High-yield hybrid breeding of Camellia oleifolia based on ISSR molecular markers.

BACKGROUND: C. Oleifera is among the world's largest four woody plants known for their edible oil production, yet the contribution rate of improved varieties is less than 20%. The species traditional breeding is lengthy cycle (20-30 years), occupation of land resources, high labor cost, and low accuracy and efficiency, which can be enhanced by molecular marker-assisted selection. However, the lack of high-quality molecular markers hinders the species genetic analysis and molecular breeding. RESULTS: Through quantitative traits characterization, genetic diversity assessment, and association studies, we generated a selection population with wide genetic diversity, and identified five excellent high-yield parental combinations associated with four reliable high-yield ISSR markers. Early selection criteria were determined based on kernel fresh weight and cultivated 1-year seedling height, aided by the identification of these 4 ISSR markers. Specific assignment of selected individuals as paternal and maternal parents was made to capitalize on their unique attributes. CONCLUSIONS: Our results indicated that molecular markers-assisted breeding can effectively shorten, enhance selection accuracy and efficiency and facilitate the development of a new breeding system for C. oleifera.

Microsatellite marker-assisted backcross breeding for improvement of wheat salt tolerance using Kharchia 65.

BACKGROUND: Salinity is a significant abiotic stress that affects plants from germination through all growth stages. This study was aimed to determine the morpho-physiological and genetic variations in BC1F2, BC2F1 and F3 generations resulting from the cross combination WH1105 × Kharchia 65. RESULTS: A significant reduction in germination percentage was observed under salt stress in BC1F2 and F3 seeds. Correlation, heritability in the broad sense, phenotypic coefficient of variability (PCV) and genotypic coefficient of variability (GCV) were measured for all traits. The presence of both Nax1 and Nax2 loci was confirmed in twenty-nine plants using the marker-assisted selection technique. Genetic relationships among the populations were assessed using twenty-four polymorphic SSR markers. CONCLUSION: Cluster analysis along with two and three-dimensional PCA scaling (Principal Component Analysis) revealed the distinct nature of WH 1105 and Kharchia 65. Six plants closer to the recurrent parent (WH1105) selected through this study can serve as valuable genetic material for salt-tolerant wheat improvement programs.

Validation and identification of promising gene specific markers governing foliar disease resistance in groundnut (Arachis hypogaea L.).

BACKGROUND: Groundnut is vulnerable to the major foliar fungal disease viz., late leaf spot (LLS) and rust in kharif season, which results in severe yield losses. Until now, LLS and rust resistance linked markers were developed based on GPBD 4 as a major donor source and were validated in its derivatives only, which restricted their use in marker assisted selection (MAS) involving other donors. METHODS AND RESULTS: The current study focused to validate LLS and rust resistance linked markers employing advanced breeding lines of F6 generation, derived from nine different crosses involving nine diverse parents, to identify potential markers for marker-assisted breeding of LLS and rust resistance in groundnut. Out of 28-trait linked markers used for validation, 8 were polymorphic (28.57%). Marker-trait association (MTA) and Single Marker Analysis (SMA) revealed that the SSR marker pPGPseq5D05 is significantly associated with both LLS (15.8% PVE) and rust (17.5% PVE) resistance, whereas, the marker IPAHM103 is tightly linked with rust resistance (26.8% PVE) alone. In silico analysis revealed that the marker gene for IPAHM103 is a zinc finger protein and the marker gene for pPGPseq5D05 is an ADP-ribosylation factor GTPase-activating protein. Both these protein products impart resistance or tolerance to biotic stress in crop plants. Two other markers namely, GMLQ975 and pPGPseq13A10 were also found to be associated with LLS resistance explaining MTA up to 60%. CONCLUSION: These gene specific markers will enable us to screen more number of germplasm lines or newly developed lines in MAS schemes for LLS and rust resistance using a wide range of resistant sources.

The role of phenomics and genomics in delineating the genetic basis of complex traits in millets.

