Quantitative metabolome and transcriptome analysis reveals complex regulatory pathway underlying photoinduced fiber color formation in cotton

Leveraging transcriptomics-based approaches to enhance genomic prediction: integrating SNPs and gene networks for cotton fibre quality improvement

Cultivated cotton plants are the world's largest source of natural fibre, where yield and quality are key traits for this renewable and biodegradable commodity. The Gossypium hirsutum cotton genome contains ~80K protein-coding genes, making precision breeding of complex traits a challenge. This study tested approaches to improving the genomic prediction (GP) accuracy of valuable cotton fibre traits to help accelerate precision breeding. With a biology-informed basis, a novel approach was tested for improving GP for key cotton fibre traits with transcriptomics of key time points during fibre development, namely, fibre cells undergoing primary, transition, and secondary wall development. Three test approaches included weighting of SNPs in DE genes overall, in target DE gene lists informed by gene annotation, and in a novel approach of gene co-expression network (GCN) clusters created with partial correlation and information theory (PCIT) as the prior information in GP models. The GCN clusters were nucleated with known genes for fibre biomechanics, i.e., fasciclin-like arabinogalactan proteins, and cluster size effects were evaluated. The most promising improvements in GP accuracy were achieved by using GCN clusters for cotton fibre elongation by 4.6%, and strength by 4.7%, where cluster sizes of two and three neighbours proved most effective. Furthermore, the improvements in GP were due to only a small number of SNPs, in the order of 30 per trait using the GCN cluster approach. Non-trait-specific biological time points, and genes, were found to have neutral effects, or even reduced GP accuracy for certain traits. As the GCN clusters were generated based on known genes for fibre biomechanics, additional candidate genes were identified for fibre elongation and strength. These results demonstrate that GCN clusters make a specific and unique contribution in improving the GP of cotton fibre traits. The findings also indicate that there is room for incorporating biology-based GCNs into GP models of genomic selection pipelines for cotton breeding to help improve precision breeding of target traits. The PCIT-GCN cluster approach may also hold potential application in other crops and trees for enhancing breeding of complex traits.

Opportunities and challenges in the application of single-cell and spatial transcriptomics in plants

Single-cell and spatial transcriptomics have diverted researchers' attention from the multicellular level to the single-cell level and spatial information. Single-cell transcriptomes provide insights into the transcriptome at the single-cell level, whereas spatial transcriptomes help preserve spatial information. Although these two omics technologies are helpful and mature, further research is needed to ensure their widespread applicability in plant studies. Reviewing recent research on plant single-cell or spatial transcriptomics, we compared the different experimental methods used in various plants. The limitations and challenges are clear for both single-cell and spatial transcriptomic analyses, such as the lack of applicability, spatial information, or high resolution. Subsequently, we put forth further applications, such as cross-species analysis of roots at the single-cell level and the idea that single-cell transcriptome analysis needs to be combined with other omics analyses to achieve superiority over individual omics analyses. Overall, the results of this review suggest that combining single-cell transcriptomics, spatial transcriptomics, and spatial element distribution can provide a promising research direction, particularly for plant research.

Deciphering the complex cotton genome for improving fiber traits and abiotic stress resilience in sustainable agriculture

BACKGROUND

Understanding the complex cotton genome is of paramount importance in devising a strategy for sustainable agriculture. Cotton is probably the most economically important cash crop known for its cellulose-rich fiber content. The cotton genome has become an ideal model for deciphering polyploidization due to its polyploidy, setting it apart from other major crops. However, the main challenge in understanding the functional and regulatory functions of many genes in cotton is still the complex cotton polyploidy genome, which is not limited to a single role. Cotton production is vulnerable to the sensitive effects of climate change, which can alter or aggravate soil, pests, and diseases. Thus, conventional plant breeding coupled with advanced technologies has led to substantial progress being made in cotton production.

GENOMICS APPROACHES IN COTTON

In the frontier areas of genomics research, cotton genomics has gained momentum accomplished by robust high-throughput sequencing platforms combined with novel computational tools to make the cotton genome more tractable. Advances in long-read sequencing have allowed for the generation of the complete set of cotton gene transcripts giving incisive scientific knowledge in cotton improvement. In contrast, the integration of the latest sequencing platforms has been used to generate multiple high-quality reference genomes in diploid and tetraploid cotton. While pan-genome and 3D genomic studies are still in the early stages in cotton, it is anticipated that rapid advances in sequencing, assembly algorithms, and analysis pipelines will have a greater impact on advanced cotton research.

CONCLUSIONS

This review article briefly compiles substantial contributions in different areas of the cotton genome, which include genome sequencing, genes, and their molecular regulatory networks in fiber development and stress tolerance mechanism. This will greatly help us in understanding the robust genomic organization which in turn will help unearth candidate genes for functionally important agronomic traits.

Transcriptome and Metabolome Profiling Unveil Pigment Formation Variations in Brown Cotton Lines (Gossypium hirsutum L.)

