scholarly journals Inheritance of soybean resistance to Corynespora cassiicola

2020 ◽  
Vol 46 (2) ◽  
pp. 85-91
Author(s):  
Rafael Moreira Soares ◽  
Carlos Alberto Arrabal Arias
Keyword(s):  
Continuous Distribution ◽  
Genetic Effect ◽  
Lesion Size ◽  
Genetic Models ◽  
Additive Genetic Effect ◽  
Corynespora Cassiicola ◽  
Additive Variance ◽  
Target Spot ◽  
Soybean Resistance ◽  
Soybean Diseases

ABSTRACT The incidence of target spot, caused by Corynespora cassiicola, has gained increasing importance among the main soybean diseases in Brazil, and using susceptible cultivars can cause yield losses. Different susceptibility/resistance levels have been observed among cultivars in commercial crops but the genetics of the resistance to this pathogen is still unknown. To study the inheritance of soybean resistance to C. cassiicola, crosses were developed between cultivars including one cultivar resistant to target spot, BRS 316RR, one moderately resistant cultivar, BRS 184, and one susceptible cultivar BMX Potência RR. Parental generations, as well as F2 and F2:3 derived from their crosses, were evaluated as to severity and lesion size after inoculation with the pathogen. Quantitative analysis was applied to the data, and genetic models were adjusted for means and variances. Predominance of additive genetic effects controlling soybean resistance to C. cassiicola is suggested for the different crosses. The genetic models adjusted for the means detected an additive genetic effect more frequently. The additive variance D was detected only for the trait lesion size and had low heritability, indicating high environmental effect influencing the reaction. Based on mean and variance genetic models, further genetic gains are expected in the cross BRS 316RR x BMX Potência RR. The effect of genetic dominance was not important. The presence of significant epistasis in crosses between susceptible cultivars indicates the existence of at least two genes affecting resistance and that are interacting. The normal continuous distribution of the frequency of the number of individuals in different classes of resistance indicates that the resistance to C. cassiicola is quantitatively inherited and there is predominance of an additive genetic effect and low heritability.

Competition effects in breeding value prediction of forest trees

2020 ◽  
Author(s):  
Gunnar Jansson ◽  
Richard Kerr ◽  
Gregory Dutkowski ◽  
Johan Kroon
Keyword(s):  
Indirect Effects ◽  
Genetic Parameter ◽  
Genetic Effect ◽  
Tree Breeding ◽  
Breeding Value ◽  
Additive Genetic Effect ◽  
Analytic Structure ◽  
Additive Variance ◽  
Value Prediction ◽  
Genetic Level

Competition is a concern to tree breeding because of its potential to reduce the genetic gain. Competition, if not accounted for in the analytical model, can potentially introduce a source of bias in genetic parameter estimation and breeding value prediction. This study modelled competition between trees in 20 Swedish progeny trials of Norway spruce, Scots pine and lodgepole pine. The competition model assumed a tree has a direct additive genetic effect, which affects the tree’s own phenotype, and an indirect additive effect, which affects the phenotypes of its neighbours. Genetic parameters were estimated via a factor analytic structure (FA) where separate indirect effects were considered for each neighbour, or via a combined indirect effect approach (CIE). We analysed diameter, as it is the trait that can be expected to be affected most by competition. Competition at the genetic level was detected in 17 of the 20 trials analysed. In most cases the ratio of indirect to direct additive variance was less than five percent and no major changes in ranking resulted. At this stage there is little incentive to incorporate indirect effects into program-wide genetic evaluation models. The added complexity is not commensurate with the benefit that would be gained.

scholarly journals First Report of Target Spot of Vaccinium corymbosum Caused by Corynespora cassiicola

Plant Disease ◽  
2007 ◽  
Vol 91 (6) ◽  
pp. 771-771 ◽  
Author(s):  
S. Hongn ◽  
A. Ramallo ◽  
O. Baino ◽  
J. C. Ramallo
Keyword(s):  
Vaccinium Corymbosum ◽  
Conidial Suspension ◽  
Corynespora Cassiicola ◽  
Cultural Patterns ◽  
Abaxial Surface ◽  
American Phytopathological Society ◽  
Target Spot ◽  
Necrotic Spots ◽  
Stem Lesions ◽  
Soybean Diseases

