scholarly journals SNP Genotyping with Target Amplicon Sequencing Using a Multiplexed Primer Panel and Its Application to Genomic Prediction in Japanese Cedar, Cryptomeria japonica (L.f.) D.Don

Forests ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 898 ◽  
Author(s):  
Soichiro Nagano ◽  
Tomonori Hirao ◽  
Yuya Takashima ◽  
Michinari Matsushita ◽  
Kentaro Mishima ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Cryptomeria Japonica ◽  
Prediction Models ◽  
Wood Property ◽  
Japanese Cedar ◽  
Amplicon Sequencing ◽  
Forest Tree ◽  
Nucleotide Polymorphisms ◽  
Forest Tree Breeding ◽  
Custom Primer

Along with progress in sequencing technology and accumulating knowledge of genome and gene sequences, molecular breeding techniques have been developed for predicting the genetic potential of individual genotypes and for selecting superior individuals. For Japanese cedar (Cryptomeria japonica (L.f.) D.Don), which is the most common coniferous species in Japanese forestry, we constructed a custom primer panel for target amplicon sequencing in order to simultaneously determine 3034 informative single nucleotide polymorphisms (SNPs). We performed primary evaluation of the custom primer panel with actual sequencing and in silico PCR. Genotyped SNPs had a distribution over almost the entire region of the C. japonica linkage map and verified the high reproducibility of genotype calls compared to SNPs obtained by genotyping arrays. Genotyping was performed for 576 individuals of the F1 population, and genomic prediction models were constructed for growth and wood property-related traits using the genotypes. Amplicon sequencing with the custom primer panel enables efficient obtaining genotype data in order to perform genomic prediction, manage clones, and advance forest tree breeding.

scholarly journals Inferring the demographic history of Japanese cedar, Cryptomeria japonica, using amplicon sequencing

Heredity ◽  
2019 ◽  
Vol 123 (3) ◽  
pp. 371-383 ◽  
Author(s):  
Natsuki Moriguchi ◽  
Kentaro Uchiyama ◽  
Ryutaro Miyagi ◽  
Etsuko Moritsuka ◽  
Aya Takahashi ◽  
...  
Keyword(s):  
Cryptomeria Japonica ◽  
Demographic History ◽  
Japanese Cedar ◽  
Amplicon Sequencing ◽  
History Of

Effect of genomic prediction on response to selection in forest tree breeding

2018 ◽  
Vol 14 (5) ◽  
Author(s):  
J. Stejskal ◽  
M. Lstibůrek ◽  
J. Klápště ◽  
J. Čepl ◽  
Y. A. El-Kassaby
Keyword(s):  
Genomic Prediction ◽  
Tree Breeding ◽  
Forest Tree ◽  
Response To Selection ◽  
Forest Tree Breeding

scholarly journals Achievements and Challenges of Genomics-Assisted Breeding in Forest Trees: From Marker-Assisted Selection to Genome Editing

2021 ◽  
Vol 22 (19) ◽  
pp. 10583
Author(s):  
Sunny Ahmar ◽  
Paulina Ballesta ◽  
Mohsin Ali ◽  
Freddy Mora-Poblete
Keyword(s):  
Genome Editing ◽  
Prediction Models ◽  
Association Studies ◽  
Tree Breeding ◽  
Forest Tree ◽  
Transformation Method ◽  
Breeding Cycle ◽  
Genome Wide Association Studies ◽  
Forest Trees ◽  
Forest Tree Breeding

Forest tree breeding efforts have focused mainly on improving traits of economic importance, selecting trees suited to new environments or generating trees that are more resilient to biotic and abiotic stressors. This review describes various methods of forest tree selection assisted by genomics and the main technological challenges and achievements in research at the genomic level. Due to the long rotation time of a forest plantation and the resulting long generation times necessary to complete a breeding cycle, the use of advanced techniques with traditional breeding have been necessary, allowing the use of more precise methods for determining the genetic architecture of traits of interest, such as genome-wide association studies (GWASs) and genomic selection (GS). In this sense, main factors that determine the accuracy of genomic prediction models are also addressed. In turn, the introduction of genome editing opens the door to new possibilities in forest trees and especially clustered regularly interspaced short palindromic repeats and CRISPR-associated protein 9 (CRISPR/Cas9). It is a highly efficient and effective genome editing technique that has been used to effectively implement targetable changes at specific places in the genome of a forest tree. In this sense, forest trees still lack a transformation method and an inefficient number of genotypes for CRISPR/Cas9. This challenge could be addressed with the use of the newly developing technique GRF-GIF with speed breeding.

