Tissue culture and Agrobacterium-mediated genetic transformation of the oil crop sunflower.

Sunflower is one of the four major oil crops in the world. 'Zaoaidatou' (ZADT), the main variety of oil sunflower in the northwest of China, has a short growth cycle, high yield, and high resistance to abiotic stress. However, the ability to tolerate adervesity is limited. Therefore, in this study, we used the retention line of backbone parent ZADT as material to establish its tissue culture and genetic transformation system for new variety cultivating to enhance resistance and yields by molecular breeding. The combination of 0.05 mg/L IAA and 2 mg/L KT in MS was more suitable for direct induction of adventitious buds with cotyledon nodes and the addition of 0.9 mg/L IBA to MS was for adventitious rooting. On this basis, an efficient Agrobacterium tumefaciens-mediated genetic transformation system for ZADT was developed by the screening of kanamycin and optimization of transformation conditions. The rate of positive seedlings reached 8.0%, as determined by polymerase chain reaction (PCR), under the condition of 45 mg/L kanamycin, bacterial density of OD600 0.8, infection time of 30 min, and co-cultivation of three days. These efficient regeneration and genetic transformation platforms are very useful for accelerating the molecular breeding process on sunflower.

Understanding the nature of blast resistance in combined bacterial leaf blight and blast gene pyramided lines of rice variety tellahamsa.

BACKGROUND: Rice blast and bacterial leaf blight (BLB) are the most limiting factors for rice production in the world which cause yield losses typically ranging from 20 to 30% and can be as high as 50% in some areas of Asia especially India under severe infection conditions. METHODS AND RESULTS: An improved line of Tellahamsa, TH-625-491 having two BLB resistance genes (xa13 and Xa21) and two blast resistance genes (Pi54 and Pi1) with 95% Tellahamsa genome was used in the present study. TH-625-491 was validated for all four target genes and was used for backcrossing with Tellahamsa. Seventeen IBC1F1 plants heterozygous for all four target genes, 19 IBC1F2 plants homozygous for four, three and two gene combinations and 19 IBC1F2:3 plants also homozygous for four, three and two gene combinations were observed. Among seventeen IBC1F1 plants, IBC1F1-62 plant recorded highest recurrent parent genome (97.5%) covering 75 polymorphic markers. Out of the total of 920 IBC1F2 plants screened, 19 homozygous plants were homozygous for four, three and two target genes along with bacterial blight resistance. Background analysis was done in all 19 homozygous IBC1F2 plants possessing BLB resistance (possessing xa13, Xa21, Pi54 and Pi1 in different combinations) with five parental polymorphic SSR markers. IBC1F2-62-515 recovered 98.5% recurrent parent genome. The four, three and two gene pyramided lines of Tellahamsa exhibited varying resistance to blast. CONCLUSIONS: Results show that there might be presence of antagonistic effect between bacterial blight and blast resistance genes since the lines with Pi54 and Pi1 combination are showing better resistance than the combinations with both bacterial blight and blast resistance genes.

Identification of Induced Copy Number Variation from Low Coverage Sequence Data.

Induced mutations have been an important tool for plant breeding and functional genomics for more than 80 years. Novel mutations can be induced by treating seed or other plant cells with chemical mutagens or ionizing radiation. The majority of released mutant crop varieties were developed using ionizing radiation. This has been shown to create a variety of different DNA lesions including large (e.g., >=10,000 bps) copy number variations (CNV). Detection of induced DNA lesions from whole genome sequence data is useful for choosing a mutagen dosage prior to committing resources to develop a large mutant population for forward or reverse-genetic screening. Here I provide a method for detecting large induced CNV from mutant plants that utilizes a new tool to streamline the process of obtaining read coverage directly from BAM files, comparing non-mutagenized controls and mutagenized samples, and plotting the results for visual evaluation. Example data is provided from low coverage sequence data from gamma-irradiated vegetatively propagated triploid banana.

CRISPR/Cas9-Mediated Genome Editing in Indica Rice (Oryza sativa L. subsp. indica var. CR-5272).

Tissue culture optimization protocols limit indica rice breeding. Such a challenge is vital because emergent techniques still rely on tissue culture methods and could allow the breeding of new varieties with higher production and toleration of adverse environmental effects caused by climate change. Genome editing technology, using CRISPR/Cas9, is a fast and precise method for accelerated plant breeding. It limited its use in indica subspecies because of the recalcitrant response to in vitro culture methods. This chapter describes a protocol for CRISPR/Cas9 editing in indica subspecies, specifically in the CR-5272 variety derived from parental lines IR-822, using Agrobacterium tumefaciens and biolistic transformation.

