. We evaluate several mating strategies and provide upper and lower bounds for the expected number of matings. While the population parameters may vary and can change the actual number of matings for a particular strategy, the order of magnitude of the number of expected matings and the relative competitiveness of the mating heuristics remains the same. Thus, our simple discrete model of the animal breeding problem provides a novel viable and robust approach to designing and comparing breeding strategies in captive populations.

Genomic prediction in early selection stages using multi-year data in a hybrid rye breeding program.

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Bernal-Vasquez, Angela-Maria; Gordillo, Andres; Schmidt, Malthe; Piepho, Hans-Peter

2017-05-31

The use of multiple genetic backgrounds across years is appealing for genomic prediction (GP) because past years' data provide valuable information on marker effects. Nonetheless, single-year GP models are less complex and computationally less demanding than multi-year GP models. In devising a suitable analysis strategy for multi-year data, we may exploit the fact that even if there is no replication of genotypes across years, there is plenty of replication at the level of marker loci. Our principal aim was to evaluate different GP approaches to simultaneously model genotype-by-year (GY) effects and breeding values using multi-year data in terms of predictive ability. The models were evaluated under different scenarios reflecting common practice in plant breeding programs, such as different degrees of relatedness between training and validation sets, and using a selected fraction of genotypes in the training set. We used empirical grain yield data of a rye hybrid breeding program. A detailed description of the prediction approaches highlighting the use of kinship for modeling GY is presented. Using the kinship to model GY was advantageous in particular for datasets disconnected across years. On average, predictive abilities were 5% higher for models using kinship to model GY over models without kinship. We confirmed that using data from multiple selection stages provides valuable GY information and helps increasing predictive ability. This increase is on average 30% higher when the predicted genotypes are closely related with the genotypes in the training set. A selection of top-yielding genotypes together with the use of kinship to model GY improves the predictive ability in datasets composed of single years of several selection cycles. Our results clearly demonstrate that the use of multi-year data and appropriate modeling is beneficial for GP because it allows dissecting GY effects from genomic estimated breeding values. The model choice, as well as ensuring

Twenty years of artificial directional selection have shaped the genome of the Italian Large White pig breed.

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Schiavo, G; Galimberti, G; Calò, D G; Samorè, A B; Bertolini, F; Russo, V; Gallo, M; Buttazzoni, L; Fontanesi, L

2016-04-01

In this study, we investigated at the genome-wide level if 20 years of artificial directional selection based on boar genetic evaluation obtained with a classical BLUP animal model shaped the genome of the Italian Large White pig breed. The most influential boars of this breed (n = 192), born from 1992 (the beginning of the selection program of this breed) to 2012, with an estimated breeding value reliability of >0.85, were genotyped with the Illumina Porcine SNP60 BeadChip. After grouping the boars in eight classes according to their year of birth, filtered single nucleotide polymorphisms (SNPs) were used to evaluate the effects of time on genotype frequency changes using multinomial logistic regression models. Of these markers, 493 had a PBonferroni  selection program. The obtained results indicated that the genome of the Italian Large White pigs was shaped by a directional selection program derived by the application of methodologies assuming the infinitesimal model that captured a continuous trend of allele frequency changes in the boar population. © 2015 Stichting International Foundation for Animal Genetics.

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation.

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Saatchi, Mahdi; McClure, Mathew C; McKay, Stephanie D; Rolf, Megan M; Kim, JaeWoo; Decker, Jared E; Taxis, Tasia M; Chapple, Richard H; Ramey, Holly R; Northcutt, Sally L; Bauck, Stewart; Woodward, Brent; Dekkers, Jack C M; Fernando, Rohan L; Schnabel, Robert D; Garrick, Dorian J; Taylor, Jeremy F

2011-11-28

Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction. Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values. Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied. These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but

Influence of model specifications on the reliabilities of genomic prediction in a Swedish-Finnish red breed cattle population

DEFF Research Database (Denmark)

Rius-Vilarrasa, E; Strandberg, E; Fikse, W F

2012-01-01

Using a combined multi-breed reference population, this study explored the influence of model specification and the effect of including a polygenic effect on the reliability of genomic breeding values (DGV and GEBV). The combined reference population consisted of 2986 Swedish Red Breed (SRB) and ...

Transgenesis and genomics in molecular breeding of pasture grasses and legumes for forage quality and other traits

International Nuclear Information System (INIS)

Spangenberg, G.

2005-01-01

Significant advances in the establishment of the methodologies required for the molecular breeding of temperate forage grasses (Lolium and Festuca species) and legumes (Trifolium and Medicago species) are reviewed. Examples of current products and approaches for the application of these methodologies to forage grass and legume improvement are outlined. The plethora of new technologies and tools now available for high-throughput gene discovery and genome-wide expression analysis have opened up opportunities for innovative applications in the identification, functional characterization and use of genes of value in forage production systems and beyond. Selected examples of current work in pasture plant genomics, xenogenomics, symbiogenomics and micro-array-based molecular phenotyping are discussed. (author)

Whole-Genome Analyses of Korean Native and Holstein Cattle Breeds by Massively Parallel Sequencing

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Stothard, Paul; Chung, Won-Hyong; Jeon, Heoyn-Jeong; Miller, Stephen P.; Choi, So-Young; Lee, Jeong-Koo; Yang, Bokyoung; Lee, Kyung-Tai; Han, Kwang-Jin; Kim, Hyeong-Cheol; Jeong, Dongkee; Oh, Jae-Don; Kim, Namshin; Kim, Tae-Hun; Lee, Hak-Kyo; Lee, Sung-Jin

2014-01-01

A main goal of cattle genomics is to identify DNA differences that account for variations in economically important traits. In this study, we performed whole-genome analyses of three important cattle breeds in Korea—Hanwoo, Jeju Heugu, and Korean Holstein—using the Illumina HiSeq 2000 sequencing platform. We achieved 25.5-, 29.6-, and 29.5-fold coverage of the Hanwoo, Jeju Heugu, and Korean Holstein genomes, respectively, and identified a total of 10.4 million single nucleotide polymorphisms (SNPs), of which 54.12% were found to be novel. We also detected 1,063,267 insertions–deletions (InDels) across the genomes (78.92% novel). Annotations of the datasets identified a total of 31,503 nonsynonymous SNPs and 859 frameshift InDels that could affect phenotypic variations in traits of interest. Furthermore, genome-wide copy number variation regions (CNVRs) were detected by comparing the Hanwoo, Jeju Heugu, and previously published Chikso genomes against that of Korean Holstein. A total of 992, 284, and 1881 CNVRs, respectively, were detected throughout the genome. Moreover, 53, 65, 45, and 82 putative regions of homozygosity (ROH) were identified in Hanwoo, Jeju Heugu, Chikso, and Korean Holstein respectively. The results of this study provide a valuable foundation for further investigations to dissect the molecular mechanisms underlying variation in economically important traits in cattle and to develop genetic markers for use in cattle breeding. PMID:24992012

Accuracy and responses of genomic selection on key traits in apple breeding

NARCIS (Netherlands)

Muranty, Hélène; Troggio, Michela; Sadok, Ben Inès; Rifaï, Al Mehdi; Auwerkerken, Annemarie; Banchi, E.; Velasco, Riccardo; Stevanato, P.; Weg, van de W.E.; Guardo, Di M.; Kumar, S.; Laurens, François; Bink, M.C.A.M.

2015-01-01

The application of genomic selection in fruit tree crops is expected to enhance breeding efficiency by increasing prediction accuracy, increasing selection intensity and decreasing generation interval. The objectives of this study were to assess the accuracy of prediction and selection response in

Mitochondrial genome sequence of Egyptian swift Rock Pigeon (Columba livia breed Egyptian swift).

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Li, Chun-Hong; Shi, Wei; Shi, Wan-Yu

2015-06-01

The Egyptian swift Rock Pigeon is a breed of fancy pigeon developed over many years of selective breeding. In this work, we report the complete mitochondrial genome sequence of Egyptian swift Rock Pigeon. The total length of the mitogenome was 17,239 bp and its overall base composition was estimated to be 30.2% for A, 24.0% for T, 31.9% for C and 13.9% for G, indicating an A-T (54.2%)-rich feature in the mitogenome. It contained the typical structure of 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes and a non-coding control region (D-loop region). The complete mitochondrial genome sequence of Egyptian swift Rock Pigeon would serve as an important data set of the germplasm resources for further study.

Genome-association analysis of Korean Holstein milk traits using genomic estimated breeding value

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Donghyun Shin

2017-03-01

Full Text Available Objective Holsteins are known as the world’s highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein using Korean Holstein data. Methods This study was performed using single nucleotide polymorphism (SNP chip data (Illumina BovineSNP50 Beadchip of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits. Results We identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein. Conclusion This study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins.

A Ranking Approach to Genomic Selection.

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Blondel, Mathieu; Onogi, Akio; Iwata, Hiroyoshi; Ueda, Naonori

2015-01-01

Genomic selection (GS) is a recent selective breeding method which uses predictive models based on whole-genome molecular markers. Until now, existing studies formulated GS as the problem of modeling an individual's breeding value for a particular trait of interest, i.e., as a regression problem. To assess predictive accuracy of the model, the Pearson correlation between observed and predicted trait values was used. In this paper, we propose to formulate GS as the problem of ranking individuals according to their breeding value. Our proposed framework allows us to employ machine learning methods for ranking which had previously not been considered in the GS literature. To assess ranking accuracy of a model, we introduce a new measure originating from the information retrieval literature called normalized discounted cumulative gain (NDCG). NDCG rewards more strongly models which assign a high rank to individuals with high breeding value. Therefore, NDCG reflects a prerequisite objective in selective breeding: accurate selection of individuals with high breeding value. We conducted a comparison of 10 existing regression methods and 3 new ranking methods on 6 datasets, consisting of 4 plant species and 25 traits. Our experimental results suggest that tree-based ensemble methods including McRank, Random Forests and Gradient Boosting Regression Trees achieve excellent ranking accuracy. RKHS regression and RankSVM also achieve good accuracy when used with an RBF kernel. Traditional regression methods such as Bayesian lasso, wBSR and BayesC were found less suitable for ranking. Pearson correlation was found to correlate poorly with NDCG. Our study suggests two important messages. First, ranking methods are a promising research direction in GS. Second, NDCG can be a useful evaluation measure for GS.

Biotechnology in maize breeding

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Mladenović-Drinić Snežana

2004-01-01

Full Text Available Maize is one of the most important economic crops and the best studied and most tractable genetic system among monocots. The development of biotechnology has led to a great increase in our knowledge of maize genetics and understanding of the structure and behaviour of maize genomes. Conventional breeding practices can now be complemented by a number of new and powerful techniques. Some of these often referred to as molecular methods, enable scientists to see the layout of the entire genome of any organism and to select plants with preferred characteristics by "reading" at the molecular level, saving precious time and resources. DNA markers have provided valuable tools in various analyses ranging from phylogenetic analysis to the positional cloning of genes. Application of molecular markers for genetic studies of maize include: assessment of genetic variability and characterization of germ plasm, identification and fingerprinting of genotypes, estimation of genetic distance, detection of monogamic and quantitative trait loci, marker assisted selection, identification of sequence of useful candidate genes, etc. The development of high-density molecular maps which has been facilitated by PCR-based markers, have made the mapping and tagging of almost any trait possible and serve as bases for marker assisted selection. Sequencing of maize genomes would help to elucidate gene function, gene regulation and their expression. Modern biotechnology also includes an array of tools for introducing or deieting a particular gene or genes to produce plants with novel traits. Development of informatics and biotechnology are resulted in bioinformatic as well as in expansion of microarrey technique. Modern biotechnologies could complement and improve the efficiency of traditional selection and breeding techniques to enhance agricultural productivity.

Comparative regulatory approaches for groups of new plant breeding techniques.

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Lusser, Maria; Davies, Howard V

2013-06-25

This manuscript provides insights into ongoing debates on the regulatory issues surrounding groups of biotechnology-driven 'New Plant Breeding Techniques' (NPBTs). It presents the outcomes of preliminary discussions and in some cases the initial decisions taken by regulators in the following countries: Argentina, Australia, Canada, EU, Japan, South Africa and USA. In the light of these discussions we suggest in this manuscript a structured approach to make the evaluation more consistent and efficient. The issue appears to be complex as these groups of new technologies vary widely in both the technologies deployed and their impact on heritable changes in the plant genome. An added complication is that the legislation, definitions and regulatory approaches for biotechnology-derived crops differ significantly between these countries. There are therefore concerns that this situation will lead to non-harmonised regulatory approaches and asynchronous development and marketing of such crops resulting in trade disruptions. Copyright © 2013 Elsevier B.V. All rights reserved.

Marker-assisted selection in Eucalyptus

International Nuclear Information System (INIS)

Grattapaglia, D.

2007-01-01

Planted Eucalyptus occupies globally more than 18 million hectares and has become the most widely planted hardwood tree in the world, supplying high-quality woody biomass for several industrial applications. In this chapter an overview is presented on the status and perspectives of marker-assisted selection (MAS) in species of Eucalyptus. After an introduction to the main features of modern eucalypt breeding and clonal forestry, some applications of molecular markers in support to operational breeding are presented. By reviewing the status of quantitative trait locus (QTL) mapping in Eucalyptus, the challenges and some realistic prospects for the application of MAS to improve relevant traits are outlined. With the expected availability of more powerful genomic tools, including a draft of the Eucalyptus genome, the main challenges in implementing MAS will be in phenotyping trees accurately, analysing the overwhelming amount of genomic data available and translating this into truly useful molecular tools for breeding. (author)

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation

Directory of Open Access Journals (Sweden)

Saatchi Mahdi

2011-11-01

Full Text Available Abstract Background Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction. Methods Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values. Results Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied. Conclusions These results suggest that genomic estimates

Genomic selection: genome-wide prediction in plant improvement.

Science.gov (United States)

Desta, Zeratsion Abera; Ortiz, Rodomiro

2014-09-01

Association analysis is used to measure relations between markers and quantitative trait loci (QTL). Their estimation ignores genes with small effects that trigger underpinning quantitative traits. By contrast, genome-wide selection estimates marker effects across the whole genome on the target population based on a prediction model developed in the training population (TP). Whole-genome prediction models estimate all marker effects in all loci and capture small QTL effects. Here, we review several genomic selection (GS) models with respect to both the prediction accuracy and genetic gain from selection. Phenotypic selection or marker-assisted breeding protocols can be replaced by selection, based on whole-genome predictions in which phenotyping updates the model to build up the prediction accuracy. Copyright © 2014 Elsevier Ltd. All rights reserved.

Prediction of malting quality traits in barley based on genome-wide marker data to assess the potential of genomic selection.

Science.gov (United States)

Schmidt, Malthe; Kollers, Sonja; Maasberg-Prelle, Anja; Großer, Jörg; Schinkel, Burkhard; Tomerius, Alexandra; Graner, Andreas; Korzun, Viktor

2016-02-01

Genomic prediction of malting quality traits in barley shows the potential of applying genomic selection to improve selection for malting quality and speed up the breeding process. Genomic selection has been applied to various plant species, mostly for yield or yield-related traits such as grain dry matter yield or thousand kernel weight, and improvement of resistances against diseases. Quality traits have not been the main scope of analysis for genomic selection, but have rather been addressed by marker-assisted selection. In this study, the potential to apply genomic selection to twelve malting quality traits in two commercial breeding programs of spring and winter barley (Hordeum vulgare L.) was assessed. Phenotypic means were calculated combining multilocational field trial data from 3 or 4 years, depending on the trait investigated. Three to five locations were available in each of these years. Heritabilities for malting traits ranged between 0.50 and 0.98. Predictive abilities (PA), as derived from cross validation, ranged between 0.14 to 0.58 for spring barley and 0.40-0.80 for winter barley. Small training sets were shown to be sufficient to obtain useful PAs, possibly due to the narrow genetic base in this breeding material. Deployment of genomic selection in malting barley breeding clearly has the potential to reduce cost intensive phenotyping for quality traits, increase selection intensity and to shorten breeding cycles.

Genomic prediction in a breeding program of perennial ryegrass

DEFF Research Database (Denmark)

Fé, Dario; Ashraf, Bilal; Greve-Pedersen, Morten

2015-01-01

We present a genomic selection study performed on 1918 rye grass families (Lolium perenne L.), which were derived from a commercial breeding program at DLF-Trifolium, Denmark. Phenotypes were recorded on standard plots, across 13 years and in 6 different countries. Variants were identified...... this set. Estimated Breeding Value and prediction accuracies were calculated trough two different cross-validation schemes: (i) k-fold (k=10); (ii) leaving out one parent combination at the time, in order to test for accuracy of predicting new families. Accuracies ranged between 0.56 and 0.97 for scheme (i....... A larger set of 1791 F2s were used as training set to predict EBVs of 127 synthetic families (originated from poly-crosses between 5-11 single plants) for heading date and crown rust resistance. Prediction accuracies were 0.93 and 0.57 respectively. Results clearly demonstrate considerable potential...

Whole-genome sequencing reveals mutational landscape underlying phenotypic differences between two widespread Chinese cattle breeds.

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Yao Xu

Full Text Available Whole-genome sequencing provides a powerful tool to obtain more genetic variability that could produce a range of benefits for cattle breeding industry. Nanyang (Bos indicus and Qinchuan (Bos taurus are two important Chinese indigenous cattle breeds with distinct phenotypes. To identify the genetic characteristics responsible for variation in phenotypes between the two breeds, in the present study, we for the first time sequenced the genomes of four Nanyang and four Qinchuan cattle with 10 to 12 fold on average of 97.86% and 98.98% coverage of genomes, respectively. Comparison with the Bos_taurus_UMD_3.1 reference assembly yielded 9,010,096 SNPs for Nanyang, and 6,965,062 for Qinchuan cattle, 51% and 29% of which were novel SNPs, respectively. A total of 154,934 and 115,032 small indels (1 to 3 bp were found in the Nanyang and Qinchuan genomes, respectively. The SNP and indel distribution revealed that Nanyang showed a genetically high diversity as compared to Qinchuan cattle. Furthermore, a total of 2,907 putative cases of copy number variation (CNV were identified by aligning Nanyang to Qinchuan genome, 783 of which (27% encompassed the coding regions of 495 functional genes. The gene ontology (GO analysis revealed that many CNV genes were enriched in the immune system and environment adaptability. Among several CNV genes related to lipid transport and fat metabolism, Lepin receptor gene (LEPR overlapping with CNV_1815 showed remarkably higher copy number in Qinchuan than Nanyang (log2 (ratio = -2.34988; P value = 1.53E-102. Further qPCR and association analysis investigated that the copy number of the LEPR gene presented positive correlations with transcriptional expression and phenotypic traits, suggesting the LEPR CNV may contribute to the higher fat deposition in muscles of Qinchuan cattle. Our findings provide evidence that the distinct phenotypes of Nanyang and Qinchuan breeds may be due to the different genetic variations including SNPs

Current Knowledge in lentil genomics and its application for crop improvement

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Shiv eKumar

2015-02-01

Full Text Available Most of the lentil growing countries face a certain set of abiotic and biotic stresses causing substantial reduction in crop growth, yield, and production. Until-to date, lentil breeders have used conventional plant breeding techniques of selection-recombination-selection cycle to develop improved cultivars. These techniques have been successful in mainstreaming some of the easy-to-manage monogenic traits. However in case of complex quantitative traits, these conventional techniques are less precise. As most of the economic traits are complex, quantitative and often influenced by environments and genotype-environment (GE interaction, the genetic improvement of these traits becomes difficult. Genomics assisted breeding is relatively powerful and fast approach to develop high yielding varieties more suitable to adverse environmental conditions. New tools such as molecular markers and bioinformatics are expected to generate new knowledge and improve our understanding on the genetics of complex traits. In the past, the limited availability of genomic resources in lentil could not allow breeders to employ these tools in mainstream breeding program. The recent application of the Next Generation Sequencing (NGS and Genotyping by sequencing (GBS technologies has facilitated to speed up the lentil genome sequencing project and large discovery of genome-wide SNP markers. Recently, several linkage maps have been developed in lentil through the use of Expressed Sequenced Tag (EST-derived Simple Sequence Repeat (SSR and Single Nucleotide Polymorphism (SNP markers. These maps have emerged as useful genomic resources to identify QTL imparting tolerance to biotic and abiotic stresses in lentil. In this review, the current knowledge on available genomic resources and its application in lentil breeding program are discussed.

Population genomic structure and linkage disequilibrium analysis of South African goat breeds using genome-wide SNP data.

Science.gov (United States)

Mdladla, K; Dzomba, E F; Huson, H J; Muchadeyi, F C

2016-08-01

The sustainability of goat farming in marginal areas of southern Africa depends on local breeds that are adapted to specific agro-ecological conditions. Unimproved non-descript goats are the main genetic resources used for the development of commercial meat-type breeds of South Africa. Little is known about genetic diversity and the genetics of adaptation of these indigenous goat populations. This study investigated the genetic diversity, population structure and breed relations, linkage disequilibrium, effective population size and persistence of gametic phase in goat populations of South Africa. Three locally developed meat-type breeds of the Boer (n = 33), Savanna (n = 31), Kalahari Red (n = 40), a feral breed of Tankwa (n = 25) and unimproved non-descript village ecotypes (n = 110) from four goat-producing provinces of the Eastern Cape, KwaZulu-Natal, Limpopo and North West were assessed using the Illumina Goat 50K SNP Bead Chip assay. The proportion of SNPs with minor allele frequencies >0.05 ranged from 84.22% in the Tankwa to 97.58% in the Xhosa ecotype, with a mean of 0.32 ± 0.13 across populations. Principal components analysis, admixture and pairwise FST identified Tankwa as a genetically distinct population and supported clustering of the populations according to their historical origins. Genome-wide FST identified 101 markers potentially under positive selection in the Tankwa. Average linkage disequilibrium was highest in the Tankwa (r(2)  = 0.25 ± 0.26) and lowest in the village ecotypes (r(2) range = 0.09 ± 0.12 to 0.11 ± 0.14). We observed an effective population size of 100 kb with the exception of those in Savanna and Tswana populations. This study highlights the high level of genetic diversity in South African indigenous goats as well as the utility of the genome-wide SNP marker panels in genetic studies of these populations. © 2016 Stichting International Foundation for Animal Genetics.

Genome-Wide Association Studies In Plant Pathosystems: Toward an Ecological Genomics Approach

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Claudia Bartoli

2017-05-01

Full Text Available The emergence and re-emergence of plant pathogenic microorganisms are processes that imply perturbations in both host and pathogen ecological niches. Global change is largely assumed to drive the emergence of new etiological agents by altering the equilibrium of the ecological habitats which in turn places hosts more in contact with pathogen reservoirs. In this context, the number of epidemics is expected to increase dramatically in the next coming decades both in wild and crop plants. Under these considerations, the identification of the genetic variants underlying natural variation of resistance is a pre-requisite to estimate the adaptive potential of wild plant populations and to develop new breeding resistant cultivars. On the other hand, the prediction of pathogen's genetic determinants underlying disease emergence can help to identify plant resistance alleles. In the genomic era, whole genome sequencing combined with the development of statistical methods led to the emergence of Genome Wide Association (GWA mapping, a powerful tool for detecting genomic regions associated with natural variation of disease resistance in both wild and cultivated plants. However, GWA mapping has been less employed for the detection of genetic variants associated with pathogenicity in microbes. Here, we reviewed GWA studies performed either in plants or in pathogenic microorganisms (bacteria, fungi and oomycetes. In addition, we highlighted the benefits and caveats of the emerging joint GWA mapping approach that allows for the simultaneous identification of genes interacting between genomes of both partners. Finally, based on co-evolutionary processes in wild populations, we highlighted a phenotyping-free joint GWA mapping approach as a promising tool for describing the molecular landscape underlying plant - microbe interactions.

Genome Microscale Heterogeneity among Wild Potatoes Revealed by Diversity Arrays Technology Marker Sequences

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Alessandra Traini

2013-01-01

Full Text Available Tuber-bearing potato species possess several genes that can be exploited to improve the genetic background of the cultivated potato Solanum tuberosum. Among them, S. bulbocastanum and S. commersonii are well known for their strong resistance to environmental stresses. However, scant information is available for these species in terms of genome organization, gene function, and regulatory networks. Consequently, genomic tools to assist breeding are meager, and efficient exploitation of these species has been limited so far. In this paper, we employed the reference genome sequences from cultivated potato and tomato and a collection of sequences of 1,423 potato Diversity Arrays Technology (DArT markers that show polymorphic representation across the genomes of S. bulbocastanum and/or S. commersonii genotypes. Our results highlighted microscale genome sequence heterogeneity that may play a significant role in functional and structural divergence between related species. Our analytical approach provides knowledge of genome structural and sequence variability that could not be detected by transcriptome and proteome approaches.

Genome Microscale Heterogeneity among Wild Potatoes Revealed by Diversity Arrays Technology Marker Sequences.

Science.gov (United States)

Traini, Alessandra; Iorizzo, Massimo; Mann, Harpartap; Bradeen, James M; Carputo, Domenico; Frusciante, Luigi; Chiusano, Maria Luisa

2013-01-01

Tuber-bearing potato species possess several genes that can be exploited to improve the genetic background of the cultivated potato Solanum tuberosum. Among them, S. bulbocastanum and S. commersonii are well known for their strong resistance to environmental stresses. However, scant information is available for these species in terms of genome organization, gene function, and regulatory networks. Consequently, genomic tools to assist breeding are meager, and efficient exploitation of these species has been limited so far. In this paper, we employed the reference genome sequences from cultivated potato and tomato and a collection of sequences of 1,423 potato Diversity Arrays Technology (DArT) markers that show polymorphic representation across the genomes of S. bulbocastanum and/or S. commersonii genotypes. Our results highlighted microscale genome sequence heterogeneity that may play a significant role in functional and structural divergence between related species. Our analytical approach provides knowledge of genome structural and sequence variability that could not be detected by transcriptome and proteome approaches.

Developing climate resilient rice through genomics assisted breeding

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Valarmathi Muthu

2017-10-01

Full Text Available Rice is one of the major cereal food crops whose production has to be doubled to achieve the projected demand [1] and current yield trends are not sufficient to meet the projected growth in production. Increasing the rice production by 30% during 2030 needs overcoming challenges viz., yield plateau, declining land, water and labor resources and predicted effects of global climate change. Development of high performance rice genotypes with enhanced yield potential and resilience to climate change will help in sustained increase in rice production. Deployment of genomic technologies can accelerate development and delivery of improved germplasm with enhanced resilience and adaptability [2, 3]. In this context, the present study was undertaken with an aim of developing rice genotypes pyramided with QTLs/genes controlling tolerance against various biotic and abiotic stresses viz., bacterial leaf blight (xa13, Xa21, blast (Pi9, Gall midge (Gm4, drought (qDTY1.1 qDTY2.1, submergence (Sub1 and salinity (Saltol. CBMAS14065 an elite culture harboring QTLs controlling tolerance against drought, salinity and submergence was crossed with a donor harboring BLB, Blast and Gall midge resistant genes. True F1s were backcrossed with CBMAS14065 and BC1F1 progenies were subjected to foreground selection using markers linked to the target traits. Superior plants (18 of BC1F1 generation were subjected to background selection which revealed 71.42 - 86.90% recurrent parent (CBMAS14065 genome recovery. Selected BC1F1 plants were advanced to BC2F1 generation backcrossing with CBMAS14065. In BC2F1 generation, through foreground selection 6-8 QTL/gene positive plants have been selected and advanced for further evaluation. The superior lines with desired QTLs/genes will be subjected to rigorous phenotypic evaluation against target stresses and advanced further.

Genomic Analyses Reveal the Influence of Geographic Origin, Migration, and Hybridization on Modern Dog Breed Development

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Heidi G. Parker

2017-04-01

Full Text Available There are nearly 400 modern domestic dog breeds with a unique histories and genetic profiles. To track the genetic signatures of breed development, we have assembled the most diverse dataset of dog breeds, reflecting their extensive phenotypic variation and heritage. Combining genetic distance, migration, and genome-wide haplotype sharing analyses, we uncover geographic patterns of development and independent origins of common traits. Our analyses reveal the hybrid history of breeds and elucidate the effects of immigration, revealing for the first time a suggestion of New World dog within some modern breeds. Finally, we used cladistics and haplotype sharing to show that some common traits have arisen more than once in the history of the dog. These analyses characterize the complexities of breed development, resolving longstanding questions regarding individual breed origination, the effect of migration on geographically distinct breeds, and, by inference, transfer of trait and disease alleles among dog breeds.

An integrated approach for increasing breeding efficiency in apple and peach in Europe

NARCIS (Netherlands)

Laurens, Francois; Aranzana, Maria José; Arus, Pere; Bassi, Daniele; Bink, Marco; Bonany, Joan; Caprera, Andrea; Corelli-Grappadelli, Luca; Costes, Evelyne; Durel, Charles Eric; Mauroux, Jehan Baptiste; Muranty, Hélène; Nazzicari, Nelson; Pascal, Thierry; Patocchi, Andrea; Peil, Andreas; Quilot-Turion, Bénédicte; Rossini, Laura; Stella, Alessandra; Troggio, Michela; Velasco, Riccardo; De Weg, Van Eric

2018-01-01

Despite the availability of whole genome sequences of apple and peach, there has been a considerable gap between genomics and breeding. To bridge the gap, the European Union funded the FruitBreedomics project (March 2011 to August 2015) involving 28 research institutes and private companies. Three

The Whole-Genome and Transcriptome of the Manila Clam (Ruditapes philippinarum).

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Mun, Seyoung; Kim, Yun-Ji; Markkandan, Kesavan; Shin, Wonseok; Oh, Sumin; Woo, Jiyoung; Yoo, Jongsu; An, Hyesuck; Han, Kyudong

2017-06-01

The manila clam, Ruditapes philippinarum, is an important bivalve species in worldwide aquaculture including Korea. The aquaculture production of R. philippinarum is under threat from diverse environmental factors including viruses, microorganisms, parasites, and water conditions with subsequently declining production. In spite of its importance as a marine resource, the reference genome of R. philippinarum for comprehensive genetic studies is largely unexplored. Here, we report the de novo whole-genome and transcriptome assembly of R. philippinarum across three different tissues (foot, gill, and adductor muscle), and provide the basic data for advanced studies in selective breeding and disease control in order to obtain successful aquaculture systems. An approximately 2.56 Gb high quality whole-genome was assembled with various library construction methods. A total of 108,034 protein coding gene models were predicted and repetitive elements including simple sequence repeats and noncoding RNAs were identified to further understanding of the genetic background of R. philippinarum for genomics-assisted breeding. Comparative analysis with the bivalve marine invertebrates uncover that the gene family related to complement C1q was enriched. Furthermore, we performed transcriptome analysis with three different tissues in order to support genome annotation and then identified 41,275 transcripts which were annotated. The R. philippinarum genome resource will markedly advance a wide range of potential genetic studies, a reference genome for comparative analysis of bivalve species and unraveling mechanisms of biological processes in molluscs. We believe that the R. philippinarum genome will serve as an initial platform for breeding better-quality clams using a genomic approach. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Future perspectives of in vitro culture and plant breeding

DEFF Research Database (Denmark)

Kuligowska, Katarzyna; Lütken, Henrik Vlk; Hegelund, Josefine Nymark

2015-01-01

Conventional breeding and plant improvement increasingly become inadequate to keep up with progression and high quality demands. Thus biotechnological techniques are more and more adopted. Initially, biotechnological tools have supported conventional breeding by in vitro culture techniques......, comprising micropropagation, speeding up multiplication and improving uniformity. Also, crossing barriers of incompatible plants have been overcome using in vitro methods and embryo rescue techniques in wide hybridization approaches. Marker-assisted breeding is employed for targeted selection of DNA...... fragments from parental plants in respect to identification of desired characteristics in offspring or among hybrid plants. Phylogeny-assisted breeding and knowledge about genetic relationships support the ability to develop new hybrids. Finally, chemical and radiation induced mutagenesis are established...

Single nucleotide variants and InDels identified from whole-genome re-sequencing of Guzerat, Gyr, Girolando and Holstein cattle breeds.