Millets, comprising a diverse group of small-seeded grains, have emerged as vital crops with immense nutritional, environmental, and economic significance. The comprehension of complex traits in millets, influenced by multifaceted genetic determinants, presents a compelling challenge and opportunity in agricultural research. This review delves into the transformative roles of phenomics and genomics in deciphering these intricate genetic architectures. On the phenomics front, high-throughput platforms generate rich datasets on plant morphology, physiology, and performance in diverse environments. This data, coupled with field trials and controlled conditions, helps to interpret how the environment interacts with genetics. Genomics provides the underlying blueprint for these complex traits. Genome sequencing and genotyping technologies have illuminated the millet genome landscape, revealing diverse gene pools and evolutionary relationships. Additionally, different omics approaches unveil the intricate information of gene expression, protein function, and metabolite accumulation driving phenotypic expression. This multi-omics approach is crucial for identifying candidate genes and unfolding the intricate pathways governing complex traits. The review highlights the synergy between phenomics and genomics. Genomically informed phenotyping targets specific traits, reducing the breeding size and cost. Conversely, phenomics identifies promising germplasm for genomic analysis, prioritizing variants with superior performance. This dynamic interplay accelerates breeding programs and facilitates the development of climate-smart, nutrient-rich millet varieties and hybrids. In conclusion, this review emphasizes the crucial roles of phenomics and genomics in unlocking the genetic enigma of millets.

Quantitative genomics-enabled selection for simultaneous improvement of lint yield and seed traits in cotton (Gossypium hirsutum L.).

KEY MESSAGE: A Bayesian linkage disequilibrium-based multiple-locus mixed model identified QTLs for fibre, seed and oil traits and predicted breeding worthiness of test lines, enabling their simultaneous improvement in cotton. Improving cotton seed and oil yields has become increasingly important while continuing to breed for higher lint yield. In this study, a novel Bayesian linkage disequilibrium-based multiple-locus mixed model was developed for QTL identification and genomic prediction (GP). A multi-parent population consisting of 256 recombinant inbred lines, derived from four elite cultivars with distinct combinations of traits, was used in the analysis of QTLs for lint percentage, seed index, lint index and seed oil content and their interrelations. All four traits were moderately heritable and correlated but with no large influence of genotype × environment interactions across multiple seasons. Seven to ten major QTLs were identified for each trait with many being adjacent or overlapping for different trait pairs. A fivefold cross-validation of the model indicated prediction accuracies of 0.46-0.62. GP results based on any two-season phenotypes were strongly correlated with phenotypic means of a pooled analysis of three-season experiments (r = 0.83-0.92). When used for selection of improvement in lint, seed and oil yields, GP captured 40-100% of individuals with comparable lint yields of those selected based on the three-season phenotypic results. Thus, this quantitative genomics-enabled approach can not only decipher the genomic variation underlying lint, seed and seed oil traits and their interrelations, but can provide predictions for their simultaneous improvement. We discuss future breeding strategies in cotton that will enhance the entire value of the crop, not just its fibre.

Omics-driven utilization of wild relatives for empowering pre-breeding in pearl millet.

MAIN CONCLUSION: Pearl millet wild relatives harbour novel alleles which could be utilized to broaden genetic base of cultivated species. Genomics-informed pre-breeding is needed to speed up introgression from wild to cultivated gene pool in pearl millet. Rising episodes of intense biotic and abiotic stresses challenge pearl millet production globally. Wild relatives provide a wide spectrum of novel alleles which could address challenges posed by climate change. Pre-breeding holds potential to introgress novel diversity in genetically narrow cultivated Pennisetum glaucum from diverse gene pool. Practical utilization of gene pool diversity remained elusive due to genetic intricacies. Harnessing promising traits from wild pennisetum is limited by lack of information on underlying candidate genes/QTLs. Next-Generation Omics provide vast scope to speed up pre-breeding in pearl millet. Genomic resources generated out of draft genome sequence and improved genome assemblies can be employed to utilize gene bank accessions effectively. The article highlights genetic richness in pearl millet and its utilization with a focus on harnessing next-generation Omics to empower pre-breeding.

Genome-wide association analysis uncovers rice blast resistance alleles of Ptr and Pia.