During March of 2006, in Famailla, Province of Tucuman, Argentina, a new foliar disease was observed on Vaccinium corymbosum L. cv. O'Neal causing severe premature leaf drop. Symptoms consisted of circular to irregular reddish brown necrotic spots varying from specks to mature lesions of 10 to 15 mm in diameter. Larger spots frequently exhibited a zonate pattern with lighter centers and darker margins that are surrounded by a black, oily halo that is consistent with target spot (3). Lesions often coalesced to form irregularly shaped necrotic areas that reached the petioles. Leaf abscission occurred soon after >50% of the foliar area was affected. No stem lesions were observed. Conidiophores were erect, brown, single or in clusters, one to seven septa, 6 to 9 × 70 to 684 μm (shorter in culture), and arose on the abaxial surface of diseased leaves; conidia were borne singly or in chains of 2 to 5, varying from cylindrical to broadest at the base and tapering toward the apex, straight to slightly curved, 3 to 20 pseudosepta, 75 to 330 × 5 to 9 μm (mean of 153 × 7 μm, shorter in culture), with conspicuous hilum. On potato dextrose agar (PDA), the rate of growth was moderate (colonies reach 25 mm in diameter after 7 days grown at 27°C) with conidia production 5 days after the culture was started. Microscopic characters and cultural patterns conformed to the description of Corynespora cassiicola (Berk & M. A. Curtis) C.T. Wei (2,4) and were identical to isolates of C. cassicola from lesions of soybean target spot. A conidial suspension (104 conidia/ml) of C. cassicola was prepared from a 2-week-old culture grown on PDA and sprayed on surface-disinfected excised blueberry stems, each with 10 healthy leaves per stem. The stems were placed in hydroponia and incubated at 27 ± 2°C with permanent light. All sprayed leaves showed symptoms within 3 days following inoculation. Within 5 days, leaves were conspicuously infected, soon followed by defoliation. C. cassicola was reisolated from the inoculated-leaves lesions and was identical morphologically to the original isolate sprayed on test leaves. Another Corynespora species, C. arctespora (Cooke & Ellis) Carris (1), was described on Vaccinium spp. stems with a distinctive feature of a phialidic synanamorph formation. This synanamorph character was not found in our isolate. C. cassiicola has a broad hosts range, but to our knowledge, has not been recorded before on V. corymbosum as the causal agent of target spot. References: (1) L. M. Carris. Mycotaxon 30:127, 1987. (2) L. S. Olive et al. Phytopathology 35:822, 1945. (3) J. B. Sinclair. Target spot. Page 27 in: Compendium of Soybean Diseases. G. L Hartman et al., eds. The American Phytopathological Society. St. Paul, MN, 1999. (4) J. A. Spencer and H. J. Walters. Phytopathology 59:58, 1969.

Personal Goals of Older Female Twins

2009 ◽  
Vol 14 (2) ◽  
pp. 160-167 ◽  
Author(s):  
Katariina Salmela-Aro ◽  
Sanna Read ◽  
Jari-Erik Nurmi ◽  
Markku Koskenvuo ◽  
Jaakko Kaprio ◽  
...  
Keyword(s):  
Physical Exercise ◽  
Independent Living ◽  
Environmental Effect ◽  
Close Relationships ◽  
Environmental Influence ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Personal Goals ◽  
Cultural Activities ◽  
The Individual

This study examined genetic and environmental influences on older women’s personal goals by using data from the Finnish Twin Study on Aging. The interview for the personal goals was completed by 67 monozygotic (MZ) pairs and 75 dizygotic (DZ) pairs. The tetrachoric correlations for personal goals related to health and functioning, close relationships, and independent living were higher in MZ than DZ twins, indicating possible genetic influence. The pattern of tetrachoric correlations for personal goals related to cultural activities, care of others, and physical exercise indicated environmental influence. For goals concerning health and functioning, independent living, and close relationships, additive genetic effect accounted for about half of the individual variation. The rest was the result of a unique environmental effect. Goals concerning physical exercise and care of others showed moderate common environmental effect, while the rest of the variance was the result of a unique environmental effect. Personal goals concerning cultural activities showed unique environmental effects only.