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Nedenia Bonvino Stafuzza

Full Text Available Whole-genome re-sequencing, alignment and annotation analyses were undertaken for 12 sires representing four important cattle breeds in Brazil: Guzerat (multi-purpose, Gyr, Girolando and Holstein (dairy production. A total of approximately 4.3 billion reads from an Illumina HiSeq 2000 sequencer generated for each animal 10.7 to 16.4-fold genome coverage. A total of 27,441,279 single nucleotide variations (SNVs and 3,828,041 insertions/deletions (InDels were detected in the samples, of which 2,557,670 SNVs and 883,219 InDels were novel. The submission of these genetic variants to the dbSNP database significantly increased the number of known variants, particularly for the indicine genome. The concordance rate between genotypes obtained using the Bovine HD BeadChip array and the same variants identified by sequencing was about 99.05%. The annotation of variants identified numerous non-synonymous SNVs and frameshift InDels which could affect phenotypic variation. Functional enrichment analysis was performed and revealed that variants in the olfactory transduction pathway was over represented in all four cattle breeds, while the ECM-receptor interaction pathway was over represented in Girolando and Guzerat breeds, the ABC transporters pathway was over represented only in Holstein breed, and the metabolic pathways was over represented only in Gyr breed. The genetic variants discovered here provide a rich resource to help identify potential genomic markers and their associated molecular mechanisms that impact economically important traits for Gyr, Girolando, Guzerat and Holstein breeding programs.

CRISPR/Cas9: A Practical Approach in Date Palm Genome Editing

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Muhammad N. Sattar

2017-08-01

Full Text Available The genetic modifications through breeding of crop plants have long been used to improve the yield and quality. However, precise genome editing (GE could be a very useful supplementary tool for improvement of crop plants by targeted genome modifications. Various GE techniques including ZFNs (zinc finger nucleases, TALENs (transcription activator-like effector nucleases, and most recently clustered regularly interspaced short palindromic repeats (CRISPR/Cas9 (CRISPR-associated protein 9-based approaches have been successfully employed for various crop plants including fruit trees. CRISPR/Cas9-based approaches hold great potential in GE due to their simplicity, competency, and versatility over other GE techniques. However, to the best of our knowledge no such genetic improvement has ever been developed in date palm—an important fruit crop in Oasis agriculture. The applications of CRISPR/Cas9 can be a challenging task in date palm GE due to its large and complex genome, high rate of heterozygosity and outcrossing, in vitro regeneration and screening of mutants, high frequency of single-nucleotide polymorphism in the genome and ultimately genetic instability. In this review, we addressed the potential application of CRISPR/Cas9-based approaches in date palm GE to improve the sustainable date palm production. The availability of the date palm whole genome sequence has made it feasible to use CRISPR/Cas9 GE approach for genetic improvement in this species. Moreover, the future prospects of GE application in date palm are also addressed in this review.

Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines.

Science.gov (United States)

Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R

2015-02-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.

Genomic selection and association mapping in rice (Oryza sativa: effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines.

Directory of Open Access Journals (Sweden)

Jennifer Spindel

2015-02-01

Full Text Available Genomic Selection (GS is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.

Genomic Selection and Association Mapping in Rice (Oryza sativa): Effect of Trait Genetic Architecture, Training Population Composition, Marker Number and Statistical Model on Accuracy of Rice Genomic Selection in Elite, Tropical Rice Breeding Lines

Science.gov (United States)

Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R.

2015-01-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline. PMID:25689273

Genomic selection strategies in breeding programs: Strong positive interaction between application of genotypic information and intensive use of young bulls on genetic gain

DEFF Research Database (Denmark)

Buch, Line Hjortø; Sørensen, Morten Kargo; Berg, Peer

2012-01-01

We tested the following hypotheses: (i) breeding schemes with genomic selection are superior to breeding schemes without genomic selection regarding annual genetic gain of the aggregate genotype (ΔGAG), annual genetic gain of the functional traits and rate of inbreeding per generation (ΔF), (ii......) a positive interaction exists between the use of genotypic information and a short generation interval on ΔGAG and (iii) the inclusion of an indicator trait in the selection index will only result in a negligible increase in ΔGAG if genotypic information about the breeding goal trait is known. We examined......, greater contributions of the functional trait to ΔGAG and lower ΔF than the two breeding schemes without genomic selection. Thus, the use of genotypic information may lead to more sustainable breeding schemes. In addition, a short generation interval increases the effect of using genotypic information...

Diversifying Selection Between Pure-Breed and Free-Breeding Dogs Inferred from Genome-Wide SNP Analysis

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Małgorzata Pilot

2016-08-01

Full Text Available Domesticated species are often composed of distinct populations differing in the character and strength of artificial and natural selection pressures, providing a valuable model to study adaptation. In contrast to pure-breed dogs that constitute artificially maintained inbred lines, free-ranging dogs are typically free-breeding, i.e., unrestrained in mate choice. Many traits in free-breeding dogs (FBDs may be under similar natural and sexual selection conditions to wild canids, while relaxation of sexual selection is expected in pure-breed dogs. We used a Bayesian approach with strict false-positive control criteria to identify FST-outlier SNPs between FBDs and either European or East Asian breeds, based on 167,989 autosomal SNPs. By identifying outlier SNPs located within coding genes, we found four candidate genes under diversifying selection shared by these two comparisons. Three of them are associated with the Hedgehog (HH signaling pathway regulating vertebrate morphogenesis. A comparison between FBDs and East Asian breeds also revealed diversifying selection on the BBS6 gene, which was earlier shown to cause snout shortening and dental crowding via disrupted HH signaling. Our results suggest that relaxation of natural and sexual selection in pure-breed dogs as opposed to FBDs could have led to mild changes in regulation of the HH signaling pathway. HH inhibits adhesion and the migration of neural crest cells from the neural tube, and minor deficits of these cells during embryonic development have been proposed as the underlying cause of “domestication syndrome.” This suggests that the process of breed formation involved the same genetic and developmental pathways as the process of domestication.

Breeding research on sake yeasts in Japan: history, recent technological advances, and future perspectives.

Science.gov (United States)

Kitagaki, Hiroshi; Kitamoto, Katsuhiko

2013-01-01

Sake is an alcoholic beverage of Japan, with a tradition lasting more than 1,300 years; it is produced from rice and water by fermenting with the koji mold Aspergillus oryzae and sake yeast Saccharomyces cerevisiae. Breeding research on sake yeasts was originally developed in Japan by incorporating microbiological and genetic research methodologies adopted in other scientific areas. Since the advent of a genetic paradigm, isolation of yeast mutants has been a dominant approach for the breeding of favorable sake yeasts. These sake yeasts include (a) those that do not form foams (produced by isolating a mutant that does not stick to foams, thus decreasing the cost of sake production); (b) those that do not produce urea, which leads to the formation of ethyl carbamate, a possible carcinogen (isolated by positive selection in a canavanine-, arginine-, and ornithine-containing medium); (c) those that produce an increased amount of ethyl caproate, an apple-like flavor (produced by isolating a mutant resistant to cerulenin, an inhibitor of fatty-acid synthesis); and (d) those that produce a decreased amount of pyruvate (produced by isolating a mutant resistant to an inhibitor of mitochondrial transport, thus decreasing the amount of diacetyl). Given that sake yeasts perform sexual reproduction, sporulation and mating are potent approaches for their breeding. Recently, the genome sequences of sake yeasts have been determined and made publicly accessible. By utilizing this information, the quantitative trait loci (QTLs) for the brewing characteristics of sake yeasts have been identified, which paves a way to DNA marker-assisted selection of the mated strains. Genetic engineering technologies for experimental yeast strains have recently been established by academic groups, and these technologies have also been applied to the breeding of sake yeasts. Sake yeasts whose genomes have been modified with these technologies correspond to genetically modified organisms (GMOs

Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.).

Science.gov (United States)

Auinger, Hans-Jürgen; Schönleben, Manfred; Lehermeier, Christina; Schmidt, Malthe; Korzun, Viktor; Geiger, Hartwig H; Piepho, Hans-Peter; Gordillo, Andres; Wilde, Peer; Bauer, Eva; Schön, Chris-Carolin

2016-11-01

Genomic prediction accuracy can be significantly increased by model calibration across multiple breeding cycles as long as selection cycles are connected by common ancestors. In hybrid rye breeding, application of genome-based prediction is expected to increase selection gain because of long selection cycles in population improvement and development of hybrid components. Essentially two prediction scenarios arise: (1) prediction of the genetic value of lines from the same breeding cycle in which model training is performed and (2) prediction of lines from subsequent cycles. It is the latter from which a reduction in cycle length and consequently the strongest impact on selection gain is expected. We empirically investigated genome-based prediction of grain yield, plant height and thousand kernel weight within and across four selection cycles of a hybrid rye breeding program. Prediction performance was assessed using genomic and pedigree-based best linear unbiased prediction (GBLUP and PBLUP). A total of 1040 S 2 lines were genotyped with 16 k SNPs and each year testcrosses of 260 S 2 lines were phenotyped in seven or eight locations. The performance gap between GBLUP and PBLUP increased significantly for all traits when model calibration was performed on aggregated data from several cycles. Prediction accuracies obtained from cross-validation were in the order of 0.70 for all traits when data from all cycles (N CS  = 832) were used for model training and exceeded within-cycle accuracies in all cases. As long as selection cycles are connected by a sufficient number of common ancestors and prediction accuracy has not reached a plateau when increasing sample size, aggregating data from several preceding cycles is recommended for predicting genetic values in subsequent cycles despite decreasing relatedness over time.

Overlap in genomic variation associated with milk fat composition in Holstein Friesian and Dutch native dual-purpose breeds

NARCIS (Netherlands)

Maurice - Van Eijndhoven, M.H.T.; Bovenhuis, H.; Veerkamp, R.F.; Calus, M.P.L.

2015-01-01

The aim of this study was to identify if genomic variations associated with fatty acid (FA) composition are similar between the Holstein-Friesian (HF) and native dual-purpose breeds used in the Dutch dairy industry. Phenotypic and genotypic information were available for the breeds Meuse-Rhine-Yssel

Light whole genome sequence for SNP discovery across domestic cat breeds

Directory of Open Access Journals (Sweden)

Driscoll Carlos

2010-06-01

Full Text Available Abstract Background The domestic cat has offered enormous genomic potential in the veterinary description of over 250 hereditary disease models as well as the occurrence of several deadly feline viruses (feline leukemia virus -- FeLV, feline coronavirus -- FECV, feline immunodeficiency virus - FIV that are homologues to human scourges (cancer, SARS, and AIDS respectively. However, to realize this bio-medical potential, a high density single nucleotide polymorphism (SNP map is required in order to accomplish disease and phenotype association discovery. Description To remedy this, we generated 3,178,297 paired fosmid-end Sanger sequence reads from seven cats, and combined these data with the publicly available 2X cat whole genome sequence. All sequence reads were assembled together to form a 3X whole genome assembly allowing the discovery of over three million SNPs. To reduce potential false positive SNPs due to the low coverage assembly, a low upper-limit was placed on sequence coverage and a high lower-limit on the quality of the discrepant bases at a potential variant site. In all domestic cats of different breeds: female Abyssinian, female American shorthair, male Cornish Rex, female European Burmese, female Persian, female Siamese, a male Ragdoll and a female African wildcat were sequenced lightly. We report a total of 964 k common SNPs suitable for a domestic cat SNP genotyping array and an additional 900 k SNPs detected between African wildcat and domestic cats breeds. An empirical sampling of 94 discovered SNPs were tested in the sequenced cats resulting in a SNP validation rate of 99%. Conclusions These data provide a large collection of mapped feline SNPs across the cat genome that will allow for the development of SNP genotyping platforms for mapping feline diseases.

Avian Polyomavirus Genome Sequences Recovered from Parrots in Captive Breeding Facilities in Poland

OpenAIRE

Dayaram, Anisha; Piasecki, Tomasz; Chrząstek, Klaudia; White, Robyn; Julian, Laurel; van Bysterveldt, Katherine; Varsani, Arvind

2015-01-01

Eight genomes of avian polyomaviruses (APVs) were recovered and sequenced from deceased Psittacula eupatria, Psittacula krameri, and Melopsittacus undulatus from various breeding facilities in Poland. Of these APV-positive samples, six had previously tested positive for beak and feather disease virus (BFDV) and/or parrot hepatitis B virus (PHBV).

Consumers & plant genomics : the positioning and acceptance of a new plant breeding practice

NARCIS (Netherlands)

Heuvel, van den T.

2008-01-01

Innovative developments in technology, such as the emergence of genomics as a plant breeding practice, hold the potential to change the supply side of the market. The success of these practices not only depends on the improved efficiency and effectiveness it brings, but also on how well they are

Genomics-Assisted Exploitation of Heterosis in Perennial Ryegrass (Lolium perenne L.)

DEFF Research Database (Denmark)

Islam, Md. Shofiqul

ryegrass for the development of improved varieties. During his PhD studies, Mohammad Shofiqul Islam studied the feasibility of developing novel hybrid breeding schemes based on cytoplasmic male sterility (CMS) systems in perennial ryegrass. He successfully completed the assembly and annotation of a male......-fertile perennial ryegrass mitochondrial genome, and identified candidate genes responsible for the CMS phenotype by comparing male-fertile and male-sterile mitochondrial genomes. His findings constitute a good basis for continuing research to produce hybrid grass varieties to address the future needs......, breeding activities have been carried out to improve the population and develop synthetic varieties. This does not fully exploit the potential of heterosis, however. Hybrid breeding is an alternative strategy and provides opportunities to fully exploit the genetically available heterosis in perennial...

Molecular approaches for genetic improvement of seed quality and characterization of genetic diversity in soybean: a critical review.

Science.gov (United States)

Tripathi, Niraj; Khare, Dhirendra

2016-10-01

Soybean is an economically important leguminous crop. Genetic improvements of soybeans have focused on enhancement of seed and oil yield, development of varieties suited to different cropping systems, and breeding resistant/tolerant varieties for various biotic and abiotic stresses. Plant breeders have used conventional breeding techniques for the improvement of these traits in soybean. The conventional breeding process can be greatly accelerated through the application of molecular and genomic approaches. Molecular markers have proved to be a new tool in soybean breeding by enhancing selection efficiency in a rapid and time-bound manner. An overview of molecular approaches for the genetic improvement of soybean seed quality parameters, considering recent applications of marker-assisted selection and 'omics' research, is provided in this article.

Accuracy of Genomic Selection in a Rice Synthetic Population Developed for Recurrent Selection Breeding.

Science.gov (United States)

Grenier, Cécile; Cao, Tuong-Vi; Ospina, Yolima; Quintero, Constanza; Châtel, Marc Henri; Tohme, Joe; Courtois, Brigitte; Ahmadi, Nourollah

2015-01-01

Genomic selection (GS) is a promising strategy for enhancing genetic gain. We investigated the accuracy of genomic estimated breeding values (GEBV) in four inter-related synthetic populations that underwent several cycles of recurrent selection in an upland rice-breeding program. A total of 343 S2:4 lines extracted from those populations were phenotyped for flowering time, plant height, grain yield and panicle weight, and genotyped with an average density of one marker per 44.8 kb. The relative effect of the linkage disequilibrium (LD) and minor allele frequency (MAF) thresholds for selecting markers, the relative size of the training population (TP) and of the validation population (VP), the selected trait and the genomic prediction models (frequentist and Bayesian) on the accuracy of GEBVs was investigated in 540 cross validation experiments with 100 replicates. The effect of kinship between the training and validation populations was tested in an additional set of 840 cross validation experiments with a single genomic prediction model. LD was high (average r2 = 0.59 at 25 kb) and decreased slowly, distribution of allele frequencies at individual loci was markedly skewed toward unbalanced frequencies (MAF average value 15.2% and median 9.6%), and differentiation between the four synthetic populations was low (FST ≤0.06). The accuracy of GEBV across all cross validation experiments ranged from 0.12 to 0.54 with an average of 0.30. Significant differences in accuracy were observed among the different levels of each factor investigated. Phenotypic traits had the biggest effect, and the size of the incidence matrix had the smallest. Significant first degree interaction was observed for GEBV accuracy between traits and all the other factors studied, and between prediction models and LD, MAF and composition of the TP. The potential of GS to accelerate genetic gain and breeding options to increase the accuracy of predictions are discussed.

Genome-wide detection of copy number variations among diverse horse breeds by array CGH.

Directory of Open Access Journals (Sweden)

Wei Wang

Full Text Available Recent studies have found that copy number variations (CNVs are widespread in human and animal genomes. CNVs are a significant source of genetic variation, and have been shown to be associated with phenotypic diversity. However, the effect of CNVs on genetic variation in horses is not well understood. In the present study, CNVs in 6 different breeds of mare horses, Mongolia horse, Abaga horse, Hequ horse and Kazakh horse (all plateau breeds and Debao pony and Thoroughbred, were determined using aCGH. In total, seven hundred CNVs were identified ranging in size from 6.1 Kb to 0.57 Mb across all autosomes, with an average size of 43.08 Kb and a median size of 15.11 Kb. By merging overlapping CNVs, we found a total of three hundred and fifty-three CNV regions (CNVRs. The length of the CNVRs ranged from 6.1 Kb to 1.45 Mb with average and median sizes of 38.49 Kb and 13.1 Kb. Collectively, 13.59 Mb of copy number variation was identified among the horses investigated and accounted for approximately 0.61% of the horse genome sequence. Five hundred and eighteen annotated genes were affected by CNVs, which corresponded to about 2.26% of all horse genes. Through the gene ontology (GO, genetic pathway analysis and comparison of CNV genes among different breeds, we found evidence that CNVs involving 7 genes may be related to the adaptation to severe environment of these plateau horses. This study is the first report of copy number variations in Chinese horses, which indicates that CNVs are ubiquitous in the horse genome and influence many biological processes of the horse. These results will be helpful not only in mapping the horse whole-genome CNVs, but also to further research for the adaption to the high altitude severe environment for plateau horses.

A review of microsatellite markers and their applications in rice breeding programs to improve blast disease resistance.

Science.gov (United States)

Miah, Gous; Rafii, Mohd Y; Ismail, Mohd R; Puteh, Adam B; Rahim, Harun A; Islam, Kh Nurul; Latif, Mohammad Abdul

2013-11-14

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

A Review of Microsatellite Markers and Their Applications in Rice Breeding Programs to Improve Blast Disease Resistance

Directory of Open Access Journals (Sweden)

Mohammad Abdul Latif

2013-11-01

Full Text Available 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

Disease resistance breeding in rose: current status and potential of biotechnological tools.

Science.gov (United States)

Debener, Thomas; Byrne, David H

2014-11-01

The cultivated rose is a multispecies complex for which a high level of disease protection is needed due to the low tolerance of blemishes in ornamental plants. The most important fungal diseases are black spot, powdery mildew, botrytis and downy mildew. Rose rosette, a lethal viral pathogen, is emerging as a devastating disease in North America. Currently rose breeders use a recurrent phenotypic selection approach and perform selection for disease resistance for most pathogen issues in a 2-3 year field trial. Marker assisted selection could accelerate this breeding process. Thus far markers have been identified for resistance to black spot (Rdrs) and powdery mildew and with the ability of genotyping by sequencing to generate 1000s of markers our ability to identify markers useful in plant improvement should increase exponentially. Transgenic rose lines with various fungal resistance genes inserted have shown limited success and RNAi technology has potential to provide virus resistance. Roses, as do other plants, have sequences homologous to characterized R-genes in their genomes, some which have been related to specific disease resistance. With improving next generation sequencing technology, our ability to do genomic and transcriptomic studies of the resistance related genes in both the rose and the pathogens to reveal novel gene targets to develop resistant roses will accelerate. Finally, the development of designer nucleases opens up a potentially non-GMO approach to directly modify a rose's DNA to create a disease resistant rose. Although there is much potential, at present rose breeders are not using marker assisted breeding primarily because a good suite of marker/trait associations (MTA) that would ensure a path to stable disease resistance is not available. As our genomic analytical tools improve, so will our ability to identify useful genes and linked markers. Once these MTAs are available, it will be the cost savings, both in time and money, that will

Effect of imputing markers from a low-density chip on the reliability of genomic breeding values in Holstein populations

DEFF Research Database (Denmark)

Dassonneville, R; Brøndum, Rasmus Froberg; Druet, T

2011-01-01

The purpose of this study was to investigate the imputation error and loss of reliability of direct genomic values (DGV) or genomically enhanced breeding values (GEBV) when using genotypes imputed from a 3,000-marker single nucleotide polymorphism (SNP) panel to a 50,000-marker SNP panel. Data...... of missing markers and prediction of breeding values were performed using 2 different reference populations in each country: either a national reference population or a combined EuroGenomics reference population. Validation for accuracy of imputation and genomic prediction was done based on national test...... with a national reference data set gave an absolute loss of 0.05 in mean reliability of GEBV in the French study, whereas a loss of 0.03 was obtained for reliability of DGV in the Nordic study. When genotypes were imputed using the EuroGenomics reference, a loss of 0.02 in mean reliability of GEBV was detected...

Genoproteomics-assisted improvement of Andrographis paniculata: toward a promising molecular and conventional breeding platform for autogamous plants affecting the pharmaceutical industry.

Science.gov (United States)

Valdiani, Alireza; Talei, Daryush; Lattoo, Surrinder K; Ortiz, Rodomiro; Rasmussen, Søren Kjærsgaard; Batley, Jacqueline; Rafii, Mohd Yusop; Maziah, Mahmood; Sabu, Kallevettankuzhy K; Abiri, Rambod; Sakuanrungsirikul, Suchirat; Tan, Soon Guan

2017-09-01

plant production and, therefore, can be regarded as prospective breeding platforms for medicinal plants that have an autogamous mode of reproduction. Finally, this review suggests that novel site-directed genome editing approaches such as TALENs (Transcription Activator-Like Effector Nucleases) and CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 (CRISPR-associated protein-9 nuclease) systems together with other new plant breeding technologies (NPBT) should simultaneously be taken into consideration for improvement of pharmaceutical plants.

Detection of alien chromatin introgression from Thinopyrum into wheat using S genomic DNA as a probe--a landmark approach for Thinopyrum genome research.

Science.gov (United States)

Chen, Q

2005-01-01

The introduction of alien genetic variation from the genus Thinopyrum through chromosome engineering into wheat is a valuable and proven technique for wheat improvement. A number of economically important traits have been transferred into wheat as single genes, chromosome arms or entire chromosomes. Successful transfers can be greatly assisted by the precise identification of alien chromatin in the recipient progenies. Chromosome identification and characterization are useful for genetic manipulation and transfer in wheat breeding following chromosome engineering. Genomic in situ hybridization (GISH) using an S genomic DNA probe from the diploid species Pseudoroegneria has proven to be a powerful diagnostic cytogenetic tool for monitoring the transfer of many promising agronomic traits from Thinopyrum. This specific S genomic probe not only allows the direct determination of the chromosome composition in wheat-Thinopyrum hybrids, but also can separate the Th. intermedium chromosomes into the J, J(S) and S genomes. The J(S) genome, which consists of a modified J genome chromosome distinguished by S genomic sequences of Pseudoroegneria near the centromere and telomere, carries many disease and mite resistance genes. Utilization of this S genomic probe leads to a better understanding of genomic affinities between Thinopyrum and wheat, and provides a molecular cytogenetic marker for monitoring the transfer of alien Thinopyrum agronomic traits into wheat recipient lines. Copyright 2005 S. Karger AG, Basel.

Avian Polyomavirus Genome Sequences Recovered from Parrots in Captive Breeding Facilities in Poland.

Science.gov (United States)

Dayaram, Anisha; Piasecki, Tomasz; Chrząstek, Klaudia; White, Robyn; Julian, Laurel; van Bysterveldt, Katherine; Varsani, Arvind

2015-09-24

Eight genomes of avian polyomaviruses (APVs) were recovered and sequenced from deceased Psittacula eupatria, Psittacula krameri, and Melopsittacus undulatus from various breeding facilities in Poland. Of these APV-positive samples, six had previously tested positive for beak and feather disease virus (BFDV) and/or parrot hepatitis B virus (PHBV). Copyright © 2015 Dayaram et al.

Textbook animal breeding : animal breeding andgenetics for BSc students

NARCIS (Netherlands)

Oldenbroek, Kor; Waaij, van der Liesbeth

2014-01-01

This textbook contains teaching material on animal breeding and genetics for BSc students. The text book started as an initiative of the Dutch Universities for Applied (Agricultural) Sciences. The textbook is made available by the Animal Breeding and Genomics Centre (ABGC) of Wageningen UR

Genome resource banking of biomedically important laboratory animals.

Science.gov (United States)

Agca, Yuksel

2012-11-01

Genome resource banking is the systematic collection, storage, and redistribution of biomaterials in an organized, logistical, and secure manner. Genome cryobanks usually contain biomaterials and associated genomic information essential for progression of biomedicine, human health, and research. In that regard, appropriate genome cryobanks could provide essential biomaterials for both current and future research projects in the form of various cell types and tissues, including sperm, oocytes, embryos, embryonic or adult stem cells, induced pluripotent stem cells, and gonadal tissues. In addition to cryobanked germplasm, cryobanking of DNA, serum, blood products, and tissues from scientifically, economically, and ecologically important species has become a common practice. For revitalization of the whole organism, cryopreserved germplasm in conjunction with assisted reproductive technologies, offer a powerful approach for research model management, as well as assisting in animal production for agriculture, conservation, and human reproductive medicine. Recently, many developed and developing countries have allocated substantial resources to establish genome resources banks which are responsible for safeguarding scientifically, economically, and ecologically important wild type, mutant, and transgenic plants, fish, and local livestock breeds, as well as wildlife species. This review is dedicated to the memory of Dr. John K. Critser, who has made profound contributions to the science of cryobiology and establishment of genome research and resources centers for mice, rats, and swine. Emphasis will be given to application of genome resource banks to species with substantial contributions to the advancement of biomedicine and human health. Copyright © 2012 Elsevier Inc. All rights reserved.

Genome wide selection in Citrus breeding.

Science.gov (United States)

Gois, I B; Borém, A; Cristofani-Yaly, M; de Resende, M D V; Azevedo, C F; Bastianel, M; Novelli, V M; Machado, M A

2016-10-17

Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seq TM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.

Strategies for implementing genomic selection in family-based aquaculture breeding schemes: double haploid sib test populations

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Nirea Kahsay G

2012-10-01

Full Text Available Abstract Background Simulation studies have shown that accuracy and genetic gain are increased in genomic selection schemes compared to traditional aquaculture sib-based schemes. In genomic selection, accuracy of selection can be maximized by increasing the precision of the estimation of SNP effects and by maximizing the relationships between test sibs and candidate sibs. Another means of increasing the accuracy of the estimation of SNP effects is to create individuals in the test population with extreme genotypes. The latter approach was studied here with creation of double haploids and use of non-random mating designs. Methods Six alternative breeding schemes were simulated in which the design of the test population was varied: test sibs inherited maternal (Mat, paternal (Pat or a mixture of maternal and paternal (MatPat double haploid genomes or test sibs were obtained by maximum coancestry mating (MaxC, minimum coancestry mating (MinC, or random (RAND mating. Three thousand test sibs and 3000 candidate sibs were genotyped. The test sibs were recorded for a trait that could not be measured on the candidates and were used to estimate SNP effects. Selection was done by truncation on genome-wide estimated breeding values and 100 individuals were selected as parents each generation, equally divided between both sexes. Results Results showed a 7 to 19% increase in selection accuracy and a 6 to 22% increase in genetic gain in the MatPat scheme compared to the RAND scheme. These increases were greater with lower heritabilities. Among all other scenarios, i.e. Mat, Pat, MaxC, and MinC, no substantial differences in selection accuracy and genetic gain were observed. Conclusions In conclusion, a test population designed with a mixture of paternal and maternal double haploids, i.e. the MatPat scheme, increases substantially the accuracy of selection and genetic gain. This will be particularly interesting for traits that cannot be recorded on the

Genomic Prediction of Manganese Efficiency in Winter Barley

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Florian Leplat

2016-07-01

Full Text Available Manganese efficiency is a quantitative abiotic stress trait controlled by several genes each with a small effect. Manganese deficiency leads to yield reduction in winter barley ( L.. Breeding new cultivars for this trait remains difficult because of the lack of visual symptoms and the polygenic features of the trait. Hence, Mn efficiency is a potential suitable trait for a genomic selection (GS approach. A collection of 248 winter barley varieties was screened for Mn efficiency using Chlorophyll (Chl fluorescence in six environments prone to induce Mn deficiency. Two models for genomic prediction were implemented to predict future performance and breeding value of untested varieties. Predictions were obtained using multivariate mixed models: best linear unbiased predictor (BLUP and genomic best linear unbiased predictor (G-BLUP. In the first model, predictions were based on the phenotypic evaluation, whereas both phenotypic and genomic marker data were included in the second model. Accuracy of predicting future phenotype, , and accuracy of predicting true breeding values, , were calculated and compared for both models using six cross-validation (CV schemes; these were designed to mimic plant breeding programs. Overall, the CVs showed that prediction accuracies increased when using the G-BLUP model compared with the prediction accuracies using the BLUP model. Furthermore, the accuracies [] of predicting breeding values were more accurate than accuracy of predicting future phenotypes []. The study confirms that genomic data may enhance the prediction accuracy. Moreover it indicates that GS is a suitable breeding approach for quantitative abiotic stress traits.

Accuracy of Genomic Selection in a Rice Synthetic Population Developed for Recurrent Selection Breeding.

Directory of Open Access Journals (Sweden)

Cécile Grenier

Full Text Available Genomic selection (GS is a promising strategy for enhancing genetic gain. We investigated the accuracy of genomic estimated breeding values (GEBV in four inter-related synthetic populations that underwent several cycles of recurrent selection in an upland rice-breeding program. A total of 343 S2:4 lines extracted from those populations were phenotyped for flowering time, plant height, grain yield and panicle weight, and genotyped with an average density of one marker per 44.8 kb. The relative effect of the linkage disequilibrium (LD and minor allele frequency (MAF thresholds for selecting markers, the relative size of the training population (TP and of the validation population (VP, the selected trait and the genomic prediction models (frequentist and Bayesian on the accuracy of GEBVs was investigated in 540 cross validation experiments with 100 replicates. The effect of kinship between the training and validation populations was tested in an additional set of 840 cross validation experiments with a single genomic prediction model. LD was high (average r2 = 0.59 at 25 kb and decreased slowly, distribution of allele frequencies at individual loci was markedly skewed toward unbalanced frequencies (MAF average value 15.2% and median 9.6%, and differentiation between the four synthetic populations was low (FST ≤0.06. The accuracy of GEBV across all cross validation experiments ranged from 0.12 to 0.54 with an average of 0.30. Significant differences in accuracy were observed among the different levels of each factor investigated. Phenotypic traits had the biggest effect, and the size of the incidence matrix had the smallest. Significant first degree interaction was observed for GEBV accuracy between traits and all the other factors studied, and between prediction models and LD, MAF and composition of the TP. The potential of GS to accelerate genetic gain and breeding options to increase the accuracy of predictions are discussed.

Genomics meets ethology: a new route to understanding domestication, behavior, and sustainability in animal breeding.

Science.gov (United States)

Jensen, Per; Andersson, Leif

2005-06-01

Animal behavior is a central part of animal welfare, a keystone in sustainable animal breeding. During domestication, animals have adapted with respect to behavior and an array of other traits. We compared the behavior of junglefowl and White Leghorn layers, selected for egg production (and indirectly for growth). Jungle-fowl had a more active behavior in social, exploratory, anti-predatory, and feeding tests. A genome scan for Quantitative Trait Loci (QTLs) in a junglefowl x White Leghorn intercross revealed several significant or suggestive QTLs for different traits. Some production QTLs coincided with QTLs for behavior, suggesting that pleiotropic effects may be important for the development of domestication phenotypes. One gene has been located, which has a strong effect on the risk of being a victim of feather pecking, a detrimental behavior disorder. Modern genomics paired with analysis of behavior may help in designing more sustainable and robust breeding in the future.

Genome-Wide Association Study Reveals Natural Variations Contributing to Drought Resistance in Crops

Directory of Open Access Journals (Sweden)

Hongwei Wang

2017-06-01

Full Text Available Crops are often cultivated in regions where they will face environmental adversities; resulting in substantial yield loss which can ultimately lead to food and societal problems. Thus, significant efforts have been made to breed stress tolerant cultivars in an attempt to minimize these problems and to produce more stability with respect to crop yields across broad geographies. Since stress tolerance is a complex and multi-genic trait, advancements with classical breeding approaches have been challenging. On the other hand, molecular breeding, which is based on transgenics, marker-assisted selection and genome editing technologies; holds great promise to enable farmers to better cope with these challenges. However, identification of the key genetic components underlying the trait is critical and will serve as the foundation for future crop genetic improvement. Recently, genome-wide association studies have made significant contributions to facilitate the discovery of natural variation contributing to stress tolerance in crops. From these studies, the identified loci can serve as targets for genomic selection or editing to enable the molecular design of new cultivars. Here, we summarize research progress on this issue and focus on the genetic basis of drought tolerance as revealed by genome-wide association studies and quantitative trait loci mapping. Although many favorable loci have been identified, elucidation of their molecular mechanisms contributing to increased stress tolerance still remains a challenge. Thus, continuous efforts are still required to functionally dissect this complex trait through comprehensive approaches, such as system biological studies. It is expected that proper application of the acquired knowledge will enable the development of stress tolerant cultivars; allowing agricultural production to become more sustainable under dynamic environmental conditions.

