Functional genomics in sugarcane breeding: key challenges and strategies

Next-generation molecular tools with AI integration can accelerate genetic gain in sugarcane by enhancing variation, accuracy, and efficiency, enabling rapid development of high-yielding, high-quality, and climate-resilient varieties. Enhancing genetic gain is essential for sustainable sugar and bioenergy production, especially amid growing global reliance on renewable energy sources. Sugarcane and its byproducts serve as important feedstocks for both first and second-generation biofuels, and face several breeding challenges due to its genetic complexity, extended breeding cycles, and strong environmental interactions. The breeder's equation offers a quantitative framework to accelerate genetic improvement by optimizing four key components: additive genetic variation (σa), heritability (h2), selection intensity (i), and breeding cycle length (L). Additive genetic variation can be enhanced through genome-wide exploration, including genome, pan-genome, and super pangenome analyses, gene discovery, characterization, and the induction of novel variations. Precise estimation of heritability in sugarcane can be achieved through the large-scale characterization of germplasm, high-throughput phenotyping, and detailed genotype × environment interaction (G × E) studies. Selection intensity can be increased by expanding population sizes via genotypic, genomic, and invitro selection, leveraging the law of large numbers, and adopting technologies that provide greater throughput, precision, and cost efficiency. Breeding cycle time can be significantly reduced using tools, such as marker-assisted selection, genomic selection, emerging doubled haploid strategies (though still challenging in polyploid crops like sugarcane), speed breeding, transgenic approaches, and genome editing technologies like CRISPR/Cas9 (including base and prime editing), TALENs. This review provides a comprehensive overview of each component of the breeder's equation in sugarcane breeding and highlights next-generation molecular strategies and tools aligned to these components. The integration of these advanced tools with artificial intelligence holds immense potential to enhance genetic gain and accelerate the development of high-yielding, high-quality, and climate-resilient sugarcane varieties.

Recent advances in genomic technologies have enabled the identification of thousands of genetic variations that are associated with hundreds of complex human diseases or traits in genome-wide association studies (GWAS). The large number of genetic loci uncovered for each disease or trait along with the difficulty in pinpointing the underlying genes and mechanisms further testify to the complexity of human pathophysiology. To alleviate the challenges of GWAS, systems biology approaches have been utilized to map the molecular mechanisms underlying complex human diseases/traits via the integration of genetic variation, functional genomics (such as genetics of gene expression), pathways, and molecular networks. Similar approaches have been applied to a spectrum of drug metabolizing enzymes to discover novel functional genetic variations that affect the expression or activities of these enzymes as well as to define the regulatory pathways/networks of genes involved in drug metabolism and toxicology in key human tissues. We envision that the increased coverage of functional genetic polymorphisms, the availability of drug metabolism-centered gene networks, and the maturing methodologies previously developed for understanding complex human diseases can be applied to pharmacogenomic and toxicogenomic studies to further our understanding of inter-individual variability in drug efficacy and toxicity and eventually help direct personalized medicine.

In recent years, major advances have been made in transcriptomics, metabolomics, proteomics, and particularly population genetics. More than 850 genome-wide association studies (GWAS) were published by the end of 2010, now covering a vast number of diseases and phenotypes and often incorporating tens of thousands of subjects or, in some cases, more than 100 000 subjects, increasing statistical power to identify and replicate contributing loci. Sequencing throughput advances and decreasing costs per sample have allowed the application of genome-wide genotyping and sequencing technology to larger DNA samples as well as transcriptome and epigenome features. This year was marked not only by continuing progress with GWAS, sequencing, and copy number variation studies but also by follow-up of GWAS and other findings with functional studies that uncover new molecular pathways contributing to disease and pave the way for future clinical applications. The American Heart Association Functional Genomics and Translational Biology Interdisciplinary Council (http://www.americanheart.org/presenter.jhtml?identifier=3016539) provides a forum for a multidisciplinary group of volunteers committed to making a substantial contribution to reduce the burden of heart disease and stroke through genetics, genomics, proteomics, and metabolomics research and translational science. With input from the Early Career Committee of the Council on Functional Genomics and Translational Biology, we considered many papers and selected 10 outstanding manuscript groups (15 articles) published in 2010 that reflect these advances, and we briefly summarize each below in chronological order.

