Application of genomic tools in plant breeding

Identification of cysteine-rich receptor-like kinase gene family in potato: revealed StCRLK9 in response to heat, salt and drought stresses

The investigation into cysteine-rich receptor-like kinases (CRLKs) holds pivotal significance as these conserved, upstream signalling molecules intricately regulate fundamental biological processes such as plant growth, development and stress adaptation. This study undertakes a comprehensive characterisation of CRLKs in Solanum tuberosum (potato), a staple food crop of immense economic importance. Employing comparative genomics and evolutionary analyses, we identified 10 distinct CRLK genes in potato. Further categorisation into three major groups based on sequence similarity was performed. Each CRLK member in potato was systematically named according to its chromosomal position. Multiple sequence alignment and phylogenetic analyses unveiled conserved gene structures and motifs within the same groups. The genomic distribution of CRLKs was observed across Chromosomes 2-5, 8 and 12. Gene duplication analysis highlighted a noteworthy trend, with most gene pairs exhibiting a Ka/Ks ratio greater than one, indicating positive selection of StCRLKs in potato. Salt and drought stresses significantly impacted peroxidase and catalase activities in potato seedlings. The presence of diverse cis -regulatory elements, including hormone-responsive elements, underscored their involvement in myriad biotic and abiotic stress responses. Interestingly, interactions between the phytohormone auxin and CRLK proteins unveiled a potential auxin-mediated regulatory mechanism. A holistic approach combining transcriptomics and quantitative PCR validation identified StCRLK9 as a potential candidate involved in plant response to heat, salt and drought stresses. This study lays a robust foundation for future research on the functional roles of the CRLK gene family in potatoes, offering valuable insights into their diverse regulatory mechanisms and potential applications in stress management.

In Vitro Collection for the Safe Storage of Grapevine Hybrids and Identification of the Presence of Plasmopara viticola Resistance Genes

This paper focuses on the creation of an in vitro collection of grapevine hybrids from the breeding program of the Kazakh Scientific Research Institute of Fruit Growing and Viticulture and investigates the presence of Plasmopara viticola resistance mediated by Rpv3 and Rpv12 loci. We looked at the optimization of in vitro establishment using either shoots taken directly from field-grown plants or from budwood cuttings forced indoors. We further screened for the presence of endophyte contamination in the initiated explants and optimized the multiplication stage. Finally, the presence of the resistance loci against P. viticola was studied. The shoots initiated from the field-sourced explants were the more effective method of providing plant sources for in vitro initiation once all plant accessions met the goal of in vitro establishment. The concentration of phytohormones and the acidity of the culture medium have a great effect on the multiplication rate and the quality of in vitro stock cultures. Out of 17 grapevine accessions, 16 showed the presence of single or combined resistance loci against P. viticola. The grapevine accessions identified as carrying Rpv3 and Rpv12 alleles represent important genetic resources for disease resistance breeding programs. These accessions may further contribute to the creation of new elite cultivars of economic interest.

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

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

Identification and Analysis of Candidate Genes Associated with Yield Structure Traits and Maize Yield Using Next-Generation Sequencing Technology

The main challenge of agriculture in the 21st century is the continuous increase in food production. In addition to ensuring food security, the goal of modern agriculture is the continued development and production of plant-derived biomaterials. Conventional plant breeding methods do not allow breeders to achieve satisfactory results in obtaining new varieties in a short time. Currently, advanced molecular biology tools play a significant role worldwide, markedly contributing to biological progress. The aim of this study was to identify new markers linked to candidate genes determining grain yield. Next-generation sequencing, gene association, and physical mapping were used to identify markers. An additional goal was to also optimize diagnostic procedures to identify molecular markers on reference materials. As a result of the conducted research, 19 SNP markers significantly associated with yield structure traits in maize were identified. Five of these markers (28629, 28625, 28640, 28649, and 29294) are located within genes that can be considered candidate genes associated with yield traits. For two markers (28639 and 29294), different amplification products were obtained on the electrophorograms. For marker 28629, a specific product of 189 bp was observed for genotypes 1, 4, and 10. For marker 29294, a specific product of 189 bp was observed for genotypes 1 and 10. Both markers can be used for the preliminary selection of well-yielding genotypes.