Biotechnological approach in crop improvement by mutation breeding in Indonesia

Energy Technology Data Exchange (ETDEWEB)

Soeranto, H.; Sobrizal; Sutarto, Ismiyati; Manurung, Simon; Mastrizal [National Nuclear Energy Agency, Center for Research and Development of Isotope and Radiation Technology, Jakarta (Indonesia)

2002-02-01

Mutation breeding has become a proven method of improving crop varieties. Most research on plant mutation breeding in Indonesia is carried out at the Center for Research and Development of Isotope and Radiation Technology, National Nuclear Energy Agency (BATAN). Nowadays, a biotechnological approach has been incorporated in some mutation breeding researches in order to improve crop cultivars. This approach is simply based on cellular totipotency, or the ability to regenerate whole, flowering plants from isolated organs, pieces of tissue, individual cells, and protoplasts. Tissue culture technique has bee extensively used for micro propagation of disease-free plants. Other usage of this technique involves in various steps of the breeding process such as germplasm preservation, clonal propagation, and distant hybridization. Mutation breeding combined with tissue culture technique has made a significant contribution in inducing plant genetic variation, by improving selection technology, and by accelerating breeding time as for that by using anther or pollen culture. In Indonesia, research on mutation breeding combined with tissue culture techniques has been practiced in different crop species including rice, ginger, banana, sorghum etc. Specially in rice, a research on identification of DNA markers linked to blast disease resistance is now still progressing. A compiled report from some research activities is presented in this paper. (author)

Accuracy of Igenity genomically estimated breeding values for predicting Australian Angus BREEDPLAN traits.

Science.gov (United States)

Boerner, V; Johnston, D; Wu, X-L; Bauck, S

2015-02-01

Genomically estimated breeding values (GEBV) for Angus beef cattle are available from at least 2 commercial suppliers (Igenity [http://www.igenity.com] and Zoetis [http://www.zoetis.com]). The utility of these GEBV for improving genetic evaluation depends on their accuracies, which can be estimated by the genetic correlation with phenotypic target traits. Genomically estimated breeding values of 1,032 Angus bulls calculated from prediction equations (PE) derived by 2 different procedures in the U.S. Angus population were supplied by Igenity. Both procedures were based on Illuminia BovineSNP50 BeadChip genotypes. In procedure sg, GEBV were calculated from PE that used subsets of only 392 SNP, where these subsets were individually selected for each trait by BayesCπ. In procedure rg GEBV were calculated from PE derived in a ridge regression approach using all available SNP. Because the total set of 1,032 bulls with GEBV contained 732 individuals used in the Igenity training population, GEBV subsets were formed characterized by a decreasing average relationship between individuals in the subsets and individuals in the training population. Accuracies of GEBV were estimated as genetic correlations between GEBV and their phenotypic target traits modeling GEBV as trait observations in a bivariate REML approach, in which phenotypic observations were those recorded in the commercial Australian Angus seed stock sector. Using results from the GEBV subset excluding all training individuals as a reference, estimated accuracies were generally in agreement with those already published, with both types of GEBV (sg and rg) yielding similar results. Accuracies for growth traits ranged from 0.29 to 0.45, for reproductive traits from 0.11 to 0.53, and for carcass traits from 0.3 to 0.75. Accuracies generally decreased with an increasing genetic distance between the training and the validation population. However, for some carcass traits characterized by a low number of phenotypic

Integrating Genomic Data Sets for Knowledge Discovery: An Informed Approach to Management of Captive Endangered Species

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Kristopher J. L. Irizarry

2016-01-01

Full Text Available Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management.

Integrating Genomic Data Sets for Knowledge Discovery: An Informed Approach to Management of Captive Endangered Species.

Science.gov (United States)

Irizarry, Kristopher J L; Bryant, Doug; Kalish, Jordan; Eng, Curtis; Schmidt, Peggy L; Barrett, Gini; Barr, Margaret C

2016-01-01

Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs) that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management.

New biotechnology enhances the application of cisgenesis in plant breeding

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Hongwei eHou

2014-08-01

Full Text Available Cisgenesis is genetic modification to transfer beneficial alleles from crossable species into a recipient plant. The donor genes transferred by cisgenesis are the same as those used in traditional breeding. It can avoid linkage drag, enhance the use of existing gene alleles. This approach combines traditional breeding techniques with modern biotechnology and dramatically speeds up the breeding process. This allows plant genomes to be modified while remaining plants within the gene pool. Therefore, cisgenic plants should not be assessed as transgenics for environmental impacts.

A Multi-Breed Genome-Wide Association Analysis for Canine Hypothyroidism Identifies a Shared Major Risk Locus on CFA12.

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Matteo Bianchi

Full Text Available Hypothyroidism is a complex clinical condition found in both humans and dogs, thought to be caused by a combination of genetic and environmental factors. In this study we present a multi-breed analysis of predisposing genetic risk factors for hypothyroidism in dogs using three high-risk breeds--the Gordon Setter, Hovawart and the Rhodesian Ridgeback. Using a genome-wide association approach and meta-analysis, we identified a major hypothyroidism risk locus shared by these breeds on chromosome 12 (p = 2.1x10(-11. Further characterisation of the candidate region revealed a shared ~167 kb risk haplotype (4,915,018-5,081,823 bp, tagged by two SNPs in almost complete linkage disequilibrium. This breed-shared risk haplotype includes three genes (LHFPL5, SRPK1 and SLC26A8 and does not extend to the dog leukocyte antigen (DLA class II gene cluster located in the vicinity. These three genes have not been identified as candidate genes for hypothyroid disease previously, but have functions that could potentially contribute to the development of the disease. Our results implicate the potential involvement of novel genes and pathways for the development of canine hypothyroidism, raising new possibilities for screening, breeding programmes and treatments in dogs. This study may also contribute to our understanding of the genetic etiology of human hypothyroid disease, which is one of the most common endocrine disorders in humans.

Genome-Wide Association Studies and Comparison of Models and Cross-Validation Strategies for Genomic Prediction of Quality Traits in Advanced Winter Wheat Breeding Lines

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Peter S. Kristensen

2018-02-01

Full Text Available The aim of the this study was to identify SNP markers associated with five important wheat quality traits (grain protein content, Zeleny sedimentation, test weight, thousand-kernel weight, and falling number, and to investigate the predictive abilities of GBLUP and Bayesian Power Lasso models for genomic prediction of these traits. In total, 635 winter wheat lines from two breeding cycles in the Danish plant breeding company Nordic Seed A/S were phenotyped for the quality traits and genotyped for 10,802 SNPs. GWAS were performed using single marker regression and Bayesian Power Lasso models. SNPs with large effects on Zeleny sedimentation were found on chromosome 1B, 1D, and 5D. However, GWAS failed to identify single SNPs with significant effects on the other traits, indicating that these traits were controlled by many QTL with small effects. The predictive abilities of the models for genomic prediction were studied using different cross-validation strategies. Leave-One-Out cross-validations resulted in correlations between observed phenotypes corrected for fixed effects and genomic estimated breeding values of 0.50 for grain protein content, 0.66 for thousand-kernel weight, 0.70 for falling number, 0.71 for test weight, and 0.79 for Zeleny sedimentation. Alternative cross-validations showed that the genetic relationship between lines in training and validation sets had a bigger impact on predictive abilities than the number of lines included in the training set. Using Bayesian Power Lasso instead of GBLUP models, gave similar or slightly higher predictive abilities. Genomic prediction based on all SNPs was more effective than prediction based on few associated SNPs.

Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach.

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Simon Boitard

2016-03-01

Full Text Available Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey, PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.

Genomic Selection for Predicting Fusarium Head Blight Resistance in a Wheat Breeding Program

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Marcio P. Arruda

2015-11-01

Full Text Available Genomic selection (GS is a breeding method that uses marker–trait models to predict unobserved phenotypes. This study developed GS models for predicting traits associated with resistance to head blight (FHB in wheat ( L.. We used genotyping-by-sequencing (GBS to identify 5054 single-nucleotide polymorphisms (SNPs, which were then treated as predictor variables in GS analysis. We compared how the prediction accuracy of the genomic-estimated breeding values (GEBVs was affected by (i five genotypic imputation methods (random forest imputation [RFI], expectation maximization imputation [EMI], -nearest neighbor imputation [kNNI], singular value decomposition imputation [SVDI], and the mean imputation [MNI]; (ii three statistical models (ridge-regression best linear unbiased predictor [RR-BLUP], least absolute shrinkage and operator selector [LASSO], and elastic net; (iii marker density ( = 500, 1500, 3000, and 4500 SNPs; (iv training population (TP size ( = 96, 144, 192, and 218; (v marker-based and pedigree-based relationship matrices; and (vi control for relatedness in TPs and validation populations (VPs. No discernable differences in prediction accuracy were observed among imputation methods. The RR-BLUP outperformed other models in nearly all scenarios. Accuracies decreased substantially when marker number decreased to 3000 or 1500 SNPs, depending on the trait; when sample size of the training set was less than 192; when using pedigree-based instead of marker-based matrix; or when no control for relatedness was implemented. Overall, moderate to high prediction accuracies were observed in this study, suggesting that GS is a very promising breeding strategy for FHB resistance in wheat.

Application of genomics to forage crop breeding for quality traits

DEFF Research Database (Denmark)

Lübberstedt, Thomas

2007-01-01

Forage quality depends on the digestibility of fodder, and can be directly measured by the intake and metabolic conversion in animal trials. However, animal trials are time-consuming, laborious, and thus expensive. It is not possible to study thousands of plant genotypes, as required in breeding...... studied in detail and sequence motifs with likely effect on forage quality have been identified by association studies. Moreover, transgenic approaches substantiated the effect of several of these genes on forage quality. Perspectives and limitations of these findings for forage crop breeding...

Use of modern tomato breeding germplasm for deciphering the genetic control of agronomical traits by Genome Wide Association study.

Science.gov (United States)

Bauchet, Guillaume; Grenier, Stéphane; Samson, Nicolas; Bonnet, Julien; Grivet, Laurent; Causse, Mathilde

2017-05-01

A panel of 300 tomato accessions including breeding materials was built and characterized with >11,000 SNP. A population structure in six subgroups was identified. Strong heterogeneity in linkage disequilibrium and recombination landscape among groups and chromosomes was shown. GWAS identified several associations for fruit weight, earliness and plant growth. Genome-wide association studies (GWAS) have become a method of choice in quantitative trait dissection. First limited to highly polymorphic and outcrossing species, it is now applied in horticultural crops, notably in tomato. Until now GWAS in tomato has been performed on panels of heirloom and wild accessions. Using modern breeding materials would be of direct interest for breeding purpose. To implement GWAS on a large panel of 300 tomato accessions including 168 breeding lines, this study assessed the genetic diversity and linkage disequilibrium decay and revealed the population structure and performed GWA experiment. Genetic diversity and population structure analyses were based on molecular markers (>11,000 SNP) covering the whole genome. Six genetic subgroups were revealed and associated to traits of agronomical interest, such as fruit weight and disease resistance. Estimates of linkage disequilibrium highlighted the heterogeneity of its decay among genetic subgroups. Haplotype definition allowed a fine characterization of the groups and their recombination landscape revealing the patterns of admixture along the genome. Selection footprints showed results in congruence with introgressions. Taken together, all these elements refined our knowledge of the genetic material included in this panel and allowed the identification of several associations for fruit weight, plant growth and earliness, deciphering the genetic architecture of these complex traits and identifying several new loci useful for tomato breeding.

Harnessing Diversity in Wheat to Enhance Grain Yield, Climate Resilience, Disease and Insect Pest Resistance and Nutrition Through Conventional and Modern Breeding Approaches

Science.gov (United States)

Mondal, Suchismita; Rutkoski, Jessica E.; Velu, Govindan; Singh, Pawan K.; Crespo-Herrera, Leonardo A.; Guzmán, Carlos; Bhavani, Sridhar; Lan, Caixia; He, Xinyao; Singh, Ravi P.

2016-01-01

Current trends in population growth and consumption patterns continue to increase the demand for wheat, a key cereal for global food security. Further, multiple abiotic challenges due to climate change and evolving pathogen and pests pose a major concern for increasing wheat production globally. Triticeae species comprising of primary, secondary, and tertiary gene pools represent a rich source of genetic diversity in wheat. The conventional breeding strategies of direct hybridization, backcrossing and selection have successfully introgressed a number of desirable traits associated with grain yield, adaptation to abiotic stresses, disease resistance, and bio-fortification of wheat varieties. However, it is time consuming to incorporate genes conferring tolerance/resistance to multiple stresses in a single wheat variety by conventional approaches due to limitations in screening methods and the lower probabilities of combining desirable alleles. Efforts on developing innovative breeding strategies, novel tools and utilizing genetic diversity for new genes/alleles are essential to improve productivity, reduce vulnerability to diseases and pests and enhance nutritional quality. New technologies of high-throughput phenotyping, genome sequencing and genomic selection are promising approaches to maximize progeny screening and selection to accelerate the genetic gains in breeding more productive varieties. Use of cisgenic techniques to transfer beneficial alleles and their combinations within related species also offer great promise especially to achieve durable rust resistance. PMID:27458472

Impact of selective genotyping in the training population on accuracy and bias of genomic selection.

Science.gov (United States)

Zhao, Yusheng; Gowda, Manje; Longin, Friedrich H; Würschum, Tobias; Ranc, Nicolas; Reif, Jochen C

2012-08-01

Estimating marker effects based on routinely generated phenotypic data of breeding programs is a cost-effective strategy to implement genomic selection. Truncation selection in breeding populations, however, could have a strong impact on the accuracy to predict genomic breeding values. The main objective of our study was to investigate the influence of phenotypic selection on the accuracy and bias of genomic selection. We used experimental data of 788 testcross progenies from an elite maize breeding program. The testcross progenies were evaluated in unreplicated field trials in ten environments and fingerprinted with 857 SNP markers. Random regression best linear unbiased prediction method was used in combination with fivefold cross-validation based on genotypic sampling. We observed a substantial loss in the accuracy to predict genomic breeding values in unidirectional selected populations. In contrast, estimating marker effects based on bidirectional selected populations led to only a marginal decrease in the prediction accuracy of genomic breeding values. We concluded that bidirectional selection is a valuable approach to efficiently implement genomic selection in applied plant breeding programs.

Genome-wide scans for delineation of candidate genes regulating seed-protein content in chickpea

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Hari Deo eUpadhyaya

2016-03-01

Full Text Available Identification of potential genes/alleles governing complex seed-protein content (SPC trait is essential in marker-assisted breeding for quality trait improvement of chickpea. Henceforth, the present study utilized an integrated genomics-assisted breeding strategy encompassing trait association analysis, selective genotyping in traditional bi-parental mapping population and differential expression profiling for the first-time to understand the complex genetic architecture of quantitative SPC trait in chickpea. For GWAS (genome-wide association study, high-throughput genotyping information of 16376 genome-based SNPs (single nucleotide polymorphism discovered from a structured population of 336 sequenced desi and kabuli accessions [with 150-200 kb LD (linkage disequilibrium decay] was utilized. This led to identification of seven most effective genomic loci (genes associated [10 to 20% with 41% combined PVE (phenotypic variation explained] with SPC trait in chickpea. Regardless of the diverse desi and kabuli genetic backgrounds, a comparable level of association potential of the identified seven genomic loci with SPC trait was observed. Five SPC-associated genes were validated successfully in parental accessions and homozygous individuals of an intra-specific desi RIL (recombinant inbred line mapping population (ICC 12299 x ICC 4958 by selective genotyping. The seed-specific expression, including differential up-regulation (> 4-fold of six SPC-associated genes particularly in accessions, parents and homozygous individuals of the aforementioned mapping population with high level of contrasting seed-protein content (21-22% was evident. Collectively, the integrated genomic approach delineated diverse naturally occurring novel functional SNP allelic variants in six potential candidate genes regulating SPC trait in chickpea. Of these, a non-synonymous SNP allele-carrying zinc finger transcription factor gene exhibiting strong association with SPC trait

Genome-wide development and deployment of informative intron-spanning and intron-length polymorphism markers for genomics-assisted breeding applications in chickpea.

Science.gov (United States)

Srivastava, Rishi; Bajaj, Deepak; Sayal, Yogesh K; Meher, Prabina K; Upadhyaya, Hari D; Kumar, Rajendra; Tripathi, Shailesh; Bharadwaj, Chellapilla; Rao, Atmakuri R; Parida, Swarup K

2016-11-01

". The designing of multiple ISM and ILP markers (2-5 markers/gene) from an individual gene (transcription factor) with numerous aforementioned desirable genetic attributes can widen the user-preference to select suitable primer combination for simultaneous large-scale assaying of functional allelic variation, natural allelic diversity, molecular mapping and expression profiling of genes among chickpea accessions. This will essentially accelerate the identification of functionally relevant molecular tags regulating vital agronomic traits for genomics-assisted crop improvement by optimal resource expenses in chickpea. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

New genomic resources for switchgrass: a BAC library and comparative analysis of homoeologous genomic regions harboring bioenergy traits

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Feltus Frank A

2011-07-01

Full Text Available Abstract Background Switchgrass, a C4 species and a warm-season grass native to the prairies of North America, has been targeted for development into an herbaceous biomass fuel crop. Genetic improvement of switchgrass feedstock traits through marker-assisted breeding and biotechnology approaches calls for genomic tools development. Establishment of integrated physical and genetic maps for switchgrass will accelerate mapping of value added traits useful to breeding programs and to isolate important target genes using map based cloning. The reported polyploidy series in switchgrass ranges from diploid (2X = 18 to duodecaploid (12X = 108. Like in other large, repeat-rich plant genomes, this genomic complexity will hinder whole genome sequencing efforts. An extensive physical map providing enough information to resolve the homoeologous genomes would provide the necessary framework for accurate assembly of the switchgrass genome. Results A switchgrass BAC library constructed by partial digestion of nuclear DNA with EcoRI contains 147,456 clones covering the effective genome approximately 10 times based on a genome size of 3.2 Gigabases (~1.6 Gb effective. Restriction digestion and PFGE analysis of 234 randomly chosen BACs indicated that 95% of the clones contained inserts, ranging from 60 to 180 kb with an average of 120 kb. Comparative sequence analysis of two homoeologous genomic regions harboring orthologs of the rice OsBRI1 locus, a low-copy gene encoding a putative protein kinase and associated with biomass, revealed that orthologous clones from homoeologous chromosomes can be unambiguously distinguished from each other and correctly assembled to respective fingerprint contigs. Thus, the data obtained not only provide genomic resources for further analysis of switchgrass genome, but also improve efforts for an accurate genome sequencing strategy. Conclusions The construction of the first switchgrass BAC library and comparative analysis of

Assessment of genomic relationship between Oryza sativa and ...

African Journals Online (AJOL)

STORAGESEVER

2010-03-01

Mar 1, 2010 ... For genomic in situ hybridization, genomic DNA from O. australiensis was used as probe for the mitotic and meiotic ... Wide hybridization is one of the plant breeding approaches ..... Disease and insect resistance in rice.

Genomic prediction of traits related to canine hip dysplasia

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Enrique eSanchez-Molano

2015-03-01

Full Text Available Increased concern for the welfare of pedigree dogs has led to development of selection programs against inherited diseases. An example is canine hip dysplasia (CHD, which has a moderate heritability and a high prevalence in some large-sized breeds. To date, selection using phenotypes has led to only modest improvement, and alternative strategies such as genomic selection may prove more effective. The primary aims of this study were to compare the performance of pedigree- and genomic-based breeding against CHD in the UK Labrador retriever population and to evaluate the performance of different genomic selection methods. A sample of 1179 Labrador Retrievers evaluated for CHD according to the UK scoring method (hip score, HS was genotyped with the Illumina CanineHD BeadChip. Twelve functions of HS and its component traits were analyzed using different statistical methods (GBLUP, Bayes C and Single-Step methods, and results were compared with a pedigree-based approach (BLUP using cross-validation. Genomic methods resulted in similar or higher accuracies than pedigree-based methods with training sets of 944 individuals for all but the untransformed HS, suggesting that genomic selection is an effective strategy. GBLUP and Bayes C gave similar prediction accuracies for HS and related traits, indicating a polygenic architecture. This conclusion was also supported by the low accuracies obtained in additional GBLUP analyses performed using only the SNPs with highest test statistics, also indicating that marker-assisted selection would not be as effective as genomic selection. A Single-Step method that combines genomic and pedigree information also showed higher accuracy than GBLUP and Bayes C for the log-transformed HS, which is currently used for pedigree based evaluations in UK. In conclusion, genomic selection is a promising alternative to pedigree-based selection against CHD, requiring more phenotypes with genomic data to improve further the accuracy

Trends in genome-wide and region-specific genetic diversity in the Dutch-Flemish Holstein-Friesian breeding program from 1986 to 2015.

Science.gov (United States)

Doekes, Harmen P; Veerkamp, Roel F; Bijma, Piter; Hiemstra, Sipke J; Windig, Jack J

2018-04-11

In recent decades, Holstein-Friesian (HF) selection schemes have undergone profound changes, including the introduction of optimal contribution selection (OCS; around 2000), a major shift in breeding goal composition (around 2000) and the implementation of genomic selection (GS; around 2010). These changes are expected to have influenced genetic diversity trends. Our aim was to evaluate genome-wide and region-specific diversity in HF artificial insemination (AI) bulls in the Dutch-Flemish breeding program from 1986 to 2015. Pedigree and genotype data (~ 75.5 k) of 6280 AI-bulls were used to estimate rates of genome-wide inbreeding and kinship and corresponding effective population sizes. Region-specific inbreeding trends were evaluated using regions of homozygosity (ROH). Changes in observed allele frequencies were compared to those expected under pure drift to identify putative regions under selection. We also investigated the direction of changes in allele frequency over time. Effective population size estimates for the 1986-2015 period ranged from 69 to 102. Two major breakpoints were observed in genome-wide inbreeding and kinship trends. Around 2000, inbreeding and kinship levels temporarily dropped. From 2010 onwards, they steeply increased, with pedigree-based, ROH-based and marker-based inbreeding rates as high as 1.8, 2.1 and 2.8% per generation, respectively. Accumulation of inbreeding varied substantially across the genome. A considerable fraction of markers showed changes in allele frequency that were greater than expected under pure drift. Putative selected regions harboured many quantitative trait loci (QTL) associated to a wide range of traits. In consecutive 5-year periods, allele frequencies changed more often in the same direction than in opposite directions, except when comparing the 1996-2000 and 2001-2005 periods. Genome-wide and region-specific diversity trends reflect major changes in the Dutch-Flemish HF breeding program. Introduction of

The genome draft of coconut (Cocos nucifera).

Science.gov (United States)

Xiao, Yong; Xu, Pengwei; Fan, Haikuo; Baudouin, Luc; Xia, Wei; Bocs, Stéphanie; Xu, Junyang; Li, Qiong; Guo, Anping; Zhou, Lixia; Li, Jing; Wu, Yi; Ma, Zilong; Armero, Alix; Issali, Auguste Emmanuel; Liu, Na; Peng, Ming; Yang, Yaodong

2017-11-01

antiporter gene family and ion channel gene families between C. nucifera and Arabidopsis thaliana indicated that significant gene expansion may have occurred in the coconut involving Na+/H+ antiporter, carnitine/acylcarnitine translocase, potassium-dependent sodium-calcium exchanger, and potassium channel genes. Despite its agronomic importance, C. nucifera is still under-studied. In this report, we present a draft genome of C. nucifera and provide genomic information that will facilitate future functional genomics and molecular-assisted breeding in this crop species. © The Author 2017. Published by Oxford University Press.

Assessing Genomic Selection Prediction Accuracy in a Dynamic Barley Breeding Population

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A. H. Sallam

2015-03-01

Full Text Available Prediction accuracy of genomic selection (GS has been previously evaluated through simulation and cross-validation; however, validation based on progeny performance in a plant breeding program has not been investigated thoroughly. We evaluated several prediction models in a dynamic barley breeding population comprised of 647 six-row lines using four traits differing in genetic architecture and 1536 single nucleotide polymorphism (SNP markers. The breeding lines were divided into six sets designated as one parent set and five consecutive progeny sets comprised of representative samples of breeding lines over a 5-yr period. We used these data sets to investigate the effect of model and training population composition on prediction accuracy over time. We found little difference in prediction accuracy among the models confirming prior studies that found the simplest model, random regression best linear unbiased prediction (RR-BLUP, to be accurate across a range of situations. In general, we found that using the parent set was sufficient to predict progeny sets with little to no gain in accuracy from generating larger training populations by combining the parent set with subsequent progeny sets. The prediction accuracy ranged from 0.03 to 0.99 across the four traits and five progeny sets. We explored characteristics of the training and validation populations (marker allele frequency, population structure, and linkage disequilibrium, LD as well as characteristics of the trait (genetic architecture and heritability, . Fixation of markers associated with a trait over time was most clearly associated with reduced prediction accuracy for the mycotoxin trait DON. Higher trait in the training population and simpler trait architecture were associated with greater prediction accuracy.

Aquaculture genomics, genetics and breeding in the United States: Current status, challenges, and priorities for future research

Science.gov (United States)

Advancing the production efficiency and profitability of aquaculture is dependent upon the ability to utilize a diverse array of genetic resources. The ultimate goals of aquaculture genomics, genetics and breeding research are to enhance aquaculture production efficiency, sustainability, product qua...

Computational pan-genomics: status, promises and challenges

NARCIS (Netherlands)

The Computational Pan-Genomics Consortium; T. Marschall (Tobias); M. Marz (Manja); T. Abeel (Thomas); L.J. Dijkstra (Louis); B.E. Dutilh (Bas); A. Ghaffaari (Ali); P. Kersey (Paul); W.P. Kloosterman (Wigard); V. Mäkinen (Veli); A.M. Novak (Adam); B. Paten (Benedict); D. Porubsky (David); E. Rivals (Eric); C. Alkan (Can); J.A. Baaijens (Jasmijn); P.I.W. de Bakker (Paul); V. Boeva (Valentina); R.J.P. Bonnal (Raoul); F. Chiaromonte (Francesca); R. Chikhi (Rayan); F.D. Ciccarelli (Francesca); C.P. Cijvat (Robin); E. Datema (Erwin); C.M. van Duijn (Cornelia); E.E. Eichler (Evan); C. Ernst (Corinna); E. Eskin (Eleazar); E. Garrison (Erik); M. El-Kebir (Mohammed); G.W. Klau (Gunnar); J.O. Korbel (Jan); E.-W. Lameijer (Eric-Wubbo); B. Langmead (Benjamin); M. Martin; P. Medvedev (Paul); J.C. Mu (John); P.B.T. Neerincx (Pieter); K. Ouwens (Klaasjan); P. Peterlongo (Pierre); N. Pisanti (Nadia); S. Rahmann (Sven); B.J. Raphael (Benjamin); K. Reinert (Knut); D. de Ridder (Dick); J. de Ridder (Jeroen); M. Schlesner (Matthias); O. Schulz-Trieglaff (Ole); A.D. Sanders (Ashley); S. Sheikhizadeh (Siavash); C. Shneider (Carl); S. Smit (Sandra); D. Valenzuela (Daniel); J. Wang (Jiayin); L.F.A. Wessels (Lodewyk); Y. Zhang (Ying); V. Guryev (Victor); F. Vandin (Fabio); K. Ye (Kai); A. Schönhuth (Alexander)

2018-01-01

textabstractMany disciplines, from human genetics and oncology to plant breeding, microbiology and virology, commonly face the challenge of analyzing rapidly increasing numbers of genomes. In case of Homo sapiens, the number of sequenced genomes will approach hundreds of thousands in the next few

Marker-assisted-selection (MAS): A fast track to increase genetic ...

African Journals Online (AJOL)

Mapping and tagging of agriculturally important genes have been greatly facilitated by an array of molecular markers in crop plants. Marker-assisted selection (MAS) is gaining considerable importance as it would improve the efficiency of plant breeding through precise transfer of genomic regions of interest (foreground ...

A Bayesian method and its variational approximation for prediction of genomic breeding values in multiple traits

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Hayashi Takeshi

2013-01-01

Full Text Available Abstract Background Genomic selection is an effective tool for animal and plant breeding, allowing effective individual selection without phenotypic records through the prediction of genomic breeding value (GBV. To date, genomic selection has focused on a single trait. However, actual breeding often targets multiple correlated traits, and, therefore, joint analysis taking into consideration the correlation between traits, which might result in more accurate GBV prediction than analyzing each trait separately, is suitable for multi-trait genomic selection. This would require an extension of the prediction model for single-trait GBV to multi-trait case. As the computational burden of multi-trait analysis is even higher than that of single-trait analysis, an effective computational method for constructing a multi-trait prediction model is also needed. Results We described a Bayesian regression model incorporating variable selection for jointly predicting GBVs of multiple traits and devised both an MCMC iteration and variational approximation for Bayesian estimation of parameters in this multi-trait model. The proposed Bayesian procedures with MCMC iteration and variational approximation were referred to as MCBayes and varBayes, respectively. Using simulated datasets of SNP genotypes and phenotypes for three traits with high and low heritabilities, we compared the accuracy in predicting GBVs between multi-trait and single-trait analyses as well as between MCBayes and varBayes. The results showed that, compared to single-trait analysis, multi-trait analysis enabled much more accurate GBV prediction for low-heritability traits correlated with high-heritability traits, by utilizing the correlation structure between traits, while the prediction accuracy for uncorrelated low-heritability traits was comparable or less with multi-trait analysis in comparison with single-trait analysis depending on the setting for prior probability that a SNP has zero

The origin and evolution of fibromelanosis in domesticated chickens: Genomic comparison of Indonesian Cemani and Chinese Silkie breeds.

Directory of Open Access Journals (Sweden)

Anik Budhi Dharmayanthi

Full Text Available Like Chinese Silkie, Indonesian Ayam Cemani exhibits fibromelanosis or dermal hyperpigmentation and possesses complex segmental duplications on chromosome 20 that involve the endothelin 3 gene, EDN3. A genomic region, DR1 of 127 kb, together with another region, DR2 of 171 kb, was duplicated by unequal crossing over, accompanied by inversion of one DR2. Quantitative PCR and copy number variation analyses on the Cemani genome sequence confirmed the duplication of EDN3. These genetic arrangements are identical in Cemani and Silkie, indicating a single origin of the genetic cause of Fm. The two DR1s harbor two distinct EDN3 haplotypes in a form of permanent heterozygosity, although they remain allelic in the ancestral Red Jungle Fowl population and some domesticated chicken breeds, with their allelic divergence time being as recent as 0.3 million years ago. In Cemani and Silkie breeds, artificial selection favoring the Fm phenotype has left an unambiguous record for selective sweep that extends in both directions from tandemly duplicated EDN3 loci. This highly homozygous tract is different in length between Cemani and Silkie, reflecting their distinct breeding histories. It is estimated that the Fm phenotype came into existence at least 6600-9100 years ago, prior to domestication of Cemani and Silkie, and that throughout domestication there has been intense artificial selection with strength s > 50% in each breed.

Genome-Wide Analysis of the World's Sheep Breeds Reveals High Levels of Historic Mixture and Strong Recent Selection

Science.gov (United States)

Kijas, James W.; Lenstra, Johannes A.; Hayes, Ben; Boitard, Simon; Porto Neto, Laercio R.; San Cristobal, Magali; Servin, Bertrand; McCulloch, Russell; Whan, Vicki; Gietzen, Kimberly; Paiva, Samuel; Barendse, William; Ciani, Elena; Raadsma, Herman; McEwan, John; Dalrymple, Brian

2012-01-01

Through their domestication and subsequent selection, sheep have been adapted to thrive in a diverse range of environments. To characterise the genetic consequence of both domestication and selection, we genotyped 49,034 SNP in 2,819 animals from a diverse collection of 74 sheep breeds. We find the majority of sheep populations contain high SNP diversity and have retained an effective population size much higher than most cattle or dog breeds, suggesting domestication occurred from a broad genetic base. Extensive haplotype sharing and generally low divergence time between breeds reveal frequent genetic exchange has occurred during the development of modern breeds. A scan of the genome for selection signals revealed 31 regions containing genes for coat pigmentation, skeletal morphology, body size, growth, and reproduction. We demonstrate the strongest selection signal has occurred in response to breeding for the absence of horns. The high density map of genetic variability provides an in-depth view of the genetic history for this important livestock species. PMID:22346734

Genome-wide analysis of the world's sheep breeds reveals high levels of historic mixture and strong recent selection.