Optimizing selection based on BLUPs or BLUEs in multiple sets of genotypes differing in their population parameters.

KEY MESSAGE: Selection response in truncation selection across multiple sets of candidates hinges on their post-selection proportions, which can deviate grossly from their initial proportions. For BLUPs, using a uniform threshold for all candidates maximizes the selection response, irrespective of differences in population parameters. Plant breeding programs typically involve multiple families from either the same or different populations, varying in means, genetic variances and prediction accuracy of BLUPs or BLUEs for true genetic values (TGVs) of candidates. We extend the classical breeder's equation for truncation selection from single to multiple sets of genotypes, indicating that the expected overall selection response ( Δ G Tot ) for TGVs depends on the selection response within individual sets and their post-selection proportions. For BLUEs, we show that maximizing Δ G Tot requires thresholds optimally tailored for each set, contingent on their population parameters. For BLUPs, we prove that Δ G Tot is maximized by applying a uniform threshold across all candidates from all sets. We provide explicit formulas for the origin of the selected candidates from different sets and show that their proportions before and after selection can differ substantially, especially for sets with inferior properties and low proportion. We discuss implications of these results for (a) optimum allocation of resources to training and prediction sets and (b) the need to counteract narrowing the genetic variation under genomic selection. For genomic selection of hybrids based on BLUPs of GCA of their parent lines, selecting distinct proportions in the two parent populations can be advantageous, if these differ substantially in the variance and/or prediction accuracy of GCA. Our study sheds light on the complex interplay of selection thresholds and population parameters for the selection response in plant breeding programs, offering insights into the effective resource management and prudent application of genomic selection for improved crop development.

Testcross performance and combining ability of early-medium maturing quality protein maize inbred lines in Eastern and Southern Africa.

Limited commercial quality protein maize (QPM) varieties with low grain yield potential are currently grown in Eastern and Southern Africa (ESA). This study was conducted to (i) assess the performance of single-cross QPM hybrids that were developed from elite inbred lines using line-by-tester mating design and (ii) estimate the general (GCA) and specific (SCA) combining ability of the QPM inbred lines for grain yield, agronomic and protein quality traits. One hundred and six testcrosses and four checks were evaluated across six environments in ESA during 2015 and 2016. Significant variations (P ≤ 0.01) were observed among environments, genotypes and genotype by environment interaction (GEI) for most traits evaluated. Hybrids H80 and H104 were the highest-yielding, most desirable, and stable QPM hybrids. Combining ability analysis showed both additive and non-additive gene effects to be important in the inheritance of grain yield. Additive effects were more important for agronomic and protein quality traits. Inbred lines L19 and L20 depicted desirable GCA effects for grain yield. Various other inbred lines with favorable GCA effects for agronomic traits, endosperm modification, and protein quality traits were identified. These inbred lines could be utilized for breeding desirable QPM cultivars. The QPM hybrids identified in this study could be commercialized after on-farm verification to replace the low-yielding QPM hybrids grown in ESA.

A wild rice CSSL population facilitated identification of salt tolerance genes and rice germplasm innovation.

Salt stress is one of the major factors that limits rice production. Therefore, identification of salt-tolerant alleles from wild rice is important for rice breeding. In this study, we constructed a set of chromosome segment substitution lines (CSSLs) using wild rice as the donor parent and cultivated rice Nipponbare (Nip) as the recurrent parent. Salt tolerance germinability (STG) was evaluated, and its association with genotypes was determined using this CSSL population. We identified 17 QTLs related to STG. By integrating the transcriptome and genome data, four candidate genes were identified, including the previously reported AGO2 and WRKY53. Compared with Nip, wild rice AGO2 has a structure variation in its promoter region and the expression levels were upregulated under salt treatments; wild rice WRKY53 also has natural variation in its promoter region, and the expression levels were downregulated under salt treatments. Wild rice AGO2 and WRKY53 alleles have combined effects for improving salt tolerance at the germination stage. One CSSL line, CSSL118 that harbors these two alleles was selected. Compared with the background parent Nip, CSSL118 showed comprehensive salt tolerance and higher yield, with improved transcript levels of reactive oxygen species scavenging genes. Our results provided promising genes and germplasm resources for future rice salt tolerance breeding.

Applicability of SCoT markers in unraveling genetic variation and population structure among sugar beet (Beta vulgaris L.) germplasm.

