Genomics-assisted Breeding Research Articles

Mapping of major QTL and candidate gene analysis for hull colour in foxtail millet (Setaria italica (L.) P. Beauv.)

BackgroundHull colour is an important morphological marker for selection in seed production of foxtail millet. However, the molecular mechanisms underlying hull colour variation remain unknown.ResultsAn F7 recombinant inbred line (RIL) population containing 215 lines derived from Hongjiugu × Yugu18 was used to analyze inheritance and detect the quantitative trait loci (QTL) for four hull colour traits using major gene plus polygene mixed inheritance analysis and composite interval mapping (CIM) in four environments. Genetic analysis revealed that the hull colour L* value (HCL*) was controlled by two major genes plus additive polygenes, the hull colour a* value (HCa*) was controlled by three major genes, the hull colour b* value (HCb*) was controlled by two major genes plus polygenes, and the hull colour C* value (HCC*) was controlled by four major genes. A high-density genetic linkage map covering 1227.383 cM of the foxtail millet genome, with an average interval of 0.879 cM between adjacent bin markers, was constructed using 1420 bin markers. Based on the genetic linkage map and the phenotypic data, a total of 39 QTL were detected for these four hull colour traits across four environments, each explaining 1.50%–49.20% of the phenotypic variation. Of these, six environmentally stable major QTL were co-localized to regions on chromosomes 1 and 9, playing a major role in hull colour. There were 556 annotated genes within the two QTL regions. Based on the functions of homologous genes in Arabidopsis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) gene annotations, five genes were predicted as candidate genes for further studies.ConclusionsThis is the first study to use an inheritance model and QTL mapping to determine the genetic mechanisms of hull colour trait in foxtail millet. We identified six major environmentally stable QTL and predicted five potential candidate genes to be associated with hull colour. These results advance the current understanding of the genetic mechanisms underlying hull colour traits in foxtail millet and provide additional resources for application in genomics-assisted breeding and potential isolation and functional characterization of the candidate genes.

A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane.

The sugarcane ratooning ability (RA) is the most important target trait for breeders seeking to enhance the profitability of sugarcane production by reducing the planting cost. Understanding the genetics governing the RA could help breeders by identifying molecular markers that could be used for genomics-assisted breeding (GAB). A replicated field trial was conducted for three crop cycles (plant cane, first ratoon, and second ratoon) using 432 sugarcane clones and used for conducting genome-wide association and genomic prediction of five sugar and yield component traits of the RA. The RA traits for economic index (EI), stalk population (SP), stalk weight (SW), tonns of cane per hectare (TCH), and tonns of sucrose per hectare (TSH) were estimated from the yield and sugar data. A total of six putative quantitative trait loci and eight nonredundant single-nucleotide polymorphism (SNP) markers were associated with all five tested RA traits and appear to be unique. Seven putative candidate genes were colocated with significant SNPs associated with the five RA traits. The genomic prediction accuracies for those tested traits were moderate and ranged from 0.21 to 0.36. However, the models fitting fixed effects for the most significant associated markers for each respective trait did not give any advantages over the standard models without fixed effects. As a result of this study, more robust markers could be used in the future for clone selection in sugarcane, potentially helping resolve the genetic control of the RA in sugarcane.

Heat-tolerant maize for rainfed hot, dry environments in the lowland tropics: From breeding to improved seed delivery

Climate change-induced heat stress combines two challenges: high day- and nighttime temperatures, and physiological water deficit due to demand-side drought caused by increase in vapor-pressure deficit. It is one of the major factors in low productivity of maize in rainfed stress-prone environments in South Asia, affecting a large population of smallholder farmers who depend on maize for their sustenance and livelihoods. The International Maize and Wheat Improvement Center (CIMMYT) maize program in Asia, in partnership with public-sector maize research institutes and private-sector seed companies in South Asian countries, is implementing an intensive initiative for developing and deploying heat-tolerant maize that combines high yield potential with resilience to heat and drought stresses. With the integration of novel breeding tools and methods, including genomics-assisted breeding, doubled haploidy, field-based precision phenotyping, and trait-based selection, new maize germplasm with increased tolerance to heat stress is being developed for the South Asian tropics. Over a decade of concerted effort has resulted in the successful development and release of 20 high-yielding heat-tolerant maize hybrids in CIMMYT genetic backgrounds. Via public–private partnerships, eight hybrids are presently being deployed on over 50,000 ha in South Asian countries, including Bangladesh, Bhutan, India, Nepal, and Pakistan.