Directory of Open Access Journals (Sweden)

James W Kijas

2012-02-01

Full Text Available Through their domestication and subsequent selection, sheep have been adapted to thrive in a diverse range of environments. To characterise the genetic consequence of both domestication and selection, we genotyped 49,034 SNP in 2,819 animals from a diverse collection of 74 sheep breeds. We find the majority of sheep populations contain high SNP diversity and have retained an effective population size much higher than most cattle or dog breeds, suggesting domestication occurred from a broad genetic base. Extensive haplotype sharing and generally low divergence time between breeds reveal frequent genetic exchange has occurred during the development of modern breeds. A scan of the genome for selection signals revealed 31 regions containing genes for coat pigmentation, skeletal morphology, body size, growth, and reproduction. We demonstrate the strongest selection signal has occurred in response to breeding for the absence of horns. The high density map of genetic variability provides an in-depth view of the genetic history for this important livestock species.

Assigning breed origin to alleles in crossbred animals.

Science.gov (United States)

Vandenplas, Jérémie; Calus, Mario P L; Sevillano, Claudia A; Windig, Jack J; Bastiaansen, John W M

2016-08-22

For some species, animal production systems are based on the use of crossbreeding to take advantage of the increased performance of crossbred compared to purebred animals. Effects of single nucleotide polymorphisms (SNPs) may differ between purebred and crossbred animals for several reasons: (1) differences in linkage disequilibrium between SNP alleles and a quantitative trait locus; (2) differences in genetic backgrounds (e.g., dominance and epistatic interactions); and (3) differences in environmental conditions, which result in genotype-by-environment interactions. Thus, SNP effects may be breed-specific, which has led to the development of genomic evaluations for crossbred performance that take such effects into account. However, to estimate breed-specific effects, it is necessary to know breed origin of alleles in crossbred animals. Therefore, our aim was to develop an approach for assigning breed origin to alleles of crossbred animals (termed BOA) without information on pedigree and to study its accuracy by considering various factors, including distance between breeds. The BOA approach consists of: (1) phasing genotypes of purebred and crossbred animals; (2) assigning breed origin to phased haplotypes; and (3) assigning breed origin to alleles of crossbred animals based on a library of assigned haplotypes, the breed composition of crossbred animals, and their SNP genotypes. The accuracy of allele assignments was determined for simulated datasets that include crosses between closely-related, distantly-related and unrelated breeds. Across these scenarios, the percentage of alleles of a crossbred animal that were correctly assigned to their breed origin was greater than 90 %, and increased with increasing distance between breeds, while the percentage of incorrectly assigned alleles was always less than 2 %. For the remaining alleles, i.e. 0 to 10 % of all alleles of a crossbred animal, breed origin could not be assigned. The BOA approach accurately assigns

Genomic Prediction from Whole Genome Sequence in Livestock: The 1000 Bull Genomes Project

DEFF Research Database (Denmark)

Hayes, Benjamin J; MacLeod, Iona M; Daetwyler, Hans D

Advantages of using whole genome sequence data to predict genomic estimated breeding values (GEBV) include better persistence of accuracy of GEBV across generations and more accurate GEBV across breeds. The 1000 Bull Genomes Project provides a database of whole genome sequenced key ancestor bulls....... In a dairy data set, predictions using BayesRC and imputed sequence data from 1000 Bull Genomes were 2% more accurate than with 800k data. We could demonstrate the method identified causal mutations in some cases. Further improvements will come from more accurate imputation of sequence variant genotypes...

Current development and application of soybean genomics

Institute of Scientific and Technical Information of China (English)

Lingli HE; Jing ZHAO; Man ZHAO; Chaoying HE

2011-01-01

Soybean (Glycine max),an important domesticated species originated in China,constitutes a major source of edible oils and high-quality plant proteins worldwide.In spite of its complex genome as a consequence of an ancient tetraploidilization,platforms for map-based genomics,sequence-based genomics,comparative genomics and functional genomics have been well developed in the last decade,thus rich repertoires of genomic tools and resources are available,which have been influencing the soybean genetic improvement.Here we mainly review the progresses of soybean (including its wild relative Glycine soja) genomics and its impetus for soybean breeding,and raise the major biological questions needing to be addressed.Genetic maps,physical maps,QTL and EST mapping have been so well achieved that the marker assisted selection and positional cloning in soybean is feasible and even routine.Whole genome sequencing and transcriptomic analyses provide a large collection of molecular markers and predicted genes,which are instrumental to comparative genomics and functional genomics.Comparative genomics has started to reveal the evolution of soybean genome and the molecular basis of soybean domestication process.Microarrays resources,mutagenesis and efficient transformation systems become essential components of soybean functional genomics.Furthermore,phenotypic functional genomics via both forward and reverse genetic approaches has inferred functions of many genes involved in plant and seed development,in response to abiotic stresses,functioning in plant-pathogenic microbe interactions,and controlling the oil and protein content of seed.These achievements have paved the way for generation of transgenic or genetically modified (GM) soybean crops.

Sequence- vs. chip-assisted genomic selection: accurate biological information is advised.

Science.gov (United States)

Pérez-Enciso, Miguel; Rincón, Juan C; Legarra, Andrés

2015-05-09

The development of next-generation sequencing technologies (NGS) has made the use of whole-genome sequence data for routine genetic evaluations possible, which has triggered a considerable interest in animal and plant breeding fields. Here, we investigated whether complete or partial sequence data can improve upon existing SNP (single nucleotide polymorphism) array-based selection strategies by simulation using a mixed coalescence - gene-dropping approach. We simulated 20 or 100 causal mutations (quantitative trait nucleotides, QTN) within 65 predefined 'gene' regions, each 10 kb long, within a genome composed of ten 3-Mb chromosomes. We compared prediction accuracy by cross-validation using a medium-density chip (7.5 k SNPs), a high-density (HD, 17 k) and sequence data (335 k). Genetic evaluation was based on a GBLUP method. The simulations showed: (1) a law of diminishing returns with increasing number of SNPs; (2) a modest effect of SNP ascertainment bias in arrays; (3) a small advantage of using whole-genome sequence data vs. HD arrays i.e. ~4%; (4) a minor effect of NGS errors except when imputation error rates are high (≥20%); and (5) if QTN were known, prediction accuracy approached 1. Since this is obviously unrealistic, we explored milder assumptions. We showed that, if all SNPs within causal genes were included in the prediction model, accuracy could also dramatically increase by ~40%. However, this criterion was highly sensitive to either misspecification (including wrong genes) or to the use of an incomplete gene list; in these cases, accuracy fell rapidly towards that reached when all SNPs from sequence data were blindly included in the model. Our study shows that, unless an accurate prior estimate on the functionality of SNPs can be included in the predictor, there is a law of diminishing returns with increasing SNP density. As a result, use of whole-genome sequence data may not result in a highly increased selection response over high

Comparative genomics and association mapping approaches for blast resistant genes in finger millet using SSRs.

Science.gov (United States)

Babu, B Kalyana; Dinesh, Pandey; Agrawal, Pawan K; Sood, S; Chandrashekara, C; Bhatt, Jagadish C; Kumar, Anil

2014-01-01

The major limiting factor for production and productivity of finger millet crop is blast disease caused by Magnaporthe grisea. Since, the genome sequence information available in finger millet crop is scarce, comparative genomics plays a very important role in identification of genes/QTLs linked to the blast resistance genes using SSR markers. In the present study, a total of 58 genic SSRs were developed for use in genetic analysis of a global collection of 190 finger millet genotypes. The 58 SSRs yielded ninety five scorable alleles and the polymorphism information content varied from 0.186 to 0.677 at an average of 0.385. The gene diversity was in the range of 0.208 to 0.726 with an average of 0.487. Association mapping for blast resistance was done using 104 SSR markers which identified four QTLs for finger blast and one QTL for neck blast resistance. The genomic marker RM262 and genic marker FMBLEST32 were linked to finger blast disease at a P value of 0.007 and explained phenotypic variance (R²) of 10% and 8% respectively. The genomic marker UGEP81 was associated to finger blast at a P value of 0.009 and explained 7.5% of R². The QTLs for neck blast was associated with the genomic SSR marker UGEP18 at a P value of 0.01, which explained 11% of R². Three QTLs for blast resistance were found common by using both GLM and MLM approaches. The resistant alleles were found to be present mostly in the exotic genotypes. Among the genotypes of NW Himalayan region of India, VHC3997, VHC3996 and VHC3930 were found highly resistant, which may be effectively used as parents for developing blast resistant cultivars in the NW Himalayan region of India. The markers linked to the QTLs for blast resistance in the present study can be further used for cloning of the full length gene, fine mapping and their further use in the marker assisted breeding programmes for introgression of blast resistant alleles into locally adapted cultivars.

Avian cooperative breeding: Old hypotheses and new directions.

Science.gov (United States)

Heinsohn, R G; Cockburn, A; Mulder, R A

1990-12-01

In cooperatively breeding birds, individuals that appear capable of reproducing on their own may instead assist others with their breeding efforts. Research into avian cooperative breeding has attempted to reconcile the apparent altruism of this behaviour with maximization of inclusive fitness. Most explanations of cooperative breeding have suggested that philopatry is enforced by ecological constraints, such as a shortage of resources critical to breeding. Non-dispersers may then benefit both directly and indirectly from contributing at the nest. Recent research has shown that such benefits may be sufficient to promote philopatry, without the need for ecological constraints, and emphasizes that consideration of both costs and benefits of philopatry is essential for a comprehensive approach to the problem. The growing body of data from long-term studies of different species should combine with an improved phylogenetic perspective on cooperative breeding, to provide a useful base for future comparative analyses and experimentation. Copyright © 1990. Published by Elsevier Ltd.

Plant Breeding Goes Microbial

NARCIS (Netherlands)

Wei, Zhong; Jousset, Alexandre

Plant breeding has traditionally improved traits encoded in the plant genome. Here we propose an alternative framework reaching novel phenotypes by modifying together genomic information and plant-associated microbiota. This concept is made possible by a novel technology that enables the

Strategies for Selecting Crosses Using Genomic Prediction in Two Wheat Breeding Programs.

Science.gov (United States)

Lado, Bettina; Battenfield, Sarah; Guzmán, Carlos; Quincke, Martín; Singh, Ravi P; Dreisigacker, Susanne; Peña, R Javier; Fritz, Allan; Silva, Paula; Poland, Jesse; Gutiérrez, Lucía

2017-07-01

The single most important decision in plant breeding programs is the selection of appropriate crosses. The ideal cross would provide superior predicted progeny performance and enough diversity to maintain genetic gain. The aim of this study was to compare the best crosses predicted using combinations of mid-parent value and variance prediction accounting for linkage disequilibrium (V) or assuming linkage equilibrium (V). After predicting the mean and the variance of each cross, we selected crosses based on mid-parent value, the top 10% of the progeny, and weighted mean and variance within progenies for grain yield, grain protein content, mixing time, and loaf volume in two applied wheat ( L.) breeding programs: Instituto Nacional de Investigación Agropecuaria (INIA) Uruguay and CIMMYT Mexico. Although the variance of the progeny is important to increase the chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses drove the genetic gain but the variance of the progeny had a small impact on genetic gain for grain yield. However, the relative importance of the variance of the progeny was larger for quality traits. Overall, the genomic resources and the statistical models are now available to plant breeders to predict both the performance of breeding lines per se as well as the value of progeny from any potential crosses. Copyright © 2017 Crop Science Society of America.

Genomic prediction for tuberculosis resistance in dairy cattle.

Directory of Open Access Journals (Sweden)

Smaragda Tsairidou

Full Text Available The increasing prevalence of bovine tuberculosis (bTB in the UK and the limitations of the currently available diagnostic and control methods require the development of complementary approaches to assist in the sustainable control of the disease. One potential approach is the identification of animals that are genetically more resistant to bTB, to enable breeding of animals with enhanced resistance. This paper focuses on prediction of resistance to bTB. We explore estimation of direct genomic estimated breeding values (DGVs for bTB resistance in UK dairy cattle, using dense SNP chip data, and test these genomic predictions for situations when disease phenotypes are not available on selection candidates.We estimated DGVs using genomic best linear unbiased prediction methodology, and assessed their predictive accuracies with a cross validation procedure and receiver operator characteristic (ROC curves. Furthermore, these results were compared with theoretical expectations for prediction accuracy and area-under-the-ROC-curve (AUC. The dataset comprised 1151 Holstein-Friesian cows (bTB cases or controls. All individuals (592 cases and 559 controls were genotyped for 727,252 loci (Illumina Bead Chip. The estimated observed heritability of bTB resistance was 0.23±0.06 (0.34 on the liability scale and five-fold cross validation, replicated six times, provided a prediction accuracy of 0.33 (95% C.I.: 0.26, 0.40. ROC curves, and the resulting AUC, gave a probability of 0.58, averaged across six replicates, of correctly classifying cows as diseased or as healthy based on SNP chip genotype alone using these data.These results provide a first step in the investigation of the potential feasibility of genomic selection for bTB resistance using SNP data. Specifically, they demonstrate that genomic selection is possible, even in populations with no pedigree data and on animals lacking bTB phenotypes. However, a larger training population will be required to

Marker-assisted selection in poultry

International Nuclear Information System (INIS)

Koning, D.-J. de; Hocking, P.M.

2007-01-01

Among livestock species, chicken has the most extensive genomics toolbox available for detection of quantitative trait loci (QTL) and marker-assisted selection (MAS). The uptake of MAS is therefore not limited by technical resources but mostly by the priorities and financial constraints of the few remaining poultry breeding companies. With the cost of genotyping decreasing rapidly, an increase in the use of direct trait- single nucleotide polymorphism (SNP)-associations in MAS can be predicted. (author)

Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery

OpenAIRE

Hickey, John M; Chiurugwi, Tinashe; Mackay, Ian; Powell, Wayne; Implementing Genomic Selection in CGIAR Breeding Programs Workshop Participants

2017-01-01

The rate of annual yield increases for major staple crops must more than double relative to current levels in order to feed a predicted global population of 9 billion by 2050. Controlled hybridization and selective breeding have been used for centuries to adapt plant and animal species for human use. However, achieving higher, sustainable rates of improvement in yields in various species will require renewed genetic interventions and dramatic improvement of agricultural practices. Genomic pre...

Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds.

Science.gov (United States)

Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter

2017-08-10

A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of "Gene Ontology" (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability. Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020). Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of

Genetic Study of the Manganese Use Efficiency Trait in Winter Barley (Hordeum vulgare L.) by Genome- Wide Association and Genomic Selection

DEFF Research Database (Denmark)

Leplat, Florian Jean Victor

Manganese (Mn) deficiency remains an unsolved nutritional problem affecting crop production worldwide. The tolerance to Mn limiting conditions, known as Mn efficiency, is a quantitative abiotic stress trait, generally controlled by several genes. However the underlying genetic background of Mn...... functionality in Mn dependent pathways and processes. In a the second step, a genuine statistical method to assist breeding programs in selecting new varieties, named Genomic Selection (GS), was applied. It was demonstrated that GS is an effective tool to be used in breeding programs for selecting more...

An innovative procedure of genome-wide association analysis fits studies on germplasm population and plant breeding.

Science.gov (United States)

He, Jianbo; Meng, Shan; Zhao, Tuanjie; Xing, Guangnan; Yang, Shouping; Li, Yan; Guan, Rongzhan; Lu, Jiangjie; Wang, Yufeng; Xia, Qiuju; Yang, Bing; Gai, Junyi

2017-11-01

The innovative RTM-GWAS procedure provides a relatively thorough detection of QTL and their multiple alleles for germplasm population characterization, gene network identification, and genomic selection strategy innovation in plant breeding. The previous genome-wide association studies (GWAS) have been concentrated on finding a handful of major quantitative trait loci (QTL), but plant breeders are interested in revealing the whole-genome QTL-allele constitution in breeding materials/germplasm (in which tremendous historical allelic variation has been accumulated) for genome-wide improvement. To match this requirement, two innovations were suggested for GWAS: first grouping tightly linked sequential SNPs into linkage disequilibrium blocks (SNPLDBs) to form markers with multi-allelic haplotypes, and second utilizing two-stage association analysis for QTL identification, where the markers were preselected by single-locus model followed by multi-locus multi-allele model stepwise regression. Our proposed GWAS procedure is characterized as a novel restricted two-stage multi-locus multi-allele GWAS (RTM-GWAS, https://github.com/njau-sri/rtm-gwas ). The Chinese soybean germplasm population (CSGP) composed of 1024 accessions with 36,952 SNPLDBs (generated from 145,558 SNPs, with reduced linkage disequilibrium decay distance) was used to demonstrate the power and efficiency of RTM-GWAS. Using the CSGP marker information, simulation studies demonstrated that RTM-GWAS achieved the highest QTL detection power and efficiency compared with the previous procedures, especially under large sample size and high trait heritability conditions. A relatively thorough detection of QTL with their multiple alleles was achieved by RTM-GWAS compared with the linear mixed model method on 100-seed weight in CSGP. A QTL-allele matrix (402 alleles of 139 QTL × 1024 accessions) was established as a compact form of the population genetic constitution. The 100-seed weight QTL-allele matrix was

Short communication: Genotyping of cows to speed up availability of genomic estimated breeding values for direct health traits in Austrian Fleckvieh (Simmental) cattle--genetic and economic aspects.

Science.gov (United States)

Egger-Danner, C; Schwarzenbacher, H; Willam, A

2014-07-01

The aim of this study was to quantify the impact of genotyping cows with reliable phenotypes for direct health traits on annual monetary genetic gain (AMGG) and discounted profit. The calculations were based on a deterministic approach using ZPLAN software (University of Hohenheim, Stuttgart, Germany). It was assumed that increases in reliability of the total merit index (TMI) of 5, 15, and 25 percentage points were achieved through genotyping 5,000, 25,000, and 50,000 cows, respectively. Costs for phenotyping, genotyping, and genomic estimated breeding values vary between €150 and €20 per cow. The gain in genotyping cows for traits with medium to high heritability is more than for direct health traits with low heritability. The AMGG is increased by 1.5% if the reliability of TMI is 5 percentage points higher (i.e., 5,000 cows genotyped) and 6.53% higher AMGG can be expected when the reliability of TMI is increased by 25 percentage points (i.e., 50,000 cows genotyped). The discounted profit depends not only on the costs of genotyping but also on the population size. This study indicates that genotyping cows with reliable phenotypes is feasible to speed up the availability of genomic estimated breeding values for direct health traits. But, because of the huge amount of valid phenotypes and genotypes needed to establish an efficient genomic evaluation, it is likely that financial constraints will be the main limiting factor for implementation into breeding program such as Fleckvieh Austria. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genomic predictions across Nordic Holstein and Nordic Red using the genomic best linear unbiased prediction model with different genomic relationship matrices.

Science.gov (United States)

Zhou, L; Lund, M S; Wang, Y; Su, G

2014-08-01

This study investigated genomic predictions across Nordic Holstein and Nordic Red using various genomic relationship matrices. Different sources of information, such as consistencies of linkage disequilibrium (LD) phase and marker effects, were used to construct the genomic relationship matrices (G-matrices) across these two breeds. Single-trait genomic best linear unbiased prediction (GBLUP) model and two-trait GBLUP model were used for single-breed and two-breed genomic predictions. The data included 5215 Nordic Holstein bulls and 4361 Nordic Red bulls, which was composed of three populations: Danish Red, Swedish Red and Finnish Ayrshire. The bulls were genotyped with 50 000 SNP chip. Using the two-breed predictions with a joint Nordic Holstein and Nordic Red reference population, accuracies increased slightly for all traits in Nordic Red, but only for some traits in Nordic Holstein. Among the three subpopulations of Nordic Red, accuracies increased more for Danish Red than for Swedish Red and Finnish Ayrshire. This is because closer genetic relationships exist between Danish Red and Nordic Holstein. Among Danish Red, individuals with higher genomic relationship coefficients with Nordic Holstein showed more increased accuracies in the two-breed predictions. Weighting the two-breed G-matrices by LD phase consistencies, marker effects or both did not further improve accuracies of the two-breed predictions. © 2014 Blackwell Verlag GmbH.

Development of genomic SSR and potential EST-SSR markers in ...

African Journals Online (AJOL)

In addition, forty four EST-SSRs which can be amplified with expected sizes were identified from a B. chinense root cDNA library. The genomic SSR markers and potential EST-SSR markers developed in the present study should be useful for genetic diversity and molecular marker assistant selection breeding research in ...

Molecular Breeding of Rice Restorer Lines and Hybrids for Brown Planthopper (BPH) Resistance Using the Bph14 and Bph15 Genes.

Science.gov (United States)

Wang, Hongbo; Ye, Shengtuo; Mou, Tongmin

2016-12-01

The development of hybrid rice is a practical approach for increasing rice production. However, the brown planthopper (BPH), Nilaparvata lugens Stål, causes severe yield loss of rice (Oryza sativa L.) and can threaten food security. Therefore, breeding hybrid rice resistant to BPH is the most effective and economical strategy to maintain high and stable production. Fortunately, numerous BPH resistance genes have been identified, and abundant linkage markers are available for molecular marker-assisted selection (MAS) in breeding programs. Hence, we pyramided two BPH resistance genes, Bph14 and Bph15, into a susceptive CMS restorer line Huahui938 and its derived hybrids using MAS to improve the BPH resistance of hybrid rice. Three near-isogenic lines (NILs) with pyramided Bph14 and Bph15 were obtained by molecular marker-assisted backcross (MAB) and phenotypic selection. The genomic components of these NILs were detected using the whole-genome SNP (Single nucleotide polymorphism) array, RICE6K, suggesting that the recurrent parent genome (RPG) recovery of the NILs was 87.88, 87.70 and 86.62 %, respectively. BPH bioassays showed that the improved NILs and their derived hybrids carrying homozygous Bph14 and Bph15 were resistant to BPH. However, the hybrids with heterozygous Bph14 and Bph15 remained susceptible to BPH. The developed NILs showed no significant differences in major agronomic traits and rice qualities compared with the recurrent parent. Moreover, the improved hybrids derived from the NILs exhibited better agronomic performance and rice quality compared with the controls under natural field conditions. This study demonstrates that it is essential to stack Bph14 and Bph15 into both the maternal and paternal parents for developing BPH-resistant hybrid rice varieties. The SNP array with abundant DNA markers is an efficient tool for analyzing the RPG recovery of progenies and can be used to monitor the donor segments in NILs, thus being extremely important

Genomics of pear and other Rosaceae fruit trees.

Science.gov (United States)

Yamamoto, Toshiya; Terakami, Shingo

2016-01-01

The family Rosaceae includes many economically important fruit trees, such as pear, apple, peach, cherry, quince, apricot, plum, raspberry, and loquat. Over the past few years, whole-genome sequences have been released for Chinese pear, European pear, apple, peach, Japanese apricot, and strawberry. These sequences help us to conduct functional and comparative genomics studies and to develop new cultivars with desirable traits by marker-assisted selection in breeding programs. These genomics resources also allow identification of evolutionary relationships in Rosaceae, development of genome-wide SNP and SSR markers, and construction of reference genetic linkage maps, which are available through the Genome Database for the Rosaceae website. Here, we review the recent advances in genomics studies and their practical applications for Rosaceae fruit trees, particularly pear, apple, peach, and cherry.

A roadmap for breeding orphan leafy vegetable species: a case study of Gynandropsis gynandra (Cleomaceae).

Science.gov (United States)

Sogbohossou, E O Deedi; Achigan-Dako, Enoch G; Maundu, Patrick; Solberg, Svein; Deguenon, Edgar M S; Mumm, Rita H; Hale, Iago; Van Deynze, Allen; Schranz, M Eric

2018-01-01

Despite an increasing awareness of the potential of "orphan" or unimproved crops to contribute to food security and enhanced livelihoods for farmers, coordinated research agendas to facilitate production and use of orphan crops by local communities are generally lacking. We provide an overview of the current knowledge on leafy vegetables with a focus on Gynandropsis gynandra , a highly nutritious species used in Africa and Asia, and highlight general and species-specific guidelines for participatory, genomics-assisted breeding of orphan crops. Key steps in genome-enabled orphan leafy vegetables improvement are identified and discussed in the context of Gynandropsis gynandra breeding, including: (1) germplasm collection and management; (2) product target definition and refinement; (3) characterization of the genetic control of key traits; (4) design of the 'process' for cultivar development; (5) integration of genomic data to optimize that 'process'; (6) multi-environmental participatory testing and end-user evaluation; and (7) crop value chain development. The review discusses each step in detail, with emphasis on improving leaf yield, phytonutrient content, organoleptic quality, resistance to biotic and abiotic stresses and post-harvest management.

Genetically influenced resistance to stress and disease in salmonids in relation to present-day breeding practice - a short review

Czech Academy of Sciences Publication Activity Database

Mendel, Jan; Jánová, K.; Palíková, M.

2018-01-01

Roč. 87, č. 1 (2018), s. 35-45 ISSN 0001-7213 R&D Projects: GA MZe QJ1510077 Institutional support: RVO:68081766 Keywords : brook trout * disease resistance * genomic selection * marker assisted selection * molecular breeding * quantitative trait loci * rainbow trout Subject RIV: GL - Fish ing OBOR OECD: Fish ery Impact factor: 0.415, year: 2016

Simultaneous improvement of grain yield and protein content in durum wheat by different phenotypic indices and genomic selection.

Science.gov (United States)

Rapp, M; Lein, V; Lacoudre, F; Lafferty, J; Müller, E; Vida, G; Bozhanova, V; Ibraliu, A; Thorwarth, P; Piepho, H P; Leiser, W L; Würschum, T; Longin, C F H

2018-06-01

Simultaneous improvement of protein content and grain yield by index selection is possible but its efficiency largely depends on the weighting of the single traits. The genetic architecture of these indices is similar to that of the primary traits. Grain yield and protein content are of major importance in durum wheat breeding, but their negative correlation has hampered their simultaneous improvement. To account for this in wheat breeding, the grain protein deviation (GPD) and the protein yield were proposed as targets for selection. The aim of this work was to investigate the potential of different indices to simultaneously improve grain yield and protein content in durum wheat and to evaluate their genetic architecture towards genomics-assisted breeding. To this end, we investigated two different durum wheat panels comprising 159 and 189 genotypes, which were tested in multiple field locations across Europe and genotyped by a genotyping-by-sequencing approach. The phenotypic analyses revealed significant genetic variances for all traits and heritabilities of the phenotypic indices that were in a similar range as those of grain yield and protein content. The GPD showed a high and positive correlation with protein content, whereas protein yield was highly and positively correlated with grain yield. Thus, selecting for a high GPD would mainly increase the protein content whereas a selection based on protein yield would mainly improve grain yield, but a combination of both indices allows to balance this selection. The genome-wide association mapping revealed a complex genetic architecture for all traits with most QTL having small effects and being detected only in one germplasm set, thus limiting the potential of marker-assisted selection for trait improvement. By contrast, genome-wide prediction appeared promising but its performance strongly depends on the relatedness between training and prediction sets.

Genomic diversity and introgression in O. sativa reveal the impact of domestication and breeding on the rice genome.

Directory of Open Access Journals (Sweden)

Keyan Zhao

2010-05-01

Full Text Available The domestication of Asian rice (Oryza sativa was a complex process punctuated by episodes of introgressive hybridization among and between subpopulations. Deep genetic divergence between the two main varietal groups (Indica and Japonica suggests domestication from at least two distinct wild populations. However, genetic uniformity surrounding key domestication genes across divergent subpopulations suggests cultural exchange of genetic material among ancient farmers.In this study, we utilize a novel 1,536 SNP panel genotyped across 395 diverse accessions of O. sativa to study genome-wide patterns of polymorphism, to characterize population structure, and to infer the introgression history of domesticated Asian rice. Our population structure analyses support the existence of five major subpopulations (indica, aus, tropical japonica, temperate japonica and GroupV consistent with previous analyses. Our introgression analysis shows that most accessions exhibit some degree of admixture, with many individuals within a population sharing the same introgressed segment due to artificial selection. Admixture mapping and association analysis of amylose content and grain length illustrate the potential for dissecting the genetic basis of complex traits in domesticated plant populations.Genes in these regions control a myriad of traits including plant stature, blast resistance, and amylose content. These analyses highlight the power of population genomics in agricultural systems to identify functionally important regions of the genome and to decipher the role of human-directed breeding in refashioning the genomes of a domesticated species.

The pomegranate (Punica granatum L.) genome and the genomics of punicalagin biosynthesis.

Science.gov (United States)

Qin, Gaihua; Xu, Chunyan; Ming, Ray; Tang, Haibao; Guyot, Romain; Kramer, Elena M; Hu, Yudong; Yi, Xingkai; Qi, Yongjie; Xu, Xiangyang; Gao, Zhenghui; Pan, Haifa; Jian, Jianbo; Tian, Yinping; Yue, Zhen; Xu, Yiliu

2017-09-01

Pomegranate (Punica granatum L.) is a perennial fruit crop grown since ancient times that has been planted worldwide and is known for its functional metabolites, particularly punicalagins. We have sequenced and assembled the pomegranate genome with 328 Mb anchored into nine pseudo-chromosomes and annotated 29 229 gene models. A Myrtales lineage-specific whole-genome duplication event was detected that occurred in the common ancestor before the divergence of pomegranate and Eucalyptus. Repetitive sequences accounted for 46.1% of the assembled genome. We found that the integument development gene INNER NO OUTER (INO) was under positive selection and potentially contributed to the development of the fleshy outer layer of the seed coat, an edible part of pomegranate fruit. The genes encoding the enzymes for synthesis and degradation of lignin, hemicelluloses and cellulose were also differentially expressed between soft- and hard-seeded varieties, reflecting differences in their accumulation in cultivars differing in seed hardness. Candidate genes for punicalagin biosynthesis were identified and their expression patterns indicated that gallic acid synthesis in tissues could follow different biochemical pathways. The genome sequence of pomegranate provides a valuable resource for the dissection of many biological and biochemical traits and also provides important insights for the acceleration of breeding. Elucidation of the biochemical pathway(s) involved in punicalagin biosynthesis could assist breeding efforts to increase production of this bioactive compound. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Bayesian methods for jointly estimating genomic breeding values of one continuous and one threshold trait.

Directory of Open Access Journals (Sweden)

Chonglong Wang

Full Text Available Genomic selection has become a useful tool for animal and plant breeding. Currently, genomic evaluation is usually carried out using a single-trait model. However, a multi-trait model has the advantage of using information on the correlated traits, leading to more accurate genomic prediction. To date, joint genomic prediction for a continuous and a threshold trait using a multi-trait model is scarce and needs more attention. Based on the previously proposed methods BayesCπ for single continuous trait and BayesTCπ for single threshold trait, we developed a novel method based on a linear-threshold model, i.e., LT-BayesCπ, for joint genomic prediction of a continuous trait and a threshold trait. Computing procedures of LT-BayesCπ using Markov Chain Monte Carlo algorithm were derived. A simulation study was performed to investigate the advantages of LT-BayesCπ over BayesCπ and BayesTCπ with regard to the accuracy of genomic prediction on both traits. Factors affecting the performance of LT-BayesCπ were addressed. The results showed that, in all scenarios, the accuracy of genomic prediction obtained from LT-BayesCπ was significantly increased for the threshold trait compared to that from single trait prediction using BayesTCπ, while the accuracy for the continuous trait was comparable with that from single trait prediction using BayesCπ. The proposed LT-BayesCπ could be a method of choice for joint genomic prediction of one continuous and one threshold trait.

A RecET-assisted CRISPR-Cas9 genome editing in Corynebacterium glutamicum.

