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Testcross performance and combining ability of early maturing maize inbreds under multiple-stress environments.

ABSTRACT: Availability of multiple-stress tolerant maize is critical for improvement in maize production in West and Central Africa (WCA). A study was carried out to (i) assess a set of inbred lines for combining ability under stressed and optimal conditions, (ii) determine the performance of the testcrosses under different conditions, and (iii) identify outstanding hybrids across the conditions. Two hundred and five testcrosses were planted with five hybrid checks under Striga-infested, low soil nitrogen, drought and optimal conditions between 2015 and 2016 in Nigeria. The grain yield inheritance under optimal condition was largely regulated by additive gene effect whereas non-additive gene effects largely regulated grain yield under the three stresses. Four of the inbreds had significant positive general combining ability effects each under low N and drought, and three under Striga infestation for grain yield. The inbreds could be vital sources of beneficial alleles for development and improvement of tropical yellow maize hybrids and populations. Hybrids TZEI 443 x ENT 13 and TZEI 462 x TZEI 10 were high yielding and stable; they out-performed the three early maturing released hybrids in WCA. The new hybrids should be extensively assessed and released in the sub-region to improve food security.

SUBMITTER: Annor B

PROVIDER: S-EPMC6760492 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Testcross performance and combining ability of early maturing maize inbreds under multiple-stress environments.

Annor Benjamin B Badu-Apraku Baffour B Nyadanu Daniel D Akromah Richard R Fakorede Morakinyo A B MAB

Scientific reports 20190924 1

Availability of multiple-stress tolerant maize is critical for improvement in maize production in West and Central Africa (WCA). A study was carried out to (i) assess a set of inbred lines for combining ability under stressed and optimal conditions, (ii) determine the performance of the testcrosses under different conditions, and (iii) identify outstanding hybrids across the conditions. Two hundred and five testcrosses were planted with five hybrid checks under Striga-infested, low soil nitrogen ...[more]

PMID: 31551523

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Project description:Knowledge of combining ability and genetic diversity are important prerequisites for the development of outstanding hybrids that are tolerant to high plant density. This work was carried out to assess general combining ability (GCA) and specific combining ability (SCA), identify promising hybrids, estimate genetic diversity among the inbred lines and correlate genetic distance to hybrid performance and SCA across different plant densities. A total of 28 F1 hybrids obtained by crossing eight adverse inbred lines (four local and four exotic) were evaluated under three plant densities 59,500 (D1), 71,400 (D2) and 83,300 (D3) plants ha-1 using spilt plot design with three replications at two locations during 2018 season. Increasing plant density from D1 to D3 significantly decreased leaf angle (LANG), chlorophyll content (CHLC), all ear characteristics and grain yield per plant (GYPP). Contrarily, days to silking (DTS), anthesis-silking interval (ASI), plant height (PLHT), ear height (EHT), and grain yield per hectare (GYPH) were significantly increased. Both additive and non-additive gene actions were involved in the inheritance of all the evaluated traits, but additive gene action was predominant for most traits. Inbred lines L1, L2, and L5 were the best general combiners for increasing grain yield and other desirable traits across research environments. Two hybrids L2 × L5 and L2 × L8 were found to be good specific combiners for ASI, LANG, GYPP and GYPH. Furthermore, these hybrids are ideal for further testing and promotion for commercialization under high plant density. Genetic distance (GD) among pairs of inbred lines ranged from 0.31 to 0.78, with an average of 0.61. Clustering based on molecular GD has effectively grouped the inbred lines according to their origin. No significant correlation was found between GD and both hybrid performance and SCA for grain yield and other traits and proved to be of no predictive value. Nevertheless, SCA could be used to predict the hybrid performance across all plant densities. Overall, this work presents useful information regarding the inheritance of maize grain yield and other important traits under high plant density.

Project description:Epigenetic variation describes heritable differences that are not attributable to changes in DNA sequence. There is the potential for pure epigenetic variation that occurs in the absence of any genetic change or for more complex situations that involve both genetic and epigenetic differences. Methylation of cytosine residues provides one mechanism for the inheritance of epigenetic information. A genome-wide profiling of DNA methylation in two different genotypes of Zea mays (ssp. mays), an organism with a complex genome of interspersed genes and repetitive elements, allowed the identification and characterization of examples of natural epigenetic variation. The distribution of DNA methylation was profiled using immunoprecipitation of methylated DNA followed by hybridization to a high-density tiling microarray. The comparison of the DNA methylation levels in the two genotypes, B73 and Mo17, allowed for the identification of approximately 700 differentially methylated regions (DMRs). Several of these DMRs occur in genomic regions that are apparently identical by descent in B73 and Mo17 suggesting that they may be examples of pure epigenetic variation. The methylation levels of the DMRs were further studied in a panel of near-isogenic lines to evaluate the stable inheritance of the methylation levels and to assess the contribution of cis- and trans- acting information to natural epigenetic variation. The majority of DMRs that occur in genomic regions without genetic variation are controlled by cis-acting differences and exhibit relatively stable inheritance. This study provides evidence for naturally occurring epigenetic variation in maize, including examples of pure epigenetic variation that is not conditioned by genetic differences. The epigenetic differences are variable within maize populations and exhibit relatively stable trans-generational inheritance. The detected examples of epigenetic variation, including some without tightly linked genetic variation, may contribute to complex trait variation.

Project description:Genomic selection (GS) is a modern breeding approach where genome-wide single-nucleotide polymorphism (SNP) marker profiles are simultaneously used to estimate performance of untested genotypes. In this study, the potential of genomic selection methods to predict testcross performance for hybrid canola breeding was applied for various agronomic traits based on genome-wide marker profiles. A total of 475 genetically diverse spring-type canola pollinator lines were genotyped at 24,403 single-copy, genome-wide SNP loci. In parallel, the 950 F1 testcross combinations between the pollinators and two representative testers were evaluated for a number of important agronomic traits including seedling emergence, days to flowering, lodging, oil yield and seed yield along with essential seed quality characters including seed oil content and seed glucosinolate content. A ridge-regression best linear unbiased prediction (RR-BLUP) model was applied in combination with 500 cross-validations for each trait to predict testcross performance, both across the whole population as well as within individual subpopulations or clusters, based solely on SNP profiles. Subpopulations were determined using multidimensional scaling and K-means clustering. Genomic prediction accuracy across the whole population was highest for seed oil content (0.81) followed by oil yield (0.75) and lowest for seedling emergence (0.29). For seed yieId, seed glucosinolate, lodging resistance and days to onset of flowering (DTF), prediction accuracies were 0.45, 0.61, 0.39 and 0.56, respectively. Prediction accuracies could be increased for some traits by treating subpopulations separately; a strategy which only led to moderate improvements for some traits with low heritability, like seedling emergence. No useful or consistent increase in accuracy was obtained by inclusion of a population substructure covariate in the model. Testcross performance prediction using genome-wide SNP markers shows considerable potential for pre-selection of promising hybrid combinations prior to resource-intensive field testing over multiple locations and years.

Dataset Information

Testcross performance and combining ability of early maturing maize inbreds under multiple-stress environments.

Publications

Testcross performance and combining ability of early maturing maize inbreds under multiple-stress environments.

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