Conventional pre-genomics breeding methodologies have significantly improved crop yields since the mid-twentieth century. Genomics provides breeders with advanced tools for whole-genome study, enabling a direct genotype–phenotype analysis. This shift has led to precise and efficient crop development through genomics-based approaches, including molecular markers, genomic selection, and genome editing. Molecular markers, such as SNPs, are crucial for identifying genomic regions linked to important traits, enhancing breeding accuracy and efficiency. Genomic resources viz. genetic markers, reference genomes, sequence and protein databases, transcriptomes, and gene expression profiles, are vital in plant breeding and aid in the identification of key traits, understanding genetic diversity, assist in genomic mapping, support marker-assisted selection and speeding up breeding programs. Advanced techniques like CRISPR/Cas9 allow precise gene modification, accelerating breeding processes. Key techniques like Genome-Wide Association study (GWAS), Marker-Assisted Selection (MAS), and Genomic Selection (GS) enable precise trait selection and prediction of breeding outcomes, improving crop yield, disease resistance, and stress tolerance. These tools are handy for complex traits influenced by multiple genes and environmental factors. This paper explores new genomic technologies like molecular markers, genomic selection, and genome editing for plant breeding showcasing their impact on developing new plant varieties.

SummaryMarker assisted breeding (MAB) supports breeding by identifying individuals or molecular markers associated with important traits. MAB methods include genome-wide association studies (GWAS) and genomic selection (GS). Local haplotypes are regions of DNA that are inherited together due to high levels of linkage disequilibrium. Local haplotypes can improve the prediction accuracy and power of GS and GWAS. Currently available local haplotyping tools improve GWAS power through fine-mapping of candidate regions or through haplotype-based GWAS. However, no local haplotyping tools utilize the benefits of haplotypes for GS. Here we present HaploVar, a local haplotyping tool designed to improve both GWAS and GS pipelines by identifying local haplotypes and formatting the output to be compatible with all major GWAS and GS tools. HaploVar can be used in any haplotype-based MAB study.Availability and implementationHaploVar can be downloaded from CRAN with R >4.0.0 (DOI: 10.32614/CRAN.package.HaploVar). HaploVar and a tutorial vignette is available on GitHub (https://github.com/TessaMacNish/HaploVar). HaploVar is available under an MIT license.

The approximately 20-year breeding cycle has severely restricted the progress of genetic improvement in poplar. Genomic selection (GS) breeding has been demonstrated as an effective approach to accelerate this process. However, its application in forest tree species remains at an early stage. To advance the genetic improvement of target traits in Populus deltoides, the primary species of poplar plantations in China, we systematically implemented GS breeding using 765 hybrid progenies from 32 multi-generational full-sib families. Firstly, we assembled a high-quality genome of one core parent P. deltoides 'Danhong', with a genome size of 419.4Mb and scaffold N50 of 22.0Mb, which is also the first telomere-to-telomere (T2T) level genome of P. deltoides. Through comparative genomic analysis, we identified 1395 specific structural variants closely associated with growth and development. Subsequently, through genome-wide association studies (GWAS), we identified 135 quantitative trait nucleotides (QTNs) associated with growth and wood quality traits. By systematically evaluating reference genomes, statistical models, and various marker selection strategies, we developed optimal genomic prediction (GP) models for six traits, with the highest prediction accuracy (PA) reaching 0.730 for DBH. Compared with using all markers, the PA was improved by an average of 136.34%. Furthermore, by integrating GP, GWAS, and RNA-seq results, we identified core breeding parents and elite clones for P. deltoides genetic improvement and discovered important candidate genes. Our results provide a promising strategy for accelerating breeding cycles and genetic improvement, offering valuable breeding and genetic resources for forest tree improvement.