Science.gov (United States)

Wang, Bo; Hu, Qitiao; Zhang, Yu; Shi, Ruilin; Chai, Xin; Liu, Zhe; Shang, Xiuling; Zhang, Yun; Wen, Tingyi

2018-04-23

Extensive modification of genome is an efficient manner to regulate the metabolic network for producing target metabolites or non-native products using Corynebacterium glutamicum as a cell factory. Genome editing approaches by means of homologous recombination and counter-selection markers are laborious and time consuming due to multiple round manipulations and low editing efficiencies. The current two-plasmid-based CRISPR-Cas9 editing methods generate false positives due to the potential instability of Cas9 on the plasmid, and require a high transformation efficiency for co-occurrence of two plasmids transformation. Here, we developed a RecET-assisted CRISPR-Cas9 genome editing method using a chromosome-borne Cas9-RecET and a single plasmid harboring sgRNA and repair templates. The inducible expression of chromosomal RecET promoted the frequencies of homologous recombination, and increased the efficiency for gene deletion. Due to the high transformation efficiency of a single plasmid, this method enabled 10- and 20-kb region deletion, 2.5-, 5.7- and 7.5-kb expression cassette insertion and precise site-specific mutation, suggesting a versatility of this method. Deletion of argR and farR regulators as well as site-directed mutation of argB and pgi genes generated the mutant capable of accumulating L-arginine, indicating the stability of chromosome-borne Cas9 for iterative genome editing. Using this method, the model-predicted target genes were modified to redirect metabolic flux towards 1,2-propanediol biosynthetic pathway. The final engineered strain produced 6.75 ± 0.46 g/L of 1,2-propanediol that is the highest titer reported in C. glutamicum. Furthermore, this method is available for Corynebacterium pekinense 1.563, suggesting its universal applicability in other Corynebacterium species. The RecET-assisted CRISPR-Cas9 genome editing method will facilitate engineering of metabolic networks for the synthesis of interested bio-based products from renewable

Exploiting Genomic Resources for Efficient Conservation and Use of Chickpea, Groundnut, and Pigeonpea Collections for Crop Improvement

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C. L. Laxmipathi Gowda

2013-11-01

Full Text Available Both chickpea ( L. and pigeonpea [ (L. Millsp.] are important dietary source of protein while groundnut ( L. is one of the major oil crops. Globally, approximately 1.1 million grain legume accessions are conserved in genebanks, of which the ICRISAT genebank holds 49,485 accessions of cultivated species and wild relatives of chickpea, pigeonpea, and groundnut from 133 countries. These genetic resources are reservoirs of many useful genes for present and future crop improvement programs. Representative subsets in the form of core and mini core collections have been used to identify trait-specific genetically diverse germplasm for use in breeding and genomic studies in these crops. Chickpea, groundnut, and pigeonpea have moved from “orphan” to “genomic resources rich crops.” The chickpea and pigeonpea genomes have been decoded, and the sequences of groundnut genome will soon be available. With the availability of these genomic resources, the germplasm curators, breeders, and molecular biologists will have abundant opportunities to enhance the efficiency of genebank operations, mine allelic variations in germplasm collection, identify genetically diverse germplasm with beneficial traits, broaden the cultigen’s genepool, and accelerate the cultivar development to address new challenges to production, particularly with respect to climate change and variability. Marker-assisted breeding approaches have already been initiated for some traits in chickpea and groundnut, which should lead to enhanced efficiency and efficacy of crop improvement. Resistance to some pests and diseases has been successfully transferred from wild relatives to cultivated species.

Annotation-Based Whole Genomic Prediction and Selection

DEFF Research Database (Denmark)

Kadarmideen, Haja; Do, Duy Ngoc; Janss, Luc

Genomic selection is widely used in both animal and plant species, however, it is performed with no input from known genomic or biological role of genetic variants and therefore is a black box approach in a genomic era. This study investigated the role of different genomic regions and detected QTLs...... in their contribution to estimated genomic variances and in prediction of genomic breeding values by applying SNP annotation approaches to feed efficiency. Ensembl Variant Predictor (EVP) and Pig QTL database were used as the source of genomic annotation for 60K chip. Genomic prediction was performed using the Bayes...... classes. Predictive accuracy was 0.531, 0.532, 0.302, and 0.344 for DFI, RFI, ADG and BF, respectively. The contribution per SNP to total genomic variance was similar among annotated classes across different traits. Predictive performance of SNP classes did not significantly differ from randomized SNP...

Comparative genomics and association mapping approaches for blast resistant genes in finger millet using SSRs.

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B Kalyana Babu

Full Text Available The major limiting factor for production and productivity of finger millet crop is blast disease caused by Magnaporthe grisea. Since, the genome sequence information available in finger millet crop is scarce, comparative genomics plays a very important role in identification of genes/QTLs linked to the blast resistance genes using SSR markers. In the present study, a total of 58 genic SSRs were developed for use in genetic analysis of a global collection of 190 finger millet genotypes. The 58 SSRs yielded ninety five scorable alleles and the polymorphism information content varied from 0.186 to 0.677 at an average of 0.385. The gene diversity was in the range of 0.208 to 0.726 with an average of 0.487. Association mapping for blast resistance was done using 104 SSR markers which identified four QTLs for finger blast and one QTL for neck blast resistance. The genomic marker RM262 and genic marker FMBLEST32 were linked to finger blast disease at a P value of 0.007 and explained phenotypic variance (R² of 10% and 8% respectively. The genomic marker UGEP81 was associated to finger blast at a P value of 0.009 and explained 7.5% of R². The QTLs for neck blast was associated with the genomic SSR marker UGEP18 at a P value of 0.01, which explained 11% of R². Three QTLs for blast resistance were found common by using both GLM and MLM approaches. The resistant alleles were found to be present mostly in the exotic genotypes. Among the genotypes of NW Himalayan region of India, VHC3997, VHC3996 and VHC3930 were found highly resistant, which may be effectively used as parents for developing blast resistant cultivars in the NW Himalayan region of India. The markers linked to the QTLs for blast resistance in the present study can be further used for cloning of the full length gene, fine mapping and their further use in the marker assisted breeding programmes for introgression of blast resistant alleles into locally adapted cultivars.

A reference genome of the European beech (Fagus sylvatica L.).

Science.gov (United States)

Mishra, Bagdevi; Gupta, Deepak K; Pfenninger, Markus; Hickler, Thomas; Langer, Ewald; Nam, Bora; Paule, Juraj; Sharma, Rahul; Ulaszewski, Bartosz; Warmbier, Joanna; Burczyk, Jaroslaw; Thines, Marco

2018-06-01

The European beech is arguably the most important climax broad-leaved tree species in Central Europe, widely planted for its valuable wood. Here, we report the 542 Mb draft genome sequence of an up to 300-year-old individual (Bhaga) from an undisturbed stand in the Kellerwald-Edersee National Park in central Germany. Using a hybrid assembly approach, Illumina reads with short- and long-insert libraries, coupled with long Pacific Biosciences reads, we obtained an assembled genome size of 542 Mb, in line with flow cytometric genome size estimation. The largest scaffold was of 1.15 Mb, the N50 length was 145 kb, and the L50 count was 983. The assembly contained 0.12% of Ns. A Benchmarking with Universal Single-Copy Orthologs (BUSCO) analysis retrieved 94% complete BUSCO genes, well in the range of other high-quality draft genomes of trees. A total of 62,012 protein-coding genes were predicted, assisted by transcriptome sequencing. In addition, we are reporting an efficient method for extracting high-molecular-weight DNA from dormant buds, by which contamination by environmental bacteria and fungi was kept at a minimum. The assembled genome will be a valuable resource and reference for future population genomics studies on the evolution and past climate change adaptation of beech and will be helpful for identifying genes, e.g., involved in drought tolerance, in order to select and breed individuals to adapt forestry to climate change in Europe. A continuously updated genome browser and download page can be accessed from beechgenome.net, which will include future genome versions of the reference individual Bhaga, as new sequencing approaches develop.

Genome-Enabled Prediction of Breeding Values for Feedlot Average Daily Weight Gain in Nelore Cattle

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Adriana L. Somavilla

2017-06-01

Full Text Available Nelore is the most economically important cattle breed in Brazil, and the use of genetically improved animals has contributed to increased beef production efficiency. The Brazilian beef feedlot industry has grown considerably in the last decade, so the selection of animals with higher growth rates on feedlot has become quite important. Genomic selection (GS could be used to reduce generation intervals and improve the rate of genetic gains. The aim of this study was to evaluate the prediction of genomic-estimated breeding values (GEBV for average daily weight gain (ADG in 718 feedlot-finished Nelore steers. Analyses of three Bayesian model specifications [Bayesian GBLUP (BGBLUP, BayesA, and BayesCπ] were performed with four genotype panels [Illumina BovineHD BeadChip, TagSNPs, and GeneSeek High- and Low-density indicus (HDi and LDi, respectively]. Estimates of Pearson correlations, regression coefficients, and mean squared errors were used to assess accuracy and bias of predictions. Overall, the BayesCπ model resulted in less biased predictions. Accuracies ranged from 0.18 to 0.27, which are reasonable values given the heritability estimates (from 0.40 to 0.44 and sample size (568 animals in the training population. Furthermore, results from Bos taurus indicus panels were as informative as those from Illumina BovineHD, indicating that they could be used to implement GS at lower costs.

An Inversion Disrupting FAM134B Is Associated with Sensory Neuropathy in the Border Collie Dog Breed

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Oliver P. Forman

2016-09-01

Full Text Available Sensory neuropathy in the Border Collie is a severe neurological disorder caused by the degeneration of sensory and, to a lesser extent, motor nerve cells with clinical signs starting between 2 and 7 months of age. Using a genome-wide association study approach with three cases and 170 breed matched controls, a suggestive locus for sensory neuropathy was identified that was followed up using a genome sequencing approach. An inversion disrupting the candidate gene FAM134B was identified. Genotyping of additional cases and controls and RNAseq analysis provided strong evidence that the inversion is causal. Evidence of cryptic splicing resulting in novel exon transcription for FAM134B was identified by RNAseq experiments. This investigation demonstrates the identification of a novel sensory neuropathy associated mutation, by mapping using a minimal set of cases and subsequent genome sequencing. Through mutation screening, it should be possible to reduce the frequency of or completely eliminate this debilitating condition from the Border Collie breed population.

Characterizing the population structure and genetic diversity of maize breeding germplasm in Southwest China using genome-wide SNP markers.

Science.gov (United States)

Zhang, Xiao; Zhang, Hua; Li, Lujiang; Lan, Hai; Ren, Zhiyong; Liu, Dan; Wu, Ling; Liu, Hailan; Jaqueth, Jennifer; Li, Bailin; Pan, Guangtang; Gao, Shibin

2016-08-31

representatively not only illustrates the foundation and evolution trend of maize breeding resource as a theoretical reference for the improvement of heterosis, but also provides plenty of information for genetic researches such as genome-wide association study and marker-assisted selection in the future.

Genomic prediction when some animals are not genotyped

Directory of Open Access Journals (Sweden)

Lund Mogens S

2010-01-01

Full Text Available Abstract Background The use of genomic selection in breeding programs may increase the rate of genetic improvement, reduce the generation time, and provide higher accuracy of estimated breeding values (EBVs. A number of different methods have been developed for genomic prediction of breeding values, but many of them assume that all animals have been genotyped. In practice, not all animals are genotyped, and the methods have to be adapted to this situation. Results In this paper we provide an extension of a linear mixed model method for genomic prediction to the situation with non-genotyped animals. The model specifies that a breeding value is the sum of a genomic and a polygenic genetic random effect, where genomic genetic random effects are correlated with a genomic relationship matrix constructed from markers and the polygenic genetic random effects are correlated with the usual relationship matrix. The extension of the model to non-genotyped animals is made by using the pedigree to derive an extension of the genomic relationship matrix to non-genotyped animals. As a result, in the extended model the estimated breeding values are obtained by blending the information used to compute traditional EBVs and the information used to compute purely genomic EBVs. Parameters in the model are estimated using average information REML and estimated breeding values are best linear unbiased predictions (BLUPs. The method is illustrated using a simulated data set. Conclusions The extension of the method to non-genotyped animals presented in this paper makes it possible to integrate all the genomic, pedigree and phenotype information into a one-step procedure for genomic prediction. Such a one-step procedure results in more accurate estimated breeding values and has the potential to become the standard tool for genomic prediction of breeding values in future practical evaluations in pig and cattle breeding.

Association Mapping of Biomass Yield and Stem Composition in a Tetraploid Alfalfa Breeding Population

Directory of Open Access Journals (Sweden)

Xuehui Li

2011-03-01

Full Text Available Alfalfa ( L., an important forage crop that is also a potential biofuel crop, has advantages of high yield, high lignocellulose concentration in stems, and has low input costs. In this study, we investigated population structure and linkage disequilibrium (LD patterns in a tetraploid alfalfa breeding population using genome-wide simple sequence repeat (SSR markers and identified markers related to yield and cell wall composition by association mapping. No obvious population structure was found in our alfalfa breeding population, which could be due to the relatively narrow genetic base of the founders and/or due to two generations of random mating. We found significant LD ( 10% alleles across the 71 SSR markers, 15 showed strong association ( < 0.005 with yield in at least one of five environments, and most of the 15 alleles were identified in multiple environments. Only one allele showed strong association with acid detergent fiber (ADF and one allele with acid detergent lignin (ADL. Alleles associated with traits could be directly applied in a breeding program using marker-assisted selection. However, based on our estimated LD level, we would need about 1000 markers to explore the whole alfalfa genome for association between markers and traits.

Plant Breeding by Using Radiation Mutation

International Nuclear Information System (INIS)

Kang, Si Yong; Kim, Dong Sub; Lee, Geung Joo

2007-06-01

A mutation breeding is to use physical or chemical mutagens to induce mutagenesis, followed by individual selections with favorable traits. The mutation breeding has many advantages over other breeding methods, which include the usefulness for improving one or two inferior characteristics, applications to broad species with different reproductive systems or to diverse plant materials, native or plant introduction with narrow genetic background, time and cost-effectiveness, and valuable mutant resources for genomic researches. Recent applications of the radiation breeding techniques to developments of flowering plants or food crops with improved functional constituents heightened the public's interests in agriculture and in our genetic resources and seed industries. The goals of this project, therefore, include achieving advances in domestic seed industries and agricultural productivities by developing and using new radiation mutants with favored traits, protecting an intellectual property right of domestic seeds or germplasm, and sharing the valuable mutants and mutated gene information for the genomic and biotech researches that eventually leads to economic benefits

Plant Breeding by Using Radiation Mutation

Energy Technology Data Exchange (ETDEWEB)

Kang, Si Yong; Kim, Dong Sub; Lee, Geung Joo (and others)

2007-06-15

A mutation breeding is to use physical or chemical mutagens to induce mutagenesis, followed by individual selections with favorable traits. The mutation breeding has many advantages over other breeding methods, which include the usefulness for improving one or two inferior characteristics, applications to broad species with different reproductive systems or to diverse plant materials, native or plant introduction with narrow genetic background, time and cost-effectiveness, and valuable mutant resources for genomic researches. Recent applications of the radiation breeding techniques to developments of flowering plants or food crops with improved functional constituents heightened the public's interests in agriculture and in our genetic resources and seed industries. The goals of this project, therefore, include achieving advances in domestic seed industries and agricultural productivities by developing and using new radiation mutants with favored traits, protecting an intellectual property right of domestic seeds or germplasm, and sharing the valuable mutants and mutated gene information for the genomic and biotech researches that eventually leads to economic benefits.

Breed-Predispositions to Cancer in Pedigree Dogs

Science.gov (United States)

Dobson, Jane M.

2013-01-01

Cancer is a common problem in dogs and although all breeds of dog and crossbred dogs may be affected, it is notable that some breeds of pedigree dogs appear to be at increased risk of certain types of cancer suggesting underlying genetic predisposition to cancer susceptibility. Although the aetiology of most cancers is likely to be multifactorial, the limited genetic diversity seen in purebred dogs facilitates genetic linkage or association studies on relatively small populations as compared to humans, and by using newly developed resources, genome-wide association studies in dog breeds are proving to be a powerful tool for unravelling complex disorders. This paper will review the literature on canine breed susceptibility to histiocytic sarcoma, osteosarcoma, haemangiosarcoma, mast cell tumours, lymphoma, melanoma, and mammary tumours including the recent advances in knowledge through molecular genetic, cytogenetic, and genome wide association studies. PMID:23738139

Comparing the predictive abilities of phenotypic and marker-assisted selection methods in a biparental lettuce population

Science.gov (United States)

Breeding and selection for the traits with polygenic inheritance is a challenging task that can be done by phenotypic selection, by marker-assisted selection or by genome wide selection. We tested predictive ability of four selection models in a biparental population genotyped with 95 SNP markers an...

Trends in genome-wide and region-specific genetic diversity in the Dutch-Flemish Holstein-Friesian breeding program from 1986 to 2015

NARCIS (Netherlands)

Doekes, Harmen P.; Veerkamp, Roel F.; Bijma, Piter; Hiemstra, Sipke J.; Windig, Jack J.

2018-01-01

Background: In recent decades, Holstein-Friesian (HF) selection schemes have undergone profound changes, including the introduction of optimal contribution selection (OCS; around 2000), a major shift in breeding goal composition (around 2000) and the implementation of genomic selection (GS;

Using the Pareto principle in genome-wide breeding value estimation.

Science.gov (United States)

Yu, Xijiang; Meuwissen, Theo H E

2011-11-01

Genome-wide breeding value (GWEBV) estimation methods can be classified based on the prior distribution assumptions of marker effects. Genome-wide BLUP methods assume a normal prior distribution for all markers with a constant variance, and are computationally fast. In Bayesian methods, more flexible prior distributions of SNP effects are applied that allow for very large SNP effects although most are small or even zero, but these prior distributions are often also computationally demanding as they rely on Monte Carlo Markov chain sampling. In this study, we adopted the Pareto principle to weight available marker loci, i.e., we consider that x% of the loci explain (100 - x)% of the total genetic variance. Assuming this principle, it is also possible to define the variances of the prior distribution of the 'big' and 'small' SNP. The relatively few large SNP explain a large proportion of the genetic variance and the majority of the SNP show small effects and explain a minor proportion of the genetic variance. We name this method MixP, where the prior distribution is a mixture of two normal distributions, i.e. one with a big variance and one with a small variance. Simulation results, using a real Norwegian Red cattle pedigree, show that MixP is at least as accurate as the other methods in all studied cases. This method also reduces the hyper-parameters of the prior distribution from 2 (proportion and variance of SNP with big effects) to 1 (proportion of SNP with big effects), assuming the overall genetic variance is known. The mixture of normal distribution prior made it possible to solve the equations iteratively, which greatly reduced computation loads by two orders of magnitude. In the era of marker density reaching million(s) and whole-genome sequence data, MixP provides a computationally feasible Bayesian method of analysis.

Genomic Selection for Drought Tolerance Using Genome-Wide SNPs in Maize

Directory of Open Access Journals (Sweden)

Thirunavukkarasu Nepolean

2017-04-01

Full Text Available Traditional breeding strategies for selecting superior genotypes depending on phenotypic traits have proven to be of limited success, as this direct selection is hindered by low heritability, genetic interactions such as epistasis, environmental-genotype interactions, and polygenic effects. With the advent of new genomic tools, breeders have paved a way for selecting superior breeds. Genomic selection (GS has emerged as one of the most important approaches for predicting genotype performance. Here, we tested the breeding values of 240 maize subtropical lines phenotyped for drought at different environments using 29,619 cured SNPs. Prediction accuracies of seven genomic selection models (ridge regression, LASSO, elastic net, random forest, reproducing kernel Hilbert space, Bayes A and Bayes B were tested for their agronomic traits. Though prediction accuracies of Bayes B, Bayes A and RKHS were comparable, Bayes B outperformed the other models by predicting highest Pearson correlation coefficient in all three environments. From Bayes B, a set of the top 1053 significant SNPs with higher marker effects was selected across all datasets to validate the genes and QTLs. Out of these 1053 SNPs, 77 SNPs associated with 10 drought-responsive transcription factors. These transcription factors were associated with different physiological and molecular functions (stomatal closure, root development, hormonal signaling and photosynthesis. Of several models, Bayes B has been shown to have the highest level of prediction accuracy for our data sets. Our experiments also highlighted several SNPs based on their performance and relative importance to drought tolerance. The result of our experiments is important for the selection of superior genotypes and candidate genes for breeding drought-tolerant maize hybrids.

Preliminary investigation on reliability of genomic estimated breeding values in the Danish and Swedish Holstein Population

DEFF Research Database (Denmark)

Su, G; Guldbrandtsen, B; Gregersen, V R

2010-01-01

or no effects, and a single prior distribution common for all SNP. It was found that, in general, the model with a common prior distribution of scaling factors had better predictive ability than any mixture prior models. Therefore, a common prior model was used to estimate SNP effects and breeding values......Abstract This study investigated the reliability of genomic estimated breeding values (GEBV) in the Danish Holstein population. The data in the analysis included 3,330 bulls with both published conventional EBV and single nucleotide polymorphism (SNP) markers. After data editing, 38,134 SNP markers...... were available. In the analysis, all SNP were fitted simultaneously as random effects in a Bayesian variable selection model, which allows heterogeneous variances for different SNP markers. The response variables were the official EBV. Direct GEBV were calculated as the sum of individual SNP effects...

Using modern plant breeding to improve the nutritional and technological qualities of oil crops

Directory of Open Access Journals (Sweden)

Murphy Denis J.

2014-11-01

Full Text Available The last few decades have seen huge advances in our understanding of plant biology and in the development of new technologies for the manipulation of crop plants. The application of relatively straightforward breeding and selection methods made possible the “Green Revolution” of the 1960s and 1970s that effectively doubled or trebled cereal production in much of the world and averted mass famine in Asia. During the 2000s, much attention has been focused on genomic approaches to plant breeding with the deployment of a new generation of technologies, such as marker-assisted selection, next-generation sequencing, transgenesis (genetic engineering or GM and automatic mutagenesis/selection (TILLING, TargetIng Local Lesions IN Genomes. These methods are now being applied to a wide range of crops and have particularly good potential for oil crop improvement in terms of both overall food and non-food yield and nutritional and technical quality of the oils. Key targets include increasing overall oil yield and stability on a per seed or per fruit basis and very high oleic acid content in seed and fruit oils for both premium edible and oleochemical applications. Other more specialised targets include oils enriched in nutritionally desirable “fish oil”-like fatty acids, especially very long chain !-3 acids such as eicosapentaenoic acid (EPA and docosahexaenoic acid (DHA, or increased levels of lipidic vitamins such as carotenoids, tocopherols and tocotrienes. Progress in producing such oils in commercial crops has been good in recent years with several varieties being released or at advanced stages of development.

Optimizing the creation of base populations for aquaculture breeding programs using phenotypic and genomic data and its consequences on genetic progress.

Science.gov (United States)

Fernández, Jesús; Toro, Miguel Á; Sonesson, Anna K; Villanueva, Beatriz

2014-01-01

The success of an aquaculture breeding program critically depends on the way in which the base population of breeders is constructed since all the genetic variability for the traits included originally in the breeding goal as well as those to be included in the future is contained in the initial founders. Traditionally, base populations were created from a number of wild strains by sampling equal numbers from each strain. However, for some aquaculture species improved strains are already available and, therefore, mean phenotypic values for economically important traits can be used as a criterion to optimize the sampling when creating base populations. Also, the increasing availability of genome-wide genotype information in aquaculture species could help to refine the estimation of relationships within and between candidate strains and, thus, to optimize the percentage of individuals to be sampled from each strain. This study explores the advantages of using phenotypic and genome-wide information when constructing base populations for aquaculture breeding programs in terms of initial and subsequent trait performance and genetic diversity level. Results show that a compromise solution between diversity and performance can be found when creating base populations. Up to 6% higher levels of phenotypic performance can be achieved at the same level of global diversity in the base population by optimizing the selection of breeders instead of sampling equal numbers from each strain. The higher performance observed in the base population persisted during 10 generations of phenotypic selection applied in the subsequent breeding program.

The accuracy of prediction of genomic selection in elite hybrid rye populations surpasses the accuracy of marker-assisted selection and is equally augmented by multiple field evaluation locations and test years.

Science.gov (United States)

Wang, Yu; Mette, Michael Florian; Miedaner, Thomas; Gottwald, Marlen; Wilde, Peer; Reif, Jochen C; Zhao, Yusheng

2014-07-04

Marker-assisted selection (MAS) and genomic selection (GS) based on genome-wide marker data provide powerful tools to predict the genotypic value of selection material in plant breeding. However, case-to-case optimization of these approaches is required to achieve maximum accuracy of prediction with reasonable input. Based on extended field evaluation data for grain yield, plant height, starch content and total pentosan content of elite hybrid rye derived from testcrosses involving two bi-parental populations that were genotyped with 1048 molecular markers, we compared the accuracy of prediction of MAS and GS in a cross-validation approach. MAS delivered generally lower and in addition potentially over-estimated accuracies of prediction than GS by ridge regression best linear unbiased prediction (RR-BLUP). The grade of relatedness of the plant material included in the estimation and test sets clearly affected the accuracy of prediction of GS. Within each of the two bi-parental populations, accuracies differed depending on the relatedness of the respective parental lines. Across populations, accuracy increased when both populations contributed to estimation and test set. In contrast, accuracy of prediction based on an estimation set from one population to a test set from the other population was low despite that the two bi-parental segregating populations under scrutiny shared one parental line. Limiting the number of locations or years in field testing reduced the accuracy of prediction of GS equally, supporting the view that to establish robust GS calibration models a sufficient number of test locations is of similar importance as extended testing for more than one year. In hybrid rye, genomic selection is superior to marker-assisted selection. However, it achieves high accuracies of prediction only for selection candidates closely related to the plant material evaluated in field trials, resulting in a rather pessimistic prognosis for distantly related material

Patient-controlled encrypted genomic data: an approach to advance clinical genomics

Directory of Open Access Journals (Sweden)

Trakadis Yannis J

2012-07-01

Full Text Available Abstract Background The revolution in DNA sequencing technologies over the past decade has made it feasible to sequence an individual’s whole genome at a relatively low cost. The potential value of the information generated by genomic technologies for medicine and society is enormous. However, in order for exome sequencing, and eventually whole genome sequencing, to be implemented clinically, a number of major challenges need to be overcome. For instance, obtaining meaningful informed-consent, managing incidental findings and the great volume of data generated (including multiple findings with uncertain clinical significance, re-interpreting the genomic data and providing additional counselling to patients as genetic knowledge evolves are issues that need to be addressed. It appears that medical genetics is shifting from the present “phenotype-first” medical model to a “data-first” model which leads to multiple complexities. Discussion This manuscript discusses the different challenges associated with integrating genomic technologies into clinical practice and describes a “phenotype-first” approach, namely, “Individualized Mutation-weighed Phenotype Search”, and its benefits. The proposed approach allows for a more efficient prioritization of the genes to be tested in a clinical lab based on both the patient’s phenotype and his/her entire genomic data. It simplifies “informed-consent” for clinical use of genomic technologies and helps to protect the patient’s autonomy and privacy. Overall, this approach could potentially render widespread use of genomic technologies, in the immediate future, practical, ethical and clinically useful. Summary The “Individualized Mutation-weighed Phenotype Search” approach allows for an incremental integration of genomic technologies into clinical practice. It ensures that we do not over-medicalize genomic data but, rather, continue our current medical model which is based on serving

An inversion disrupting FAM134B is associated with sensory neuropathy in the Border Collie dog breed

OpenAIRE

Forman, Oliver P.; Hitti, Rebekkah J.; Pettitt, Louise; Jenkins, Christopher A.; O'Brien, Dennis P.; Shelton, G. Diane; De Risio, Luisa; Gutierrez Quintana, Rodrigo; Beltran, Elsa; Mellersh, Cathryn

2016-01-01

Sensory neuropathy in the Border Collie is a severe neurological disorder caused by the degeneration of sensory and, to a lesser extent, motor nerve cells with clinical signs starting between 2 and 7 months of age. Using a genome-wide association study approach with three cases and 170 breed matched controls, a suggestive locus for sensory neuropathy was identified that was followed up using a genome sequencing approach. An inversion disrupting the candidate gene FAM134B was identified. Genot...

Kazusa Marker DataBase: a database for genomics, genetics, and molecular breeding in plants

Science.gov (United States)

Shirasawa, Kenta; Isobe, Sachiko; Tabata, Satoshi; Hirakawa, Hideki

2014-01-01

In order to provide useful genomic information for agronomical plants, we have established a database, the Kazusa Marker DataBase (http://marker.kazusa.or.jp). This database includes information on DNA markers, e.g., SSR and SNP markers, genetic linkage maps, and physical maps, that were developed at the Kazusa DNA Research Institute. Keyword searches for the markers, sequence data used for marker development, and experimental conditions are also available through this database. Currently, 10 plant species have been targeted: tomato (Solanum lycopersicum), pepper (Capsicum annuum), strawberry (Fragaria × ananassa), radish (Raphanus sativus), Lotus japonicus, soybean (Glycine max), peanut (Arachis hypogaea), red clover (Trifolium pratense), white clover (Trifolium repens), and eucalyptus (Eucalyptus camaldulensis). In addition, the number of plant species registered in this database will be increased as our research progresses. The Kazusa Marker DataBase will be a useful tool for both basic and applied sciences, such as genomics, genetics, and molecular breeding in crops. PMID:25320561

Relationships among and variation within rare breeds of swine.

Science.gov (United States)

Roberts, K S; Lamberson, W R

2015-08-01

Extinction of rare breeds of livestock threatens to reduce the total genetic variation available for selection in the face of the changing environment and new diseases. Swine breeds facing extinction typically share characteristics such as small size, slow growth rate, and high fat percentage, which limit them from contributing to commercial production. Compounding the risk of loss of variation is the lack of pedigree information for many rare breeds due to inadequate herd books, which increases the chance that producers are breeding closely related individuals. By making genetic data available, producers can make more educated breeding decisions to preserve genetic diversity in future generations, and conservation organizations can prioritize investments in breed preservation. The objective of this study was to characterize genetic variation within and among breeds of swine and prioritize heritage breeds for preservation. Genotypes from the Illumina PorcineSNP60 BeadChip (GeneSeek, Lincoln, NE) were obtained for Guinea, Ossabaw Island, Red Wattle, American Saddleback, Mulefoot, British Saddleback, Duroc, Landrace, Large White, Pietrain, and Tamworth pigs. A whole-genome analysis toolset was used to construct a genomic relationship matrix and to calculate inbreeding coefficients for the animals within each breed. Relatedness and average inbreeding coefficient differed among breeds, and pigs from rare breeds were generally more closely related and more inbred ( Guinea pigs. Tamworth, Duroc, and Mulefoot tended to not cluster with the other 7 breeds.

Genomic heritabilities and genomic estimated breeding values for methane traits in Angus cattle.

Science.gov (United States)

Hayes, B J; Donoghue, K A; Reich, C M; Mason, B A; Bird-Gardiner, T; Herd, R M; Arthur, P F

2016-03-01

Enteric methane emissions from beef cattle are a significant component of total greenhouse gas emissions from agriculture. The variation between beef cattle in methane emissions is partly genetic, whether measured as methane production, methane yield (methane production/DMI), or residual methane production (observed methane production - expected methane production), with heritabilities ranging from 0.19 to 0.29. This suggests methane emissions could be reduced by selection. Given the high cost of measuring methane production from individual beef cattle, genomic selection is the most feasible approach to achieve this reduction in emissions. We derived genomic EBV (GEBV) for methane traits from a reference set of 747 Angus animals phenotyped for methane traits and genotyped for 630,000 SNP. The accuracy of GEBV was tested in a validation set of 273 Angus animals phenotyped for the same traits. Accuracies of GEBV ranged from 0.29 ± 0.06 for methane yield and 0.35 ± 0.06 for residual methane production. Selection on GEBV using the genomic prediction equations derived here could reduce emissions for Angus cattle by roughly 5% over 10 yr.

Draft genome of the lined seahorse, Hippocampus erectus.

Science.gov (United States)

Lin, Qiang; Qiu, Ying; Gu, Ruobo; Xu, Meng; Li, Jia; Bian, Chao; Zhang, Huixian; Qin, Geng; Zhang, Yanhong; Luo, Wei; Chen, Jieming; You, Xinxin; Fan, Mingjun; Sun, Min; Xu, Pao; Venkatesh, Byrappa; Xu, Junming; Fu, Hongtuo; Shi, Qiong

2017-06-01

The lined seahorse, Hippocampus erectus , is an Atlantic species and mainly inhabits shallow sea beds or coral reefs. It has become very popular in China for its wide use in traditional Chinese medicine. In order to improve the aquaculture yield of this valuable fish species, we are trying to develop genomic resources for assistant selection in genetic breeding. Here, we provide whole genome sequencing, assembly, and gene annotation of the lined seahorse, which can enrich genome resource and further application for its molecular breeding. A total of 174.6 Gb (Gigabase) raw DNA sequences were generated by the Illumina Hiseq2500 platform. The final assembly of the lined seahorse genome is around 458 Mb, representing 94% of the estimated genome size (489 Mb by k-mer analysis). The contig N50 and scaffold N50 reached 14.57 kb and 1.97 Mb, respectively. Quality of the assembled genome was assessed by BUSCO with prediction of 85% of the known vertebrate genes and evaluated using the de novo assembled RNA-seq transcripts to prove a high mapping ratio (more than 99% transcripts could be mapped to the assembly). Using homology-based, de novo and transcriptome-based prediction methods, we predicted 20 788 protein-coding genes in the generated assembly, which is less than our previously reported gene number (23 458) of the tiger tail seahorse ( H. comes ). We report a draft genome of the lined seahorse. These generated genomic data are going to enrich genome resource of this economically important fish, and also provide insights into the genetic mechanisms of its iconic morphology and male pregnancy behavior. © The Authors 2017. Published by Oxford University Press.