A critical step to maximize the usefulness of genome-wide association studies (GWAS) in plant breeding is the identification and validation of candidate genes underlying genetic associations. This is of particular importance in disease resistance breeding where allelic variants of resistance genes often confer resistance to distinct populations, or races, of a pathogen. Here, we perform a genome-wide association analysis of rice blast resistance in 500 genetically diverse rice accessions. To facilitate candidate gene identification, we produce de-novo genome assemblies of ten rice accessions with various rice blast resistance associations. These genome assemblies facilitate the identification and functional validation of novel alleles of the rice blast resistance genes Ptr and Pia. We uncover an allelic series for the unusual Ptr rice blast resistance gene, and additional alleles of the Pia resistance genes RGA4 and RGA5. By linking these associations to three thousand rice genomes we provide a useful tool to inform future rice blast breeding efforts. Our work shows that GWAS in combination with whole-genome sequencing is a powerful tool for gene cloning and to facilitate selection of specific resistance alleles for plant breeding.

Application and prospect of BSA method based on bibliometrics in crop breeding.

In order to understand the progress and frontier in the application of BSA(bulked segregant analysis) method in crop breeding and to reflect objectively the contribution of different countries, institutions and researchers in this field at home and abroad, this study analyzed 2111 items in the WOS (Web of Science) database from 2000 to 2023 and 446 items in the CNKI (China National through Knowledge Infrastructure) database from 2003 to 2023, regarding the researches of the application of BSA in crop breeding, basing on bibliometric analysis methods using CiteSpace software including keyword co-occurrence analysis, highlight word analysis, keyword clustering analysis, clustering timeline analysis and author co-citation. The results showed that there was an consistent increasing trend in the publication number of the application of BSA in crop breeding both in the domestic and foreign journals year by year. Ranking of the top countries according to the number of publications was China, the United States and India. The Huazhong Agricultural University displayed the highest number of publications in the CNKI database, while the Chinese Academy of Agricultural Sciences was found to have the highest number of publications in the WOS database. The published articles related to the application of BSA in crop breeding abroad mainly focused on the disciplines such as plant science, agronomy, horticulture and genetics, while those in China mainly concentrated on such disciplines as plant science, plant protection, horticulture and biology. The top three authors in terms of influence in the field of appling BSA in crop breeding were Michelmore RW, Kosambi DD and Li H, while Michelmore RW, Lander ES and Li H had closer cooperations with other authors. The top three crops relating to the studies of BSA were rice(Oryza sativa), soybean(Glycine max), corn(Zea mays L.) with the hot spot traits of disease resistance and plant height domestically. The top three crops involving the studies of BSA were rice, Arabidopsis thaliana and wheat(Triticum aestivum L.) with hot spot traits of disease resistance abroad. Up to now, BSA was mainly used to localize and functionally verify the candidate genes linking target traits and the mutated genes in crops in the domestical documents, while the foreign published studies based on BSA were mainly focused on the fine mapping and functional verification of target trait genes aiming at the revelation of genetic mechanisms in crops. Research frontier analysis indicated that rice, peanuts(Arachis hypogaea L.), upland cotton(Gossypium hirsutum L.) would be the main objects of studies concerning application of BSA in crop breeding with the hot topics of crop mutants and crop metabolites in the future.

Progress in Rice Breeding Based on Genomic Research.

The role of rice genomics in breeding progress is becoming increasingly important. Deeper research into the rice genome will contribute to the identification and utilization of outstanding functional genes, enriching the diversity and genetic basis of breeding materials and meeting the diverse demands for various improvements. Here, we review the significant contributions of rice genomics research to breeding progress over the last 25 years, discussing the profound impact of genomics on rice genome sequencing, functional gene exploration, and novel breeding methods, and we provide valuable insights for future research and breeding practices.

Insights into Salinity Tolerance in Wheat.

Salt stress has a detrimental impact on food crop production, with its severity escalating due to both natural and man-made factors. As one of the most important food crops, wheat is susceptible to salt stress, resulting in abnormal plant growth and reduced yields; therefore, damage from salt stress should be of great concern. Additionally, the utilization of land in coastal areas warrants increased attention, given diminishing supplies of fresh water and arable land, and the escalating demand for wheat. A comprehensive understanding of the physiological and molecular changes in wheat under salt stress can offer insights into mitigating the adverse effects of salt stress on wheat. In this review, we summarized the genes and molecular mechanisms involved in ion transport, signal transduction, and enzyme and hormone regulation, in response to salt stress based on the physiological processes in wheat. Then, we surveyed the latest progress in improving the salt tolerance of wheat through breeding, exogenous applications, and microbial pathways. Breeding efficiency can be improved through a combination of gene editing and multiple omics techniques, which is the fundamental strategy for dealing with salt stress. Possible challenges and prospects in this process were also discussed.