Multi-environment association study highlights candidate genes for robust agronomic quantitative trait loci in a novel worldwide Capsicum core collection

Investigating crop diversity through genome-wide association studies (GWAS) on core collections helps in deciphering the genetic determinants of complex quantitative traits. Using the G2P-SOL project world collection of 10 038 wild and cultivated Capsicum accessions from 10 major genebanks, we assembled a core collection of 423 accessions representing the known genetic diversity. Since complex traits are often highly dependent upon environmental variables and genotype-by-environment (G × E) interactions, multi-environment GWAS with a 10 195-marker genotypic matrix were conducted on a highly diverse subset of 350 Capsicum annuum accessions, extensively phenotyped in up to six independent trials from five climatically differing countries. Environment-specific and multi-environment quantitative trait loci (QTLs) were detected for 23 diverse agronomic traits. We identified 97 candidate genes potentially implicated in 53 of the most robust and high-confidence QTLs for fruit flavor, color, size, and shape traits, and for plant productivity, vigor, and earliness traits. Investigating the genetic architecture of agronomic traits in this way will assist the development of genetic markers and pave the way for marker-assisted selection. The G2P-SOL pepper core collection will be available upon request as a unique and universal resource for further exploitation in future gene discovery and marker-assisted breeding efforts by the pepper community.

Construction and Application of an F1-Derived Doubled-Haploid Population and High-Density Genetic Map for Ornamental Kale Breeding

Ornamental kale (Brassica oleracea var. acephala) is an attractive ornamental plant with a range of leaf colors and shapes. Breeding new varieties of ornamental kale has proven challenging due to its lengthy breeding cycle and the limited availability of genetic markers. In this study, a F1DH ornamental kale population comprising 300 DH lines was constructed using microspore culture. A high-density genetic map was developed by conducting whole-genome sequencing on 150 individuals from the F1DH population. The genetic map contained 1696 bin markers with 982,642 single-nucleotide polymorphisms (SNPs) spanning a total distance of 775.81 cM on all nine chromosomes with an average distance between markers of 0.46 cM. The ornamental kale genetic map contained substantially more SNP markers compared with published genetic maps for other B. oleracea crops. Furthermore, utilizing this high-density genetic map, we identified seven quantitative trait loci (QTLs) that significantly influence the leaf shape of ornamental kale. These findings are valuable for understanding the genetic basis of key agronomic traits in ornamental kale. The F1DH progenies provide an excellent resource for germplasm innovation and breeding new varieties of ornamental kale. Additionally, the high-density genetic map provides crucial insights for gene mapping and unraveling the molecular mechanisms behind important agronomic traits in ornamental kale.

Transcriptome analysis reveals important regulatory genes and pathways for tuber color variation in Pinellia ternata (Thunb.) Breit

During the growth of Pinellia ternata (Thunb.) Breit. (P. ternata), the violet-red skin was occasionally produced spontaneously under natural cultivation. However, the specific mechanism leading to the color change is still unclear. This study performed transcriptomes in violet-red and pale-yellow skin and their peeled tubers of P. ternata, and the total flavonoids and anthocyanin contents were also determined. The results showed that the majority of genes involved in anthocyanin production were considerably increased in the violet-red skin of P. ternata tuber compared to the pale-yellow skin. Especially, phenylalanine ammonia-lyase (PAL) and chalcone synthase (CHS) showed a remarkable increase in gene expression levels. Notably, shikimate O-hydroxycinnamoyltransferase (HCT), naringenin 3-dioxygenase (F3H), flavanone 4-reductase (DFR), and anthocyanidin synthase (ANS) were explicitly expressed in violet-red skin of P. ternata tuber, while undetectable in pale-yellow skin. The upregulation of these genes may explain the accumulation of anthocyanins, which forms the violet-red skin of P. ternata tuber. The transcription factors, including C2H2, bZIP, ERF, GATA, bHLH, C3H, NAC, MYB-related, and MYB families, might trigger the skin color change in P. ternata. The entire anthocyanin content in the violet-red skin of P. ternata tuber was 71.10 μg/g, and pale-yellow skin was 7.74 μg/g. According to phenotypic and transcriptome results, the elevated expression levels of genes linked to the synthesis of anthocyanins considerably contributed to the violet-red skin alterations in P. ternata tuber. This study provides a new understanding of the formation of the violet-red skin, lays a theoretical foundation for the cultivation of unique varieties of P. ternata, and provides transcriptome data for further study of the differences between different colors of P. ternata.

Construction of a genetic linkage map and QTL mapping of fruit quality traits in guava (Psidium guajava L.)