scholarly journals Genomic prediction with non-additive effects in beef cattle: stability of variance component and genetic effect estimates against population size

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Akio Onogi ◽  
Toshio Watanabe ◽  
Atsushi Ogino ◽  
Kazuhito Kurogi ◽  
Kenji Togashi
Keyword(s):  
Population Size ◽  
Genomic Prediction ◽  
Variance Components ◽  
Variance Component ◽  
Predictive Accuracy ◽  
Genetic Effect ◽  
Genetic Effects ◽  
Additive Effects ◽  
Additive Variance ◽  
Additive Genetic Effects

Abstract Background Genomic prediction is now an essential technology for genetic improvement in animal and plant breeding. Whereas emphasis has been placed on predicting the breeding values, the prediction of non-additive genetic effects has also been of interest. In this study, we assessed the potential of genomic prediction using non-additive effects for phenotypic prediction in Japanese Black, a beef cattle breed. In addition, we examined the stability of variance component and genetic effect estimates against population size by subsampling with different sample sizes. Results Records of six carcass traits, namely, carcass weight, rib eye area, rib thickness, subcutaneous fat thickness, yield rate and beef marbling score, for 9850 animals were used for analyses. As the non-additive genetic effects, dominance, additive-by-additive, additive-by-dominance and dominance-by-dominance effects were considered. The covariance structures of these genetic effects were defined using genome-wide SNPs. Using single-trait animal models with different combinations of genetic effects, it was found that 12.6–19.5 % of phenotypic variance were occupied by the additive-by-additive variance, whereas little dominance variance was observed. In cross-validation, adding the additive-by-additive effects had little influence on predictive accuracy and bias. Subsampling analyses showed that estimation of the additive-by-additive effects was highly variable when phenotypes were not available. On the other hand, the estimates of the additive-by-additive variance components were less affected by reduction of the population size. Conclusions The six carcass traits of Japanese Black cattle showed moderate or relatively high levels of additive-by-additive variance components, although incorporating the additive-by-additive effects did not improve the predictive accuracy. Subsampling analysis suggested that estimation of the additive-by-additive effects was highly reliant on the phenotypic values of the animals to be estimated, as supported by low off-diagonal values of the relationship matrix. On the other hand, estimates of the additive-by-additive variance components were relatively stable against reduction of the population size compared with the estimates of the corresponding genetic effects.

scholarly journals A review of deep learning applications for genomic selection

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Osval Antonio Montesinos-López ◽  
Abelardo Montesinos-López ◽  
Paulino Pérez-Rodríguez ◽  
José Alberto Barrón-López ◽  
Johannes W. R. Martini ◽  
...  
Keyword(s):  
Deep Learning ◽  
Plant Breeding ◽  
Genomic Selection ◽  
Genomic Prediction ◽  
Mixed Model ◽  
Prediction Models ◽  
Genetic Effect ◽  
Training Data ◽  
Additive Genetic Effect ◽  
Main Body

Abstract Background Several conventional genomic Bayesian (or no Bayesian) prediction methods have been proposed including the standard additive genetic effect model for which the variance components are estimated with mixed model equations. In recent years, deep learning (DL) methods have been considered in the context of genomic prediction. The DL methods are nonparametric models providing flexibility to adapt to complicated associations between data and output with the ability to adapt to very complex patterns. Main body We review the applications of deep learning (DL) methods in genomic selection (GS) to obtain a meta-picture of GS performance and highlight how these tools can help solve challenging plant breeding problems. We also provide general guidance for the effective use of DL methods including the fundamentals of DL and the requirements for its appropriate use. We discuss the pros and cons of this technique compared to traditional genomic prediction approaches as well as the current trends in DL applications. Conclusions The main requirement for using DL is the quality and sufficiently large training data. Although, based on current literature GS in plant and animal breeding we did not find clear superiority of DL in terms of prediction power compared to conventional genome based prediction models. Nevertheless, there are clear evidences that DL algorithms capture nonlinear patterns more efficiently than conventional genome based. Deep learning algorithms are able to integrate data from different sources as is usually needed in GS assisted breeding and it shows the ability for improving prediction accuracy for large plant breeding data. It is important to apply DL to large training-testing data sets.

