Category Archives: Wiley: Plant Breeding

Genetic analysis and characterisation of Cmowf, a gene controlling the white petal colour phenotype in pumpkin (Cucurbita moschata D)

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Abstract

Flower colour, as an important morphological marker, plays an essential role in improving the identification efficiency of the purity seed in hybrid production. However, the molecular mechanism of white-flower trait has not been reported in pumpkin (Cucurbita moschata D.). In this study, we obtained a white-flower mutant (wf) through the ethyl methane sulfonate (EMS) mutagenesis of inbred line N87 (yellow flower). F2 populations were then constructed by crossing wf mutant and N87 plant to fine map the genes controlling white-flower trait in pumpkin. Phenotypic identification revealed that carotenoid content significantly decreased in the petals of wf mutants compared with N87 plants. Genetic analysis indicated that the white flower mutant trait was controlled by a single recessive gene, Cmowf. Using bulked segregant analysis and KASP phenotyping, Cmowf was mapped to a 762 kb region on chromosome 14 containing three annotated genes. Among them, a nonsynonymous single-nucleotide polymorphisms mutation was identified only in CmoCh14G005820 gene, which encoded a DUF1997 family protein. Compared with CmoDUF1997 amino acid sequences between the wf mutants and N87 plants, the critical amino acid mutations (early termination of amino acids) occurred in wf mutants, so CmoCh14G005820 was predicted as a potential candidate for controlling the white-flower trait. RNA-sequencing analysis revealed that the expression of CmoCh14G005820 and most genes involved in carotenoid biosynthesis was significantly downregulated in wf mutants, whereas the expression of several genes responsible for carotenoid degradation was upregulated in wf mutants. This finding suggested that carotenoid metabolism may participate in the formation of flower colour in pumpkin. Overall, our results provided a theoretical basis for understanding the genetic mechanisms underlying white-flower formation in pumpkin.

QTL mapping of nitrogen use efficiency traits at the seedling and maturity stages under different nitrogen conditions in barley (Hordeum vulgare L.)

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Abstract

Nitrogen (N) is an essential element for plant growth and development. The identification and utilization of N use efficiency (NUE) loci are essential for breeding high NUE cultivars. In this study, 15 NUE traits were measured in a recombinant inbred line population containing 121 lines derived from the cross between a cultivated barley (Baudin) and a wild barley (CN4027). The hydroponic culture was conducted with normal N and low N treatments in one-time frame, and field trials were conducted with N sufficiency and N deficiency treatments in two growing seasons. Twenty-two quantitative trait loci (QTLs) and four clusters were detected. Of them, the five stable QTLs Qgna.sau-3H for grain N concentration, Qtna.sau-3H for total N accumulation per plant, Qnhi.sau-3H for N harvest index, Qnutegy.sau-3H for N utilization efficiency for grain yield and Qanutedm.sau-3H.1 for N utilization efficiency for aboveground dry matter were co-located on chromosome 3H flanked by the markers bpb6282426 and bpb4786261. These two novel QTL clusters simultaneously controlled NUE traits at the seedling and maturity stages. Some genes related to NUE traits in intervals of the major QTLs were predicted. The significant relationships between NUE traits and agronomic and physiological traits were detected and discussed. In conclusion, this study uncovers the most promising genomic regions for the marker-assisted selection of NUE traits to improve NUE in barley.

New liguleless (lg2) maize stocks: Genetic resources for leaf architectural and haploid induction rate assessment studies

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Abstract

Liguleless mutants produce defective ligules and auricles and, consequently, have more upright leaves than their ligulate counterparts, making them useful genetic material for plant architectural studies. Besides, owing to the recessive nature and amenability of the liguleless trait to phenotyping at the seedling stage, liguleless mutants are popularly used for ‘proof-of-concept’ demonstration and assessment of haploid induction rate (HIR) of haploid inducer lines (HILs) in maize. The commonly used liguleless testers in maize are of temperate origin and are challenging to use and maintain under tropical/sub-tropical conditions. In the present study, liguleless lines (V 601, V 602, V 603 and V 604) derived from crosses between agronomically superior locally adapted tropical ligulate lines (V 407 and CM 152) and liguleless donors of temperate origin (PDH-3 and PDH-8) were evaluated for different agro-morphological traits. Liguleless line V 602 was also used as a tester to assess the HIR of haploid inducer line EC937890 (CIM2GTAILP2). The results showed a mean HIR of 12.42% for EC937890, consistent with the HIR reported in other studies, thus demonstrating the efficacy of V 602 as a tester for determining HIR. The agronomically superior liguleless maize lines reported in this study will, therefore, be a valuable resource for leaf architectural studies, assessment of HIR of candidate HILs and maintenance of high HIR in the HILs presently in wide use in the doubled haploid (DH) programmes. Additionally, these genetic stocks carry the liguleless trait in genetic backgrounds with known heterotic affinity with early maturity Indian public maize germplasm and, therefore, can be used directly as parents in hybrid development programmes.