Guava (Psidium guajava L.) is an important fruit crop of the Indian sub-continent, with potential for improvements in quality and yield. The goal of the present study was to construct a genetic linkage map in an intraspecific cross between the elite cultivar 'Allahabad Safeda' and the Purple Guava landrace to identify the genomic regions responsible for important fruit quality traits, viz., total soluble solids, titratable acidity, vitamin C, and sugars. This population was phenotyped in field trials (as a winter crop) for three consecutive years, and showed moderate-to-high values of heterogeneity coefficients along with higher heritability (60.0%-97.0%) and genetic-advance-over-mean values (13.23%-31.17%), suggesting minimal environmental influence on the expression of fruit-quality traits and indicating that these traits can be improved by phenotypic selection methods. Significant correlations and strong associations were also detected among fruit physico-chemical traits in segregating progeny. The constructed linkage map consisted of 195 markers distributed across 11 chromosomes, spanning a length of 1,604.47 cM (average inter-loci distance of 8.80 markers) and with 88.00% coverage of the guava genome. Fifty-eight quantitative trait loci (QTLs) were detected in three environments with best linear unbiased prediction (BLUP) values using the composite interval mapping algorithm of the BIP (biparental populations) module. The QTLs were distributed on seven different chromosomes, explaining 10.95%-17.77% of phenotypic variance, with the highest LOD score being 5.96 for qTSS.AS.pau-6.2. Thirteen QTLs detected across multiple environments with BLUPs indicate stability and utility in a future breeding program for guava. Furthermore, seven QTL clusters with stable or common individual QTLs affecting two or more different traits were located on six linkage groups (LGs), explaining the correlation among fruit-quality traits. Thus, the multiple environmental evaluations conducted here have increased our understanding of the molecular basis of phenotypic variation, providing the basis for future high-resolution fine-mapping and paving the way for marker-assisted breeding of fruit-quality traits.

Clustered Regularly Interspaced Short Palindromic Repeats-Associated Protein System for Resistance Against Plant Viruses: Applications and Perspectives

Different genome editing approaches have been used to engineer resistance against plant viruses. The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas; CRISPR/Cas) systems to create pinpoint genetic mutations have emerged as a powerful tool for molecular engineering of plant immunity and increasing resistance against plant viruses. This review presents (i) recent advances in engineering resistance against plant viruses by CRISPR/Cas and (ii) an overview of the potential host factors as targets for the CRISPR/Cas system-mediated broad-range resistance and immunity. Applications, challenges, and perspectives in enabling the CRISPR/Cas system for crop protection are also outlined.

The Use of DArTseq Technology to Identify New SNP and SilicoDArT Markers Related to the Yield-Related Traits Components in Maize

In the last decade, many scientists have used molecular biology methods in their research to locate the grain-yield-determining loci and yield structure characteristics in maize. Large-scale molecular analyses in maize do not only focus on the identification of new markers and quantitative trait locus (QTL) regions. DNA analysis in the selection of parental components for heterotic crosses is a very important tool for breeders. The aim of this research was to identify and select new markers for maize (SNP and SilicoDArT) linked to genes influencing the size of the yield components in maize. The plant material used for the research was 186 inbred maize lines. The field experiment was established in twolocations. The yield and six yield components were analyzed. For identification of SNP and SilicoDArT markers related to the yield and yield components, next-generation sequencing was used. As a result of the biometric measurements analysis, differentiation in the average elevation of the analyzed traits for the lines in both locations was found. The above-mentioned results indicate the existence of genotype–environment interactions. The analysis of variance for the observed quality between genotypes indicated a statistically significant differentiation between genotypes and a statistically significant differentiation for all the observed properties betweenlocations. A canonical variable analysis was applied to present a multi-trait assessment of the similarity of the tested maize genotypes in a lower number of dimensions with the lowest possible loss of information. No grouping of lines due to the analyzed was observed. As a result of next-generation sequencing, the molecular markers SilicoDArT (53,031) and SNP (28,571) were obtained. The genetic distance between the analyzed lines was estimated on the basis of these markers. Out of 81,602 identified SilicoDArT and SNP markers, 15,409 (1559 SilicoDArT and 13,850 SNPs) significantly related to the analyzed yield components were selected as a result of association mapping. The greatest numbers of molecular markers were associated with cob length (1203), cob diameter (1759), core length (1201) and core diameter (2326). From 15,409 markers significantly related to the analyzed traits of the yield components, 18 DArT markers were selected, which were significant for the same four traits (cob length, cob diameter, core length, core diameter) in both Kobierzyce and Smolice. These markers were used for physical mapping. As a result of the analyses, it was found that 6 out of 18 (1818; 14,506; 2317; 3233; 11,657; 12,812) identified markers are located inside genes. These markers are located on chromosomes 8, 9, 7, 3, 5, and 1, respectively.