Genomic basis of selective breeding from the closest wild relative of large-fruited tomato.

The long and intricate domestication history of the tomato (Solanum lycopersicum) includes selection sweeps that have not been fully explored, and these sweeps show significant evolutionary trajectories of domestication traits. Using three distinct selection strategies, we represented comprehensive selected sweeps from 53 Solanum pimpinellifolium (PIM) and 166 S. lycopersicum (BIG) accessions, which are defined as pseudo-domestication in this study. We identified 390 potential selection sweeps, some of which had a significant impact on fruit-related traits and were crucial to the pseudo-domestication process. During tomato pseudo-domestication, we discovered a minor-effect allele of the SlLEA gene related to fruit weight (FW), as well as the major haplotypes of fw2.2/cell number regulator (CNR), fw3.2/SlKLUH, and fw11.3/cell size regulator (CSR) in cultivars. Furthermore, 18 loci were found to be significantly associated with FW and six fruit-related agronomic traits in genome-wide association studies. By examining population differentiation, we identified the causative variation underlying the divergence of fruit flavonoids across the large-fruited tomatoes and validated BRI1-EMS-SUPPRESSOR 1.2 (SlBES1.2), a gene that may affect flavonoid content by modulating the MYB12 expression profile. Our results provide new research routes for the genetic basis of fruit traits and excellent genomic resources for tomato genomics-assisted breeding.

Genetic mapping identified major main-effect and three co-localized quantitative trait loci controlling high iron and zinc content in groundnut.

Malnutrition is a major challenge globally, and groundnut is a highly nutritious self-pollinated legume crop blessed with ample genomic resources, including the routine deployment of genomic-assisted breeding. This study aimed to identify genomic regions and candidate genes for high iron (Fe) and zinc (Zn) content, utilizing a biparental mapping population (ICGV 00440×ICGV 06040;). Genetic mapping and quantitative trait locus (QTL) analysis (474 mapped single-nucleotide polymorphism loci; 1536.33cM) using 2 seasons of phenotypic data together with genotypic data identified 5 major main-effect QTLs for Fe content. These QTLs exhibited log-of-odds (LOD) scores ranging from 6.5 to 7.4, explaining phenotypic variation (PVE) ranging from 22% (qFe-Ah01) to 30.0% (qFe-Ah14). Likewise, four major main effect QTLs were identified for Zn content, with LOD score ranging from 4.4 to 6.8 and PVE ranging from 21.8% (qZn-Ah01) to 32.8% (qZn-Ah08). Interestingly, three co-localized major and main effect QTLs (qFe-Ah01, qZn-Ah03, and qFe-Ah11) were identified for both Fe and Zn contents. These genomic regions harbored key candidate genes, including zinc/iron permease transporter, bZIP transcription factor, and vacuolar iron transporter which likely play pivotal roles in the accumulation of Fe and Zn contents in seeds. The findings of this study hold potential for fine mapping and diagnostic marker development for high Fe and Zn contents in groundnut.

Genome assembly of the hybrid grapevine Vitis 'Chambourcin'.

'Chambourcin' is a French-American interspecific hybrid grape grown in the eastern and midwestern United States and used for making wine. Few genomic resources are available for hybrid grapevines like 'Chambourcin'. Here, we assembled the genome of 'Chambourcin' using PacBio HiFi long-read, Bionano optical map, and Illumina short-read sequencing technologies. We generated an assembly for 'Chambourcin' with 26 scaffolds, with an N50 length of 23.3 Mb and an estimated BUSCO completeness of 97.9%. We predicted 33,791 gene models and identified 16,056 common orthologs between 'Chambourcin', V. vinifera 'PN40024' 12X.v2, VCOST.v3, Shine Muscat and V. riparia Gloire. We found 1,606 plant transcription factors from 58 gene families. Finally, we identified 304,571 simple sequence repeats (up to six base pairs long). Our work provides the genome assembly, annotation and the protein and coding sequences of 'Chambourcin'. Our genome assembly is a valuable resource for genome comparisons, functional genomic analyses and genome-assisted breeding research.

