scholarly journals Hybrid Breeding for MLN Resistance: Heterosis, Combining Ability, and Hybrid Prediction

Plants ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 468
Author(s):  
Christine Nyaga ◽  
Manje Gowda ◽  
Yoseph Beyene ◽  
Wilson T. Murithi ◽  
Juan Burgueno ◽  
...  
Keyword(s):  
Disease Severity ◽  
Combining Ability ◽  
Genetic Parameters ◽  
Artificial Inoculation ◽  
Hybrid Breeding ◽  
Hybrid Performance ◽  
Hybrid Prediction ◽  
Quantitative Genetic ◽  
Per Se ◽  
Quantitative Genetic Parameters

Prior knowledge on heterosis and quantitative genetic parameters on maize lethal necrosis (MLN) can help the breeders to develop numerous resistant or tolerant hybrids with optimum resources. Our objectives were to (1) estimate the quantitative genetic parameters for MLN disease severity, (2) investigate the efficiency of the prediction of hybrid performance based on parental per se and general combining ability (GCA) effects, and (3) examine the potential of hybrid prediction for MLN resistance or tolerance based on markers. Fifty elite maize inbred lines were selected based on their response to MLN under artificial inoculation. Crosses were made in a half diallel mating design to produce 307 F1 hybrids. All hybrids were evaluated in MLN quarantine facility in Naivasha, Kenya for two seasons under artificial inoculation. All 50 inbreds were genotyped with genotyping-by-sequencing (GBS) SNPs. The phenotypic variation was significant for all traits and the heritability was moderate to high. We observed that hybrids were superior to the mean performance of the parents for disease severity (−14.57%) and area under disease progress curve (AUDPC) (14.9%). Correlations were significant and moderate between line per se and GCA; and mean of parental value with hybrid performance for both disease severity and AUDPC value. Very low and negative correlation was observed between parental lines marker based genetic distance and heterosis. Nevertheless, the correlation of GCA effects was very high with hybrid performance which can suggests as a good predictor of MLN resistance. Genomic prediction of hybrid performance for MLN is high for both traits. We therefore conclude that there is potential for prediction of hybrid performance for MLN. Overall, the estimated quantitative genetic parameters suggest that through targeted approach, it is possible to develop outstanding lines and hybrids for MLN resistance.

scholarly journals Use of F2 bulks in training sets for genomic prediction of combining ability and hybrid performance

2018 ◽  
Author(s):  
Frank Technow
Keyword(s):  
Genomic Prediction ◽  
Combining Ability ◽  
Hybrid Breeding ◽  
F1 Hybrids ◽  
Hybrid Performance ◽  
Crop Species ◽  
Heterotic Groups ◽  
Quantitative Genetic ◽  
Hand Pollination ◽  
Training Sets

ABSTRACTDeveloping training sets for genomic prediction in hybrid crops requires producing hybrid seed for a large number of entries. In autogamous crop species (e.g., wheat, rice, rapeseed, cotton) this requires elaborate hybridization systems to prevent self-pollination and presents a significant impediment to the implementation of hybrid breeding in general and genomic selection in particular. An alternative to F1 hybrids are bulks of F2 seed from selfed F1 plants (F1:2). Seed production for F1:2 bulks requires no hybridization system because the number of F1 plants needed for producing enough F1:2 seed for multi-environment testing can be generated by hand-pollination. This study evaluated the suitability of F1:2 bulks for use in training sets for genomic prediction of F1 level general combining ability and hybrid performance, under different degrees of divergence between heterotic groups and modes of gene action, using quantitative genetic theory and simulation of a genomic prediction experiment. The simulation, backed by theory, showed that F1:2 training sets are expected to have a lower prediction accuracy relative to F1 training sets, particularly when heterotic groups have strongly diverged. The accuracy penalty, however, was only modest and mostly because of a lower heritability, rather than because of a difference in F1 and F1:2 genetic values. It is concluded that resorting to F1:2 bulks is, in theory at least, a promising approach to remove the significant complication of a hybridization system from the breeding process.