Genome-Wide Association Analysis Reveals Genetic Architecture and Candidate Genes Associated with Grain Yield and Other Traits under Low Soil Nitrogen in Early-Maturing White Quality Protein Maize Inbred Lines

Maize production in the savannas of sub-Saharan Africa (SSA) is constrained by the low nitrogen in the soils. The identification of quantitative trait loci (QTL) conferring tolerance to low soil nitrogen (low-N) is crucial for the successful breeding of high-yielding QPM maize genotypes under low-N conditions. The objective of this study was to identify QTLs significantly associated with grain yield and other low-N tolerance-related traits under low-N. The phenotypic data of 140 early-maturing white quality protein maize (QPM) inbred lines were evaluated under low-N. The inbred lines were genotyped using 49,185 DArTseq markers, from which 7599 markers were filtered for population structure analysis and genome-wide association study (GWAS). The inbred lines were grouped into two major clusters based on the population structure analysis. The GWAS identified 24, 3, 10, and 3 significant SNPs respectively associated with grain yield, stay-green characteristic, and plant and ear aspects, under low-N. Sixteen SNP markers were physically located in proximity to 32 putative genes associated with grain yield, stay-green characteristic, and plant and ear aspects. The putative genes GRMZM2G127139, GRMZM5G848945, GRMZM2G031331, GRMZM2G003493, GRMZM2G067964, GRMZM2G180254, on chromosomes 1, 2, 8, and 10 were involved in cellular nitrogen assimilation and biosynthesis, normal plant growth and development, nitrogen assimilation, and disease resistance. Following the validation of the markers, the putative candidate genes and SNPs could be used as genomic markers for marker-assisted selection, to facilitate genetic gains for low-N tolerance in maize production.

Novel Plant Breeding Techniques Shake Hands with Cereals to Increase Production

Cereals are the main source of human food on our planet. The ever-increasing food demand, continuously changing environment, and diseases of cereal crops have made adequate production a challenging task for feeding the ever-increasing population. Plant breeders are striving their hardest to increase production by manipulating conventional breeding methods based on the biology of plants, either self-pollinating or cross-pollinating. However, traditional approaches take a decade, space, and inputs in order to make crosses and release improved varieties. Recent advancements in genome editing tools (GETs) have increased the possibility of precise and rapid genome editing. New GETs such as CRISPR/Cas9, CRISPR/Cpf1, prime editing, base editing, dCas9 epigenetic modification, and several other transgene-free genome editing approaches are available to fill the lacuna of selection cycles and limited genetic diversity. Over the last few years, these technologies have led to revolutionary developments and researchers have quickly attained remarkable achievements. However, GETs are associated with various bottlenecks that prevent the scaling development of new varieties that can be dealt with by integrating the GETs with the improved conventional breeding methods such as speed breeding, which would take plant breeding to the next level. In this review, we have summarized all these traditional, molecular, and integrated approaches to speed up the breeding procedure of cereals.

Imaging Flow Cytometry as a Quick and Effective Identification Technique of Pollen Grains from Betulaceae, Oleaceae, Urticaceae and Asteraceae

Despite the continuous and intensive development of laboratory techniques, a light microscope is still the most common tool used in pollen grains differentiation. However, microscopy is time-consuming and needs well-educated and experienced researchers. Other currently used techniques can be categorised as images and non-images analysis, but each has certain limitations. We propose a new approach to differentiate pollen grains using the Imaging Flow Cytometry (IFC) technique. It allows for high-throughput fluorescence data recording, which, in contrast to the standard FC, also enables real-time control of the results thanks to the possibility of digital image recording of cells flowing through the measuring capillary. The developed method allows us to determine the characteristics of the pollen grains population based on the obtained fluorescence data, using various combinations of parameters available in the IDEAS software, which can be analysed on different fluorescence channels. On this basis, we distinguished pollen grains both between and within different genera belonging to the Betulaceae, Oleaceae, Urticaceae and Asteraceae families. Thereby, we prove that the proposed methodology is sufficient for accurate, fast, and cost-effective identification and potentially can be used in the routine analysis of allergenic pollen grains.