Recent advances in artificial intelligence, mechanistic models and speed breeding offer exciting opportunities for precise and accelerated genomics-assisted breeding.

Given the challenges of population growth and climate change, there is an urgent need to expedite the development of high-yielding stress-tolerant crop cultivars. While traditional breeding methods have been instrumental in ensuring global food security, their efficiency, precision, and labor intensiveness have become increasingly inadequate to address present and future challenges. Fortunately, recent advances in high-throughput phenomics and genomics-assisted breeding (GAB) provide a promising platform for enhancing crop cultivars with greater efficiency. However, several obstacles must be overcome to optimize the use of these techniques in crop improvement, such as the complexity of phenotypic analysis of big image data. In addition, the prevalent use of linear models in genome-wide association studies (GWAS) and genomic selection (GS) fails to capture the non-linear interactions of complex traits, limiting their applicability for GAB and impeding crop improvement. Recent advances in artificial intelligence (AI) techniques have opened doors to non-linear modeling approaches in crop breeding, enabling the capture of non-linear and epistatic interactions in GWAS and GS and thus making this variation available for GAB. While statistical and software challenges persist in AI-based models, they are expected to be resolved soon. Furthermore, recent advances in speed breeding have significantly reduced the time (3-5-fold) required for conventional breeding. Thus, integrating speed breeding with AI and GAB could improve crop cultivar development within a considerably shorter timeframe while ensuring greater accuracy and efficiency. In conclusion, this integrated approach could revolutionize crop breeding paradigms and safeguard food production in the face of population growth and climate change. This article is protected by copyright. All rights reserved.

Multi-Omics Pipeline and Omics-Integration Approach to Decipher Plant's Abiotic Stress Tolerance Responses.

The present day's ongoing global warming and climate change adversely affect plants through imposing environmental (abiotic) stresses and disease pressure. The major abiotic factors such as drought, heat, cold, salinity, etc., hamper a plant's innate growth and development, resulting in reduced yield and quality, with the possibility of undesired traits. In the 21st century, the advent of high-throughput sequencing tools, state-of-the-art biotechnological techniques and bioinformatic analyzing pipelines led to the easy characterization of plant traits for abiotic stress response and tolerance mechanisms by applying the 'omics' toolbox. Panomics pipeline including genomics, transcriptomics, proteomics, metabolomics, epigenomics, proteogenomics, interactomics, ionomics, phenomics, etc., have become very handy nowadays. This is important to produce climate-smart future crops with a proper understanding of the molecular mechanisms of abiotic stress responses by the plant's genes, transcripts, proteins, epigenome, cellular metabolic circuits and resultant phenotype. Instead of mono-omics, two or more (hence 'multi-omics') integrated-omics approaches can decipher the plant's abiotic stress tolerance response very well. Multi-omics-characterized plants can be used as potent genetic resources to incorporate into the future breeding program. For the practical utility of crop improvement, multi-omics approaches for particular abiotic stress tolerance can be combined with genome-assisted breeding (GAB) by being pyramided with improved crop yield, food quality and associated agronomic traits and can open a new era of omics-assisted breeding. Thus, multi-omics pipelines together are able to decipher molecular processes, biomarkers, targets for genetic engineering, regulatory networks and precision agriculture solutions for a crop's variable abiotic stress tolerance to ensure food security under changing environmental circumstances.

Optimizing genomic selection of agricultural traits using K-wheat core collection.