PlantMine: A Machine-Learning Framework to Detect Core SNPs in Rice Genomics.

As a fundamental global staple crop, rice plays a pivotal role in human nutrition and agricultural production systems. However, its complex genetic architecture and extensive trait variability pose challenges for breeders and researchers in optimizing yield and quality. Particularly to expedite breeding methods like genomic selection, isolating core SNPs related to target traits from genome-wide data reduces irrelevant mutation noise, enhancing computational precision and efficiency. Thus, exploring efficient computational approaches to mine core SNPs is of great importance. This study introduces PlantMine, an innovative computational framework that integrates feature selection and machine learning techniques to effectively identify core SNPs critical for the improvement of rice traits. Utilizing the dataset from the 3000 Rice Genomes Project, we applied different algorithms for analysis. The findings underscore the effectiveness of combining feature selection with machine learning in accurately identifying core SNPs, offering a promising avenue to expedite rice breeding efforts and improve crop productivity and resilience to stress.

The Landscape of Presence/Absence Variations during the Improvement of Rice.

Rice is one of the most important staple crops in the world; therefore, the improvement of rice holds great significance for enhancing agricultural production and addressing food security challenges. Although there have been numerous studies on the role of single-nucleotide polymorphisms (SNPs) in rice improvement with the development of next-generation sequencing technologies, research on the role of presence/absence variations (PAVs) in the improvement of rice is limited. In particular, there is a scarcity of studies exploring the traits and genes that may be affected by PAVs in rice. Here, we extracted PAVs utilizing resequencing data from 148 improved rice varieties distributed in Asia. We detected a total of 33,220 PAVs and found that the number of variations decreased gradually as the length of the PAVs increased. The number of PAVs was the highest on chromosome 1. Furthermore, we identified a 6 Mb hotspot region on chromosome 11 containing 1091 PAVs in which there were 29 genes related to defense responses. By conducting a genome-wide association study (GWAS) using PAV variation data and phenotypic data for five traits (flowering time, plant height, flag leaf length, flag leaf width, and panicle number) across all materials, we identified 186 significantly associated PAVs involving 20 cloned genes. A haplotype analysis and expression analysis of candidate genes revealed that important genes might be affected by PAVs, such as the flowering time gene OsSFL1 and the flag leaf width gene NAL1. Our work investigated the pattern in PAVs and explored important PAV key functional genes associated with agronomic traits. Consequently, these results provide potential and exploitable genetic resources for rice breeding.

Abiotic Stress Tolerance Boosted by Genetic Diversity in Plants.

Plant breeding [...].

Identification of soybean mosaic virus strain SC7 resistance loci and candidate genes in soybean [Glycine max (L.) Merr.].

Soybean [Glycine max (L.) Merr.] is an important legume crop worldwide, which provides abundant plant protein and oil for human beings. Soybean mosaic virus (SMV) can cause serious damage to the yield and quality of soybean, but it is difficult to control SMV with chemicals, breeding SMV-resistant varieties has become the most effective way to control the disease. Therefore, it is important to identify SMV resistance genes from soybean resources and apply them to soybean breeding. In this study, the disease rates (DRs) of 219 soybean accessions to SMV strain SC7 in two environments were investigated. A high-density NJAU 355 K SoySNP array was used for genome-wide association study (GWAS) of DR. A 274 kb region on chromosome 15 (1,110,567 bp to 1,384,173 bp) was repeatedly detected in two environments. Six new significant single nucleotide polymorphisms (SNPs) on chromosome 15 were identified. Four of these six SNPs were located within two candidate genes, Glyma.15G015700 and Glyma.15G015800. The elite haplotype Glyma.15G015700Hap I with low DR exhibited strong resistance to SC7. The expression of Glyma.15G015700 in the SMV-resistant accession increased significantly after inoculation with SC7. Furthermore, most of the proteins predicted to interact with Glyma.15G015700 are heat shock proteins, which have been shown to be related to disease resistance. In summary, new SMV resistance loci and a new candidate gene, Glyma.15G015700, were identified and might be utilized in further soybean disease resistance breeding.