An Inversion Disrupting FAM134B Is Associated with Sensory Neuropathy in the Border Collie Dog Breed.

Science.gov (United States)

Forman, Oliver P; Hitti, Rebekkah J; Pettitt, Louise; Jenkins, Christopher A; O'Brien, Dennis P; Shelton, G Diane; De Risio, Luisa; Quintana, Rodrigo Gutierrez; Beltran, Elsa; Mellersh, Cathryn

2016-09-08

Sensory neuropathy in the Border Collie is a severe neurological disorder caused by the degeneration of sensory and, to a lesser extent, motor nerve cells with clinical signs starting between 2 and 7 months of age. Using a genome-wide association study approach with three cases and 170 breed matched controls, a suggestive locus for sensory neuropathy was identified that was followed up using a genome sequencing approach. An inversion disrupting the candidate gene FAM134B was identified. Genotyping of additional cases and controls and RNAseq analysis provided strong evidence that the inversion is causal. Evidence of cryptic splicing resulting in novel exon transcription for FAM134B was identified by RNAseq experiments. This investigation demonstrates the identification of a novel sensory neuropathy associated mutation, by mapping using a minimal set of cases and subsequent genome sequencing. Through mutation screening, it should be possible to reduce the frequency of or completely eliminate this debilitating condition from the Border Collie breed population. Copyright © 2016 Forman et al.

Genomic prediction for Nordic Red Cattle using one-step and selection index blending

DEFF Research Database (Denmark)

Guosheng, Su; Madsen, Per; Nielsen, Ulrik Sander

2012-01-01

This study investigated the accuracy of direct genomic breeding values (DGV) using a genomic BLUP model, genomic enhanced breeding values (GEBV) using a one-step blending approach, and GEBV using a selection index blending approach for 15 traits of Nordic Red Cattle. The data comprised 6,631 bulls...... genotyped and nongenotyped bulls for one-step blending, and to scale DGV and its expected reliability in the selection index blending. Weighting (scaling) factors had a small influence on reliabilities of GEBV, but a large influence on the variation of GEBV. Based on the validation analyses, averaged over...... the 15 traits, the reliability of DGV for bulls without daughter records was 11.0 percentage points higher than the reliability of conventional pedigree index. Further gain of 0.9 percentage points was achieved by combining information from conventional pedigree index using the selection index blending...

Best linear unbiased prediction of genomic breeding values using a trait-specific marker-derived relationship matrix.

Directory of Open Access Journals (Sweden)

Zhe Zhang

2010-09-01

Full Text Available With the availability of high density whole-genome single nucleotide polymorphism chips, genomic selection has become a promising method to estimate genetic merit with potentially high accuracy for animal, plant and aquaculture species of economic importance. With markers covering the entire genome, genetic merit of genotyped individuals can be predicted directly within the framework of mixed model equations, by using a matrix of relationships among individuals that is derived from the markers. Here we extend that approach by deriving a marker-based relationship matrix specifically for the trait of interest.In the framework of mixed model equations, a new best linear unbiased prediction (BLUP method including a trait-specific relationship matrix (TA was presented and termed TABLUP. The TA matrix was constructed on the basis of marker genotypes and their weights in relation to the trait of interest. A simulation study with 1,000 individuals as the training population and five successive generations as candidate population was carried out to validate the proposed method. The proposed TABLUP method outperformed the ridge regression BLUP (RRBLUP and BLUP with realized relationship matrix (GBLUP. It performed slightly worse than BayesB with an accuracy of 0.79 in the standard scenario.The proposed TABLUP method is an improvement of the RRBLUP and GBLUP method. It might be equivalent to the BayesB method but it has additional benefits like the calculation of accuracies for individual breeding values. The results also showed that the TA-matrix performs better in predicting ability than the classical numerator relationship matrix and the realized relationship matrix which are derived solely from pedigree or markers without regard to the trait. This is because the TA-matrix not only accounts for the Mendelian sampling term, but also puts the greater emphasis on those markers that explain more of the genetic variance in the trait.

Effects of the number of markers per haplotype and clustering of haplotypes on the accuracy of QTL mapping and prediction of genomic breeding values

Directory of Open Access Journals (Sweden)

Schrooten Chris

2009-01-01

Full Text Available Abstract The aim of this paper was to compare the effect of haplotype definition on the precision of QTL-mapping and on the accuracy of predicted genomic breeding values. In a multiple QTL model using identity-by-descent (IBD probabilities between haplotypes, various haplotype definitions were tested i.e. including 2, 6, 12 or 20 marker alleles and clustering base haplotypes related with an IBD probability of > 0.55, 0.75 or 0.95. Simulated data contained 1100 animals with known genotypes and phenotypes and 1000 animals with known genotypes and unknown phenotypes. Genomes comprising 3 Morgan were simulated and contained 74 polymorphic QTL and 383 polymorphic SNP markers with an average r2 value of 0.14 between adjacent markers. The total number of haplotypes decreased up to 50% when the window size was increased from two to 20 markers and decreased by at least 50% when haplotypes related with an IBD probability of > 0.55 instead of > 0.95 were clustered. An intermediate window size led to more precise QTL mapping. Window size and clustering had a limited effect on the accuracy of predicted total breeding values, ranging from 0.79 to 0.81. Our conclusion is that different optimal window sizes should be used in QTL-mapping versus genome-wide breeding value prediction.

Genome sequence and genetic diversity of the common carp, Cyprinus carpio.

Science.gov (United States)

Xu, Peng; Zhang, Xiaofeng; Wang, Xumin; Li, Jiongtang; Liu, Guiming; Kuang, Youyi; Xu, Jian; Zheng, Xianhu; Ren, Lufeng; Wang, Guoliang; Zhang, Yan; Huo, Linhe; Zhao, Zixia; Cao, Dingchen; Lu, Cuiyun; Li, Chao; Zhou, Yi; Liu, Zhanjiang; Fan, Zhonghua; Shan, Guangle; Li, Xingang; Wu, Shuangxiu; Song, Lipu; Hou, Guangyuan; Jiang, Yanliang; Jeney, Zsigmond; Yu, Dan; Wang, Li; Shao, Changjun; Song, Lai; Sun, Jing; Ji, Peifeng; Wang, Jian; Li, Qiang; Xu, Liming; Sun, Fanyue; Feng, Jianxin; Wang, Chenghui; Wang, Shaolin; Wang, Baosen; Li, Yan; Zhu, Yaping; Xue, Wei; Zhao, Lan; Wang, Jintu; Gu, Ying; Lv, Weihua; Wu, Kejing; Xiao, Jingfa; Wu, Jiayan; Zhang, Zhang; Yu, Jun; Sun, Xiaowen

2014-11-01

The common carp, Cyprinus carpio, is one of the most important cyprinid species and globally accounts for 10% of freshwater aquaculture production. Here we present a draft genome of domesticated C. carpio (strain Songpu), whose current assembly contains 52,610 protein-coding genes and approximately 92.3% coverage of its paleotetraploidized genome (2n = 100). The latest round of whole-genome duplication has been estimated to have occurred approximately 8.2 million years ago. Genome resequencing of 33 representative individuals from worldwide populations demonstrates a single origin for C. carpio in 2 subspecies (C. carpio Haematopterus and C. carpio carpio). Integrative genomic and transcriptomic analyses were used to identify loci potentially associated with traits including scaling patterns and skin color. In combination with the high-resolution genetic map, the draft genome paves the way for better molecular studies and improved genome-assisted breeding of C. carpio and other closely related species.

Accelerated Generation of Selfed Pure Line Plants for Gene Identification and Crop Breeding

Directory of Open Access Journals (Sweden)

Guijun Yan

2017-10-01

Full Text Available Production of pure lines is an important step in biological studies and breeding of many crop plants. The major types of pure lines for biological studies and breeding include doubled haploid (DH lines, recombinant inbred lines (RILs, and near isogenic lines (NILs. DH lines can be produced through microspore and megaspore culture followed by chromosome doubling while RILs and NILs can be produced through introgressions or repeated selfing of hybrids. DH approach was developed as a quicker method than conventional method to produce pure lines. However, its drawbacks of genotype-dependency and only a single chance of recombination limited its wider application. A recently developed fast generation cycling system (FGCS achieved similar times to those of DH for the production of selfed pure lines but is more versatile as it is much less genotype-dependent than DH technology and does not restrict recombination to a single event. The advantages and disadvantages of the technologies and their produced pure line populations for different purposes of biological research and breeding are discussed. The development of a concept of complete in vitro meiosis and mitosis system is also proposed. This could integrate with the recently developed technologies of single cell genomic sequencing and genome wide selection, leading to a complete laboratory based pre-breeding scheme.

Reduced representation approaches to interrogate genome diversity in large repetitive plant genomes.

Science.gov (United States)

Hirsch, Cory D; Evans, Joseph; Buell, C Robin; Hirsch, Candice N

2014-07-01

Technology and software improvements in the last decade now provide methodologies to access the genome sequence of not only a single accession, but also multiple accessions of plant species. This provides a means to interrogate species diversity at the genome level. Ample diversity among accessions in a collection of species can be found, including single-nucleotide polymorphisms, insertions and deletions, copy number variation and presence/absence variation. For species with small, non-repetitive rich genomes, re-sequencing of query accessions is robust, highly informative, and economically feasible. However, for species with moderate to large sized repetitive-rich genomes, technical and economic barriers prevent en masse genome re-sequencing of accessions. Multiple approaches to access a focused subset of loci in species with larger genomes have been developed, including reduced representation sequencing, exome capture and transcriptome sequencing. Collectively, these approaches have enabled interrogation of diversity on a genome scale for large plant genomes, including crop species important to worldwide food security. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Draft Sequencing of the Heterozygous Diploid Genome of Satsuma (Citrus unshiu Marc. Using a Hybrid Assembly Approach

Directory of Open Access Journals (Sweden)

Tokurou Shimizu

2017-12-01

Full Text Available Satsuma (Citrus unshiu Marc. is one of the most abundantly produced mandarin varieties of citrus, known for its seedless fruit production and as a breeding parent of citrus. De novo assembly of the heterozygous diploid genome of Satsuma (“Miyagawa Wase” was conducted by a hybrid assembly approach using short-read sequences, three mate-pair libraries, and a long-read sequence of PacBio by the PLATANUS assembler. The assembled sequence, with a total size of 359.7 Mb at the N50 length of 386,404 bp, consisted of 20,876 scaffolds. Pseudomolecules of Satsuma constructed by aligning the scaffolds to three genetic maps showed genome-wide synteny to the genomes of Clementine, pummelo, and sweet orange. Gene prediction by modeling with MAKER-P proposed 29,024 genes and 37,970 mRNA; additionally, gene prediction analysis found candidates for novel genes in several biosynthesis pathways for gibberellin and violaxanthin catabolism. BUSCO scores for the assembled scaffold and predicted transcripts, and another analysis by BAC end sequence mapping indicated the assembled genome consistency was close to those of the haploid Clementine, pummel, and sweet orange genomes. The number of repeat elements and long terminal repeat retrotransposon were comparable to those of the seven citrus genomes; this suggested no significant failure in the assembly at the repeat region. A resequencing application using the assembled sequence confirmed that both kunenbo-A and Satsuma are offsprings of Kishu, and Satsuma is a back-crossed offspring of Kishu. These results illustrated the performance of the hybrid assembly approach and its ability to construct an accurate heterozygous diploid genome.

Genetic distinctiveness of the Herdwick sheep breed and two other locally adapted hill breeds of the UK.

Science.gov (United States)

Bowles, Dianna; Carson, Amanda; Isaac, Peter

2014-01-01

There is considerable interest in locally adapted breeds of livestock as reservoirs of genetic diversity that may provide important fitness traits for future use in agriculture. In marginal areas, these animals contribute to food security and extract value from land unsuitable for other systems of farming. In England, close to 50% of the national sheep flock is farmed on grassland designated as disadvantaged areas for agricultural production. Many of these areas are in the uplands, where some native breeds of sheep continue to be commercially farmed only in highly localised geographical regions to which they are adapted. This study focuses on three of these breeds, selected for their adaptation to near identical environments and their geographical concentration in regions close to one another. Our objective has been to use retrotyping, microsatellites and single nucleotide polymorphisms to explore the origins of the breeds and whether, despite their similar adaptations and proximity, they are genetically distinctive. We find the three breeds each have a surprisingly different pattern of retrovirus insertions into their genomes compared with one another and with other UK breeds. Uniquely, there is a high incidence of the R0 retrotype in the Herdwick population, characteristic of a primitive genome found previously in very few breeds worldwide and none in the UK mainland. The Herdwick and Rough Fells carry two rare retroviral insertion events, common only in Texels, suggesting sheep populations in the northern uplands have a historical association with the original pin-tail sheep of Texel Island. Microsatellite data and analyses of SNPs associated with RXFP2 (horn traits) and PRLR (reproductive performance traits) also distinguished the three breeds. Significantly, an SNP linked to TMEM154, a locus controlling susceptibility to infection by Maedi-Visna, indicated that all three native hill breeds have a lower than average risk of infection to the lentivirus.

Genetic distinctiveness of the Herdwick sheep breed and two other locally adapted hill breeds of the UK.

Directory of Open Access Journals (Sweden)

Dianna Bowles

Full Text Available There is considerable interest in locally adapted breeds of livestock as reservoirs of genetic diversity that may provide important fitness traits for future use in agriculture. In marginal areas, these animals contribute to food security and extract value from land unsuitable for other systems of farming. In England, close to 50% of the national sheep flock is farmed on grassland designated as disadvantaged areas for agricultural production. Many of these areas are in the uplands, where some native breeds of sheep continue to be commercially farmed only in highly localised geographical regions to which they are adapted. This study focuses on three of these breeds, selected for their adaptation to near identical environments and their geographical concentration in regions close to one another. Our objective has been to use retrotyping, microsatellites and single nucleotide polymorphisms to explore the origins of the breeds and whether, despite their similar adaptations and proximity, they are genetically distinctive. We find the three breeds each have a surprisingly different pattern of retrovirus insertions into their genomes compared with one another and with other UK breeds. Uniquely, there is a high incidence of the R0 retrotype in the Herdwick population, characteristic of a primitive genome found previously in very few breeds worldwide and none in the UK mainland. The Herdwick and Rough Fells carry two rare retroviral insertion events, common only in Texels, suggesting sheep populations in the northern uplands have a historical association with the original pin-tail sheep of Texel Island. Microsatellite data and analyses of SNPs associated with RXFP2 (horn traits and PRLR (reproductive performance traits also distinguished the three breeds. Significantly, an SNP linked to TMEM154, a locus controlling susceptibility to infection by Maedi-Visna, indicated that all three native hill breeds have a lower than average risk of infection to the

Mapping the sensory perception of apple using descriptive sensory evaluation in a genome wide association study.

Science.gov (United States)

Amyotte, Beatrice; Bowen, Amy J; Banks, Travis; Rajcan, Istvan; Somers, Daryl J

2017-01-01

Breeding apples is a long-term endeavour and it is imperative that new cultivars are selected to have outstanding consumer appeal. This study has taken the approach of merging sensory science with genome wide association analyses in order to map the human perception of apple flavour and texture onto the apple genome. The goal was to identify genomic associations that could be used in breeding apples for improved fruit quality. A collection of 85 apple cultivars was examined over two years through descriptive sensory evaluation by a trained sensory panel. The trained sensory panel scored randomized sliced samples of each apple cultivar for seventeen taste, flavour and texture attributes using controlled sensory evaluation practices. In addition, the apple collection was subjected to genotyping by sequencing for marker discovery. A genome wide association analysis suggested significant genomic associations for several sensory traits including juiciness, crispness, mealiness and fresh green apple flavour. The findings include previously unreported genomic regions that could be used in apple breeding and suggest that similar sensory association mapping methods could be applied in other plants.

Mapping the sensory perception of apple using descriptive sensory evaluation in a genome wide association study

Science.gov (United States)

Amyotte, Beatrice; Bowen, Amy J.; Banks, Travis; Rajcan, Istvan; Somers, Daryl J.

2017-01-01

Breeding apples is a long-term endeavour and it is imperative that new cultivars are selected to have outstanding consumer appeal. This study has taken the approach of merging sensory science with genome wide association analyses in order to map the human perception of apple flavour and texture onto the apple genome. The goal was to identify genomic associations that could be used in breeding apples for improved fruit quality. A collection of 85 apple cultivars was examined over two years through descriptive sensory evaluation by a trained sensory panel. The trained sensory panel scored randomized sliced samples of each apple cultivar for seventeen taste, flavour and texture attributes using controlled sensory evaluation practices. In addition, the apple collection was subjected to genotyping by sequencing for marker discovery. A genome wide association analysis suggested significant genomic associations for several sensory traits including juiciness, crispness, mealiness and fresh green apple flavour. The findings include previously unreported genomic regions that could be used in apple breeding and suggest that similar sensory association mapping methods could be applied in other plants. PMID:28231290

Genome editing and assisted reproduction: curing embryos, society or prospective parents?

Science.gov (United States)

Cavaliere, Giulia

2018-06-01

This paper explores the ethics of introducing genome-editing technologies as a new reproductive option. In particular, it focuses on whether genome editing can be considered a morally valuable alternative to preimplantation genetic diagnosis (PGD). Two arguments against the use of genome editing in reproduction are analysed, namely safety concerns and germline modification. These arguments are then contrasted with arguments in favour of genome editing, in particular with the argument of the child's welfare and the argument of parental reproductive autonomy. In addition to these two arguments, genome editing could be considered as a worthy alternative to PGD as it may not be subjected to some of the moral critiques moved against this technology. Even if these arguments offer sound reasons in favour of introducing genome editing as a new reproductive option, I conclude that these benefits should be balanced against other considerations. More specifically, I maintain that concerns regarding the equality of access to assisted reproduction and the allocation of scarce resources should be addressed prior to the adoption of genome editing as a new reproductive option.

DNA-informed breeding of rosaceous crops: promises, progress and prospects

Science.gov (United States)

Peace, Cameron P

2017-01-01

Crops of the Rosaceae family provide valuable contributions to rural economies and human health and enjoyment. Sustained solutions to production challenges and market demands can be met with genetically improved new cultivars. Traditional rosaceous crop breeding is expensive and time-consuming and would benefit from improvements in efficiency and accuracy. Use of DNA information is becoming conventional in rosaceous crop breeding, contributing to many decisions and operations, but only after past decades of solved challenges and generation of sufficient resources. Successes in deployment of DNA-based knowledge and tools have arisen when the ‘chasm’ between genomics discoveries and practical application is bridged systematically. Key steps are establishing breeder desire for use of DNA information, adapting tools to local breeding utility, identifying efficient application schemes, accessing effective services in DNA-based diagnostics and gaining experience in integrating DNA information into breeding operations and decisions. DNA-informed germplasm characterization for revealing identity and relatedness has benefitted many programs and provides a compelling entry point to reaping benefits of genomics research. DNA-informed germplasm evaluation for predicting trait performance has enabled effective reallocation of breeding resources when applied in pioneering programs. DNA-based diagnostics is now expanding from specific loci to genome-wide considerations. Realizing the full potential of this expansion will require improved accuracy of predictions, multi-trait DNA profiling capabilities, streamlined breeding information management systems, strategies that overcome plant-based features that limit breeding progress and widespread training of current and future breeding personnel and allied scientists. PMID:28326185

A validated genome wide association study to breed cattle adapted to an environment altered by climate change.

Directory of Open Access Journals (Sweden)

Ben J Hayes

Full Text Available Continued production of food in areas predicted to be most affected by climate change, such as dairy farming regions of Australia, will be a major challenge in coming decades. Along with rising temperatures and water shortages, scarcity of inputs such as high energy feeds is predicted. With the motivation of selecting cattle adapted to these changing environments, we conducted a genome wide association study to detect DNA markers (single nucleotide polymorphisms associated with the sensitivity of milk production to environmental conditions. To do this we combined historical milk production and weather records with dense marker genotypes on dairy sires with many daughters milking across a wide range of production environments in Australia. Markers associated with sensitivity of milk production to feeding level and sensitivity of milk production to temperature humidity index on chromosome nine and twenty nine respectively were validated in two independent populations, one a different breed of cattle. As the extent of linkage disequilibrium across cattle breeds is limited, the underlying causative mutations have been mapped to a small genomic interval containing two promising candidate genes. The validated marker panels we have reported here will aid selection for high milk production under anticipated climate change scenarios, for example selection of sires whose daughters will be most productive at low levels of feeding.

Cow genotyping strategies for genomic selection in a small dairy cattle population.

Science.gov (United States)

Jenko, J; Wiggans, G R; Cooper, T A; Eaglen, S A E; Luff, W G de L; Bichard, M; Pong-Wong, R; Woolliams, J A

2017-01-01

This study compares how different cow genotyping strategies increase the accuracy of genomic estimated breeding values (EBV) in dairy cattle breeds with low numbers. In these breeds, few sires have progeny records, and genotyping cows can improve the accuracy of genomic EBV. The Guernsey breed is a small dairy cattle breed with approximately 14,000 recorded individuals worldwide. Predictions of phenotypes of milk yield, fat yield, protein yield, and calving interval were made for Guernsey cows from England and Guernsey Island using genomic EBV, with training sets including 197 de-regressed proofs of genotyped bulls, with cows selected from among 1,440 genotyped cows using different genotyping strategies. Accuracies of predictions were tested using 10-fold cross-validation among the cows. Genomic EBV were predicted using 4 different methods: (1) pedigree BLUP, (2) genomic BLUP using only bulls, (3) univariate genomic BLUP using bulls and cows, and (4) bivariate genomic BLUP. Genotyping cows with phenotypes and using their data for the prediction of single nucleotide polymorphism effects increased the correlation between genomic EBV and phenotypes compared with using only bulls by 0.163±0.022 for milk yield, 0.111±0.021 for fat yield, and 0.113±0.018 for protein yield; a decrease of 0.014±0.010 for calving interval from a low base was the only exception. Genetic correlation between phenotypes from bulls and cows were approximately 0.6 for all yield traits and significantly different from 1. Only a very small change occurred in correlation between genomic EBV and phenotypes when using the bivariate model. It was always better to genotype all the cows, but when only half of the cows were genotyped, a divergent selection strategy was better compared with the random or directional selection approach. Divergent selection of 30% of the cows remained superior for the yield traits in 8 of 10 folds. Copyright © 2017 American Dairy Science Association. Published by

Unlocking the diversity of genebanks: whole-genome marker analysis of Swiss bread wheat and spelt

KAUST Repository

Mü ller, Thomas; Schierscher-Viret, Beate; Fossati, Dario; Brabant, Cé cile; Schori, Arnold; Keller, Beat; Krattinger, Simon G.

2017-01-01

Genebanks play a pivotal role in preserving the genetic diversity present among old landraces and wild progenitors of modern crops and they represent sources of agriculturally important genes that were lost during domestication and in modern breeding. However, undesirable genes that negatively affect crop performance are often co-introduced when landraces and wild crop progenitors are crossed with elite cultivars, which often limit the use of genebank material in modern breeding programs. A detailed genetic characterization is an important prerequisite to solve this problem and to make genebank material more accessible to breeding. Here, we genotyped 502 bread wheat and 293 spelt accessions held in the Swiss National Genebank using a 15K wheat SNP array. The material included both spring and winter wheats and consisted of old landraces and modern cultivars. Genome- and sub-genome-wide analyses revealed that spelt and bread wheat form two distinct gene pools. In addition, we identified bread wheat landraces that were genetically distinct from modern cultivars. Such accessions were possibly missed in the early Swiss wheat breeding program and are promising targets for the identification of novel genes. The genetic information obtained in this study is appropriate to perform genome-wide association studies, which will facilitate the identification and transfer of agriculturally important genes from the genebank into modern cultivars through marker-assisted selection.

Unlocking the diversity of genebanks: whole-genome marker analysis of Swiss bread wheat and spelt

KAUST Repository

Müller, Thomas

2017-11-04

Genebanks play a pivotal role in preserving the genetic diversity present among old landraces and wild progenitors of modern crops and they represent sources of agriculturally important genes that were lost during domestication and in modern breeding. However, undesirable genes that negatively affect crop performance are often co-introduced when landraces and wild crop progenitors are crossed with elite cultivars, which often limit the use of genebank material in modern breeding programs. A detailed genetic characterization is an important prerequisite to solve this problem and to make genebank material more accessible to breeding. Here, we genotyped 502 bread wheat and 293 spelt accessions held in the Swiss National Genebank using a 15K wheat SNP array. The material included both spring and winter wheats and consisted of old landraces and modern cultivars. Genome- and sub-genome-wide analyses revealed that spelt and bread wheat form two distinct gene pools. In addition, we identified bread wheat landraces that were genetically distinct from modern cultivars. Such accessions were possibly missed in the early Swiss wheat breeding program and are promising targets for the identification of novel genes. The genetic information obtained in this study is appropriate to perform genome-wide association studies, which will facilitate the identification and transfer of agriculturally important genes from the genebank into modern cultivars through marker-assisted selection.

Landscape genomics and biased FST approaches reveal single nucleotide polymorphisms under selection in goat breeds of North-East Mediterranean

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Joost Stephane

2009-02-01

Full Text Available Abstract Background In this study we compare outlier loci detected using a FST based method with those identified by a recently described method based on spatial analysis (SAM. We tested a panel of single nucleotide polymorphisms (SNPs previously genotyped in individuals of goat breeds of southern areas of the Mediterranean basin (Italy, Greece and Albania. We evaluate how the SAM method performs with SNPs, which are increasingly employed due to their high number, low cost and easy of scoring. Results The combined use of the two outlier detection approaches, never tested before using SNP polymorphisms, resulted in the identification of the same three loci involved in milk and meat quality data by using the two methods, while the FST based method identified 3 more loci as under selection sweep in the breeds examined. Conclusion Data appear congruent by using the two methods for FST values exceeding the 99% confidence limits. The methods of FST and SAM can independently detect signatures of selection and therefore can reduce the probability of finding false positives if employed together. The outlier loci identified in this study could indicate adaptive variation in the analysed species, characterized by a large range of climatic conditions in the rearing areas and by a history of intense trade, that implies plasticity in adapting to new environments.

Microbiome Selection Could Spur Next-Generation Plant Breeding Strategies.

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Gopal, Murali; Gupta, Alka

2016-01-01

" No plant is an island too …" Plants, though sessile, have developed a unique strategy to counter biotic and abiotic stresses by symbiotically co-evolving with microorganisms and tapping into their genome for this purpose. Soil is the bank of microbial diversity from which a plant selectively sources its microbiome to suit its needs. Besides soil, seeds, which carry the genetic blueprint of plants during trans-generational propagation, are home to diverse microbiota that acts as the principal source of microbial inoculum in crop cultivation. Overall, a plant is ensconced both on the outside and inside with a diverse assemblage of microbiota. Together, the plant genome and the genes of the microbiota that the plant harbors in different plant tissues, i.e., the 'plant microbiome,' form the holobiome which is now considered as unit of selection: 'the holobiont.' The 'plant microbiome' not only helps plants to remain fit but also offers critical genetic variability, hitherto, not employed in the breeding strategy by plant breeders, who traditionally have exploited the genetic variability of the host for developing high yielding or disease tolerant or drought resistant varieties. This fresh knowledge of the microbiome, particularly of the rhizosphere, offering genetic variability to plants, opens up new horizons for breeding that could usher in cultivation of next-generation crops depending less on inorganic inputs, resistant to insect pest and diseases and resilient to climatic perturbations. We surmise, from ever increasing evidences, that plants and their microbial symbionts need to be co-propagated as life-long partners in future strategies for plant breeding. In this perspective, we propose bottom-up approach to co-propagate the co-evolved, the plant along with the target microbiome, through - (i) reciprocal soil transplantation method, or (ii) artificial ecosystem selection method of synthetic microbiome inocula, or (iii) by exploration of microRNA transfer

Genome-Wide Approaches to Drosophila Heart Development

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Manfred Frasch

2016-05-01

Full Text Available The development of the dorsal vessel in Drosophila is one of the first systems in which key mechanisms regulating cardiogenesis have been defined in great detail at the genetic and molecular level. Due to evolutionary conservation, these findings have also provided major inputs into studies of cardiogenesis in vertebrates. Many of the major components that control Drosophila cardiogenesis were discovered based on candidate gene approaches and their functions were defined by employing the outstanding genetic tools and molecular techniques available in this system. More recently, approaches have been taken that aim to interrogate the entire genome in order to identify novel components and describe genomic features that are pertinent to the regulation of heart development. Apart from classical forward genetic screens, the availability of the thoroughly annotated Drosophila genome sequence made new genome-wide approaches possible, which include the generation of massive numbers of RNA interference (RNAi reagents that were used in forward genetic screens, as well as studies of the transcriptomes and proteomes of the developing heart under normal and experimentally manipulated conditions. Moreover, genome-wide chromatin immunoprecipitation experiments have been performed with the aim to define the full set of genomic binding sites of the major cardiogenic transcription factors, their relevant target genes, and a more complete picture of the regulatory network that drives cardiogenesis. This review will give an overview on these genome-wide approaches to Drosophila heart development and on computational analyses of the obtained information that ultimately aim to provide a description of this process at the systems level.

The importance of identity-by-state information for the accuracy of genomic selection

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Luan Tu

2012-08-01

Full Text Available Abstract Background It is commonly assumed that prediction of genome-wide breeding values in genomic selection is achieved by capitalizing on linkage disequilibrium between markers and QTL but also on genetic relationships. Here, we investigated the reliability of predicting genome-wide breeding values based on population-wide linkage disequilibrium information, based on identity-by-descent relationships within the known pedigree, and to what extent linkage disequilibrium information improves predictions based on identity-by-descent genomic relationship information. Methods The study was performed on milk, fat, and protein yield, using genotype data on 35 706 SNP and deregressed proofs of 1086 Italian Brown Swiss bulls. Genome-wide breeding values were predicted using a genomic identity-by-state relationship matrix and a genomic identity-by-descent relationship matrix (averaged over all marker loci. The identity-by-descent matrix was calculated by linkage analysis using one to five generations of pedigree data. Results We showed that genome-wide breeding values prediction based only on identity-by-descent genomic relationships within the known pedigree was as or more reliable than that based on identity-by-state, which implicitly also accounts for genomic relationships that occurred before the known pedigree. Furthermore, combining the two matrices did not improve the prediction compared to using identity-by-descent alone. Including different numbers of generations in the pedigree showed that most of the information in genome-wide breeding values prediction comes from animals with known common ancestors less than four generations back in the pedigree. Conclusions Our results show that, in pedigreed breeding populations, the accuracy of genome-wide breeding values obtained by identity-by-descent relationships was not improved by identity-by-state information. Although, in principle, genomic selection based on identity-by-state does not require

Genome-Wide Association Analyses Highlight the Potential for Different Genetic Mechanisms for Litter Size Among Sheep Breeds

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Xu, Song-Song; Gao, Lei; Xie, Xing-Long; Ren, Yan-Ling; Shen, Zhi-Qiang; Wang, Feng; Shen, Min; Eyϸórsdóttir, Emma; Hallsson, Jón H.; Kiseleva, Tatyana; Kantanen, Juha; Li, Meng-Hua

2018-01-01

Reproduction is an important trait in sheep breeding as well as in other livestock. However, despite its importance the genetic mechanisms of litter size in domestic sheep (Ovis aries) are still poorly understood. To explore genetic mechanisms underlying the variation in litter size, we conducted multiple independent genome-wide association studies in five sheep breeds of high prolificacy (Wadi, Hu, Icelandic, Finnsheep, and Romanov) and one low prolificacy (Texel) using the Ovine Infinium HD BeadChip, respectively. We identified different sets of candidate genes associated with litter size in different breeds: BMPR1B, FBN1, and MMP2 in Wadi; GRIA2, SMAD1, and CTNNB1 in Hu; NCOA1 in Icelandic; INHBB, NF1, FLT1, PTGS2, and PLCB3 in Finnsheep; ESR2 in Romanov and ESR1, GHR, ETS1, MMP15, FLI1, and SPP1 in Texel. Further annotation of genes and bioinformatics analyses revealed that different biological pathways could be involved in the variation in litter size of females: hormone secretion (FSH and LH) in Wadi and Hu, placenta and embryonic lethality in Icelandic, folliculogenesis and LH signaling in Finnsheep, ovulation and preovulatory follicle maturation in Romanov, and estrogen and follicular growth in Texel. Taken together, our results provide new insights into the genetic mechanisms underlying the prolificacy trait in sheep and other mammals, suggesting targets for selection where the aim is to increase prolificacy in breeding projects.