scholarly journals Sorghum Hybrids for Low-Input Farming Systems in West Africa: Quantitative Genetic Parameters to Guide Hybrid Breeding

Crop Science ◽  
2019 ◽  
Vol 59 (6) ◽  
pp. 2544-2561 ◽  
Author(s):  
Moctar Kante ◽  
Fred Rattunde ◽  
Baloua Nébié ◽  
Ibrahima Sissoko ◽  
Bocar Diallo ◽  
...  
Keyword(s):  
West Africa ◽  
Genetic Parameters ◽  
Farming Systems ◽  
Hybrid Breeding ◽  
Low Input ◽  
Quantitative Genetic ◽  
Quantitative Genetic Parameters

scholarly journals Combining ability for yield and yield attributes in rice (Oryza sativa l.) genotypes using CMS system

2014 ◽  
Vol 11 (1) ◽  
pp. 23-33 ◽  
Author(s):  
CL Sharma ◽  
NK Singh ◽  
AK Mall ◽  
K Kumar ◽  
ON Singh
Keyword(s):  
Combining Ability ◽  
Genetic Variance ◽  
Gene Action ◽  
Oryza Sativa L ◽  
Additive Genetic Variance ◽  
Hybrid Breeding ◽  
Male Sterile ◽  
Yield Attributes ◽  
Genetic Components ◽  
Per Se

Seventy five hybrids generated from crossing three cytoplasmic male sterile lines with 25 testers were studied along with parents for combining ability and gene action involved in expression of characters in rice. The GCA and SCA effects were significant for all the characters except seedling height, indicating the importance of both additive and non additive genetic components. The ratio of gca and sca variance was less than unity for all the characters also indicated preponderance of non additive genetic variance and suggested good prospects of the exploitation of variation through hybrid breeding. Amongst the parental lines, UPR-2080-24-1-R, IR-60076-1-R, PNR-165-10-6-R and IR-58025- A were found to be good general combiners which can be taken up to generate desirable segregates for further selection. None of the crosses showed significant sca effects for all the characters. On the basis of per se performance and high sca effects, IR-58025-A x CSRC-50-2-1-4-BR, PMS-10-A x IR-42688-2-118-6-3, RPMS-100-A x UPRI-92-79-R and NMS-4-A x IR-32419-28-3-1-3-R were good specific combiners for grain yield plant-1 and their components which could be used for exploitation of heterosis for yield. DOI: http://dx.doi.org/10.3329/sja.v11i1.18372 SAARC J. Agri., 11(1): 23-33 (2013)

scholarly journals EVOLUTIONARY POTENTIAL OF A LARGE MARINE VERTEBRATE: QUANTITATIVE GENETIC PARAMETERS IN A WILD POPULATION

Evolution ◽  
2009 ◽  
Vol 63 (4) ◽  
pp. 1051-1067 ◽  
Author(s):  
Joseph D. DiBattista ◽  
Kevin A. Feldheim ◽  
Dany Garant ◽  
Samuel H. Gruber ◽  
Andrew P. Hendry
Keyword(s):  
Genetic Parameters ◽  
Wild Population ◽  
Evolutionary Potential ◽  
Quantitative Genetic ◽  
Quantitative Genetic Parameters

scholarly journals Heterosis and Combining Abilities in a Diverse Seven-Parent Pearl Millet Population Diallel Tested in West Africa

2021 ◽  
Author(s):  
Sonali Dutta ◽  
Felix T. Sattler ◽  
Anna Pucher ◽  
Drabo Inoussa ◽  
Ahmad Issaka ◽  
...  
Keyword(s):  
West Africa ◽  
Pearl Millet ◽  
Combining Ability ◽  
Pennisetum Glaucum ◽  
Smallholder Farmers ◽  
Hybrid Breeding ◽  
High Yield ◽  
Variance Ratios ◽  
High Heritability ◽  
Quantitative Genetic Parameters