BACKGROUND: Sugar beet (Beta vulgaris L.) holds significant importance as a crop globally cultivated for sugar production. The genetic diversity present in sugar beet accessions plays a crucial role in crop improvement programs. METHODS AND RESULTS: During the present study, we collected 96 sugar beet accessions from different regions and extracted DNA from their leaves. Genomic DNA was amplified using SCoT primers, and the resulting fragments were separated by gel electrophoresis. The data were analyzed using various genetic diversity indices, and constructed a population STRUCTURE, applied the unweighted pair-group method with arithmetic mean (UPGMA), and conducted Principle Coordinate Analysis (PCoA). The results revealed a high level of genetic diversity among the sugar beet accessions, with 265 bands produced by the 10 SCoT primers used. The percentage of polymorphic bands was 97.60%, indicating substantial genetic variation. The study uncovered significant genetic variation, leading to higher values for overall gene diversity (0.21), genetic distance (0.517), number of effective alleles (1.36), Shannon's information index (0.33), and polymorphism information contents (0.239). The analysis of molecular variance suggested a considerable amount of genetic variation, with 89% existing within the population. Using STRUCTURE and UPGMA analysis, the sugar beet germplasm was divided into two major populations. Structure analysis partitioned the germplasm based on the origin and domestication history of sugar beet, resulting in neighboring countries clustering together. CONCLUSION: The utilization of SCoT markers unveiled a noteworthy degree of genetic variation within the sugar beet germplasm in this study. These findings can be used in future breeding programs with the objective of enhancing both sugar beet yield and quality.

Genomic Prediction from Multi-Environment Trials of Wheat Breeding.

Genomic prediction relates a set of markers to variability in observed phenotypes of cultivars and allows for the prediction of phenotypes or breeding values of genotypes on unobserved individuals. Most genomic prediction approaches predict breeding values based solely on additive effects. However, the economic value of wheat lines is not only influenced by their additive component but also encompasses a non-additive part (e.g., additive × additive epistasis interaction). In this study, genomic prediction models were implemented in three target populations of environments (TPE) in South Asia. Four models that incorporate genotype × environment interaction (G × E) and genotype × genotype (GG) were tested: Factor Analytic (FA), FA with genomic relationship matrix (FA + G), FA with epistatic relationship matrix (FA + GG), and FA with both genomic and epistatic relationship matrices (FA + G + GG). Results show that the FA + G and FA + G + GG models displayed the best and a similar performance across all tests, leading us to infer that the FA + G model effectively captures certain epistatic effects. The wheat lines tested in sites in different TPE were predicted with different precisions depending on the cross-validation employed. In general, the best prediction accuracy was obtained when some lines were observed in some sites of particular TPEs and the worse genomic prediction was observed when wheat lines were never observed in any site of one TPE.

Country-wide, multi-location trials of Green Super Rice lines for yield performance and stability analysis using genetic and stability parameters.

Rice (Oryza sativa L.) is an important member of the family Poaceae and more than half of world population depend for their dietary nutrition on rice. Rice cultivars with higher yield, resilience to stress and wider adaptability are essential to ensure production stability and food security. The fundamental objective of this study was to identify higher-yielding rice genotypes with stable performance and wider adaptability in a rice growing areas of Pakistan. A triplicate RCBD design experiment with 20 Green Super Rice (GSR) advanced lines was conducted at 12 rice growing ecologies in four Provinces of Pakistan. Grain yield stability performance was assessed by using different univariate and multivariate statistics. Analysis of variance revealed significant differences among genotypes, locations, and G x E interaction for mean squares (p < 0.05) of major yield contributing traits. All the studied traits except for number of tillers per plant revealed higher genotypic variance than environmental variance. Broad sense heritability was estimated in the range of 44.36% to 98.60%. Based on ASV, ASI, bi, Wi2, σ2i and WAAS statistics, the genotypes G1, G4, G5, G8, G11 and G12 revealed lowest values for parametric statistics and considered more stable genotypes based on  paddy yield. The additive main effects and multiplicative interaction (AMMI) model revealed significant variation (p < 0.05) for genotypes, non-signification for environment and highly significant for G × E interaction. The variation proportion of PC1 and PC2 from interaction revealed 67.2% variability for paddy yield. Based on 'mean verses stability analysis of GGE biplot', 'Which-won-where' GGE Biplot, 'discriminativeness vs. representativeness' pattern of stability, 'IPCA and WAASB/GY' ratio-based stability Heat-map, and ranking of genotypes, the genotypes G1, G2, G3, G5, G8, G10, G11 and G13 were observed ideal genotypes with yield potential more than 8 tons ha-1. Discriminativeness vs. representativeness' pattern of stability identifies two environments, E5 (D.I Khan, KPK) and E6 (Usta Muhammad, Baluchistan) were best suited for evaluating genotypic yield performance. Based on these findings we have concluded that the genotypes G1, G2, G3, G5, G8, G10, G11 and G13 could be included in the commercial varietal development process and future breeding program.