Investigating Drought Tolerance in Chickpea Using Genome-Wide Association Mapping and Genomic Selection Based on Whole-Genome Resequencing Data.

Science.gov (United States)

Li, Yongle; Ruperao, Pradeep; Batley, Jacqueline; Edwards, David; Khan, Tanveer; Colmer, Timothy D; Pang, Jiayin; Siddique, Kadambot H M; Sutton, Tim

2018-01-01

Drought tolerance is a complex trait that involves numerous genes. Identifying key causal genes or linked molecular markers can facilitate the fast development of drought tolerant varieties. Using a whole-genome resequencing approach, we sequenced 132 chickpea varieties and advanced breeding lines and found more than 144,000 single nucleotide polymorphisms (SNPs). We measured 13 yield and yield-related traits in three drought-prone environments of Western Australia. The genotypic effects were significant for all traits, and many traits showed highly significant correlations, ranging from 0.83 between grain yield and biomass to -0.67 between seed weight and seed emergence rate. To identify candidate genes, the SNP and trait data were incorporated into the SUPER genome-wide association study (GWAS) model, a modified version of the linear mixed model. We found that several SNPs from auxin-related genes, including auxin efflux carrier protein (PIN3), p-glycoprotein, and nodulin MtN21/EamA-like transporter, were significantly associated with yield and yield-related traits under drought-prone environments. We identified four genetic regions containing SNPs significantly associated with several different traits, which was an indication of pleiotropic effects. We also investigated the possibility of incorporating the GWAS results into a genomic selection (GS) model, which is another approach to deal with complex traits. Compared to using all SNPs, application of the GS model using subsets of SNPs significantly associated with the traits under investigation increased the prediction accuracies of three yield and yield-related traits by more than twofold. This has important implication for implementing GS in plant breeding programs.

A new genomic resource dedicated to wood formation in Eucalyptus

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Couloux Arnaud

2009-03-01

large set of wood-related Eucalyptus unigenes called EUCAWOOD, thus creating a valuable resource for functional genomics studies of wood formation and molecular breeding in this economically important genus. This set of publicly available annotated sequences will be instrumental for candidate gene approaches, custom array development and marker-assisted selection programs aimed at improving and modulating wood properties.

Recent and historical recombination in the admixed Norwegian Red cattle breed

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Grove Harald

2011-01-01

Full Text Available Abstract Background Comparison of recent patterns of recombination derived from linkage maps to historical patterns of recombination from linkage disequilibrium (LD could help identify genomic regions affected by strong artificial selection, appearing as reduced recent recombination. Norwegian Red cattle (NRF make an interesting case study for investigating these patterns as it is an admixed breed with an extensively recorded pedigree. NRF have been under strong artificial selection for traits such as milk and meat production, fertility and health. While measures of LD is also crucial for determining the number of markers required for association mapping studies, estimates of recombination rate can be used to assess quality of genomic assemblies. Results A dataset containing more than 17,000 genome-wide distributed SNPs and 2600 animals was used to assess recombination rates and LD in NRF. Although low LD measured by r2 was observed in NRF relative to some of the breeds from which this breed originates, reports from breeds other than those assessed in this study have described more rapid decline in r2 at short distances than what was found in NRF. Rate of decline in r2 for NRF suggested that to obtain an expected r2 between markers and a causal polymorphism of at least 0.5 for genome-wide association studies, approximately one SNP every 15 kb or a total of 200,000 SNPs would be required. For well known quantitative trait loci (QTLs for milk production traits on Bos Taurus chromosomes 1, 6 and 20, map length based on historic recombination was greater than map length based on recent recombination in NRF. Further, positions for 130 previously unpositioned contigs from assembly of the bovine genome sequence (Btau_4.0 found using comparative sequence analysis were validated by linkage analysis, and 28% of these positions corresponded to extreme values of population recombination rate. Conclusion While LD is reduced in NRF compared to some of the

Bayesian genomic selection: the effect of haplotype lenghts and priors

DEFF Research Database (Denmark)

Villumsen, Trine Michelle; Janss, Luc

2009-01-01

Breeding values for animals with marker data are estimated using a genomic selection approach where data is analyzed using Bayesian multi-marker association models. Fourteen model scenarios with varying haplotype lengths, hyper parameter and prior distributions were compared to find the scenario ...

Genome Editing: A New Approach to Human Therapeutics.

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Porteus, Matthew

2016-01-01

The ability to manipulate the genome with precise spatial and nucleotide resolution (genome editing) has been a powerful research tool. In the past decade, the tools and expertise for using genome editing in human somatic cells and pluripotent cells have increased to such an extent that the approach is now being developed widely as a strategy to treat human disease. The fundamental process depends on creating a site-specific DNA double-strand break (DSB) in the genome and then allowing the cell's endogenous DSB repair machinery to fix the break such that precise nucleotide changes are made to the DNA sequence. With the development and discovery of several different nuclease platforms and increasing knowledge of the parameters affecting different genome editing outcomes, genome editing frequencies now reach therapeutic relevance for a wide variety of diseases. Moreover, there is a series of complementary approaches to assessing the safety and toxicity of any genome editing process, irrespective of the underlying nuclease used. Finally, the development of genome editing has raised the issue of whether it should be used to engineer the human germline. Although such an approach could clearly prevent the birth of people with devastating and destructive genetic diseases, questions remain about whether human society is morally responsible enough to use this tool.

Stakeholder involvement in establishing a milk quality sub-index in dairy cow breeding goals: a Delphi approach.

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Henchion, M; McCarthy, M; Resconi, V C; Berry, D P; McParland, S

2016-05-01

The relative weighting on traits within breeding goals are generally determined by bio-economic models or profit functions. While such methods have generally delivered profitability gains to producers, and are being expanded to consider non-market values, current approaches generally do not consider the numerous and diverse stakeholders that affect, or are affected, by such tools. Based on principles of respondent anonymity, iteration, controlled feedback and statistical aggregation of feedback, a Delphi study was undertaken to gauge stakeholder opinion of the importance of detailed milk quality traits within an overall dairy breeding goal for profit, with the aim of assessing its suitability as a complementary, participatory approach to defining breeding goals. The questionnaires used over two survey rounds asked stakeholders: (a) their opinion on incorporating an explicit sub-index for milk quality into a national breeding goal; (b) the importance they would assign to a pre-determined list of milk quality traits and (c) the (relative) weighting they would give such a milk quality sub-index. Results from the survey highlighted a good degree of consensus among stakeholders on the issues raised. Similarly, revelation of the underlying assumptions and knowledge used by stakeholders to make their judgements illustrated their ability to consider a range of perspectives when evaluating traits, and to reconsider their answers based on the responses and rationales given by others, which demonstrated social learning. Finally, while the relative importance assigned by stakeholders in the Delphi survey (4% to 10%) and the results of calculations based on selection index theory of the relative emphasis that should be placed on milk quality to halt any deterioration (16%) are broadly in line, the difference indicates the benefit of considering more than one approach to determining breeding goals. This study thus illustrates the role of the Delphi technique, as a complementary

Empowering breeding programs with new approaches to overcome constraints for selecting superior quality traits of rice

NARCIS (Netherlands)

Calingacion, M.N.

2015-01-01

Empowering breeding programs with new approaches to overcome constraints for selecting superior quality traits of rice

Mariafe N. Calingacion

Most rice breeding programs have focused on improving agronomic traits such as yield, while enhancing grain quality traits

The research progress of genomic selection in livestock.

Science.gov (United States)

Li, Hong-wei; Wang, Rui-jun; Wang, Zhi-ying; Li, Xue-wu; Wang, Zhen-yu; Yanjun, Zhang; Rui, Su; Zhihong, Liu; Jinquan, Li

2017-05-20

With the development of gene chip and breeding technology, genomic selection in plants and animals has become research hotspots in recent years. Genomic selection has been extensively applied to all kinds of economic livestock, due to its high accuracy, short generation intervals and low breeding costs. In this review, we summarize genotyping technology and the methods for genomic breeding value estimation, the latter including the least square method, RR-BLUP, GBLUP, ssGBLUP, BayesA and BayesB. We also cover basic principles of genomic selection and compare their genetic marker ranges, genomic selection accuracy and operational speed. In addition, we list common indicators, methods and influencing factors that are related to genomic selection accuracy. Lastly, we discuss latest applications and the current problems of genomic selection at home and abroad. Importantly, we envision future status of genomic selection research, including multi-trait and multi-population genomic selection, as well as impact of whole genome sequencing and dominant effects on genomic selection. This review will provide some venues for other breeders to further understand genome selection.

Breeding rootstocks for Prunus species: Advances in genetic and genomics of peach and cherry as a model

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Verónica Guajardo

2015-08-01

Full Text Available Prunus rootstock is an important choice in optimizing productivity of grafted cultivars. Nevertheless, many Prunus rootstocks are notoriously intolerant to hypoxia which is caused by waterlogging and/or heavy soils. There is no available information to help select Prunus rootstocks that are tolerant to stress conditions such as root hypoxia caused by excess moisture. Information from genetic maps has demonstrated a high level of synteny among Prunus species, and this suggests that they all share a similar genomic structure. It should be possible to identify the genetic determinants involved in tolerance to hypoxia and other traits in Prunus rootstocks by applying methods to identify regions of the genome involved in the expression of important traits; these have been developed mainly in peach which is the model species for the genus. Molecular markers that are tightly linked to major genes would be useful in marker-assisted selection (MAS to optimize new rootstock selection. This article provides insight on the advances in the development of molecular markers, genetic maps, and gene identification in Prunus, mainly in peach; the aim is to provide a general approach for identifying the genetic determinants of hypoxia stress in rootstocks.

Genome-Wide Analysis of Grain Yield Stability and Environmental Interactions in a Multiparental Soybean Population

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Alencar Xavier

2018-02-01

Full Text Available Genetic improvement toward optimized and stable agronomic performance of soybean genotypes is desirable for food security. Understanding how genotypes perform in different environmental conditions helps breeders develop sustainable cultivars adapted to target regions. Complex traits of importance are known to be controlled by a large number of genomic regions with small effects whose magnitude and direction are modulated by environmental factors. Knowledge of the constraints and undesirable effects resulting from genotype by environmental interactions is a key objective in improving selection procedures in soybean breeding programs. In this study, the genetic basis of soybean grain yield responsiveness to environmental factors was examined in a large soybean nested association population. For this, a genome-wide association to performance stability estimates generated from a Finlay-Wilkinson analysis and the inclusion of the interaction between marker genotypes and environmental factors was implemented. Genomic footprints were investigated by analysis and meta-analysis using a recently published multiparent model. Results indicated that specific soybean genomic regions were associated with stability, and that multiplicative interactions were present between environments and genetic background. Seven genomic regions in six chromosomes were identified as being associated with genotype-by-environment interactions. This study provides insight into genomic assisted breeding aimed at achieving a more stable agronomic performance of soybean, and documented opportunities to exploit genomic regions that were specifically associated with interactions involving environments and subpopulations.

Breeding approaches for crenate broomrape (Orobanche crenata Forsk.) management in pea (Pisum sativum L.).

Science.gov (United States)

Rubiales, Diego; Fernández-Aparicio, Monica; Pérez-de-Luque, Alejandro; Castillejo, Mari A; Prats, Elena; Sillero, Josefina C; Rispail, Nicolas; Fondevilla, Sara

2009-05-01

Pea cultivation is strongly hampered in Mediterranean and Middle East farming systems by the occurrence of Orobanche crenata Forsk. Strategies of control have been developed, but only marginal successes have been achieved. Most control methods are either unfeasible, uneconomical, hard to achieve or result in incomplete protection. The integration of several control measures is the most desirable strategy. [corrected] Recent developments in control are presented and re-evaluated in light of recent developments in crop breeding and molecular genetics. These developments are placed within a framework that is compatible with current agronomic practices. The current focus in applied breeding is leveraging biotechnological tools to develop more and better markers to speed up the delivery of improved cultivars to the farmer. To date, however, progress in marker development and delivery of useful markers has been slow. The application of knowledge gained from basic genomic research and genetic engineering will contribute to more rapid pea improvement for resistance against O. crenata and/or the herbicide.

Ridge Regression and Other Kernels for Genomic Selection with R Package rrBLUP

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Jeffrey B. Endelman

2011-11-01

Full Text Available Many important traits in plant breeding are polygenic and therefore recalcitrant to traditional marker-assisted selection. Genomic selection addresses this complexity by including all markers in the prediction model. A key method for the genomic prediction of breeding values is ridge regression (RR, which is equivalent to best linear unbiased prediction (BLUP when the genetic covariance between lines is proportional to their similarity in genotype space. This additive model can be broadened to include epistatic effects by using other kernels, such as the Gaussian, which represent inner products in a complex feature space. To facilitate the use of RR and nonadditive kernels in plant breeding, a new software package for R called rrBLUP has been developed. At its core is a fast maximum-likelihood algorithm for mixed models with a single variance component besides the residual error, which allows for efficient prediction with unreplicated training data. Use of the rrBLUP software is demonstrated through several examples, including the identification of optimal crosses based on superior progeny value. In cross-validation tests, the prediction accuracy with nonadditive kernels was significantly higher than RR for wheat ( L. grain yield but equivalent for several maize ( L. traits.

Microbial genome analysis: the COG approach.

Science.gov (United States)

Galperin, Michael Y; Kristensen, David M; Makarova, Kira S; Wolf, Yuri I; Koonin, Eugene V

2017-09-14

For the past 20 years, the Clusters of Orthologous Genes (COG) database had been a popular tool for microbial genome annotation and comparative genomics. Initially created for the purpose of evolutionary classification of protein families, the COG have been used, apart from straightforward functional annotation of sequenced genomes, for such tasks as (i) unification of genome annotation in groups of related organisms; (ii) identification of missing and/or undetected genes in complete microbial genomes; (iii) analysis of genomic neighborhoods, in many cases allowing prediction of novel functional systems; (iv) analysis of metabolic pathways and prediction of alternative forms of enzymes; (v) comparison of organisms by COG functional categories; and (vi) prioritization of targets for structural and functional characterization. Here we review the principles of the COG approach and discuss its key advantages and drawbacks in microbial genome analysis. Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.

Genomic and pedigree-based prediction for leaf, stem, and stripe rust resistance in wheat.

Science.gov (United States)

Juliana, Philomin; Singh, Ravi P; Singh, Pawan K; Crossa, Jose; Huerta-Espino, Julio; Lan, Caixia; Bhavani, Sridhar; Rutkoski, Jessica E; Poland, Jesse A; Bergstrom, Gary C; Sorrells, Mark E

2017-07-01

Genomic prediction for seedling and adult plant resistance to wheat rusts was compared to prediction using few markers as fixed effects in a least-squares approach and pedigree-based prediction. The unceasing plant-pathogen arms race and ephemeral nature of some rust resistance genes have been challenging for wheat (Triticum aestivum L.) breeding programs and farmers. Hence, it is important to devise strategies for effective evaluation and exploitation of quantitative rust resistance. One promising approach that could accelerate gain from selection for rust resistance is 'genomic selection' which utilizes dense genome-wide markers to estimate the breeding values (BVs) for quantitative traits. Our objective was to compare three genomic prediction models including genomic best linear unbiased prediction (GBLUP), GBLUP A that was GBLUP with selected loci as fixed effects and reproducing kernel Hilbert spaces-markers (RKHS-M) with least-squares (LS) approach, RKHS-pedigree (RKHS-P), and RKHS markers and pedigree (RKHS-MP) to determine the BVs for seedling and/or adult plant resistance (APR) to leaf rust (LR), stem rust (SR), and stripe rust (YR). The 333 lines in the 45th IBWSN and the 313 lines in the 46th IBWSN were genotyped using genotyping-by-sequencing and phenotyped in replicated trials. The mean prediction accuracies ranged from 0.31-0.74 for LR seedling, 0.12-0.56 for LR APR, 0.31-0.65 for SR APR, 0.70-0.78 for YR seedling, and 0.34-0.71 for YR APR. For most datasets, the RKHS-MP model gave the highest accuracies, while LS gave the lowest. GBLUP, GBLUP A, RKHS-M, and RKHS-P models gave similar accuracies. Using genome-wide marker-based models resulted in an average of 42% increase in accuracy over LS. We conclude that GS is a promising approach for improvement of quantitative rust resistance and can be implemented in the breeding pipeline.

Analysis of Plant Breeding on Hadoop and Spark

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Shuangxi Chen

2016-01-01

Full Text Available Analysis of crop breeding technology is one of the important means of computer-assisted breeding techniques which have huge data, high dimensions, and a lot of unstructured data. We propose a crop breeding data analysis platform on Spark. The platform consists of Hadoop distributed file system (HDFS and cluster based on memory iterative components. With this cluster, we achieve crop breeding large data analysis tasks in parallel through API provided by Spark. By experiments and tests of Indica and Japonica rice traits, plant breeding analysis platform can significantly improve the breeding of big data analysis speed, reducing the workload of concurrent programming.

Tritium breeding in fusion reactors

International Nuclear Information System (INIS)

Abdou, M.A.

1982-10-01

Key technological problems that influence tritium breeding in fusion blankets are reviewed. The breeding potential of candidate materials is evaluated and compared to the tritium breeding requirements. The sensitivity of tritium breeding to design and nuclear data parameters is reviewed. A framework for an integrated approach to improve tritium breeding prediction is discussed with emphasis on nuclear data requirements

Compression distance can discriminate animals by genetic profile, build relationship matrices and estimate breeding values.

Science.gov (United States)

Hudson, Nicholas J; Porto-Neto, Laercio; Kijas, James W; Reverter, Antonio

2015-10-13

Genetic relatedness is currently estimated by a combination of traditional pedigree-based approaches (i.e. numerator relationship matrices, NRM) and, given the recent availability of molecular information, using marker genotypes (via genomic relationship matrices, GRM). To date, GRM are computed by genome-wide pair-wise SNP (single nucleotide polymorphism) correlations. We describe a new estimate of genetic relatedness using the concept of normalised compression distance (NCD) that is borrowed from Information Theory. Analogous to GRM, the resultant compression relationship matrix (CRM) exploits numerical patterns in genome-wide allele order and proportion, which are known to vary systematically with relatedness. We explored properties of the CRM in two industry cattle datasets by analysing the genetic basis of yearling weight, a phenotype of moderate heritability. In both Brahman (Bos indicus) and Tropical Composite (Bos taurus by Bos indicus) populations, the clustering inferred by NCD was comparable to that based on SNP correlations using standard principal component analysis approaches. One of the versions of the CRM modestly increased the amount of explained genetic variance, slightly reduced the 'missing heritability' and tended to improve the prediction accuracy of breeding values in both populations when compared to both NRM and GRM. Finally, a sliding window-based application of the compression approach on these populations identified genomic regions influenced by introgression of taurine haplotypes. For these two bovine populations, CRM reduced the missing heritability and increased the amount of explained genetic variation for a moderately heritable complex trait. Given that NCD can sensitively discriminate closely related individuals, we foresee CRM having possible value for estimating breeding values in highly inbred populations.

Genomic Selection in Multi-environment Crop Trials.

Science.gov (United States)

Oakey, Helena; Cullis, Brian; Thompson, Robin; Comadran, Jordi; Halpin, Claire; Waugh, Robbie

2016-05-03

Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers. Copyright © 2016 Oakey et al.

Genome-wide resequencing of KRICE_CORE reveals their potential for future breeding, as well as functional and evolutionary studies in the post-genomic era.

Science.gov (United States)

Kim, Tae-Sung; He, Qiang; Kim, Kyu-Won; Yoon, Min-Young; Ra, Won-Hee; Li, Feng Peng; Tong, Wei; Yu, Jie; Oo, Win Htet; Choi, Buung; Heo, Eun-Beom; Yun, Byoung-Kook; Kwon, Soon-Jae; Kwon, Soon-Wook; Cho, Yoo-Hyun; Lee, Chang-Yong; Park, Beom-Seok; Park, Yong-Jin

2016-05-26

Rice germplasm collections continue to grow in number and size around the world. Since maintaining and screening such massive resources remains challenging, it is important to establish practical methods to manage them. A core collection, by definition, refers to a subset of the entire population that preserves the majority of genetic diversity, enhancing the efficiency of germplasm utilization. Here, we report whole-genome resequencing of the 137 rice mini core collection or Korean rice core set (KRICE_CORE) that represents 25,604 rice germplasms deposited in the Korean genebank of the Rural Development Administration (RDA). We implemented the Illumina HiSeq 2000 and 2500 platform to produce short reads and then assembled those with 9.8 depths using Nipponbare as a reference. Comparisons of the sequences with the reference genome yielded more than 15 million (M) single nucleotide polymorphisms (SNPs) and 1.3 M INDELs. Phylogenetic and population analyses using 2,046,529 high-quality SNPs successfully assigned rice accessions to the relevant rice subgroups, suggesting that these SNPs capture evolutionary signatures that have accumulated in rice subpopulations. Furthermore, genome-wide association studies (GWAS) for four exemplary agronomic traits in the KRIC_CORE manifest the utility of KRICE_CORE; that is, identifying previously defined genes or novel genetic factors that potentially regulate important phenotypes. This study provides strong evidence that the size of KRICE_CORE is small but contains high genetic and functional diversity across the genome. Thus, our resequencing results will be useful for future breeding, as well as functional and evolutionary studies, in the post-genomic era.

Investigating Drought Tolerance in Chickpea Using Genome-Wide Association Mapping and Genomic Selection Based on Whole-Genome Resequencing Data

Directory of Open Access Journals (Sweden)

Yongle Li

2018-02-01

Full Text Available Drought tolerance is a complex trait that involves numerous genes. Identifying key causal genes or linked molecular markers can facilitate the fast development of drought tolerant varieties. Using a whole-genome resequencing approach, we sequenced 132 chickpea varieties and advanced breeding lines and found more than 144,000 single nucleotide polymorphisms (SNPs. We measured 13 yield and yield-related traits in three drought-prone environments of Western Australia. The genotypic effects were significant for all traits, and many traits showed highly significant correlations, ranging from 0.83 between grain yield and biomass to -0.67 between seed weight and seed emergence rate. To identify candidate genes, the SNP and trait data were incorporated into the SUPER genome-wide association study (GWAS model, a modified version of the linear mixed model. We found that several SNPs from auxin-related genes, including auxin efflux carrier protein (PIN3, p-glycoprotein, and nodulin MtN21/EamA-like transporter, were significantly associated with yield and yield-related traits under drought-prone environments. We identified four genetic regions containing SNPs significantly associated with several different traits, which was an indication of pleiotropic effects. We also investigated the possibility of incorporating the GWAS results into a genomic selection (GS model, which is another approach to deal with complex traits. Compared to using all SNPs, application of the GS model using subsets of SNPs significantly associated with the traits under investigation increased the prediction accuracies of three yield and yield-related traits by more than twofold. This has important implication for implementing GS in plant breeding programs.

Genomics and Evolution in Traditional Medicinal Plants: Road to a Healthier Life.

Science.gov (United States)

Hao, Da-Cheng; Xiao, Pei-Gen

2015-01-01

Medicinal plants have long been utilized in traditional medicine and ethnomedicine worldwide. This review presents a glimpse of the current status of and future trends in medicinal plant genomics, evolution, and phylogeny. These dynamic fields are at the intersection of phytochemistry and plant biology and are concerned with the evolution mechanisms and systematics of medicinal plant genomes, origin and evolution of the plant genotype and metabolic phenotype, interaction between medicinal plant genomes and their environment, the correlation between genomic diversity and metabolite diversity, and so on. Use of the emerging high-end genomic technologies can be expanded from crop plants to traditional medicinal plants, in order to expedite medicinal plant breeding and transform them into living factories of medicinal compounds. The utility of molecular phylogeny and phylogenomics in predicting chemodiversity and bioprospecting is also highlighted within the context of natural-product-based drug discovery and development. Representative case studies of medicinal plant genome, phylogeny, and evolution are summarized to exemplify the expansion of knowledge pedigree and the paradigm shift to the omics-based approaches, which update our awareness about plant genome evolution and enable the molecular breeding of medicinal plants and the sustainable utilization of plant pharmaceutical resources.

Prediction of Genes Related to Positive Selection Using Whole-Genome Resequencing in Three Commercial Pig Breeds

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HyoYoung Kim

2015-12-01

Full Text Available Selective sweep can cause genetic differentiation across populations, which allows for the identification of possible causative regions/genes underlying important traits. The pig has experienced a long history of allele frequency changes through artificial selection in the domestication process. We obtained an average of 329,482,871 sequence reads for 24 pigs from three pig breeds: Yorkshire (n = 5, Landrace (n = 13, and Duroc (n = 6. An average read depth of 11.7 was obtained using whole-genome resequencing on an Illumina HiSeq2000 platform. In this study, cross-population extended haplotype homozygosity and cross-population composite likelihood ratio tests were implemented to detect genes experiencing positive selection for the genome-wide resequencing data generated from three commercial pig breeds. In our results, 26, 7, and 14 genes from Yorkshire, Landrace, and Duroc, respectively were detected by two kinds of statistical tests. Significant evidence for positive selection was identified on genes ST6GALNAC2 and EPHX1 in Yorkshire, PARK2 in Landrace, and BMP6, SLA-DQA1, and PRKG1 in Duroc.These genes are reportedly relevant to lactation, reproduction, meat quality, and growth traits. To understand how these single nucleotide polymorphisms (SNPs related positive selection affect protein function, we analyzed the effect of non-synonymous SNPs. Three SNPs (rs324509622, rs80931851, and rs80937718 in the SLA-DQA1 gene were significant in the enrichment tests, indicating strong evidence for positive selection in Duroc. Our analyses identified genes under positive selection for lactation, reproduction, and meat-quality and growth traits in Yorkshire, Landrace, and Duroc, respectively.

Cereal Crop Proteomics: Systemic Analysis of Crop Drought Stress Responses Towards Marker-Assisted Selection Breeding

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Arindam Ghatak

2017-06-01

Full Text Available Sustainable crop production is the major challenge in the current global climate change scenario. Drought stress is one of the most critical abiotic factors which negatively impact crop productivity. In recent years, knowledge about molecular regulation has been generated to understand drought stress responses. For example, information obtained by transcriptome analysis has enhanced our knowledge and facilitated the identification of candidate genes which can be utilized for plant breeding. On the other hand, it becomes more and more evident that the translational and post-translational machinery plays a major role in stress adaptation, especially for immediate molecular processes during stress adaptation. Therefore, it is essential to measure protein levels and post-translational protein modifications to reveal information about stress inducible signal perception and transduction, translational activity and induced protein levels. This information cannot be revealed by genomic or transcriptomic analysis. Eventually, these processes will provide more direct insight into stress perception then genetic markers and might build a complementary basis for future marker-assisted selection of drought resistance. In this review, we survey the role of proteomic studies to illustrate their applications in crop stress adaptation analysis with respect to productivity. Cereal crops such as wheat, rice, maize, barley, sorghum and pearl millet are discussed in detail. We provide a comprehensive and comparative overview of all detected protein changes involved in drought stress in these crops and have summarized existing knowledge into a proposed scheme of drought response. Based on a recent proteome study of pearl millet under drought stress we compare our findings with wheat proteomes and another recent study which defined genetic marker in pearl millet.

Exploiting linkage disequilibrium in statistical modelling in quantitative genomics

DEFF Research Database (Denmark)

Wang, Lei

Alleles at two loci are said to be in linkage disequilibrium (LD) when they are correlated or statistically dependent. Genomic prediction and gene mapping rely on the existence of LD between gentic markers and causul variants of complex traits. In the first part of the thesis, a novel method...... to quantify and visualize local variation in LD along chromosomes in describet, and applied to characterize LD patters at the local and genome-wide scale in three Danish pig breeds. In the second part, different ways of taking LD into account in genomic prediction models are studied. One approach is to use...... the recently proposed antedependence models, which treat neighbouring marker effects as correlated; another approach involves use of haplotype block information derived using the program Beagle. The overall conclusion is that taking LD information into account in genomic prediction models potentially improves...

QTL analysis by sequencing of Water Use Efficiency (WUE) in potato

DEFF Research Database (Denmark)

Kaminski, Kacper Piotr; Sønderkær, Mads; Sørensen, Kirsten Kørup

2013-01-01

The traditional approach to potato breeding, the classical “mate and phenotype” approach is relatively costly and because phenotyping and growth capacity is limited, this are being slowly replaced by Marker Assisted Selection (MAS) breeding schemes. MAS is based on the presence of DNA polymorphic.......sparsipilum), phenotyped for water use efficiency. This population has also previously been phenotyped for the total glycoalkaloid (TGA) content....... and time consuming process. Here, a novel method for Quantitative Trait Locus (QTL) analysis has been developed, that allows for development of specific markers by use of genomic sequence reads and the recently published reference genome sequence for potato. Prior to sequencing the mapping population...

Performance of genomic prediction within and across generations in maritime pine

NARCIS (Netherlands)

Bartholomé, Jérôme; Heerwaarden, Van Joost; Isik, Fikret; Boury, Christophe; Vidal, Marjorie; Plomion, Christophe; Bouffier, Laurent

2016-01-01

Background: Genomic selection (GS) is a promising approach for decreasing breeding cycle length in forest trees. Assessment of progeny performance and of the prediction accuracy of GS models over generations is therefore a key issue. Results: A reference population of maritime pine (Pinus

Exploring Triacylglycerol Biosynthetic Pathway in Developing Seeds of Chia (Salvia hispanica L.): A Transcriptomic Approach

OpenAIRE

R. V., Sreedhar; Kumari, Priya; Rupwate, Sunny D.; Rajasekharan, Ram; Srinivasan, Malathi

2015-01-01

Chia (Salvia hispanica L.), a member of the mint family (Lamiaceae), is a rediscovered crop with great importance in health and nutrition and is also the highest known terrestrial plant source of heart-healthy omega-3 fatty acid, alpha linolenic acid (ALA). At present, there is no public genomic information or database available for this crop, hindering research on its genetic improvement through genomics-assisted breeding programs. The first comprehensive analysis of the global transcriptome...

BAUM: Improving genome assembly by adaptive unique mapping and local overlap-layout-consensus approach.

Science.gov (United States)

Wang, Anqi; Wang, Zhanyu; Li, Zheng; Li, Lei M

2018-01-15

It is highly desirable to assemble genomes of high continuity and consistency at low cost. The current bottleneck of draft genome continuity using the Second Generation Sequencing (SGS) reads is primarily caused by uncertainty among repetitive sequences. Even though the Single-Molecule Real-Time sequencing technology is very promising to overcome the uncertainty issue, its relatively high cost and error rate add burden on budget or computation. Many long-read assemblers take the overlap-layout-consensus (OLC) paradigm, which is less sensitive to sequencing errors, heterozygosity and variability of coverage. However, current assemblers of SGS data do not sufficiently take advantage of the OLC approach. Aiming at minimizing uncertainty, the proposed method BAUM, breaks the whole genome into regions by adaptive unique mapping; then the local OLC is used to assemble each region in parallel. BAUM can: (1) perform reference-assisted assembly based on the genome of a close species; (2) or improve the results of existing assemblies that are obtained based on short or long sequencing reads. The tests on two eukaryote genomes, a wild rice Oryza longistaminata and a parrot Melopsittacus undulatus, show that BAUM achieved substantial improvement on genome size and continuity. Besides, BAUM reconstructed a considerable amount of repetitive regions that failed to be assembled by existing short read assemblers. We also propose statistical approaches to control the uncertainty in different steps of BAUM. http://www.zhanyuwang.xin/wordpress/index.php/2017/07/21/baum. lilei@amss.ac.cn. Supplementary data are available at Bioinformatics online. © The Author (2018). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Effects of the number of markers per haplotype and clustering of haplotypes on the accuracy of QTL mapping and prediction of genomic breeding values

NARCIS (Netherlands)

Calus, M.P.L.; Meuwissen, T.H.E.; Windig, J.J.; Knol, E.F.; Schrooten, C.; Vereijken, A.L.J.; Veerkamp, R.F.

2009-01-01

The aim of this paper was to compare the effect of haplotype definition on the precision of QTL-mapping and on the accuracy of predicted genomic breeding values. In a multiple QTL model using identity-by-descent (IBD) probabilities between haplotypes, various haplotype definitions were tested i.e.

Recovery of native genetic background in admixed populations using haplotypes, phenotypes, and pedigree information--using Cika cattle as a case breed.

