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.

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.

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.

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.

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.

Genotyping by sequencing for the construction of oil palm (Elaeis guineensis Jacq.) genetic linkage map and mapping of yield related quantitative trait loci.

Background: Oil palm (Elaeis guineensis Jacq.) is one of the major oil-producing crops. Improving the quality and increasing the production yield of oil palm have been the primary focuses of both conventional and modern breeding approaches. However, the conventional breeding approach for oil palm is very challenging due to its longevity, which results in a long breeding cycle. Thus, the establishment of marker assisted selection (MAS) for oil palm breeding programs would speed up the breeding pipeline by generating new oil palm varieties that possess high commercial traits. With the decreasing cost of sequencing, Genotyping-by-sequencing (GBS) is currently feasible to many researchers and it provides a platform to accelerate the discovery of single nucleotide polymorphism (SNP) as well as insertion and deletion (InDel) markers for the construction of a genetic linkage map. A genetic linkage map facilitates the identification of significant DNA regions associated with the trait of interest via quantitative trait loci (QTL) analysis. Methods: A mapping population of 112 F1 individuals from a cross of Deli dura and Serdang pisifera was used in this study. GBS libraries were constructed using the double digestion method with HindIII and TaqI enzymes. Reduced representation libraries (RRL) of 112 F1 progeny and their parents were sequenced and the reads were mapped against the E. guineensis reference genome. To construct the oil palm genetic linkage map, informative SNP and InDel markers were used to discover significant DNA regions associated with the traits of interest. The nine traits of interest in this study were fresh fruit bunch (FFB) yield, oil yield (OY), oil to bunch ratio (O/B), oil to dry mesocarp ratio (O/DM) ratio, oil to wet mesocarp ratio (O/WM), mesocarp to fruit ratio (M/F), kernel to fruit ratio (K/F), shell to fruit ratio (S/F), and fruit to bunch ratio (F/B). Results: A total of 2.5 million SNP and 153,547 InDel markers were identified. However, only a subset of 5,278 markers comprising of 4,838 SNPs and 440 InDels were informative for the construction of a genetic linkage map. Sixteen linkage groups were produced, spanning 2,737.6 cM for the maternal map and 4,571.6 cM for the paternal map, with average marker densities of one marker per 2.9 cM and one per 2.0 cM respectively, were produced. A QTL analysis was performed on nine traits; however, only QTL regions linked to M/F, K/F and S/F were declared to be significant. Of those QTLs were detected: two for M/F, four for K/F and one for S/F. These QTLs explained 18.1-25.6% of the phenotypic variance and were located near putative genes, such as casein kinase II and the zinc finger CCCH domain, which are involved in seed germination and growth. The identified QTL regions for M/F, K/F and S/F from this study could be applied in an oil palm breeding program and used to screen palms with desired traits via marker assisted selection (MAS).

AMMI and GGE biplot analysis for genotype × environment interactions affecting the yield and quality characteristics of sugar beet.

Sugar beet, an important sugar crop, contributes significantly to the world's sugar production. However, genotype-environment interactions (GEI) often affect the quality characteristics of sugar beet. Hence, understanding the effects of GEI on sugar beet quality can aid in identifying high-quality genotypes that can adapt to different environments. Traditional variance analysis can only be used to examine the yield of a variety and not its specific adaptability to specific conditions. Therefore, more comprehensive analytical methods are required to evaluate the characteristics of the variety under specific environments. Additive main effects and multiplicative interaction (AMMI) and genotype main effect and genotype × environment interaction (GGE) biplot models can be employed to comprehensively evaluate different varieties and address the drawbacks associated with a single evaluation method. Moreover, these models also allow us to explore new varieties more objectively and comprehensively. In this study, the adaptability and stability of 16 sugar beet varieties, in terms of yield and sugar content, were evaluated using AMMI and GGE biplot analysis in seven pilot projects undertaken in 2022. In the assessment of a small but significant proportion of the total GEI variance for the two qualitative traits (yield and sugar content), 80.58% of the variance was explained by the cumulative contribution of IPC1, IPC2, and IPC3. AMMI and GGE biplots clearly highlighted that KWS4207 (G3) exhibited high and stable quality. They also demonstrated that the experiments in Jalaid Banner (Inner Mongolia) (E7) were the most representative. Together, the results suggested that the comprehensive application of AMMI and GGE biplot analysis allowed for a more comprehensive, scientific, and effective evaluation of sugar beet varieties across different regions. The findings offer a theoretical basis for sugar beet breeding and could guide the rational design of experiments for testing new varieties of sugar beet.

