Yearly Archives: 2023

Genomic selection and enablers for agronomic traits in maize (Zea mays): A review

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Abstract

Maize is a commodity crop providing millions of people with food, feed, industrial raw material and economic opportunities. However, maize yields in Africa are relatively stagnant and low, at a mean of 1.7 t ha−1 compared with the global average of 6 t ha−1. The yield gap can be narrowed with accelerated and precision breeding strategies that are required to develop and deploy high-yielding and climate-resilient maize varieties. Genomic and phenotypic selections are complementary methods that offer opportunities for the speedy choice of contrasting parents and derived progenies for hybrid breeding and commercialization. Genomic selection (GS) will shorten the crop breeding cycle by identifying and tracking desirable genotypes and aid the timeous commercialization of market-preferred varieties. The technology, however, has not yet been fully embraced by most public and private breeding programmes, notably in Africa. This review aims to present the importance, current status, challenges and opportunities of GS to accelerate genetic gains for economic traits to speed up the breeding of high-yielding maize varieties. The first section summarizes genomic selection and the contemporary phenotypic selection and phenotyping platforms as a foundation for GS and trait integration in maize. This is followed by highlights on the reported genetic gains and progress through phenotypic selection and GS for grain yield and yield components. Training population development, genetic design and statistical models used in GS in maize breeding are discussed. Lastly, the review summarizes the challenges of GS, including prediction accuracy, and integrates GS with speed breeding, doubled haploid breeding and genome editing technologies to increase breeding efficiency and accelerate cultivar release. The paper will guide breeders in selection and trait introgression using GS to develop cultivars preferred by the marketplace.

Identification of potential sources of mungbean yellow mosaic India virus resistance in black gram (Vigna mungo) and expression of antioxidants and R‐genes modulating resistance response in cultivated and its two wild relatives

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Abstract

Black gram is one of the most important short duration grain legume, which contributes significantly towards nutritional security and environmental sustainability. The virus specific primers confirms the presence of mungbean yellow mosaic India virus (MYMIV) in representative samples. A total of 27 cultivated and two wild species were found as highly resistant (HR) to MYMIV and validated through molecular markers. The start codon target (SCoT) markers analysis revealed that the SCoT loci, namely, SCoT-4 (2200 bp), SCot-9 (1150/ 1200 bp), SCoT-15 (1150/1100 bp), SCoT-16 (700 bp), SCoT-24 (2500 bp), SCoT-25 (700 bp), SCoT-33 (900/1000 bp), and SCoT-34 (600 bp), were found unique, able to distinguish HR and highly susceptible (HS) genotypes. Biochemical characterization and gene expression profiling revealed the higher expression of antioxidants and R-genes just after pathogen inoculation indicated the activation of defence mechanism in both cultivated and its wild relatives, which modulates the resistant responses in cultivated and wild accessions. These information will be really helpful in accelerating resistance breeding in black gram.

Designing optimal training sets for genomic prediction using adversarial validation with probit regression

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Abstract

Genomic selection (GS) is a disruptive methodology that is revolutionizing animal and plant breeding. However, its practical implementation is challenging since many times there is a mismatch in the distribution of the training and testing sets. Adversarial validation is an approach popular in machine learning to detect and address the difference between the training and testing distributions. For this reason, the adversarial validation method in this research was implemented using probit regression to detect the mismatch in distributions and also to select an optimal training set. We evaluated the proposed method with 14 datasets, and the results were benchmarked regarding of using the whole reference population and simple random samples. We found that the proposed method is effective for detecting the mismatch in distributions and outperformed in prediction accuracy by 11.67% (in terms of mean square error) and by 5.35% (in terms of normalized mean square error) when the whole reference population was used as training sets. Also, in general, this outperformed some existing methods for optimal training designs in the context of GS.