The agricultural traits that constitute basic plant breeding information are usually quantitative or complex in nature. This quantitative and complex combination of traits complicates the process of selection in breeding. This study examined the potential of genome-wide association studies (GWAS) and genomewide selection (GS) for breeding ten agricultural traits by using genome-wide SNPs. As a first step, a trait-associated candidate marker was identified by GWAS using a genetically diverse 567 Korean (K)-wheat core collection. The accessions were genotyped using an Axiom® 35K wheat DNA chip, and ten agricultural traits were determined (awn color, awn length, culm color, culm length, ear color, ear length, days to heading, days to maturity, leaf length, and leaf width). It is essential to sustain global wheat production by utilizing accessions in wheat breeding. Among the traits associated with awn color and ear color that showed a high positive correlation, a SNP located on chr1B was significantly associated with both traits. Next, GS evaluated the prediction accuracy using six predictive models (G-BLUP, LASSO, BayseA, reproducing kernel Hilbert space, support vector machine (SVM), and random forest) and various training populations (TPs). With the exception of the SVM, all statistical models demonstrated a prediction accuracy of 0.4 or better. For the optimization of the TP, the number of TPs was randomly selected (10%, 30%, 50% and 70%) or divided into three subgroups (CC-sub 1, CC-sub 2 and CC-sub 3) based on the subpopulation structure. Based on subgroup-based TPs, better prediction accuracy was found for awn color, culm color, culm length, ear color, ear length, and leaf width. A variety of Korean wheat cultivars were used for validation to evaluate the prediction ability of populations. Seven out of ten cultivars showed phenotype-consistent results based on genomics-evaluated breeding values (GEBVs) calculated by the reproducing kernel Hilbert space (RKHS) predictive model. Our research provides a basis for improving complex traits in wheat breeding programs through genomics assisted breeding. The results of our research can be used as a basis for improving wheat breeding programs by using genomics-assisted breeding.

Genetic mapping identified three hotspot genomic regions and candidate genes controlling heat tolerance-related traits in groundnut.

Groundnut productivity and quality have been impeded by rising temperatures in semi-arid environments. Hence, understanding the effects and molecular mechanisms of heat stress tolerance will aid in tackling yield losses. In this context, a recombinant inbred line (RIL) population was developed and phenotyped for eight seasons at three locations for agronomic, phenological, and physiological traits under heat stress. A genetic map was constructed using genotyping-by-sequencing with 478 single-nucleotide polymorphism (SNP) loci spanning a map distance of 1,961.39 cM. Quantitative trait locus (QTL) analysis using phenotypic and genotypic data identified 45 major main-effect QTLs for 21 traits. Intriguingly, three QTL clusters (Cluster-1-Ah03, Cluster-2-Ah12, and Cluster-3-Ah20) harbor more than half of the major QTLs (30/45, 66.6%) for various heat tolerant traits, explaining 10.4%-38.6%, 10.6%-44.6%, and 10.1%-49.5% of phenotypic variance, respectively. Furthermore, important candidate genes encoding DHHC-type zinc finger family protein (arahy.J0Y6Y5), peptide transporter 1 (arahy.8ZMT0C), pentatricopeptide repeat-containing protein (arahy.4A4JE9), Ulp1 protease family (arahy.X568GS), Kelch repeat F-box protein (arahy.I7X4PC), FRIGIDA-like protein (arahy.0C3V8Z), and post-illumination chlorophyll fluorescence increase (arahy.92ZGJC) were the underlying three QTL clusters. The putative functions of these genes suggested their involvement in seed development, regulating plant architecture, yield, genesis and growth of plants, flowering time regulation, and photosynthesis. Our results could provide a platform for further fine mapping, gene discovery, and developing markers for genomics-assisted breeding to develop heat-tolerant groundnut varieties.

Genetic diversity and population structure of the endangered Japanese sea cucumber (Apostichopus japonicus) in natural seas of northern China

Overfishing and habitat destruction have decimated wild sea cucumber (Apostichopus japonicus) stocks, causing this species to become endangered. Several conservation measures have been implemented to assist in the recovery of A. japonicus. Due to the low efficiency of conventional domestication methods and the current prevalence of bottom-sowing culture in marine ranches, it is urgent to evaluate the genetic diversity and population structure of sea cucumber geographical groups in the natural seas of northern China using genome-wide molecular markers. In this study, six sea cucumber geographical groups were collected from marine ranches in Shandong, Hebei, and Liaoning provinces. A total of 18,191 high-quality genome-wide single nucleotide polymorphisms (SNPs) were identified in 70 A. japonicus individuals using 2b-RAD technology. These SNPs were used to assess the genetic diversity and population structure of the six groups. Compared with previous studies, these six geographical groups showed much lower levels of genetic diversity both among and between groups, with all individuals clustering into one population. These findings demonstrate the necessity of continuous genetic monitoring of A. japonicus in the natural seas of northern China. Furthermore, this study serves as a valuable reference for future genome-assisted breeding and germplasm improvement in this economically critical species.