A Review of Corynespora cassiicola and Its Increasing Relevance to Tomato in Florida

2018 ◽  
Vol 19 (4) ◽  
pp. 303-309 ◽  
Author(s):  
Keevan J. MacKenzie ◽  
Leilani G. Sumabat ◽  
Katia V. Xavier ◽  
Gary E. Vallad
Keyword(s):  
Fungal Pathogen ◽  
Effective Control ◽  
Corynespora Cassiicola ◽  
Varietal Resistance ◽  
Vegetable Crop ◽  
Fresh Market ◽  
Resistance Development ◽  
Pathogen Diversity ◽  
Target Spot ◽  
Insight Into

Corynespora cassiicola is a highly diverse fungal pathogen that can infect more than 500 species of plants, including many economically important crops such as cotton, soybean, tomato, and cucumber. In Florida, the number one vegetable crop by market value are fresh-market tomatoes, which generate nearly half a billion dollars annually. Florida’s subtropical to tropical climate is conducive to infection and development of the target spot pathogen on tomato caused by C. cassiicola. There is no varietal resistance available for target spot of tomato, and preventative fungicide treatments are the primary method for control. In the last decade, C. cassiicola has been more frequently reported by Florida tomato growers, appearing not only more aggressive but also increasingly insensitive to various fungicides. This review brings together the most recent C. cassiicola literature, providing a history and understanding of the immense pathogen diversity and its relevance to tomato. It also provides insight into fungicide resistance development and pathogen survivability, which are important factors in providing effective control recommendations and in understanding the epidemiology of this disease, respectively.

scholarly journals Genomic Breeding Values for Claw Diseases/Disorders in Czech Holstein Cows

2019 ◽  
Vol 67 (5) ◽  
pp. 1245-1251
Author(s):  
Ludmila Zavadilová ◽  
Eva Kašná ◽  
Zuzana Krupová
Keyword(s):  
Infectious Diseases ◽  
Fixed Effects ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Holstein Cows ◽  
Additive Genetic Effect ◽  
Genomic Information ◽  
White Line ◽  
Genomic Breeding ◽  
Breeding Values

Genomic breeding values (GEBV) were predicted for claw diseases/disorders in Holstein cows. The data sets included 6,498, 6,641 and 16,208 cows for the three groups of analysed disorders. The analysed traits were infectious diseases (ID), including digital and interdigital dermatitis and interdigital phlegmon, and non-infectious diseases (NID), including ulcers, white line disease, horn fissures, and double sole and overall claw disease (OCD), comprising all recorded disorders. Claw diseases/disorders were defined as 0/1 occurrence per lactation. Linear animal models were employed for prediction of conventional breeding values (BV) and genomic breeding values (GEBV), including the random additive genetic effect of animal and the permanent environmental effect of cow and fixed effects of parity, herd, year and month of calving. Both high and intermediate weights (80% and 50%, respectively) of genomic information were employed for GEBV50 and GEBV80 prediction. The estimated heritability for ID was 3.47%, whereas that for NID 4.61% and for OCD was 2.29%. Approximate genetic correlations among claw diseases/disorders traits ranged from 19% (ID x NID) to 81% (NID x OCD). The correlations between predicted BV and GEBV50 (84–99%) were higher than those between BV and GEBV80 (70–98%). Reliability of breeding values was low for each claw disease/disorder (on average, 3.7 to 14.8%) and increased with the weight of genomic information employed.

scholarly journals Genetic-Quantitative Uni- and Bi-Trait Analysis for Growth Traits in the Colombian Creole Breed Blanco Orejinegro (BON)