Comparative studies of four cumin landraces grown in Egypt.

One of the significant aromatic plants applied in food and pharma is cumin. Despite its massive trading in Egypt, there are no comprehensive reports on cumin landraces profile screening. This study aimed to investigate the variation in seeds' physical and biochemical profiles and genetic diversity as well as assess the efficiency of seeds' germination under salinity stress. Consequently, during the 2020/2021 growing season, four common cumin seed landraces were gathered from various agro-climatic regions: El Gharbia, El Menia, Assiut, and Qena. Results showed a significant variation in physical profile among the four seeds of landraces. In addition, Assiut had the highest percentage of essential oil at 8.04%, whilst Qena had the largest amount of cumin aldehyde, the primary essential oil component, at 25.19%. Lauric acid was found to be the predominant fatty acid (54.78 to 62.73%). According to ISSR amplification, El Menia presented a negative unique band, whereas other landraces offered a positive band. Additionally, the cumin genotypes were separated into two clusters by the dendrogram, with El Gharbia being located in an entirely separate cluster. There were two sub-clusters within the other cluster: El Menia in one and Assiut and Qena in the other. Moreover, the germination sensitivity to the diverse salinity concentrations (control, 4, 8, 12, and 16 dS/m) findings showed that landraces exhibited varying responses to increased salinity when El Gharbia and El Menia showed a moderate response at four dS/m. Whilst, Qena landraces showed supreme values among other landraces under 12 and 16 dS/m. The majority of the examined features had strong positive associations over a range of salinity levels, according to phenotypic correlation coefficient analysis. To accomplish the aims of sustainable agriculture in Egypt, it would be imperative that the potential breeding program for cumin landraces consider this screening study.

Advances in the evolution research and genetic breeding of peanut.

Peanut is an important cash crop used in oil, food and feed in our country. The rapid development of sequencing technology has promoted the research on the related aspects of peanut genetic breeding. This paper reviews the research progress of peanut origin and evolution, genetic breeding, molecular markers and their applications, genomics, QTL mapping and genome selection techniques. The main problems of molecular genetic breeding in peanut research worldwide include: the narrow genetic resources of cultivated species, unstable genetic transformation and unclear molecular mechanism of important agronomic traits. Considering the severe challenges regarding the supply of edible oil, and the main problems in peanut production, the urgent research directions of peanut are put forward: The de novo domestication and the exploitation of excellent genes from wild resources to improve modern cultivars; Integration of multi-omics data to enhance the importance of big data in peanut genetics and breeding; Cloning the important genes related to peanut agronomic traits and analyzing their fine regulation mechanisms; Precision molecular design breeding and using gene editing technology to accurately improve the key traits of peanut.

Finger millet (Eleusine coracana) enhancement through genomic resources and breeding methods: current implications and potential future interventions.

Finger millet (Eleusine coracana) is an essential staple crop in many regions of Africa and Asia, valued for its nutritional content and resilience in challenging agro-ecological conditions. The enhancement of finger millet through genomic resources and breeding methods represents a promising avenue for addressing food and nutritional security. Current efforts in this field have harnessed genomic technologies to decipher the crop's genetic diversity and identify key traits related to yield, disease resistance, and nutritional content. These insights have facilitated the development of improved varieties through selective breeding, accelerating the crop's adaptation to changing environmental conditions. In the future, continued advancements in genomics and breeding methodologies hold the potential to further enhance finger millet's resilience, nutritional value, and productivity, ultimately benefiting both farmers and consumers. This review article synthesizes the current state of research and development in finger millet enhancement through the integration of genomic resources and innovative breeding methods. The utilization of these insights in selective breeding has already yielded promising results in developing improved finger millet varieties that meet the evolving needs of farmers and consumers. Moreover, this article discusses potential future interventions, including the continued advancement of genomics, precision breeding, and sustainable agricultural practices. These interventions hold the promise of further enhancing finger millet's adaptability to changing climates, its nutritional quality, and its overall productivity, thereby contributing to food security and improved livelihoods in finger millet-dependent regions.