Naturally brown colored cotton (NBCC) is becoming increasingly popular due to its natural properties of coloration. However, poor fiber quality and color fading are key issues that are hindering the cultivation of naturally colored cotton. In this study, based on transcriptome and metabolome of 18 days post-anthesis (DPA), we compared the variations of pigment formation in two brown cotton fibers (DCF and LCF), with white cotton fiber (WCF) belonging to a near-isogenic line. A transcriptome study revealed a total of 15,785 differentially expressed genes significantly enriched in the flavonoid biosynthesis pathway. Furthermore, for flavonoid biosynthesis-related genes, such as flavonoid 3′5′-hydroxylase (F3′5′H), anthocyanidin synthase (ANS), anthocyanidin reductase (ANR), chalcone synthase (CHS), dihydroflavonol 4-reductase (DFR), and chalcone isomerase (CHI), their expressions significantly increased in LCF compared with DCF and WCF. Moreover, transcription factors MYB and bHLH were significantly expressed in LCF and DCF. Most flavonoid-related metabolites (myricetin naringenin, catechin, epicatechin-epiafzelechin, and epigallocatechin) were found to be more highly up-regulated in LCF and DCF than WCF. These findings reveal the regulatory mechanism controlling different brown pigmentation in cotton fibers and elucidate the need for the proper selection of high-quality brown cotton fiber breeding lines for promising fiber quality and durable brown color pigmentation.

Integrated transcriptomic and metabolomic analyses reveal key genes controlling flavonoid biosynthesis in Citrus grandis 'Tomentosa' fruits

As a well-recognized traditional Chinese medicine (TCM), immature fruits of Citrus grandis 'Tomentosa' (CGT) serve to cure chronic cough in humans. Specialized metabolites including flavonoids may have contribute to this curing effect. Knowledge about the molecular mechanisms underlying flavonoid biosynthesis in 'Tomentosa' fruits will, therefore, support the breeding of varieties with improved medicinal properties. Hence, we profiled the transcriptomes and metabolites of the fruits of two contrasting C. grandis varieties, namely 'Zheng-Mao' ('ZM') used in TCM production, and a locally cultivated pomelo, namely 'Guang-Qing' ('GQ'), at four developmental stages. A total of 39 flavonoids, including 14 flavanone/flavone, 5 isoflavonoids, 12 flavonols, and 6 anthocyanins, were identified, and 16 of which were quantitatively determined in the fruits of the two varieties. We found that 'ZM' fruits contain more flavonoids than 'GQ'. Specifically, rhoifolin levels were significantly higher in 'ZM' than in 'GQ'. We annotated 31,510 genes, including 1,387 previously unknown ones, via transcriptome sequencing of 'ZM' and 'GQ.' A total of 646 genes were found to be differentially expressed between 'ZM' and 'GQ' throughout at all four fruit developmental stages, indicating that they are robust expression markers for future breeding programs. Weighted gene co-expression network analysis identified 18 modules. Combined transcriptional and metabolic analysis revealed 25 genes related to flavonoid biosynthesis and 16 transcriptional regulators (MYBs, bHLHs, WD40) that may be involved in the flavonoids biosynthesis in C. grandis 'Tomentosa' fruits.

CottonMD: a multi-omics database for cotton biological study

Cotton is an important economic crop, and many loci for important traits have been identified, but it remains challenging and time-consuming to identify candidate or causal genes/variants and clarify their roles in phenotype formation and regulation. Here, we first collected and integrated the multi-omics datasets including 25 genomes, transcriptomes in 76 tissue samples, epigenome data of five species and metabolome data of 768 metabolites from four tissues, and genetic variation, trait and transcriptome datasets from 4180 cotton accessions. Then, a cotton multi-omics database (CottonMD, http://yanglab.hzau.edu.cn/CottonMD/) was constructed. In CottonMD, multiple statistical methods were applied to identify the associations between variations and phenotypes, and many easy-to-use analysis tools were provided to help researchers quickly acquire the related omics information and perform multi-omics data analysis. Two case studies demonstrated the power of CottonMD for identifying and analyzing the candidate genes, as well as the great potential of integrating multi-omics data for cotton genetic breeding and functional genomics research.

Function deficiency of GhOMT1 causes anthocyanidins over-accumulation and diversifies fibre colours in cotton (Gossypium hirsutum)