AMMI and GGE biplot analysis of genotype by environment interaction for yield and yield contributing traits in confectionery groundnut.

The global market has a high demand for premium edible grade groundnut, particularly for table use. India, in particular, exhibits significant potential for exporting confectionary grade large seeded groundnut. The environment plays a significant impact in influencing the expression of seed traits, which subsequently affects the confectionary quality of groundnut genotypes. The states of Gujarat and Rajasthan in India are prominent producers of high-quality groundnuts specifically used for confectionary purposes. The current study was conducted with 43 confectionery groundnut genotypes at Junagadh, Gujarat, and Bikaner, Rajasthan, with the goals of understanding genotype-by-environment interaction (GEI) effects and identifying stable, high yielding confectionery quality groundnut genotypes using AMMI and GGE biplot models. Pod yield per plant (PYP), number of pods per plant (NPP), hundred kernel weight (HKW), and shelling percent (SP) were estimated. The interplay between the environment and genotype has had a notable impact on the manifestation of confectionary grade characteristics in peanuts. The results from the Interaction Principal Component Analysis (IPCA) indicate that HKW contributed 76.68% and 18.95% towards the Global Environmental Index (GEI) through IPCA1 and IPCA2, respectively. Similarly, NPP contributed 87.52% and 8.65%, PYP contributed 95.87% and 2.1%, and SP contributed 77.4% and 16.22% towards GEI through IPCA1 and IPCA2, respectively. Based on the ranking of genotypes, the ideal genotypes were PBS 29079B for HKW, PBS 29230 for NPP. The genotypes PBS 29233 and PBS 29230 exhibited superior performance and stability in terms of pod yield, hundred kernel weight, number of pods per plant, and shelling percentage across various sites. These breeding lines have the potential to be developed for the purpose of producing confectionary grade groundnut with larger seeds, in order to fulfil the growing demand for export.

Application of genome editing techniques to regulate gene expression in crops.

BACKGROUND: Enhanced agricultural production is urgently required to meet the food demands of the increasing global population. Abundant genetic diversity is expected to accelerate crop development. In particular, the development of the CRISPR/Cas genome editing technology has greatly enhanced our ability to improve crop's genetic diversity through direct artificial gene modification. However, recent studies have shown that most crop improvement efforts using CRISPR/Cas techniques have mainly focused on the coding regions, and there is a relatively lack of studies on the regulatory regions of gene expression. RESULTS: This review briefly summarizes the development of CRISPR/Cas system in the beginning. Subsequently, the importance of gene regulatory regions in plants is discussed. The review focuses on recent developments and applications of mutations in regulatory regions via CRISPR/Cas techniques in crop breeding. CONCLUSION: Finally, an outline of perspectives for future crop breeding using genome editing technologies is provided. This review provides new research insights for crop improvement using genome editing techniques.

Breeding of ornamental orchids with focus on Phalaenopsis: current approaches, tools, and challenges for this century.

Ornamental orchid breeding programs have been conducted to develop commercially valuable cultivars with improved characteristics of commercial interest, such as size, flower color, pattern, shape, and resistance to pathogens. Conventional breeding, including sexual hybridization followed by selection of desirable characteristics in plants, has so far been the main method for ornamental breeding, but other techniques, including mutation induction by polyploidization and gamma irradiation, and biotechnological techniques, such as genetic transformation, have also been studied and used in ornamental breeding programs. Orchids are one of the most commercially important families in floriculture industry, having very particular reproductive biology characteristics and being a well-studied group of ornamentals in terms of genetic improvement. The present review focuses on the conventional and biotechnological techniques and approaches specially employed in breeding Phalaenopsis orchids, the genus with highest worldwide importance as an ornamental orchid, highlighting the main limitations and strengths of the approaches. Furthermore, new opportunities and future prospects for ornamental breeding in the CRISPR/Cas9 genome editing era are also discussed. We conclude that conventional hybridization remains the most used method to obtain new cultivars in orchids. However, the emergence of the first biotechnology-derived cultivars, as well as the new biotechnological tools available, such as CRISPR-Cas9, rekindled the full potential of biotechnology approaches and their importance for improve ornamental orchid breeding programs.

CRISPR-Cas9 based molecular breeding in crop plants: a review.