scholarly journals Genomic Selection for Forest Tree Improvement: Methods, Achievements and Perspectives

Forests ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1190
Author(s):  
Vadim G. Lebedev ◽  
Tatyana N. Lebedeva ◽  
Aleksey I. Chernodubov ◽  
Konstantin A. Shestibratov
Keyword(s):  
Molecular Markers ◽  
Genomic Selection ◽  
Complex Traits ◽  
Prediction Models ◽  
Forest Tree ◽  
Tree Improvement ◽  
Breeding Value ◽  
Breeding Cycle ◽  
Forest Trees ◽  
Forest Tree Breeding

The breeding of forest trees is only a few decades old, and is a much more complicated, longer, and expensive endeavor than the breeding of agricultural crops. One breeding cycle for forest trees can take 20–30 years. Recent advances in genomics and molecular biology have revolutionized traditional plant breeding based on visual phenotype assessment: the development of different types of molecular markers has made genotype selection possible. Marker-assisted breeding can significantly accelerate the breeding process, but this method has not been shown to be effective for selection of complex traits on forest trees. This new method of genomic selection is based on the analysis of all effects of quantitative trait loci (QTLs) using a large number of molecular markers distributed throughout the genome, which makes it possible to assess the genomic estimated breeding value (GEBV) of an individual. This approach is expected to be much more efficient for forest tree improvement than traditional breeding. Here, we review the current state of the art in the application of genomic selection in forest tree breeding and discuss different methods of genotyping and phenotyping. We also compare the accuracies of genomic prediction models and highlight the importance of a prior cost-benefit analysis before implementing genomic selection. Perspectives for the further development of this approach in forest breeding are also discussed: expanding the range of species and the list of valuable traits, the application of high-throughput phenotyping methods, and the possibility of using epigenetic variance to improve of forest trees.

scholarly journals GPS Coordinates for Modelling Correlated Herd Effects in Genomic Prediction Models Applied to Hanwoo Beef Cattle

Animals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 2050
Author(s):  
Beatriz Castro Dias Cuyabano ◽  
Gabriel Rovere ◽  
Dajeong Lim ◽  
Tae Hun Kim ◽  
Hak Kyo Lee ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Genomic Prediction ◽  
Prediction Models ◽  
Phenotypic Expression ◽  
Genetic Evaluation ◽  
Genomic Breeding ◽  
Breeding Values ◽  
Korean Cattle ◽  
Evaluation Programs ◽  
The Impact

It is widely known that the environment influences phenotypic expression and that its effects must be accounted for in genetic evaluation programs. The most used method to account for environmental effects is to add herd and contemporary group to the model. Although generally informative, the herd effect treats different farms as independent units. However, if two farms are located physically close to each other, they potentially share correlated environmental factors. We introduce a method to model herd effects that uses the physical distances between farms based on the Global Positioning System (GPS) coordinates as a proxy for the correlation matrix of these effects that aims to account for similarities and differences between farms due to environmental factors. A population of Hanwoo Korean cattle was used to evaluate the impact of modelling herd effects as correlated, in comparison to assuming the farms as completely independent units, on the variance components and genomic prediction. The main result was an increase in the reliabilities of the predicted genomic breeding values compared to reliabilities obtained with traditional models (across four traits evaluated, reliabilities of prediction presented increases that ranged from 0.05 ± 0.01 to 0.33 ± 0.03), suggesting that these models may overestimate heritabilities. Although little to no significant gain was obtained in phenotypic prediction, the increased reliability of the predicted genomic breeding values is of practical relevance for genetic evaluation programs.