An Overview of Breeding Objectives to Improve the Economically Important Traits in Oat

The history of the modern oat may be traced to its intergeneric contamination of wheat and barley in southwest Asia, particularly in Mesopotamia and due to its use in only forage crop rather than a staple food in most of the countries it’s been neglected. There are just a few economically cultivated species of this self-pollinated crop, including A. sativa, A. nuda, and A. byzantina. After rice, wheat, maize, sorghum, and barley, oat production comes in at number six and in terms of oat production (FAO 2019). The present review was undertaken in order to address the present scenario of oats utilization and its consideration in research. The work majorly focussed in present are β glucan (due to its nutritional status) and disease resistance (majorly powdery mildew, pyrenophora leaf spot and crown rust) throughout the world but some drawbacks is that oats is usually neglected because of its limited use as forage value and also of its hexaploid nature. The different breeding methods employed till date for crop improvement are described in the chapter viz, traditional methods, diversity studies, mapping strategies, Marker aided breeding Association mapping, Genomic assisted breeding etc. Some of the qtls mapped by various researchers for different traits is also been listed in this article. Apart from these studies, the novel techniques which are still lacking in oats has much scope now to get it utilized through various improvement programmes like in other cereal crops.

Genetic resources and breeding of maize for Striga resistance: a review.

The potential yield of maize (Zea mays L.) and other major crops is curtailed by several biotic, abiotic, and socio-economic constraints. Parasitic weeds, Striga spp., are major constraints to cereal and legume crop production in sub-Saharan Africa (SSA). Yield losses reaching 100% are reported in maize under severe Striga infestation. Breeding for Striga resistance has been shown to be the most economical, feasible, and sustainable approach for resource-poor farmers and for being environmentally friendly. Knowledge of the genetic and genomic resources and components of Striga resistance is vital to guide genetic analysis and precision breeding of maize varieties with desirable product profiles under Striga infestation. This review aims to present the genetic and genomic resources, research progress, and opportunities in the genetic analysis of Striga resistance and yield components in maize for breeding. The paper outlines the vital genetic resources of maize for Striga resistance, including landraces, wild relatives, mutants, and synthetic varieties, followed by breeding technologies and genomic resources. Integrating conventional breeding, mutation breeding, and genomic-assisted breeding [i.e., marker-assisted selection, quantitative trait loci (QTL) analysis, next-generation sequencing, and genome editing] will enhance genetic gains in Striga resistance breeding programs. This review may guide new variety designs for Striga-resistance and desirable product profiles in maize.

Exploring genetic diversity and population structure of a large grapevine (Vitis vinifera L.) germplasm collection in Türkiye.

Grapevine (Vitis Vinifera L.) has been one of the significant perennial crops in widespread temperate climate regions since its domestication around 6000 years ago. Grapevine and its products, particularly wine, table grapes, and raisins, have significant economic importance not only in grapevine-growing countries but also worldwide. Grapevine cultivation in Türkiye dates back to ancient times, and Anatolia is considered one of the main grapevine migration routes around the Mediterranean basin. Turkish germplasm collection, conserved at the Turkish Viticulture Research Institutes, includes cultivars and wild relatives mainly collected in Türkiye, breeding lines, rootstock varieties, and mutants, but also cultivars of international origin. Genotyping with high-throughput markers enables the investigation of genetic diversity, population structure, and linkage disequilibrium, which are crucial for applying genomic-assisted breeding. Here, we present the results of a high-throughput genotyping-by-sequencing (GBS) study of 341 genotypes from grapevine germplasm collection at Manisa Viticulture Research Institute. A total of 272,962 high-quality single nucleotide polymorphisms (SNP) markers on the nineteen chromosomes were identified using genotyping-by-sequencing (GBS) technology. The high-density coverage of SNPs resulted in an average of 14,366 markers per chromosome, an average polymorphism information content (PIC) value of 0.23 and an expected heterozygosity (He) value of 0.28 indicating the genetic diversity within 341 genotypes. LD decayed very fast when r2 was between 0.45 and 0.2 and became flat when r2 was 0.05. The average LD decay for the entire genome was 30 kb when r2=0.2. The PCA and structure analysis did not distinguish the grapevine genotypes based on different origins, highlighting the occurrence of gene flow and a high amount of admixture. Analysis of molecular variance (AMOVA) results indicated a high level of genetic differentiation within populations, while variation among populations was extremely low. This study provides comprehensive information on the genetic diversity and population structure of Turkish grapevine genotypes.