Traditional crop breeding techniques are not quickly boosting yields to fulfill the expanding population needs. Long crop lifespans hinder the ability of plant breeding to develop superior crop varieties. Due to the arduous crossing, selecting, and challenging processes, it can take decades to establish new varieties with desired agronomic traits. Develop new plant varieties instantly to reduce hunger and improve food security. As a result of the adoption of conventional agricultural techniques, crop genetic diversity has decreased over time. Several traditional and molecular techniques, such as genetic selection, mutant breeding, somaclonal variation, genome-wide association studies, and others, have improved agronomic traits associated with agricultural plant productivity, quality, and resistance to biotic and abiotic stresses. In addition, modern genome editing approaches based on programmable nucleases, CRISPR, and Cas9 proteins have escorted an exciting new era of plant breeding. Plant breeders and scientists worldwide rely on cutting-edge techniques like quick breeding, genome editing tools, and high-throughput phenotyping to boost crop breeding output. This review compiles discoveries in numerous areas of crop breeding, such as using genome editing tools to accelerate the breeding process and create yearly crop generations with the desired features, to describe the shift from conventional to modern plant breeding techniques.

Genotype by environment and genotype by yield*trait interactions in sugar beet: analyzing yield stability and determining key traits association.

The genotype by environment interaction significantly influences plant yield, making it imperative to understand its nature for the creation of breeding programs to enhance crop production. However, this is not the only obstacle in the yield improvement process. Breeders also face the significant challenge of unfavorable and negative correlations among key traits. In this study, the stability of root yield and white sugar yield, and the association between the key traits of root yield, sugar content, nitrogen, sodium, and potassium were examined in 20 sugar beet genotypes. The study was conducted using a randomized complete block design with four replications over two consecutive years across five locations. The combined analysis of variance results revealed significant main effects of year, location, and genotype on both root yield and white sugar yield. Notably, two-way and three-way interactions between these main effects on root yield and white sugar yield resulted in a significant difference. The additive main effect and multiplicative interaction analysis revealed that the first five interaction principal components significantly impacted both the root yield and white sugar yield. The linear mixed model results for root yield and white sugar yield indicated that the genotype effect and the genotype by environment interaction were significant. The weighted average absolute scores of the best linear unbiased predictions biplot demonstrated that genotypes 20, 4, 7, 2, 16, 3, 6, 1, 14, and 15 were superior in terms of root yield. For white sugar yield, genotypes 4, 16, 3, 7, 5, 1, 10, 20, 2, and 6 stood out. These genotypes were not only stable but also had a yield value higher than the total average. All key traits, which include sugar content, sodium, potassium, and alpha amino nitrogen, demonstrated a negative correlation with root yield. Based on the genotype by yield*trait analysis results, genotypes 20, 19, and 16 demonstrated optimal performance when considering the combination of root yield with sugar content, sodium, alpha amino nitrogen, and potassium. The multi-trait stability study, genotype 13 ranked first, and genotypes 10, 8, and 9 were identified as the most ideal stable genotypes across all traits. According to the multi-trait stability index, genotype 13 emerged as the top-ranking genotype. Additionally, genotypes 10, 8, and 9 were recognized as the most stable genotypes.

Unravelling inversions: Technological advances, challenges, and potential impact on crop breeding.

Inversions, a type of chromosomal structural variation, significantly influence plant adaptation and gene functions by impacting gene expression and recombination rates. However, compared with other structural variations, their roles in functional biology and crop improvement remain largely unexplored. In this review, we highlight technological and methodological advancements that have allowed a comprehensive understanding of inversion variants through the pangenome framework and machine learning algorithms. Genome editing is an efficient method for inducing or reversing inversion mutations in plants, providing an effective mechanism to modify local recombination rates. Given the potential of inversions in crop breeding, we anticipate increasing attention on inversions from the scientific community in future research and breeding applications.

CRISPR/Cas as a Genome-Editing Technique in Fruit Tree Breeding.

CRISPR (short for "Clustered Regularly Interspaced Short Palindromic Repeats") is a technology that research scientists use to selectively modify the DNA of living organisms. CRISPR was adapted for use in the laboratory from the naturally occurring genome-editing systems found in bacteria. In this work, we reviewed the methods used to introduce CRISPR/Cas-mediated genome editing into fruit species, as well as the impacts of the application of this technology to activate and knock out target genes in different fruit tree species, including on tree development, yield, fruit quality, and tolerance to biotic and abiotic stresses. The application of this gene-editing technology could allow the development of new generations of fruit crops with improved traits by targeting different genetic segments or even could facilitate the introduction of traits into elite cultivars without changing other traits. However, currently, the scarcity of efficient regeneration and transformation protocols in some species, the fact that many of those procedures are genotype-dependent, and the convenience of segregating the transgenic parts of the CRISPR system represent the main handicaps limiting the potential of genetic editing techniques for fruit trees. Finally, the latest news on the legislation and regulations about the use of plants modified using CRISPR/Cas systems has been also discussed.