Status of yam (Dioscorea spp.) in the Democratic Republic of Congo

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Abstract

Yam is an important tuber crop with enormous potential to enhance rural sustenance and livelihood in DRC. However, studies to enhance its genetic improvement are very far from sufficient with only a handful of information available on the crop. Yam has been treated as an orphan crop compared to contemporary crops such as cassava and sweet potato which have adapted to different cropping systems and become widespread in production. The lack of research attention to address the major production challenges has further decreased the value and potential of the crop compared to its contemporaries. These production constraints include lack of adequate quality planting materials, low yield potential, poor resistance/tolerance to yam mosaic and anthracnose diseases and ultimately poor tuber quality attributes focusing on tuber taste, flesh oxidation and dry matter contents of the majority of the farmers preferred varieties. In this review, we evaluated the status of yam in DRC and presented the needful activities to be incorporated for its improvement. Diversity has however been maintained mainly through ennoblement efforts in house gardens and small farmlands using traditional farming methods. Studies from other nations where yam has been successful with prominence in characterization and genetic improvement brought to light the need for DRC to consider yam as a staple carbohydrate food source, even to the extent of modifications in food public policy. Reversal of the yam's current stigma is a challenge to the scientific community and the population in general.

Characterization of resistance to angular leaf spot of common bean (Phaseolus vulgaris L.) breeding line SPS50HB

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Abstract

The common bean (Phaseolus vulgaris L.) makes an important contribution to the human diet, particularly in Africa and Latin America. Because angular leaf spot (ALS), caused by the fungal pathogen Pseudocercospora griseola, is one of the most severe foliar diseases of the bean plant, an important priority is to identify genes encoding resistance. The present study focused on the resistance shown by the Mesoamerican common bean breeding line SPS50HB. From the pattern of segregation for resistance displayed in an F2 population bred from a cross between SPS50HB and the ALS-susceptible Ethiopian variety Red Wolaita, it was concluded that the resistance of SPS50HB is controlled by two unlinked dominant genes. An allelism test indicated that one of these genes was either identical with, allelic to, or closely linked to the major gene Phg-2 carried by variety Mexico 54. The sequence-characterized amplified region assays OPEO4 and PF13, which are diagnostic for an ALS resistance gene carried by the germplasm accession G10909, both tracked a possible second gene present in SPS50HB.

Genetic analysis and identification of SSR marker linked to Phomopsis blight resistance in eggplant (Solanum melongena L.)

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The present investigation was carried out to decipher inheritance of resistance and to identify linked SSR markers for Phomopsis blight resistance in eggplant. An F2 population comprising 161 plants was developed from the cross of Pusa Kranti and BR-40-7. Genetic analysis was carried out using Chi square test. Artificial inoculation of fruits was carried out using pin prick method, and scoring was done as per the standard scoring scale. The F2 plants segregated into 92 susceptible (77—highly susceptible, 15—susceptible): 69 resistant (17—highly resistant, 27—resistant, 25—moderately resistant) suggesting complimentary epistasis with ratio of 9:7. To identify the putatively linked markers to resistance gene, parental polymorphic markers were subjected to bulk segregant analysis (BSA), and two markers (emk03O04 and emf11A03) could differentiate resistant and susceptible bulk and co-segregated with resistance gene. The genetic distance between the identified markers was found to be 18.12 cM using QTL IciMapping V3.2 software depicting two new QTLs on chromosome number 6. The identified QTLs have great significant importance in marker assisted breeding programme.

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.