Major viral diseases in grain legumes: designing disease resistant legumes from plant breeding and OMICS integration.

Grain legumes play a crucial role in human nutrition and as a staple crop for low-income farmers in developing and underdeveloped nations, contributing to overall food security and agroecosystem services. Viral diseases are major biotic stresses that severely challenge global grain legume production. In this review, we discuss how exploring naturally resistant grain legume genotypes within germplasm, landraces, and crop wild relatives could be used as promising, economically viable, and eco-environmentally friendly solution to reduce yield losses. Studies based on Mendelian and classical genetics have enhanced our understanding of key genetic determinants that govern resistance to various viral diseases in grain legumes. Recent advances in molecular marker technology and genomic resources have enabled us to identify genomic regions controlling viral disease resistance in various grain legumes using techniques such as QTL mapping, genome-wide association studies, whole-genome resequencing, pangenome and 'omics' approaches. These comprehensive genomic resources have expedited the adoption of genomics-assisted breeding for developing virus-resistant grain legumes. Concurrently, progress in functional genomics, especially transcriptomics, has helped unravel underlying candidate gene(s) and their roles in viral disease resistance in legumes. This review also examines the progress in genetic engineering-based strategies, including RNA interference, and the potential of synthetic biology techniques, such as synthetic promoters and synthetic transcription factors, for creating viral-resistant grain legumes. It also elaborates on the prospects and limitations of cutting-edge breeding technologies and emerging biotechnological tools (e.g., genomic selection, rapid generation advances, and CRISPR/Cas9-based genome editing tool) in developing virus-disease-resistant grain legumes to ensure global food security.

Efficacy of plant breeding using genomic information.

Genomic selection (GS) proposed by Meuwissen etal. more than 20 years ago, is revolutionizing plant and animal breeding. Although GS has been widely accepted and applied to plant and animal breeding, there are many factors affecting its efficacy. We studied 14 real datasets to respond to the practical question of whether the accuracy of genomic prediction increases when considering genomic as compared with not using genomic. We found across traits, environments, datasets, and metrics, that the average gain in prediction accuracy when genomic information is considered was 26.31%, while only in terms of Pearson's correlation the gain was of 46.1%, while only in terms of normalized root mean squared error the gain was of 6.6%. If the quality of the makers and relatedness of the individuals increase, major gains in prediction accuracy can be obtained, but if these two factors decrease, a lower increase is possible. Finally, our findings reinforce genomic is vital for improving the prediction accuracy and, therefore, the realized genetic gain in genomic assisted plant breeding programs.

Genomics‐assisted breeding: The next‐generation wheat breeding era

AbstractCommon wheat provides approximately 20% of the total dietary calorie intake of human beings. Recent technological advances in whole‐genome sequencing and their application in wheat and its progenitor species provide new opportunities to uncover the genetic variation of wheat traits and to accelerate the traditional breeding (TB) strategies in the context of genomics‐assisted breeding (GAB). Integration of TB, marker‐assisted selection (MAS) and genomic selection (GS) with high‐density SNP markers is expected to accelerate the breeding process and to further enhance genetic gain. With the assistance of the next‐ or third‐generation sequencing technologies and high‐throughput phenotyping platforms, GAB can now realistically be considered in the following area: (i) genome sequencing and high‐quality assembly to uncover new variations, (ii) whole‐genome sequence‐based association studies, (iii) gene function (or functional gene) identification and (iv) integration of whole genomic breeding information, utilizing multi‐omics data and different breeding strategies. We argue that GAB is becoming the preferred strategy in pursuit of new wheat cultivars with superior traits on high yielding, high nutritional quality, climate‐resilience and so on.