Naturally coloured cotton (NCC) fibres need little or no dyeing process in textile industry to low-carbon emission and are environment-friendly. Proanthocyanidins (PAs) and their derivatives were considered as the main components causing fibre coloration and made NCCs very popular and healthy, but the monotonous fibre colours greatly limit the wide application of NCCs. Here a G. hirsutum empurpled mutant (HS2) caused by T-DNA insertion is found to enhance the anthocyanidins biosynthesis and accumulate anthocyanidins in the whole plant. HPLC and LC/MS-ESI analysis confirmed the anthocyanidins methylation and peonidin, petunidin and malvidin formation are blocked. The deficiency of GhOMT1 in HS2 was associated with the activation of the anthocyanidin biosynthesis and the altered components of anthocyanidins. The transcripts of key genes in anthocyanidin biosynthesis pathway are significantly up-regulated in HS2, while transcripts of the genes for transport and decoration were at similar levels as in WT. To investigate the potential mechanism of GhOMT1 deficiency in cotton fibre coloration, HS2 mutant was crossed with NCCs. Surprisingly, offsprings of HS2 and NCCs enhanced PAs biosynthesis and increased PAs levels in their fibres from the accumulated anthocyanidins through up-regulated GhANR and GhLAR. As expected, multiple novel lines with improved fibre colours including orange red and navy blue were produced in their generations. Based on this work, a new strategy for breeding diversified NCCs was brought out by promoting PA biosynthesis. This work will help shed light on mechanisms of PA biosynthesis and bring out potential molecular breeding strategy to increase PA levels in NCCs.

Advances in Plant Metabolomics and Its Applications in Stress and Single-Cell Biology

In the past two decades, the post-genomic era envisaged high-throughput technologies, resulting in more species with available genome sequences. In-depth multi-omics approaches have evolved to integrate cellular processes at various levels into a systems biology knowledge base. Metabolomics plays a crucial role in molecular networking to bridge the gaps between genotypes and phenotypes. However, the greater complexity of metabolites with diverse chemical and physical properties has limited the advances in plant metabolomics. For several years, applications of liquid/gas chromatography (LC/GC)-mass spectrometry (MS) and nuclear magnetic resonance (NMR) have been constantly developed. Recently, ion mobility spectrometry (IMS)-MS has shown utility in resolving isomeric and isobaric metabolites. Both MS and NMR combined metabolomics significantly increased the identification and quantification of metabolites in an untargeted and targeted manner. Thus, hyphenated metabolomics tools will narrow the gap between the number of metabolite features and the identified metabolites. Metabolites change in response to environmental conditions, including biotic and abiotic stress factors. The spatial distribution of metabolites across different organs, tissues, cells and cellular compartments is a trending research area in metabolomics. Herein, we review recent technological advancements in metabolomics and their applications in understanding plant stress biology and different levels of spatial organization. In addition, we discuss the opportunities and challenges in multiple stress interactions, multi-omics, and single-cell metabolomics.

Metabolite Profiling and Classification of Highbush Blueberry Leaves under Different Shade Treatments

Blueberry belongs to the genus Vaccinium L. in the Ericaceae and is an economically important shrub that produces small berries that are rich in nutrients. There were differences in the appearance of blueberry leaves under different shade treatments. To explore the differences in metabolites in blueberry leaves under different shading treatments, nontargeted liquid chromatography-mass spectrometry (LC-MS) metabonomic analysis was performed. Different shade intensities resulted in significant differences in the contents of metabolites. A total of 6879 known metabolites were detected, including 750 significantly differentially expressed metabolites, including mainly lipids and lipid-like molecules and phenylpropanoid and polyketide superclass members. Based on a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, the flavone and flavonol biosynthesis pathways were the most significantly enriched. The results of this study provide a reference and scientific basis for the establishment of a high-quality and high-yield shaded blueberry cultivation system.

Breeding Next-Generation Naturally Colored Cotton

Use of naturally colored cotton (NCC) in the textile industry is limited due to its inferior fiber quality. Recent advances in understanding pigmentation in NCC fiber and the genetic relationship between pigmentation and fiber development may overcome this hindrance and can guide developing high fiber quality and yield NCC.

Molecular cloning and characterization of GhERF105, a gene contributing to the regulation of gland formation in upland cotton (Gossypium hirsutum L.)

BACKGROUND

Gossypium hirsutum L. (cotton) is one of the most economically important crops in the world due to its significant source of fiber, feed, foodstuff, oil and biofuel products. However, the utilization of cottonseed was limited due to the presence of small and darkly pigmented glands that contain large amounts of gossypol, which is toxic to human beings and non-ruminant animals. To date, some progress has been made in the pigment gland formation, but the underlying molecular mechanism of its formation was still unclear.

RESULTS

In this study, we identified an AP2/ERF transcription factor named GhERF105 (GH_A12G2166), which was involved in the regulation of gland pigmentation by the comparative transcriptome analysis of the leaf of glanded and glandless plants. It encoded an ERF protein containing a converved AP2 domain which was localized in the nucleus with transcriptional activity, and showed the high expression in glanded cotton accessions that contained much gossypol. Virus-induced gene silencing (VIGS) against GhERF105 caused the dramatic reduction in the number of glands and significantly lowered levels of gossypol in cotton leaves. GhERF105 showed the patterns of spatiotemporal and inducible expression in the glanded plants.

CONCLUSIONS

These results suggest that GhERF105 contributes to the pigment gland formation and gossypol biosynthesis in partial organs of glanded plant. It also provides a potential molecular basis to generate 'glandless-seed' and 'glanded-plant' cotton cultivar.