Seeds are a major source of protein in human and livestock diets. Cereal grains are some of the most consumed seeds by both humans and livestock worldwide, with maize, wheat, and rice alone accounting for ~70 percent of the total cereal production. Maize is one of the major staple crops used for food, feed, and fuel. A mature maize kernel contains small embryo (10 percent of the volume) and a large endosperm (~90 percent of its volume). In terms of composition, majority of the kernel proportion contains around 90 percent of starch and around 8-10 percent of protein. Nine of the twenty amino acids cannot be synthesized by monogastric animals, including humans, and must be obtained through the diet and are considered essential amino acids (EAA): lysine, isoleucine, leucine, histidine, methionine, phenylalanine, threonine, tryptophan, and valine. The protein quality is poor in maize endosperm as the primary storage proteins are severely deficient in EAA such as lysine, tryptophan, and methionine. Such deficiencies can be detrimental since corn provides an important source of proteins for food in developing countries and for feed in developed countries such as the U.S. Failure to consume sufficient levels of EAA per day leads to severe malnutrition, even if one's calories requirements are met. Many attempts to increase the EAA has demonstrated only limited success since seed can rebalance their amino acids composition even when major changes are introduced in their proteome. One possible approach to solve this applied problem is by seed EAA biofortification; however, many attempts at this task fall short and strongly indicates that even though we know most of the metabolic pathways of amino acids, we know very little about their regulation especially in seed. Therefore, the first step towards efficient amino acid biofortification is to increase our fundamental understanding of their function, as well as the metabolic regulation and the biology of the plant seeds. Despite the tight regulation within any given genotype seed amino acid composition display extensive natural variation which can be utilized to uncover the genetic basis and identify new targets for seed amino acids biofortification. Hence to uncover the genetic architecture of amino acids composition in maize kernels we used Goodman-Buckler maize association panel that consists of 282 diverse maize inbred lines including stiff stalk, non-stiff stalk, tropical and subtropical, sweetcorn and popcorn lines. I performed genome wide association study (GWAS) on both the protein bound amino acids (PBAA) and free amino acids (FAA). Although, GWAS is widely used to dissect the genetic architecture of complex traits, oftentimes the GWAS outputs the extensive list of genes particularly when using multiple phenotypic traits. To overcome this, I used an integrative multi-omics approach that combines GWAS and co-expression networks modules obtained from ten seed filling stages of B73 to uncover novel key regulatory genes, characterize biological process and prioritized the candidate genes that involved in shaping the natural variation of amino acid composition. Chapter one of the dissertation is the general introduction and literature review on the seed amino acids. It briefly discuss the general introduction of PBAA and FAA, previous attempts done to improve seed PBAA and FAA composition, natural variation used to uncover the genetic architecture of complex traits including metabolic traits such as amino acids and finally discuss the multi-omics integration to uncover the genetic basis of complex traits. Chapter two elaborates the comprehensive genetic basis of PBAA in maize kernels using integrative analysis of 76 PBAA GWAS with protein co-expression network modules. Previous studies have shown that manipulation of storage proteins and amino acid pathway genes have contributed in the improvement of quality protein maize however, my study strongly suggests that in addition to the manipulation of storage protein and amino acid metabolic genes, specific ribosomal genes along with other translation machinery could be the novel target for seed amino acids biofortification. Chapter three discusses the genetic basis of FAA in maize kernels using integrative analysis of 109 FAA GWAS with protein co-expression network modules. I have presented here the comprehensive list of SNPs as well as the candidate genes and several biological processes including the translational machinery responsible for shaping the genetic architecture of FAA in seed. Chapter four includes the conclusion and future works. Maize is an important crop used for both food and feed and possesses great genotypic and phenotypic diversity. The results from my study has validated several previous characterized genes and identified novel key genes that regulate and shape the PBAA and FAA in maize kernels, which could be used further to target for amino acid biofortification.

Brassica juncea is a crucial oilseed crop, and its seeds possess high economic value as they are a source of edible oil. In order to understand the role of long non coding RNAs (lncRNAs) in the regulation of seed development, we carried out computational analysis using transcriptome data of developing seeds of two contrasting genotypes of B. juncea, Pusajaikisan (PJK) and Early Heera 2 (EH2). The seeds were sampled at three stages, 15, 30, and 45 days after pollination. We identified 1,539 lncRNAs, of which 809 were differentially expressed. We also carried out extensive characterization and functional analysis of seed lncRNAome. The expression patterns were analysed using k-means clustering, and the targets were analysed using pathway, transcription factor, and GO enrichment, as well as ortholog information. We shortlisted a total of 25 robust lncRNA candidates for seed size, oil content, and seed coat color. We also identified 4 lncRNAs as putative precursors of miRNAs regulating seed development. Moreover, a total of 28 miRNA-lncRNA-mRNA regulatory networks regulating seed traits were identified. We also developed a comprehensive database, (BrassIca juncea database or "BIJ" ( https://bij.cuh.ac.in/ ), which provides seed omics as well as other functional genomics and genetics data in an easily accessible form. These candidate lncRNAs are suitable for including in crop improvement programs through molecular breeding, as well as for future validations through genome editing. Together, the knowledge of these candidate lncRNAs and availability of BIJ database shall leverage the crop improvement efforts in B. juncea.