Cotton pedigree genome reveals restriction of cultivar-driven strategy in cotton breeding.

BACKGROUND: Many elite genes have been identified from the available cotton genomic data, providing various genetic resources for gene-driven breeding. However, backbone cultivar-driven breeding is the most widely applied strategy. Revealing the genetic basis of cultivar-driven strategy's restriction is crucial for transition of cotton breeding strategy. RESULT: CRI12 is a backbone cultivar in cultivar-driven breeding. Here we sequence the pedigree of CRI12 using Nanopore long-read sequencing. We construct a graphical pedigree genome using the high-quality CRI12 genome and 13,138 structural variations within 20 different pedigree members. We find that low hereditary stability of elite segments in backbone cultivars is a drawback of cultivar-driven strategy. We also identify 623 functional segments in CRI12 for multiple agronomic traits in presence and absence variation-based genome-wide association study on three cohorts. We demonstrate that 25 deleterious segments are responsible for the geographical divergence of cotton in pathogen resistance. We also characterize an elite pathogen-resistant gene (GhKHCP) utilized in modern cotton breeding. In addition, we identify 386 pedigree fingerprint segments by comparing the segments of the CRI12 pedigree with those of a large cotton population. CONCLUSION: We characterize the genetic patterns of functional segments in the pedigree of CRI12 using graphical genome method, revealing restrictions of cultivar-driven strategies in cotton breeding. These findings provide theoretical support for transitioning from cultivar-driven to gene-driven strategy in cotton breeding.

Assessing the Potential for Genome-Assisted Breeding in Red Perilla Using Quantitative Trait Locus Analysis and Genomic Prediction.

Red perilla is an important medicinal plant used in Kampo medicine. The development of elite varieties of this species is urgently required. Medicinal compounds are generally considered target traits in medicinal plant breeding; however, selection based on compound phenotypes (i.e., conventional selection) is expensive and time consuming. Here, we propose genomic selection (GS) and marker-assisted selection (MAS), which use marker information for selection, as suitable selection methods for medicinal plants, and we evaluate the effectiveness of these methods in perilla breeding. Three breeding populations generated from crosses between one red and three green perilla genotypes were used to elucidate the genetic mechanisms underlying the production of major medicinal compounds using quantitative trait locus analysis and evaluating the accuracy of genomic prediction (GP). We found that GP had a sufficiently high accuracy for all traits, confirming that GS is an effective method for perilla breeding. Moreover, the three populations showed varying degrees of segregation, suggesting that using these populations in breeding may simultaneously enhance multiple target traits. This study contributes to research on the genetic mechanisms of the major medicinal compounds of red perilla, as well as the breeding efficiency of this medicinal plant.

Potato and sweetpotato breeding at the international potato center: approaches, outcomes and the way forward.

Root and tuber crop breeding is at the front and center of CIP's science program, which seeks to develop and disseminate sustainable agri-food technologies, information and practices to serve objectives including poverty alleviation, income generation, food security and the sustainable use of natural resources. CIP was established in 1971 in Peru, which is part of potato's center of origin and diversity, with an initial mandate on potato and expanding to include sweetpotato in 1986. Potato and sweetpotato are among the top 10 most consumed food staples globally and provide some of the most affordable sources of energy and vital nutrients. Sweetpotato plays a key role in securing food for many households in Africa and South Asia, while potato is important worldwide. Both crops grow in a range of conditions with relatively few inputs and simple agronomic techniques. Potato is adapted to the cooler environments, while sweetpotato grows well in hot climates, and hence, the two crops complement each other. Germplasm enhancement (pre-breeding), the development of new varieties and building capacity for breeding and variety testing in changing climates with emphasis on adaptation, resistance, nutritional quality and resource-use efficiency are CIP's central activities with significant benefits to the poor. Investments in potato and sweetpotato breeding and allied disciplines at CIP have resulted in the release of many varieties some of which have had documented impact in the release countries. Partnership with diverse types of organizations has been key to the centers way of working toward improving livelihoods through crop production in the global South.

Meta-QTL analysis in wheat: progress, challenges and opportunities.