Boosting genome-wide association power and genomic prediction accuracy for date palm fruit traits with advanced statistics.

The date palm is economically vital in the Middle East and North Africa, providing essential fibres, vitamins, and carbohydrates. Understanding the genetic architecture of its traits remains complex due to the tree's perennial nature and long generation times. This study aims to address these complexities by employing advanced genome-wide association (GWAS) and genomic prediction models using previously published data involving fruit acid content, sugar content, dimension, and colour traits. The multivariate GWAS model identified seven QTL, including five novel associations, that shed light on the genetic control of these traits. Furthermore, the research evaluates different genomic prediction models that considered genotype by environment and genotype by trait interactions. While colour- traits demonstrate strong predictive power, other traits display moderate accuracies across different models and scenarios aligned with the expectations when using small reference populations. When designing the cross-validation to predict new individuals, the accuracy of the best multi-trait model was significantly higher than all single-trait models for dimension traits, but not for the remaining traits, which showed similar performances. However, the cross-validation strategy that masked random phenotypic records (i.e., mimicking the unbalanced phenotypic records) showed significantly higher accuracy for all traits except acid contents. The findings underscore the importance of understanding genetic architecture for informed breeding strategies. The research emphasises the need for larger population sizes and multivariate models to enhance gene tagging power and predictive accuracy to advance date palm breeding programs. These findings support more targeted breeding in date palm, improving productivity and resilience to various environments.

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.

Characterization of chromosomal segment substitution lines developed in the genetic background of rice variety K 343.

In this study, BC3F2 convergent population [(K343*3/RML22 × K343*3/DHMAS) × K343] was constructed by marker-assisted backcross breeding using K343 as the recurrent parent. DHMAS and RML22 were used as donor parents for the rice blast resistance genes Pi54 and Pi9, respectively. The population was first characterized using GGT 2.0 software, which showed 96.7% of the recurrent genome recovery covering 13953.6 cM, while DHMAS and RML22 showed 1.6% (235.5 cM) and 1.2% (177.1 cM) introgression respectively. The chromosomal segment substitution lines (CSSLs) were then identified using CSSL Finder software. A total of 36 CSSLs were identified, including 22 for DHMAS/K343 and 14 for RML22/K343. Introgression rates for donor substituted segments in DHMAS/K343 CSSLs ranged from 0.54% to 5.99%, with donor coverage of 44.5%, while in RML22/K343 CSSLs, introgression rates ranged from 0.54% to 4.75%, with donor coverage of 24.5%. The identified CSSLs would be a valuable genetic pool and could be used as genomic resources for the discovery and mapping of important genes and QTLs in rice genetic improvement.

Current status of community resources and priorities for weed genomics research.

Weeds are attractive models for basic and applied research due to their impacts on agricultural systems and capacity to swiftly adapt in response to anthropogenic selection pressures. Currently, a lack of genomic information precludes research to elucidate the genetic basis of rapid adaptation for important traits like herbicide resistance and stress tolerance and the effect of evolutionary mechanisms on wild populations. The International Weed Genomics Consortium is a collaborative group of scientists focused on developing genomic resources to impact research into sustainable, effective weed control methods and to provide insights about stress tolerance and adaptation to assist crop breeding.

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.

Haplotype-resolved gapless genome and chromosome segment substitution lines facilitate gene identification in wild rice.

The abundant genetic variation harbored by wild rice (Oryza rufipogon) has provided a reservoir of useful genes for rice breeding. However, the genome of wild rice has not yet been comprehensively assessed. Here, we report the haplotype-resolved gapless genome assembly and annotation of wild rice Y476. In addition, we develop two sets of chromosome segment substitution lines (CSSLs) using Y476 as the donor parent and cultivated rice as the recurrent parents. By analyzing the gapless reference genome and CSSL population, we identify 254 QTLs associated with agronomic traits, biotic and abiotic stresses. We clone a receptor-like kinase gene associated with rice blast resistance and confirm its wild rice allele improves rice blast resistance. Collectively, our study provides a haplotype-resolved gapless reference genome and demonstrates a highly efficient platform for gene identification from wild rice.