Provitamin A, lysine and tryptophan enrichment in shrunken2-based sweet corn genotypes through genomics-assisted breeding for crtRB1 and opaque2 genes

Malnutrition affects large section of population worldwide. VitaminA and protein deficiencies have emerged as the major global health-issue. Traditional shrunken2 (sh2)-based sweet corn is deficient in provitaminA (proA), lysine and tryptophan. Natural variant of β-carotene hydroxylase1 (crtRB1) and opaque2 (o2) enhances proA, lysine and tryptophan in maize. So far, no sweet corn hybrid rich in these nutrients has been released elsewhere. Development of biofortified sweet corn hybrids would help in providing the balanced nutrition. We targeted three sh2-based sweet corn inbreds (SWT-19, SWT-20 and SWT-21) for introgression of mutant crtRB1 and o2 genes using molecular breeding. The gene-based 3'TE-InDel and simple sequence repeat(SSR) (umc1066) markers specific to crtRB1 and o2, respectively were utilized in foreground selection in BC1F1, BC2F1 and BC2F2. Segregation distortion was observed for crtRB1 and o2 genes in majority of populations. Background selection using 91-100 SSRs revealed recovery of recurrent parent genome (RPG) up to 96%. The introgressed progenies possessed significantly higher proA (13.56µg/g) as compared to the original versions (proA: 2.70µg/g). Further, the introgressed progenies had accumulated moderately higher level of lysine (0.336%) and tryptophan (0.082%) over original versions (lysine: 0.154% and tryptophan: 0.038%). Kernel sweetness among introgressed progenies (17.3%) was comparable to original sweet corn (17.4%). The introgressed inbreds exhibited higher resemblance with their recurrent parents for yield and morphological characters. These newly developed biofortified sweet corn genotypes hold immense promise to alleviate malnutrition.

Advances in Genomics: Crops Adapting to Climate Change

In a world where food consumption is rising, climate change poses a severe danger to feeding a growing population. Previously, increased agricultural output was achieved by using fertilizer and insecticides for improved weed and pest control. However, these techniques rely on exhaustible resources and are frequently unstable. Current developments in advanced genetics are paving the door for long-term agricultural intensification and greater global warming crop adaptability. The amount of quality genomic information accessible has been rapidly increasing as a result of the widespread usage of genome sequencing technology. The increasing availability of genomic data has facilitated the shift to plant pan-genomics, allowing researchers to easily know the diversity and available traits for crop improvement and cultivar development. These advancements enhance genomic-assisted breeding, which allows for the quick engagement of candidate genes in climatic conditions and agricultural characteristics, enabling the development of resilient crops.

Chromosome-Scale Genome Assembly and Triterpenoid Saponin Biosynthesis in Korean Bellflower (Platycodon grandiflorum)

Platycodon grandiflorum belongs to the Campanulaceae family and is an important medicinal and food plant in East Asia. However, on the whole, the genome evolution of P. grandiflorum and the molecular basis of its major biochemical pathways are poorly understood. We reported a chromosome-scale genome assembly of P. grandiflorum based on a hybrid method using Oxford Nanopore Technologies, Illumina sequences, and high-throughput chromosome conformation capture (Hi-C) analysis. The assembled genome was finalized as 574 Mb, containing 41,355 protein-coding genes, and the genome completeness was assessed as 97.6% using a Benchmarking Universal Single-Copy Orthologs analysis. The P. grandiflorum genome comprises nine pseudo-chromosomes with 56.9% repeat sequences, and the transcriptome analysis revealed an expansion of the 14 beta-amylin genes related to triterpenoid saponin biosynthesis. Our findings provide an understanding of P. grandiflorum genome evolution and enable genomic-assisted breeding for the mass production of important components such as triterpenoid saponins.