Screening for drought tolerance and genetic diversity of wheat varieties using agronomic and molecular markers.

BACKGROUND: The future predictions for frequent and severe droughts will represent a significant threat to wheat yield and food security. In this context, breeding has proven to be the most efficient approach to enhance wheat productivity in dry environments. METHODS AND RESULTS: In this study, both agronomic and molecular-based approaches were used to evaluate the response of twenty-eight Tunisian wheat varieties to drought stress. The primary objective was to screen these varieties for drought tolerance using molecular and agro-morphological markers. All varieties were significantly affected by drought stress regarding various traits including total dry matter, straw length, flag leaf area, number of senescent leaves, SPAD value, grain yield and grain number. Furthermore, substantial variability in drought-stress tolerance was observed among wheat genotypes. The cluster analysis and principal component analyses confirmed the existence of genotypic variation in growth and yield impairments induced by drought. The stress susceptibility index (SSI) and tolerance index (TOL) proved to be the most effective indices and were strongly correlated with the varying levels of genotypic tolerance. The genotyping evaluation resulted in the amplification of 101 alleles using highly polymorphic 12 SSR markers, showed an average polymorphism of 74%. CONCLUSIONS: Taken together, the combination of agronomic and molecular approaches revealed that Karim, Td7, D117 and Utique are the most drought-tolerant wheat varieties. These varieties are particularly promising candidates for genetic improvements and can be utilized as potential genitors for future breeding programs in arid and semi-arid regions.

Cyto-swapping in maize by haploid induction with a cenh3 mutant.

Maize mutants of the centromeric histone H3 (CENP-A/CENH3) gene can form haploids that inherit only chromosomes of the pollinating parent but the cytoplasm from the female parent. We developed CENH3 haploid inducers carrying a dominant anthocyanin colour marker for efficient haploid identification and harbouring cytoplasmic male sterile cytoplasm, a type of cytoplasm that results in male sterility useful for efficient hybrid seed production. The resulting cytoplasmic male sterility cyto-swapping method provides a faster and cheaper way to convert commercial lines to cytoplasmic male sterile compared to conventional trait introgression.

Emerging Trends in Wheat (Triticum spp.) Breeding: Implications for the Future.

Wheat (Triticum spp and, particularly, T. aestivum L.) is an essential cereal with increased human and animal nutritional demand. Therefore, there is a need to enhance wheat yield and genetic gain using modern breeding technologies alongside proven methods to achieve the necessary increases in productivity. These modern technologies will allow breeders to develop improved wheat cultivars more quickly and efficiently. This review aims to highlight the emerging technological trends used worldwide in wheat breeding, with a focus on enhancing wheat yield. The key technologies for introducing variation (hybridization among the species, synthetic wheat, and hybridization; genetically modified wheat; transgenic and gene-edited), inbreeding (double haploid (DH) and speed breeding (SB)), selection and evaluation (marker-assisted selection (MAS), genomic selection (GS), and machine learning (ML)) and hybrid wheat are discussed to highlight the current opportunities in wheat breeding and for the development of future wheat cultivars.

Meta-analysis of identified genomic regions and candidate genes underlying salinity tolerance in rice (Oryza sativa L.).

Rice output has grown globally, yet abiotic factors are still a key cause for worry. Salinity stress seems to have the more impact on crop production out of all abiotic stresses. Currently one of the most significant challenges in paddy breeding for salinity tolerance with the help of QTLs, is to determine the QTLs having the best chance of improving salinity tolerance with the least amount of background noise from the tolerant parent. Minimizing the size of the QTL confidence interval (CI) is essential in order to primarily include the genes responsible for salinity stress tolerance. By considering that, a genome-wide meta-QTL analysis on 768 QTLs from 35 rice populations published from 2001 to 2022 was conducted to identify consensus regions and the candidate genes underlying those regions responsible for the salinity tolerance, as it reduces the confidence interval (CI) to many folds from the initial QTL studies. In the present investigation, a total of 65 MQTLs were extracted with an average CI reduced from 17.35 to 1.66 cM including the smallest of 0.01 cM. Identification of the MQTLs for individual traits and then classifying the target traits into correlated morphological, physiological and biochemical aspects, resulted in more efficient interpretation of the salinity tolerance, identifying the candidate genes and to understand the salinity tolerance mechanism as a whole. The results of this study have a huge potential to improve the rice genotypes for salinity tolerance with the help of MAS and MABC.