Abstract Pearl millet [Pennisetum glaucum (L.) R. Br.] is an important food-security crop to smallholder farmers in West Africa (WA). Breeding for high yield and stability is a major challenge in the harsh environments of WA but could be tackled by hybrid breeding. Knowledge of combining ability patterns and quantitative-genetic parameters is required for an efficient development of hybrid varieties. Hence, our objectives were to estimate the combining ability of seven genetically diverse Sahelian pearl millet populations from Senegal, Mali, Benin, Burkina Faso, Niger, Sudan and Nigeria and the heterosis and stability of their 42 diallel-derived population hybrids to inform pearl millet hybrid breeding. The genotypes were evaluated in six environments in WA in 2007. Grain yield (GY) exhibited an average panmictic mid-parent heterosis (PMPH) of 24%, ranging from -1.51% to 64.69%. General combining ability (GCA) was significant across test environments as reflected by high heritability estimates and high GCA:SCA variance ratios. Thus, early selection for parental per se performance would be rewarding. The parental population from Sudan (IP8679) had strongly negative GCA for GY. Its lack of adaptation contributed to the predominance of additive effects in the present germplasm set. Parental populations PE02987 (Senegal), PE05344 (Mali) and ICMV IS 92222 (Niger) showed large positive GCA for GY. Their offspring, especially PE02987 × PE05344 and Kapelga × ICMV IS 92222, exhibited a high and stable GY across all test environments. Tapping the regional pearl millet genetic diversity seems therefore beneficial for hybrid breeding to increase pearl millet productivity in WA.

Estimation of Quantitative Genetic Parameters for Outcrossing-Related Traits in Barley

Crop Science ◽  
2005 ◽  
Vol 45 (1) ◽  
pp. cropsci2005.0098 ◽  
Author(s):  
Adel H. Abdel-Ghani ◽  
Heiko K. Parzies ◽  
Salvatore Ceccarelli ◽  
Stefania Grando ◽  
Hartwig H. Geiger
Keyword(s):  
Genetic Parameters ◽  
Quantitative Genetic ◽  
Quantitative Genetic Parameters

Estimating Quantitative Genetic Parameters Using Sibships Reconstructed From Marker Data

Genetics ◽  
2000 ◽  
Vol 155 (4) ◽  
pp. 1961-1972 ◽  
Author(s):  
Stuart C Thomas ◽  
William G Hill
Keyword(s):  
Prior Knowledge ◽  
Genetic Parameters ◽  
Allele Frequencies ◽  
Parameter Estimates ◽  
Monte Carlo Techniques ◽  
Quantitative Genetic ◽  
Downward Bias ◽  
Mean Square Errors ◽  
Sibship Reconstruction ◽  
Quantitative Genetic Parameters

Abstract Previous techniques for estimating quantitative genetic parameters, such as heritability in populations where exact relationships are unknown but are instead inferred from marker genotypes, have used data from individuals on a pairwise level only. At this level, families are weighted according to the number of pairs within which each family appears, hence by size rather than information content, and information from multiple relationships is lost. Estimates of parameters are therefore not the most efficient achievable. Here, Markov chain Monte Carlo techniques have been used to partition the population into complete sibships, including, if known, prior knowledge of the distribution of family sizes. These pedigrees have then been used with restricted maximum likelihood under an animal model to estimate quantitative genetic parameters. Simulations to compare the properties of parameter estimates with those of existing techniques indicate that the use of sibship reconstruction is superior to earlier methods, having lower mean square errors and showing nonsignificant downward bias. In addition, sibship reconstruction allows the estimation of population allele frequencies that account for the relationships within the sample, so prior knowledge of allele frequencies need not be assumed. Extensions to these techniques allow reconstruction of half sibships when some or all of the maternal genotypes are known.

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