scholarly journals Genomic prediction models trained with historical records enable populating the German ex situ genebank bio-digital resource center of barley (Hordeum sp.) with information on resistances to soilborne barley mosaic viruses

2021 ◽  
Author(s):  
Maria Y. Gonzalez ◽  
Yusheng Zhao ◽  
Yong Jiang ◽  
Nils Stein ◽  
Antje Habekuss ◽  
...  
Keyword(s):  
Genetic Resources ◽  
Mosaic Virus ◽  
Genomic Prediction ◽  
Prediction Models ◽  
Ex Situ ◽  
Yellow Mosaic Virus ◽  
Plant Responses ◽  
Resource Center ◽  
Digital Resource ◽  
Best Linear Unbiased

AbstractKey messageGenomic prediction with special weight of major genes is a valuable tool to populate bio-digital resource centers.AbstractPhenotypic information of crop genetic resources is a prerequisite for an informed selection that aims to broaden the genetic base of the elite breeding pools. We investigated the potential of genomic prediction based on historical screening data of plant responses against theBarley yellow mosaic virusesfor populating the bio-digital resource center of barley. Our study includes dense marker data for 3838 accessions of winter barley, and historical screening data of 1751 accessions forBarley yellow mosaic virus(BaYMV) and of 1771 accessions forBarley mild mosaic virus(BaMMV). Linear mixed models were fitted by considering combinations for the effects of genotypes, years, and locations. The best linear unbiased estimations displayed a broad spectrum of plant responses against BaYMV and BaMMV. Prediction abilities, computed as correlations between predictions and observed phenotypes of accessions, were low for the marker-assisted selection approach amounting to 0.42. In contrast, prediction abilities of genomic best linear unbiased predictions were high, with values of 0.62 for BaYMV and 0.64 for BaMMV. Prediction abilities of genomic prediction were improved by up to ~ 5% using W-BLUP, in which more weight is given to markers with significant major effects found by association mapping. Our results outline the utility of historical screening data and W-BLUP model to predict the performance of the non-phenotyped individuals in genebank collections. The presented strategy can be considered as part of the different approaches used in genebank genomics to valorize genetic resources for their usage in disease resistance breeding and research.

scholarly journals CRISPR/Cas9-mediated targeted mutagenesis in Japanese cedar (Cryptomeria japonica D. Don)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yoshihiko Nanasato ◽  
Masafumi Mikami ◽  
Norihiro Futamura ◽  
Masaki Endo ◽  
Mitsuru Nishiguchi ◽  
...  
Keyword(s):  
Genome Editing ◽  
Cryptomeria Japonica ◽  
Fluorescent Protein ◽  
Japanese Cedar ◽  
Targeted Mutagenesis ◽  
Embryogenic Tissue ◽  
Breeding Period ◽  
Single Mutation ◽  
Knock Out ◽  
Guide Rna

AbstractCryptomeria japonica (Japanese cedar or sugi) is one of the most important coniferous tree species in Japan and breeding programs for this species have been launched since 1950s. Genome editing technology can be used to shorten the breeding period. In this study, we performed targeted mutagenesis using the CRISPR/Cas9 system in C. japonica. First, the CRISPR/Cas9 system was tested using green fluorescent protein (GFP)-expressing transgenic embryogenic tissue lines. Knock-out efficiency of GFP ranged from 3.1 to 41.4% depending on U6 promoters and target sequences. The GFP knock-out region was mottled in many lines, indicating genome editing in individual cells. However, in 101 of 102 mutated individuals (> 99%) from 6 GFP knock-out lines, embryos had a single mutation pattern. Next, we knocked out the endogenous C. japonica magnesium chelatase subunit I (CjChlI) gene using two guide RNA targets. Green, pale green, and albino phenotypes were obtained in the gene-edited cell lines. Sequence analysis revealed random deletions, insertions, and replacements in the target region. Thus, targeted mutagenesis using the CRISPR/Cas9 system can be used to modify the C. japonica genome.

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