Wheat, an important cereal crop globally, faces major challenges due to increasing global population and changing climates. The production and productivity are challenged by several biotic and abiotic stresses. There is also a pressing demand to enhance grain yield and quality/nutrition to ensure global food and nutritional security. To address these multifaceted concerns, researchers have conducted numerous meta-QTL (MQTL) studies in wheat, resulting in the identification of candidate genes that govern these complex quantitative traits. MQTL analysis has successfully unraveled the complex genetic architecture of polygenic quantitative traits in wheat. Candidate genes associated with stress adaptation have been pinpointed for abiotic and biotic traits, facilitating targeted breeding efforts to enhance stress tolerance. Furthermore, high-confidence candidate genes (CGs) and flanking markers to MQTLs will help in marker-assisted breeding programs aimed at enhancing stress tolerance, yield, quality and nutrition. Functional analysis of these CGs can enhance our understanding of intricate trait-related genetics. The discovery of orthologous MQTLs shared between wheat and other crops sheds light on common evolutionary pathways governing these traits. Breeders can leverage the most promising MQTLs and CGs associated with multiple traits to develop superior next-generation wheat cultivars with improved trait performance. This review provides a comprehensive overview of MQTL analysis in wheat, highlighting progress, challenges, validation methods and future opportunities in wheat genetics and breeding, contributing to global food security and sustainable agriculture.

Characterization of the Moroccan Barley Germplasm Preserved in the Polish Genebank as a First Step towards Selecting Forms with Increased Drought Tolerance.

In marginal, arid, and semi-arid areas of Morocco, crops are often exposed to multiple abiotic and biotic stresses that have a major impact on yield. Farmer-maintained Moroccan landraces have been shaped by the impact of very strong selection pressures, gradually adapting to the local ecosystem and obsolete low-input agricultural practices without improvement towards high yield and quality. Considering the increasing threat of drought in Poland, it is necessary to introduce germplasm with tolerance to water deficit into barley breeding programs. The aim of this research was a DArTseq-based genetic characterization of a collection of germplasm of Moroccan origin, conserved in the Polish genebank. The results showed that all conserved landraces have a high level of heterogeneity and their gene pool is different from the material developed by Polish breeders. Based on the analysis of eco-geographical data, locations with extremely different intensities of drought stress were selected. A total of 129 SNPs unique to accessions from these locations were identified. In the neighborhood of the clusters of unique SNPs on chromosomes 5H and 6H, genes that may be associated with plant response to drought stress were identified. The results obtained may provide a roadmap for further research to support Polish barley breeding for increased drought tolerance.

Genetic diversity and population structure of modern wheat (Triticum aestivum L.) cultivars in Henan Province of China based on SNP markers.

BACKGROUND: Henan is the province with the greatest wheat production in China. Although more than 100 cultivars are used for production, many cultivars are still insufficient in quality, disease resistance, adaptability and yield potential. To overcome these limitations, it is necessary to constantly breed new cultivars to maintain the continuous and stable growth of wheat yield and quality. To improve breeding efficiency, it is important to evaluate the genetic diversity and population genetic structure of its cultivars. However, there are no such reports from Henan Province. Therefore, in this study, single nucleotide polymorphism (SNP) markers were used to study the population genetic structure and genetic diversity of 243 wheat cultivars included in a comparative test of wheat varieties in Henan Province, aiming to provide a reference for the utilization of backbone parents and the selection of hybrid combinations in the genetic improvement of wheat cultivars. RESULTS: In this study, 243 wheat cultivars from Henan Province of China were genotyped by the Affymetrix Axiom Wheat660K SNP chip, and 21 characteristics were investigated. The cultivars were divided into ten subgroups; each subgroup had distinct characteristics and unique utilization value. Furthermore, based on principal component analysis, Zhoumai cultivars were the main hybrid parents, followed by Aikang 58, high-quality cultivars, and Shandong cultivars. Genetic diversity analysis showed that 61.3% of SNPs had a high degree of genetic differentiation, whereas 33.4% showed a moderate degree. The nucleotide diversity of subgenome B was relatively high, with an average π value of 3.91E-5; the nucleotide diversity of subgenome D was the lowest, with an average π value of 2.44E-5. CONCLUSION: The parents used in wheat cross-breeding in Henan Province are similar, with a relatively homogeneous genetic background and low genetic diversity. These results will not only contribute to the objective evaluation and utilization of the tested cultivars but also provide insights into the current conditions and existing challenges of wheat cultivar breeding in Henan Province, thereby facilitating the scientific formulation of breeding objectives and strategies to improve breeding efficiency.