Bombyx mori, the domesticated silkworm, is one of the most economically significant and scientifically tractable insects. Since the publication of its draft genome sequence in 2004 and the subsequent production of a refined, consortium-level assembly in 2008, silkworm genomics has undergone a transformative evolution encompassing whole-genome resequencing, functional genomics, epigenomics, small RNA biology, and comparative and population genomics. These advances have not only illuminated the molecular mechanisms underlying silk production, development, immunity, and domestication, but have also catalysed a wide range of applications spanning biotechnology and biomedicine. This review synthesises current knowledge on silkworm genomics, tracing the progression from early sequencing initiatives to state-of-the-art genome editing strategies including the CRISPR/Cas9 system. A systematic literature search was conducted to identify peer-reviewed publications relevant to silkworm genomics and its applications. The primary databases consulted were Web of Science, Scopus, PubMed, and Google Scholar. The primary date range for inclusion was 2006 to 2026, with an exception for foundational studies published before 2006, which were included when they represented seminal contributions to the field. Special attention is given to the genomic architecture of silk protein genes, the regulatory roles of non-coding RNAs, epigenetic landscapes, and comparative genomics with related Lepidoptera. The biotechnological utility of the silkworm is explored in the context of silk-based biomaterials for tissue engineering, silk as a drug delivery scaffold, the production of chimeric spider silk fibres in transgenic silkworms, and the silkworm as an in vivo model for infectious disease research. The review further addresses the improvement of sericulture through molecular breeding, marker-assisted selection, and precision genome editing, as well as the genomic basis of innate immunity and disease resistance. Future directions in multi-omics integration, single-cell transcriptomics, synthetic biology, and pangenomics are discussed. Together, these developments affirm the central importance of silkworm genomics at the interface of fundamental biology and applied innovation.

The ever-increasing food requirement with globally growing population demands advanced agricultural practices to improve grain yield, to gain crop resilience under unpredictable extreme weather, and to reduce production loss caused by insects and pathogens. To fulfill such requests, genome engineering technology has been applied to various plant species. To date, several generations of genome engineering methods have been developed. Among these methods, the new mainstream technology is clustered regularly interspaced short palindromic repeats (CRISPR) with nucleases. One of the most important processes in genome engineering is to deliver gene cassettes into plant cells. Conventionally used systems have several shortcomings, such as being labor- and time-consuming procedures, potential tissue damage, and low transformation efficiency. Taking advantage of nanotechnology, the nanoparticle-mediated gene delivery method presents technical superiority over conventional approaches due to its high efficiency and adaptability in different plant species. In this review, we summarize the evolution of plant biomolecular delivery methods and discussed their characteristics as well as limitations. We focused on the cutting-edge nanotechnology-based delivery system, and reviewed different types of nanoparticles, preparation of nanomaterials, mechanism of nanoparticle transport, and advanced application in plant genome engineering. On the basis of established methods, we concluded that the combination of genome editing, nanoparticle-mediated gene transformation and de novo regeneration technologies can accelerate crop improvement efficiently in the future.

The European Commission's Farm to Fork (F2F) strategy, under the European Green Deal, acknowledges that innovative techniques, including biotechnology, may play a role in increasing sustainability. At the same time, organic farming will be promoted, and at least 25% of the EU's agricultural land shall be under organic farming by 2030. How can both biotechnology and organic farming be developed and promoted simultaneously to contribute to achieving the Sustainable Development Goals (SDGs)? We illustrate that achieving the SDGs benefits from the inclusion of recent innovations in biotechnology in organic farming. This requires a change in the law. Otherwise, the planned increase of organic production in the F2F strategy may result in less sustainable, not more sustainable, food systems.