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Mojca Simčič

Full Text Available The aim of this study was to obtain unbiased estimates of the diversity parameters, the population history, and the degree of admixture in Cika cattle which represents the local admixed breeds at risk of extinction undergoing challenging conservation programs. Genetic analyses were performed on the genome-wide Single Nucleotide Polymorphism (SNP Illumina Bovine SNP50 array data of 76 Cika animals and 531 animals from 14 reference populations. To obtain unbiased estimates we used short haplotypes spanning four markers instead of single SNPs to avoid an ascertainment bias of the BovineSNP50 array. Genome-wide haplotypes combined with partial pedigree and type trait classification show the potential to improve identification of purebred animals with a low degree of admixture. Phylogenetic analyses demonstrated unique genetic identity of Cika animals. Genetic distance matrix presented by rooted Neighbour-Net suggested long and broad phylogenetic connection between Cika and Pinzgauer. Unsupervised clustering performed by the admixture analysis and two-dimensional presentation of the genetic distances between individuals also suggest Cika is a distinct breed despite being similar in appearance to Pinzgauer. Animals identified as the most purebred could be used as a nucleus for a recovery of the native genetic background in the current admixed population. The results show that local well-adapted strains, which have never been intensively managed and differentiated into specific breeds, exhibit large haplotype diversity. They suggest a conservation and recovery approach that does not rely exclusively on the search for the original native genetic background but rather on the identification and removal of common introgressed haplotypes would be more powerful. Successful implementation of such an approach should be based on combining phenotype, pedigree, and genome-wide haplotype data of the breed of interest and a spectrum of reference breeds which

Assessment of Genetic Heterogeneity in Structured Plant Populations Using Multivariate Whole-Genome Regression Models.

Science.gov (United States)

Lehermeier, Christina; Schön, Chris-Carolin; de Los Campos, Gustavo

2015-09-01

Plant breeding populations exhibit varying levels of structure and admixture; these features are likely to induce heterogeneity of marker effects across subpopulations. Traditionally, structure has been dealt with as a potential confounder, and various methods exist to "correct" for population stratification. However, these methods induce a mean correction that does not account for heterogeneity of marker effects. The animal breeding literature offers a few recent studies that consider modeling genetic heterogeneity in multibreed data, using multivariate models. However, these methods have received little attention in plant breeding where population structure can have different forms. In this article we address the problem of analyzing data from heterogeneous plant breeding populations, using three approaches: (a) a model that ignores population structure [A-genome-based best linear unbiased prediction (A-GBLUP)], (b) a stratified (i.e., within-group) analysis (W-GBLUP), and (c) a multivariate approach that uses multigroup data and accounts for heterogeneity (MG-GBLUP). The performance of the three models was assessed on three different data sets: a diversity panel of rice (Oryza sativa), a maize (Zea mays L.) half-sib panel, and a wheat (Triticum aestivum L.) data set that originated from plant breeding programs. The estimated genomic correlations between subpopulations varied from null to moderate, depending on the genetic distance between subpopulations and traits. Our assessment of prediction accuracy features cases where ignoring population structure leads to a parsimonious more powerful model as well as others where the multivariate and stratified approaches have higher predictive power. In general, the multivariate approach appeared slightly more robust than either the A- or the W-GBLUP. Copyright © 2015 by the Genetics Society of America.

An efficient approach to BAC based assembly of complex genomes.

Science.gov (United States)

Visendi, Paul; Berkman, Paul J; Hayashi, Satomi; Golicz, Agnieszka A; Bayer, Philipp E; Ruperao, Pradeep; Hurgobin, Bhavna; Montenegro, Juan; Chan, Chon-Kit Kenneth; Staňková, Helena; Batley, Jacqueline; Šimková, Hana; Doležel, Jaroslav; Edwards, David

2016-01-01

There has been an exponential growth in the number of genome sequencing projects since the introduction of next generation DNA sequencing technologies. Genome projects have increasingly involved assembly of whole genome data which produces inferior assemblies compared to traditional Sanger sequencing of genomic fragments cloned into bacterial artificial chromosomes (BACs). While whole genome shotgun sequencing using next generation sequencing (NGS) is relatively fast and inexpensive, this method is extremely challenging for highly complex genomes, where polyploidy or high repeat content confounds accurate assembly, or where a highly accurate 'gold' reference is required. Several attempts have been made to improve genome sequencing approaches by incorporating NGS methods, to variable success. We present the application of a novel BAC sequencing approach which combines indexed pools of BACs, Illumina paired read sequencing, a sequence assembler specifically designed for complex BAC assembly, and a custom bioinformatics pipeline. We demonstrate this method by sequencing and assembling BAC cloned fragments from bread wheat and sugarcane genomes. We demonstrate that our assembly approach is accurate, robust, cost effective and scalable, with applications for complete genome sequencing in large and complex genomes.

Impact of Molecular Technologies on Faba Bean (Vicia faba L. Breeding Strategies

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Tao Yang

2012-07-01

Full Text Available Faba bean (Vicia faba L. is a major food and feed legume because of the high nutritional value of its seeds. The main objectives of faba bean breeding are to improve yield, disease resistance, abiotic stress tolerance, seed quality and other agronomic traits. The partial cross-pollinated nature of faba bean introduces both challenges and opportunities for population development and breeding. Breeding methods that are applicable to self-pollinated crops or open-pollinated crops are not highly suitable for faba bean. However, traditional breeding methods such as recurrent mass selection have been established in faba bean and used successfully in breeding for resistance to diseases. Molecular breeding strategies that integrate the latest innovations in genetics and genomics with traditional breeding strategies have many potential applications for future faba bean cultivar development. Hence, considerable efforts have been undertaken in identifying molecular markers, enriching genetic and genomic resources using high-throughput sequencing technologies and improving genetic transformation techniques in faba bean. However, the impact of research on practical faba bean breeding and cultivar release to farmers has been limited due to disconnects between research and breeding objectives and the high costs of research and implementation. The situation with faba bean is similar to other small crops and highlights the need for coordinated, collaborative research programs that interact closely with commercially focused breeding programs to ensure that technologies are implemented effectively.

1000 Bull Genomes - Toward genomic Selectionf from whole genome sequence Data in Dairy and Beef Cattle

NARCIS (Netherlands)

Hayes, B.; Daetwyler, H.D.; Fries, R.; Guldbrandtsen, B.; Mogens Sando Lund, M.; Didier A. Boichard, D.A.; Stothard, P.; Veerkamp, R.F.; Hulsegge, B.; Rocha, D.; Tassell, C.; Mullaart, E.; Gredler, B.; Druet, T.; Bagnato, A.; Goddard, M.E.; Chamberlain, H.L.

2013-01-01

Genomic prediction of breeding values is now used as the basis for selection of dairy cattle, and in some cases beef cattle, in a number of countries. When genomic prediction was introduced most of the information was to thought to be derived from linkage disequilibrium between markers and causative

Extent of linkage disequilibrium and effective population size in four South African Sanga cattle breeds

Directory of Open Access Journals (Sweden)

Sithembile Olga Makina

2015-12-01

Full Text Available Knowledge on the extent of linkage disequilibrium (LD in livestock populations is essential to determine the minimum distance between markers required for effective coverage when conducting genome-wide association studies. This study evaluated the extent of LD, persistence of allelic phase and effective population size (Ne for four Sanga cattle breeds in South Africa including the Afrikaner (n=44, Nguni (n=54, Drakensberger (n=47 and Bonsmara breeds (n=46, using Angus (n=31 and Holstein (n=29 as reference populations. We found that moderate LD extends up to inter-marker distances of 40-60 kb in Angus (0.21 and Holstein (0.21 and up to 100 kb in Afrikaner (0.20. This suggests that genomic selection and association studies performed within these breeds using an average inter-marker r2 ≥ 0.20 would require about 30,000 -50,000 SNPs. However, r2 ≥ 0.20 extended only up to 10-20 kb in the Nguni and Drakensberger and 20-40 kb in the Bonsmara indicating that 75,000 to 150,000 SNPs would be necessary for genome-wide association studies in these breeds. Correlation between alleles at contiguous loci indicated that phase was not strongly preserved between breeds. This suggests the need for breed-specific reference populations in which a much greater density of markers should be scored to identify breed specific haplotypes which may then be imputed into multi-breed commercial populations. Analysis of effective population size based on the extent of LD, revealed Ne=95 (Nguni, Ne=87 (Drakensberger, Ne=77 (Bonsmara and Ne=41 (Afrikaner. Results of this study form the basis for implementation of genomic selection programs in the Sanga breeds of South Africa.

Genome-Wide Association Mapping of Flowering and Ripening Periods in Apple

Directory of Open Access Journals (Sweden)

Jorge Urrestarazu

2017-11-01

regions identified by linkage mapping approaches. Our findings can be used for the improvement of apple through marker-assisted breeding strategies that take advantage of the accumulating additive effects of the identified SNPs.

A comprehensive survey on selective breeding programs and seed market in the European aquaculture fish industry

DEFF Research Database (Denmark)

Chavanne, Hervé; Janssen, Kasper; Hofherr, Johann

2016-01-01

–50 % market share. Only part of the European fish aquaculture industry today fully exploits selective breeding to the best advantage. A larger impact assessment still needs to be made by the remainder, particularly on the market share of fish seed (eggs, larvae or juveniles) and its consequences for hatchery...... of molecular tools is now common in all programs, mainly for pedigree traceability. An increasing number of programs use either genomic or marker-assisted selection. Results related to the seed production market confirmed that for Atlantic salmon there are a few dominant players at the European level, with 30...

Comprehensive evaluation of genome-wide 5-hydroxymethylcytosine profiling approaches in human DNA.

Science.gov (United States)

Skvortsova, Ksenia; Zotenko, Elena; Luu, Phuc-Loi; Gould, Cathryn M; Nair, Shalima S; Clark, Susan J; Stirzaker, Clare

2017-01-01

The discovery that 5-methylcytosine (5mC) can be oxidized to 5-hydroxymethylcytosine (5hmC) by the ten-eleven translocation (TET) proteins has prompted wide interest in the potential role of 5hmC in reshaping the mammalian DNA methylation landscape. The gold-standard bisulphite conversion technologies to study DNA methylation do not distinguish between 5mC and 5hmC. However, new approaches to mapping 5hmC genome-wide have advanced rapidly, although it is unclear how the different methods compare in accurately calling 5hmC. In this study, we provide a comparative analysis on brain DNA using three 5hmC genome-wide approaches, namely whole-genome bisulphite/oxidative bisulphite sequencing (WG Bis/OxBis-seq), Infinium HumanMethylation450 BeadChip arrays coupled with oxidative bisulphite (HM450K Bis/OxBis) and antibody-based immunoprecipitation and sequencing of hydroxymethylated DNA (hMeDIP-seq). We also perform loci-specific TET-assisted bisulphite sequencing (TAB-seq) for validation of candidate regions. We show that whole-genome single-base resolution approaches are advantaged in providing precise 5hmC values but require high sequencing depth to accurately measure 5hmC, as this modification is commonly in low abundance in mammalian cells. HM450K arrays coupled with oxidative bisulphite provide a cost-effective representation of 5hmC distribution, at CpG sites with 5hmC levels >~10%. However, 5hmC analysis is restricted to the genomic location of the probes, which is an important consideration as 5hmC modification is commonly enriched at enhancer elements. Finally, we show that the widely used hMeDIP-seq method provides an efficient genome-wide profile of 5hmC and shows high correlation with WG Bis/OxBis-seq 5hmC distribution in brain DNA. However, in cell line DNA with low levels of 5hmC, hMeDIP-seq-enriched regions are not detected by WG Bis/OxBis or HM450K, either suggesting misinterpretation of 5hmC calls by hMeDIP or lack of sensitivity of the latter methods. We

Advances in Setaria genomics for genetic improvement of cereals and bioenergy grasses.

Science.gov (United States)

Muthamilarasan, Mehanathan; Prasad, Manoj

2015-01-01

Recent advances in Setaria genomics appear promising for genetic improvement of cereals and biofuel crops towards providing multiple securities to the steadily increasing global population. The prominent attributes of foxtail millet (Setaria italica, cultivated) and green foxtail (S. viridis, wild) including small genome size, short life-cycle, in-breeding nature, genetic close-relatedness to several cereals, millets and bioenergy grasses, and potential abiotic stress tolerance have accentuated these two Setaria species as novel model system for studying C4 photosynthesis, stress biology and biofuel traits. Considering this, studies have been performed on structural and functional genomics of these plants to develop genetic and genomic resources, and to delineate the physiology and molecular biology of stress tolerance, for the improvement of millets, cereals and bioenergy grasses. The release of foxtail millet genome sequence has provided a new dimension to Setaria genomics, resulting in large-scale development of genetic and genomic tools, construction of informative databases, and genome-wide association and functional genomic studies. In this context, this review discusses the advancements made in Setaria genomics, which have generated a considerable knowledge that could be used for the improvement of millets, cereals and biofuel crops. Further, this review also shows the nutritional potential of foxtail millet in providing health benefits to global population and provides a preliminary information on introgressing the nutritional properties in graminaceous species through molecular breeding and transgene-based approaches.

Use of Genomic Estimated Breeding Values Results in Rapid Genetic Gains for Drought Tolerance in Maize

Directory of Open Access Journals (Sweden)

B.S. Vivek

2017-03-01

Full Text Available More than 80% of the 19 million ha of maize ( L. in tropical Asia is rainfed and prone to drought. The breeding methods for improving drought tolerance (DT, including genomic selection (GS, are geared to increase the frequency of favorable alleles. Two biparental populations (CIMMYT-Asia Population 1 [CAP1] and CAP2 were generated by crossing elite Asian-adapted yellow inbreds (CML470 and VL1012767 with an African white drought-tolerant line, CML444. Marker effects of polymorphic single-nucleotide polymorphisms (SNPs were determined from testcross (TC performance of F families under drought and optimal conditions. Cycle 1 (C1 was formed by recombining the top 10% of the F families based on TC data. Subsequently, (i C2[PerSe_PS] was derived by recombining those C1 plants that exhibited superior per se phenotypes (phenotype-only selection, and (ii C2[TC-GS] was derived by recombining a second set of C1 plants with high genomic estimated breeding values (GEBVs derived from TC phenotypes of F families (marker-only selection. All the generations and their top crosses to testers were evaluated under drought and optimal conditions. Per se grain yields (GYs of C2[PerSe_PS] and that of C2[TC-GS] were 23 to 39 and 31 to 53% better, respectively, than that of the corresponding F population. The C2[TC-GS] populations showed superiority of 10 to 20% over C2[PerSe-PS] of respective populations. Top crosses of C2[TC-GS] showed 4 to 43% superiority of GY over that of C2[PerSe_PS] of respective populations. Thus, GEBV-enabled selection of superior phenotypes (without the target stress resulted in rapid genetic gains for DT.

A high-density SNP genetic linkage map for the silver-lipped pearl oyster, Pinctada maxima: a valuable resource for gene localisation and marker-assisted selection.

Science.gov (United States)

Jones, David B; Jerry, Dean R; Khatkar, Mehar S; Raadsma, Herman W; Zenger, Kyall R

2013-11-20

The silver-lipped pearl oyster, Pinctada maxima, is an important tropical aquaculture species extensively farmed for the highly sought "South Sea" pearls. Traditional breeding programs have been initiated for this species in order to select for improved pearl quality, but many economic traits under selection are complex, polygenic and confounded with environmental factors, limiting the accuracy of selection. The incorporation of a marker-assisted selection (MAS) breeding approach would greatly benefit pearl breeding programs by allowing the direct selection of genes responsible for pearl quality. However, before MAS can be incorporated, substantial genomic resources such as genetic linkage maps need to be generated. The construction of a high-density genetic linkage map for P. maxima is not only essential for unravelling the genomic architecture of complex pearl quality traits, but also provides indispensable information on the genome structure of pearl oysters. A total of 1,189 informative genome-wide single nucleotide polymorphisms (SNPs) were incorporated into linkage map construction. The final linkage map consisted of 887 SNPs in 14 linkage groups, spans a total genetic distance of 831.7 centimorgans (cM), and covers an estimated 96% of the P. maxima genome. Assessment of sex-specific recombination across all linkage groups revealed limited overall heterochiasmy between the sexes (i.e. 1.15:1 F/M map length ratio). However, there were pronounced localised differences throughout the linkage groups, whereby male recombination was suppressed near the centromeres compared to female recombination, but inflated towards telomeric regions. Mean values of LD for adjacent SNP pairs suggest that a higher density of markers will be required for powerful genome-wide association studies. Finally, numerous nacre biomineralization genes were localised providing novel positional information for these genes. This high-density SNP genetic map is the first comprehensive linkage

Genome-wide identification of breed-informative single-nucleotide ...

African Journals Online (AJOL)

Avhashoni AA. Zwane

2016-09-20

Sep 20, 2016 ... ... high temperatures and low-quality grass and for their resistance to ... growth rate, early marketability, grazing performance and good ... development of the Bonsmara breed (Scholtz, 2010). ..... transferability to water buffalo.

Genomic prediction accounting for genotype by environment interaction offers an effective framework for breeding simultaneously for adaptation to an abiotic stress and performance under normal cropping conditions in rice

OpenAIRE

Ahmadi, Nourollah; Cao, Tuong-Vi; Valé, Giampiero; Bartholomé, Jérôme; Hassen, Manel

2018-01-01

Developing rice varieties adapted to alternate wetting and drying water management is crucial for the sustainability of irrigated rice cropping systems. Here we report the first study exploring the feasibility of breeding rice for adaptation to alternate wetting and drying using genomic prediction methods that account for genotype by environment interactions. Two breeding populations (a reference panel of 284 accessions and a progeny population of 97 advanced lines) were evaluated under alter...

Potential of Genomic Selection in Mass Selection Breeding of an Allogamous Crop: An Empirical Study to Increase Yield of Common Buckwheat.

Science.gov (United States)

Yabe, Shiori; Hara, Takashi; Ueno, Mariko; Enoki, Hiroyuki; Kimura, Tatsuro; Nishimura, Satoru; Yasui, Yasuo; Ohsawa, Ryo; Iwata, Hiroyoshi

2018-01-01

To evaluate the potential of genomic selection (GS), a selection experiment with GS and phenotypic selection (PS) was performed in an allogamous crop, common buckwheat ( Fagopyrum esculentum Moench). To indirectly select for seed yield per unit area, which cannot be measured on a single-plant basis, a selection index was constructed from seven agro-morphological traits measurable on a single plant basis. Over 3 years, we performed two GS and one PS cycles per year for improvement in the selection index. In GS, a prediction model was updated every year on the basis of genotypes of 14,598-50,000 markers and phenotypes. Plants grown from seeds derived from a series of generations of GS and PS populations were evaluated for the traits in the selection index and other yield-related traits. GS resulted in a 20.9% increase and PS in a 15.0% increase in the selection index in comparison with the initial population. Although the level of linkage disequilibrium in the breeding population was low, the target trait was improved with GS. Traits with higher weights in the selection index were improved more than those with lower weights, especially when prediction accuracy was high. No trait changed in an unintended direction in either GS or PS. The accuracy of genomic prediction models built in the first cycle decreased in the later cycles because the genetic bottleneck through the selection cycles changed linkage disequilibrium patterns in the breeding population. The present study emphasizes the importance of updating models in GS and demonstrates the potential of GS in mass selection of allogamous crop species, and provided a pilot example of successful application of GS to plant breeding.

Development of Novel SSR Markers for Flax (Linum usitatissimum L.) Using Reduced-Representation Genome Sequencing.

Science.gov (United States)

Wu, Jianzhong; Zhao, Qian; Wu, Guangwen; Zhang, Shuquan; Jiang, Tingbo

2016-01-01

Flax ( Linum usitatissimum L.) is a major fiber and oil yielding crop grown in northeastern China. Identification of flax molecular markers is a key step toward improving flax yield and quality via marker-assisted breeding. Simple sequence repeat (SSR) markers, which are based on genomic structural variation, are considered the most valuable type of genetic marker for this purpose. In this study, we screened 1574 microsatellites from Linum usitatissimum L. obtained using reduced representation genome sequencing (RRGS) to systematically identify SSR markers. The resulting set of microsatellites consisted mainly of trinucleotide (56.10%) and dinucleotide (35.23%) repeats, with each motif consisting of 5-8 repeats. We then evaluated marker sensitivity and specificity based on samples of 48 flax isolates obtained from northeastern China. Using the new SSR panel, the results demonstrated that fiber flax and oilseed flax varieties clustered into two well separated groups. The novel SSR markers developed in this study show potential value for selection of varieties for use in flax breeding programs.

Molecular marker-assisted selection for resistance to pathogens in tomato

International Nuclear Information System (INIS)

Barone, A.; Frusciante, L.

2007-01-01

Since the 1980s, the use of molecular markers has been suggested to improve the efficiency of releasing resistant varieties, thus overcoming difficulties met with classical breeding. For tomato, a high-density molecular map is available in which more than 40 resistance genes are localized. Markers linked to these genes can be used to speed up gene transfer and pyramiding. Suitable PCR markers targeting resistance genes were constructed directly on the sequences of resistance genes or on restriction fragment length polymorphisms (RFLPs) tightly linked to them, and used to select resistant genotypes in backcross schemes. In some cases, the BC 5 generation was reached, and genotypes that cumulated two homozygous resistant genes were also obtained. These results supported the feasibility of using marker-assisted selection (MAS) in tomato and reinforcing the potential of this approach for other genes, which is today also driven by the development of new techniques and increasing knowledge about the tomato genome. (author)

Visualization of Genome Diversity in German Shepherd Dogs

OpenAIRE

Sally-Anne Mortlock; Rachel Booth; Hamutal Mazrier; Mehar S. Khatkar; Peter Williamson

2016-01-01

A loss of genetic diversity may lead to increased disease risks in subpopulations of dogs. The canine breed structure has contributed to relatively small effective population size in many breeds and can limit the options for selective breeding strategies to maintain diversity. With the completion of the canine genome sequencing project, and the subsequent reduction in the cost of genotyping on a genomic scale, evaluating diversity in dogs has become much more accurate and accessible. This pro...

Recent developments in cattle, pig, sheep and horse breeding - a review

Directory of Open Access Journals (Sweden)

Alena Svitáková

2014-01-01

Full Text Available The aim of this review was to summarize new genetic approaches and techniques in the breeding of cattle, pigs, sheep and horses. Often production and reproductive traits are treated separately in genetic evaluations, but advantages may accrue to their joint evaluation. A good example is the system in pig breeding. Simplified breeding objectives are generally no longer appropriate and consequently becoming increasingly complex. The goal of selection for improved animal performance is to increase the profit of the production system; therefore, economic selection indices are now used in most livestock breeding programmes. Recent developments in dairy cattle breeding have focused on the incorporation of molecular information into genetic evaluations and on increasing the importance of longevity and health in breeding objectives to maximize the change in profit. For a genetic evaluation of meat yield (beef, pig, sheep, several types of information can be used, including data from performance test stations, records from progeny tests and measurements taken at slaughter. The standard genetic evaluation method of evaluation of growth or milk production has been the multi-trait animal model, but a test-day model with random regression is becoming the new standard, in sheep as well. Reviews of molecular genetics and pedigree analyses for performance traits in horses are described. Genome – wide selection is becoming a world standard for dairy cattle, and for other farm animals it is under development.

Approximation of reliability of direct genomic breeding values

Science.gov (United States)

Two methods to efficiently approximate theoretical genomic reliabilities are presented. The first method is based on the direct inverse of the left hand side (LHS) of mixed model equations. It uses the genomic relationship matrix for a small subset of individuals with the highest genomic relationshi...

A two step Bayesian approach for genomic prediction of breeding values

DEFF Research Database (Denmark)

Mahdi Shariati, Mohammad; Sørensen, Peter; Janss, Luc

2012-01-01

. A better alternative could be to form clusters of markers with similar effects where markers in a cluster have a common variance. Therefore, the influence of each marker group of size p on the posterior distribution of the marker variances will be p df. Methods: The simulated data from the 15th QTL......Background: In genomic models that assign an individual variance to each marker, the contribution of one marker to the posterior distribution of the marker variance is only one degree of freedom (df), which introduces many variance parameters with only little information per variance parameter......-MAS workshop were analyzed such that SNP markers were ranked based on their effects and markers with similar estimated effects were grouped together. In step 1, all markers with minor allele frequency more than 0.01 were included in a SNP-BLUP prediction model. In step 2, markers were ranked based...

Omics and Environmental Science Genomic Approaches With Natural Fish Populations From Polluted Environments

Science.gov (United States)

Bozinovic, Goran; Oleksiak, Marjorie F.

2010-01-01

Transcriptomics and population genomics are two complementary genomic approaches that can be used to gain insight into pollutant effects in natural populations. Transcriptomics identify altered gene expression pathways while population genomics approaches more directly target the causative genomic polymorphisms. Neither approach is restricted to a pre-determined set of genes or loci. Instead, both approaches allow a broad overview of genomic processes. Transcriptomics and population genomic approaches have been used to explore genomic responses in populations of fish from polluted environments and have identified sets of candidate genes and loci that appear biologically important in response to pollution. Often differences in gene expression or loci between polluted and reference populations are not conserved among polluted populations suggesting a biological complexity that we do not yet fully understand. As genomic approaches become less expensive with the advent of new sequencing and genotyping technologies, they will be more widely used in complimentary studies. However, while these genomic approaches are immensely powerful for identifying candidate gene and loci, the challenge of determining biological mechanisms that link genotypes and phenotypes remains. PMID:21072843

Animal breeding strategies can improve meat quality attributes within entire populations.

Science.gov (United States)

Berry, D P; Conroy, S; Pabiou, T; Cromie, A R

2017-10-01

The contribution of animal breeding to changes in animal performance is well documented across a range of species. Once genetic variation in a trait exists, then breeding to improve the characteristics of that trait is possible, if so desired. Considerable genetic variation exists in a range of meat quality attributes across a range of species. The genetic variation that exists for meat quality is as large as observed for most performance traits; thus, within a well-structured breeding program, rapid genetic gain for meat quality could be possible. The rate of genetic gain can be augmented through the integration of DNA-based technologies into the breeding program; such DNA-based technologies should, however, be based on thousands of DNA markers dispersed across the entire genome. Genetic and genomic technologies can also have beneficial impact outside the farm gate as a tool to segregate carcasses or meat cuts based on expected meat quality features. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cytoplasmic male sterility (CMS) in hybrid breeding in field crops.

Science.gov (United States)

Bohra, Abhishek; Jha, Uday C; Adhimoolam, Premkumar; Bisht, Deepak; Singh, Narendra P

2016-05-01

A comprehensive understanding of CMS/Rf system enabled by modern omics tools and technologies considerably improves our ability to harness hybrid technology for enhancing the productivity of field crops. Harnessing hybrid vigor or heterosis is a promising approach to tackle the current challenge of sustaining enhanced yield gains of field crops. In the context, cytoplasmic male sterility (CMS) owing to its heritable nature to manifest non-functional male gametophyte remains a cost-effective system to promote efficient hybrid seed production. The phenomenon of CMS stems from a complex interplay between maternally-inherited (mitochondrion) and bi-parental (nucleus) genomic elements. In recent years, attempts aimed to comprehend the sterility-inducing factors (orfs) and corresponding fertility determinants (Rf) in plants have greatly increased our access to candidate genomic segments and the cloned genes. To this end, novel insights obtained by applying state-of-the-art omics platforms have substantially enriched our understanding of cytoplasmic-nuclear communication. Concomitantly, molecular tools including DNA markers have been implicated in crop hybrid breeding in order to greatly expedite the progress. Here, we review the status of diverse sterility-inducing cytoplasms and associated Rf factors reported across different field crops along with exploring opportunities for integrating modern omics tools with CMS-based hybrid breeding.

FACS-Assisted CRISPR-Cas9 Genome Editing Facilitates Parkinson's Disease Modeling

Directory of Open Access Journals (Sweden)

Jonathan Arias-Fuenzalida

2017-11-01

Full Text Available Genome editing and human induced pluripotent stem cells hold great promise for the development of isogenic disease models and the correction of disease-associated mutations for isogenic tissue therapy. CRISPR-Cas9 has emerged as a versatile and simple tool for engineering human cells for such purposes. However, the current protocols to derive genome-edited lines require the screening of a great number of clones to obtain one free of random integration or on-locus non-homologous end joining (NHEJ-containing alleles. Here, we describe an efficient method to derive biallelic genome-edited populations by the use of fluorescent markers. We call this technique FACS-assisted CRISPR-Cas9 editing (FACE. FACE allows the derivation of correctly edited polyclones carrying a positive selection fluorescent module and the exclusion of non-edited, random integrations and on-target allele NHEJ-containing cells. We derived a set of isogenic lines containing Parkinson's-disease-associated mutations in α-synuclein and present their comparative phenotypes.

KASPTM genotyping technology and its use in gene­tic-breeding programs (a study of maize

Directory of Open Access Journals (Sweden)

Н. Е. Волкова

2017-06-01

Full Text Available Purpose. To review publications relating to the key point of the genotyping technology that is competitive allele-specific polymerase chain reaction (which is called now Kompetitive Allele Specific PCR, KASPTM and its use in various genetic-breeding researching (a study of maize. Results. The essence of KASP-genotyping, its advantages are highlighted. The requirements for matrix DNA are presented, since the success of the KASP-analysis depends on its qua­lity and quantity. Examples of global projects of plant breeding for increasing crop yields using the KASP genoty­ping technology are given. The results of KASP genotyping and their introduction into breeding and seed production, in particular, for determining genetic identity, genetic purity, origin check, marker-assisted selection, etc. are presented using maize as an example. It is demonstrated how geno­mic selection according to KASP genotyping technology can lead to rapid genetic enhancement of drought resistance in maize. Comparison of the effectiveness of creating lines with certain traits (for example, combination of high grain yield and drought resistance using traditional breeding approaches (phenotype selection and molecular genetic methods (selection by markers was proved that it takes four seasons (two years in case of greenhouses in order to unlock the potential of the plant genotype using traditional self-pollination, test-crossing and definitions, while using markers, the population was enriched with target alleles during one season. At the same time, there was no need for a stress factor. Conclusions. KASP genotyping technology is a high-precision and effective tool for modern genetics and breeding, which is successfully used to study genetic diversity, genetic relationship, population structure, gene­tic identity, genetic purity, origin check, quantitative locus mapping, allele mapping, marker-assisted selection, marker-assisted breeding. It is expedient and timely to

Advances in genetics and molecular breeding of three legume crops ...

Indian Academy of Sciences (India)

Molecular markers are the most powerful genomic tools to increase the efficiency and precision of breeding practices for crop improvement. Progress in the development of genomic resources in the leading legume crops of the semi-arid tropics (SAT), namely, chickpea (Cicer arietinum), pigeonpea (Cajanus cajan) and ...

Prospecting sugarcane resistance to Sugarcane yellow leaf virus by genome-wide association.

Science.gov (United States)

Debibakas, S; Rocher, S; Garsmeur, O; Toubi, L; Roques, D; D'Hont, A; Hoarau, J-Y; Daugrois, J H

2014-08-01

Using GWAS approaches, we detected independent resistant markers in sugarcane towards a vectored virus disease. Based on comparative genomics, several candidate genes potentially involved in virus/aphid/plant interactions were pinpointed. Yellow leaf of sugarcane is an emerging viral disease whose causal agent is a Polerovirus, the Sugarcane yellow leaf virus (SCYLV) transmitted by aphids. To identify quantitative trait loci controlling resistance to yellow leaf which are of direct relevance for breeding, we undertook a genome-wide association study (GWAS) on a sugarcane cultivar panel (n = 189) representative of current breeding germplasm. This panel was fingerprinted with 3,949 polymorphic markers (DArT and AFLP). The panel was phenotyped for SCYLV infection in leaves and stalks in two trials for two crop cycles, under natural disease pressure prevalent in Guadeloupe. Mixed linear models including co-factors representing population structure fixed effects and pairwise kinship random effects provided an efficient control of the risk of inflated type-I error at a genome-wide level. Six independent markers were significantly detected in association with SCYLV resistance phenotype. These markers explained individually between 9 and 14 % of the disease variation of the cultivar panel. Their frequency in the panel was relatively low (8-20 %). Among them, two markers were detected repeatedly across the GWAS exercises based on the different disease resistance parameters. These two markers could be blasted on Sorghum bicolor genome and candidate genes potentially involved in plant-aphid or plant-virus interactions were localized in the vicinity of sorghum homologs of sugarcane markers. Our results illustrate the potential of GWAS approaches to prospect among sugarcane germplasm for accessions likely bearing resistance alleles of significant effect useful in breeding programs.