2021 ◽  
Author(s):  
Marisol Londoño-Gil ◽  
Juan Carlos Rincón Flórez ◽  
Albeiro López-Herrera ◽  
Luis Gabriel Gonzalez-Herrera
Keyword(s):  
Growth Traits ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Cattle Breed ◽  
Live Weight ◽  
Daily Weight Gain ◽  
Additive Genetic Effect ◽  
Selection Processes ◽  
Heritability Estimates ◽  
Maternal Heritability

Abstract The Blanco Orejinegro (BON) is a Colombian creole cattle breed that is not genetically well characterized for growth traits. The aim of this work was to estimate genetic parameters for birth weight (BW), weaning weight (WW), yearling weight (YW), daily weight gain between birth and weaning (DWG), time to reach 120 kg of live weight (T120), and time to reach 60% of adult weight (T60%), and establish the selection criteria for growth traits in the BON population of Colombia. Genealogical and phenotypic information for BW, WW, YW, DWG, T120, and T60% traits of BON animals from 14 Colombian herds were used. These traits were analyzed with the AIREML method in a uni- and bi-trait animal model including the maternal effect for BW, WW, DWG, and T120. The direct heritability estimates values were 0.22 ± 0.059 (BW), 0.20 ± 0.057 (WW), 0.20 ± 0.153 (YW), 0.17 ± 0.07 (DWG), 0.26 (T120), and 0.44 ± 0.03 (T60%). The maternal heritability estimates values were 0.14 ± 0.040 (BW), 0.15 ± 0.039 (WW), 0.25 ± 0.06 (DWG), and 0.16 (T120). The direct genetic correlations were high (>|0.60|) among all the traits, except between T60% with BW, WW, YW, and DWG (ranged from -0.02 to -0.51), all in a favorable direction. The results showed that there is genetic variation in the growth traits associated with the additive genetic effect and they might respond to selection processes. Furthermore, genetic gains would improve through selection, especially for YW and T60% when WW is used as criterion.

Efecto de dos estrategias de agrupación de padres fantasmas en la evaluación genética de rasgos de crecimiento en el ganado Braunvieh mexicano

2021 ◽  
Vol 12 (3) ◽  
pp. 878-892
Author(s):  
Luis Antonio Saavedra-Jiménez ◽  
Rodolfo Ramírez-Valverde ◽  
Rafael Núñez-Domínguez ◽  
Agustín Ruíz-Flores ◽  
José Guadalupe García-Muñiz ◽  
...  
Keyword(s):  
Fixed Effects ◽  
Growth Traits ◽  
Genetic Effect ◽  
Additive Genetic Effect ◽  
Genetic Trend ◽  
Phenotypic Data ◽  
Genetic Groups ◽  
Grouping Strategies ◽  
Parent Groups ◽  
Different Sources

The study aimed to compare two grouping strategies for unknown parents or phantom parent groups (PPG) on the genetic evaluation of growth traits for Mexican Braunvieh cattle. Phenotypic data included birth (BW), weaning (WW) and yearling (YW) weights. Pedigree included 57,341 animals. The first strategy involved 12 PPG (G12) based on the birth year of the unknown parent’s progeny and the sex of the unknown parent, while the second involved 24 PPG (G24) based on the birth year of the unknown parent’s progeny and 4-selection pathways. The animal models included fixed effects and the random direct additive genetic effect; WW also included random maternal genetic and maternal permanent environmental effects. Product-moment correlations between EBV from G0 (no PPG) and G12 were 0.96, 0.77 and 0.69 for BW, WW and YW, respectively, and between EBV from G0 and G24 were 0.91, 0.54, and 0.53, respectively. Corresponding rank correlations between G0 and G12 were 0.94, 0.77, and 0.72, and between G0 and G24 were 0.89, 0.61, and 0.60. Genetic trends showed a base deviation from the genetic trend of G0, except for BW of G12. The results did not support the use of the two grouping strategies on the studied population and traits, and further research is required. Introducing PPG to the model, enough phenotype contribution from descendants to PPG, and avoiding collinearity between PPG and fixed effects are important. Genetic groups should reflect changes in the genetic structure of the population to the unknown parents, including different sources of genetic materials, and changes made by selection over time.

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