Combined transcriptome and proteome analyses between the cytoplasmic male sterile line and its maintainer line in Welsh onion (Allium fistulosum)

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Abstract

Cytoplasmic male sterility (CMS) is dispensable for research of heterosis and investigation of nuclear–cytoplasmic interaction in Welsh onion. The molecular mechanism of the cytoplasmic male sterile line and its maintainer line was investigated by combined transcriptome and proteome analyses in Welsh onion. The 410,585 full-length non-chimeric (FLNC, full-length readsnon-Chimeric) sequences were obtained, and AS events and lncRNAs were identified by full-length transcriptome. Towards a comprehensive understanding and identification of related genes for male sterility, the transcriptome and proteome sequencing were utilized to explore the differences between the cytoplasmic male sterile line and its maintainer line. The 287 differentially expressed genes (DEGs) and 49 differentially expressed proteins (DEPs) were identified, and we furthermore explored the function of genes and proteins. The heat map preliminarily demonstrated the expression change of the key genes and proteins in two cultivars. CMS-related genes were screened form differentially expressed genes, and verified by quantitative real-time quantitative polymerase chain reaction (qRT-PCR). Our research found the CMS regulatory genes, proteins and related pathways. The transcriptome and proteome datasets contribute to accelerate the development of CMS gene clones and functional genomics research on Welsh onions.

Hybrid breeding for fall armyworm resistance: Combining ability and hybrid prediction

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Abstract

Fall armyworm (FAW, Spodoptera frugiperda) emerged as a major lepidopteran pest destroying maize in sub-Saharan Africa. A diallel mating design was used to generate 210 experimental hybrids from 21 lines. Experimental hybrids and four checks were evaluated in two locations. Commercial checks suffered higher foliar and ear damage compared to the top 15 hybrids. Mean squares associated with the genotypic variation were higher than genotype-by-environment interactions for foliar and ear damage traits. Heritabilities were moderate to high. Significant correlations were observed between grain yield (GY) with ear rot (−0.54) and ear damage (−0.45). Positive and significant GCA effects were observed for GY in seven parental lines, which were developed from multiple insect resistance breeding programmes. CKSBL10153 has the highest GCA value for GY and shows significant GCA effects for foliar and ear damage traits. These lines were identified as the ideal combiners for GY and FAW resistance and are therefore recommended for utilization as testers in the development of FAW-resistant three-way cross-hybrid maize with correlated response for increased GY. GCA and marker-based prediction correlations of GY were 0.79 and 0.96, respectively. Both GCA effects and marker-based models were effective in predicting hybrid performance for FAW resistance.

Responses of differentially expressed proteins and endogenous hormones in winter rapeseed (Brassica rapa L.) roots under water deficit stress

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Winter rapeseed (Brassica rapa L.) can well-adapt to environmental conditions such as barrenness, water deficit and low temperature in arid and semi-arid planting regions and is the preferred rapeseed type. In this study, we analysed changes of root system morphology, antioxidant enzyme activity, endogenous hormone contents and differentially expressed proteins (DEPs) under control (CK), slight water deficit (SWD, 50–55% of maximum field water capacity), moderate water deficit (MWD, 40–45% of maximum field water capacity) and high water deficit (HWD, 30–35% of maximum field water capacity) conditions. Winter rapeseed experienced taproot elongation, decreased taproot diameter and increased lateral root number, under water deficit stress. The accumulation of reactive oxygen species (ROS) can cause membrane system peroxidation, and antioxidant enzyme activity increases to remove ROS. Changes in jasmonic acid (JA), salicylic acid (SA), cytokinin (CTK), auxin (IAA) and gibberellin (GA) levels promote the absorption of water and minerals by driving changes in the root system architecture to resist water deficit stress. A proteomic analysis has shown that DEPs are involved in energy metabolism, antioxidation response, osmotic regulation, hormone signal transduction, protein metabolism and the stress response, and these proteins are located in the peroxisome, chloroplast, mitochondrion, cell wall, vacuole, cytoplasm, extracellular space and cell membrane. In this study, multiple DEPs (malate dehydrogenase cytoplasmic 1 OS, 14-3-3-like protein GF14 Psi, GA 3-beta-dioxygenase, glutathione reductase and jasmonate-inducible protein) were involved in the root system architecture, revealing the complexity of the root response to water deficit. Significant/extremely significant synergistic relationships were observed between antioxidant enzyme activity and endogenous hormone contents. In conclusion, ROS, endogenous hormones and stress-related proteins work synergistically to control the root system architecture of winter rapeseed roots in response to water deficit stress.