Sugarcane is probably the crop produced in the greatest quantities globally. More than 1,000 million tons of sugarcane are harvested each year. This exceeds the level of production of the major grain food crops, wheat, rice and maize, each of which has production of around 600 million tons per annum. Sugarcane is the source of most of the sugar produced in the world greatly exceeding sugar beet as a source of sugar (Cordeiro et al. 2007).

Precision genome editing, particularly using Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated protein 9 (Cas9), is advancing crop improvement by enabling targeted and efficient genetic modifications. Root and tuber crops such as potato, cassava, sweet potato, and yam are vital for global food and nutritional security but remain highly vulnerable to climate change, pests, diseases, and limited genetic diversity. Genome editing technologies facilitate the development of improved traits, including enhanced disease resistance, tolerance to abiotic stress, improved nutritional quality, and extended shelf life. This review synthesizes recent advances in genome editing for root and tuber crops across global production systems, including illustrative examples from Sub-Saharan Africa, where active genome editing initiatives are being implemented. It further examines key technical constraints, such as low efficiency of plant transformation and regeneration, and highlights regulatory challenges arising from differing policy frameworks across countries. Emerging solutions are discussed, including genotype-independent editing strategies and DNA-free approaches that avoid the integration of foreign genetic material. Addressing these challenges will be critical for developing resilient and sustainable food systems. Unlike previous reviews, this study integrates mechanistic insights with cross-crop synthesis and proposes next-generation genome editing strategies for engineering complex traits in polyploid root and tuber crops.

Improving fruit quality is an important but challenging breeding goal in winter squash. Squash breeding in general is resource-intensive, especially in terms of space, and the biology of squash makes it difficult to practice selection on both parents. These restrictions translate to smaller breeding populations and limited use of greenhouse generations, which in turn, limit genetic gain per breeding cycle and increases cycle length. Genomic selection is a promising technology for improving breeding efficiency; yet, few studies have explored its use in horticultural crops. We present results demonstrating the predictive ability of whole-genome models for fruit quality traits. Predictive abilities for quality traits were low to moderate, but sufficient for implementation. To test the use of genomic selection for improving fruit quality, we conducted three rounds of genomic recurrent selection in a butternut squash (Cucurbita moschata) population. Selections were based on a fruit quality index derived from a multi-trait genomic selection model. Remnant seed from selected populations was used to assess realized gain from selection. Analysis revealed significant improvement in fruit quality index value and changes in correlated traits. This study is one of the first empirical studies to evaluate gain from a multi-trait genomic selection model in a resource-limited horticultural crop.

Horticultural crops-including fruits, vegetables, ornamentals, spices, and plantation crops-are essential to global food security, human nutrition, and agricultural economies. However, their genetic improvement has long been constrained by biological complexities such as polyploidy, extended juvenile phases, vegetative propagation, and narrow elite germplasm pools. This review synthesizes breeding strategies across major horticultural crops, tracing the progression from classical phenotypic selection to molecular marker-assisted approaches and advanced genome editing technologies. Conventional breeding established the genetic foundation for crop improvement through hybridization, backcrossing, mutation breeding, and heterosis exploitation. The integration of molecular markers (RFLPs, SSRs, SNPs) with marker-assisted selection (MAS), quantitative trait locus (QTL) mapping, genome-wide association studies (GWAS), and genomic selection (GS) significantly enhanced breeding precision and efficiency. Advances in whole-genome sequencing, transcriptomics, metabolomics, and pan-genomics have further strengthened genomic resources for trait discovery and predictive breeding. More recently, CRISPR/Cas9 systems, including base editing and prime editing, have enabled precise targeted trait modification, demonstrated in applications such as extended shelf-life tomato, waxy-starch potato, Fusarium-resistant banana, and canker-resistant citrus. Despite these advances, challenges remain, including regulatory heterogeneity, transformation recalcitrance in elite genotypes, polyploid genome complexity, and public acceptance concerns. This review highlights critical research gaps and proposes an integrated breeding framework that combines classical genetics, genomic prediction, and precision genome editing to accelerate the development of climate-resilient, nutritionally enhanced, and commercially competitive horticultural crops.