A new approach to Fourier transform Raman: Identification of haploids in maize (Zea mays)

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The objective of this work was to adapt the FT Raman spectroscopy analysis in the differentiation of haploid and diploid kernels in maize, developing a new efficient, agile, precise, and nondestructive methodology. The main difference observed in FT Raman readings was a peak in the region between 1600 and 1700 cm−1 in possibly haploid kernels. It was possible to correlate the characteristics of the kernels with the presence of the R1-nj gene and the readings obtained in the Raman spectrometry technique. Most of the kernels previously classified as haploid showed positive values for principal component analysis (PCAs), indicating a correlation in the identification of haploids by the techniques adopted. The identification of haploids by R-Navajo was superior to FT Raman. However, FT Raman spectroscopy is an agile analysis technique that enables the development of non-invasive and non-destructive analytical methods in maize kernels, in addition to providing relevant information about the chemical structures present in the composition of the samples.

Extending Finlay–Wilkinson regression with environmental covariates

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Finlay–Wilkinson regression is a popular method for analysing genotype–environment interaction in series of plant breeding and variety trials. It involves a regression on the environmental mean, indexing the productivity of an environment, which is driven by a wide array of environmental factors. Increasingly, it is becoming feasible to characterize environments explicitly using observable environmental covariates. Hence, there is mounting interest to replace the environmental index with an explicit regression on such observable environmental covariates. This paper reviews the development of such methods. The focus is on parsimonious models that allow replacing the environmental index by regression on synthetic environmental covariates formed as linear combinations of a larger number of observable environmental covariates. Two new methods are proposed for obtaining such synthetic covariates, which may be integrated into genotype-specific regression models, that is, criss-cross regression and a factor-analytic approach. The main advantage of such explicit modelling is that predictions can be made also for new environments where trials have not been conducted. A published dataset is employed to illustrate the proposed methods.

Genetic dissection of endosperm hydration in malting barley (Hordeum vulgare)

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Hydration of the endosperm is a critical part of the malting process that ensures proper modification of the grain. However, little is known about the genetic controls of endosperm hydration and its relationship to agronomic and malt quality traits. The extent of endosperm hydration is estimated through hydration index (HYI). We measured HYI, agronomic, and malt quality traits on a 169-line subset of the NSGC Barley Core Panel, which includes global malt lines, some dating from the inception of European breeding programmes. Utilizing GWAS, 61 QTLs were identified for HYI, dormancy, agronomic, and malt quality traits. Of these, six were found to be related to HYI and were located on 1H, 2H, 3H, 6H, and 7H. We found HYI QTLs cosegregating with kernel size and hardness (1H and 3H), malting quality (2H and 6H), and dormancy (2H and 6H). These results indicate that endosperm hydration after steeping can be improved by selecting high HYI alleles on 2H, 6H, and 7H, positively impacting malting quality without negatively impacting kernel size or dormancy.

Characterisation of starch properties and physical characteristics in buckwheat (Fagopyrum esculentum Moench.) mutant lacking accumulation of ‘granule‐bound starch synthase a’

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Abstract

The concentration of amylose, which is synthesised using granule-bound starch synthase, affects the physical properties of food. However, no studies have focused on starch properties and physical characteristics of low-amylose buckwheat. Here, we hypothesised that low-amylose buckwheat would be useful to produce new buckwheat products because low-amylose characteristics change the texture of buckwheat food. In this study, we bred relatively low-amylose buckwheat compared to wild type and investigated the causative genes of the traits, starch properties and physical properties of noodles. In the GBSSa mutant, the amylose concentration was lower than that in the wild type. Compared with the wild type, the mutant exhibited the following traits: Amylose concentration decreased by approximately 2%, setback in the Rapid Visco Analyzer decreased by 30 points and the physical characteristics of noodles in the sensory analysis were soft and sticky. These results suggest that this trait may be useful for changing the texture of foods. In addition, the mutant is promising for producing new foods with physical characteristics that are different from those of the wild type.