A high quality reference genome for Fraxinus pennsylvanica for ash species restoration and research

Green ash (Fraxinus pennsylvanica) is the most widely distributed ash tree in North America. Once common, it has experienced high mortality from the non‐native invasive emerald ash borer (EAB; Agrilus planipennis). A small percentage of native green ash trees that remain healthy in long‐infested areas, termed “lingering ash,” display partial resistance to the insect, indicating that breeding and propagating populations with higher resistance to EAB may be possible. To assist in ash breeding, ecology and evolution studies, we report the first chromosome‐level assembly from the genus Fraxinus for F. pennsylvanica with over 99% of bases anchored to 23 haploid chromosomes, spanning 757 Mb in total, composed of 49.43% repetitive DNA, and containing 35,470 high‐confidence gene models assigned to 22,976 Asterid orthogroups. We also present results of range‐wide genetic variation studies, the identification of candidate genes for important traits including potential EAB‐resistance genes, and an investigation of comparative genome organization among Asterids based on this reference genome platform. Residual duplicated regions within the genome probably resulting from a recent whole genome duplication event in Oleaceae were visualized in relation to wild olive (Olea europaea var. sylvestris). We used our F. pennsylvanica chromosome assembly to construct reference‐guided assemblies of 27 previously sequenced Fraxinus taxa, including F. excelsior. Thus, we present a significant step forward in genomic resources for research and protection of Fraxinus species.

Molecular Fingerprinting and Hybridity Authentication in Cowpea Using Single Nucleotide Polymorphism Based Kompetitive Allele-Specific PCR Assay

Optimization of a breeding program for increased genetic gain requires quality assurance (QA) and quality control (QC) at key phases of the breeding process. One vital phase in a breeding program that requires QC and QA is the choice of parents and successful hybridizations to combine parental attributes and create variations. The objective of this study was to determine parental diversity and confirm hybridity of cowpea F₁ progenies using KASP (Kompetitive Allele-Specific PCR)-based single nucleotide polymorphism (SNP) markers. A total of 1,436 F₁ plants were derived from crossing 220 cowpea breeding lines and landraces to 2 elite sister lines IT99K-573-1-1 and IT99K-573-2-1 as male parents, constituting 225 cross combinations. The progenies and the parents were genotyped with 17 QC SNP markers via high-throughput KASP genotyping assay. The QC markers differentiated the parents with mean efficiency of 37.90% and a range of 3.4-82.8%, revealing unique fingerprints of the parents. Neighbor-Joining cladogram divided the 222 parents into 3 clusters. Genetic distances between parents ranged from 0 to 3.74 with a mean of 2.41. Principal component analysis (PCA) depicted a considerable overlap between parents and F₁ progenies with more scatters among parents than the F₁s. The differentiation among parents and F₁s was best contributed to by 82% of the markers. As expected, parents and F₁s showed a significant contrast in proportion of heterozygous individuals, with mean values of 0.02 and 0.32, respectively. KASP markers detected true hybridity with 100% success rate in 72% of the populations. Overall, 79% of the putative F₁ plants were true hybrids, 14% were selfed plants, and 7% were undetermined due to missing data and lack of marker polymorphism between parents. The study demonstrated an effective application of KASP-based SNP assay in fingerprinting, confirmation of hybridity, and early detection of false F₁ plants. The results further uncovered the need to deploy markers as a QC step in a breeding program.

Plant-Microbe Interaction: Aboveground to Belowground, from the Good to the Bad

Soil health and fertility issues are constantly addressed in the agricultural industry. Through the continuous and prolonged use of chemical heavy agricultural systems, most agricultural lands have been impacted, resulting in plateaued or reduced productivity. As such, to invigorate the agricultural industry, we would have to resort to alternative practices that will restore soil health and fertility. Therefore, in recent decades, studies have been directed towards taking a Magellan voyage of the soil rhizosphere region, to identify the diversity, density, and microbial population structure of the soil, and predict possible ways to restore soil health. Microbes that inhabit this region possess niche functions, such as the stimulation or promotion of plant growth, disease suppression, management of toxicity, and the cycling and utilization of nutrients. Therefore, studies should be conducted to identify microbes or groups of organisms that have assigned niche functions. Based on the above, this article reviews the aboveground and below-ground microbiomes, their roles in plant immunity, physiological functions, and challenges and tools available in studying these organisms. The information collected over the years may contribute toward future applications, and in designing sustainable agriculture.

Genome-wide association study identifies QTL for eight fruit traits in cultivated tomato (Solanum lycopersicum L.)

Genome-wide association study (GWAS) is effective in identifying favorable alleles for traits of interest with high mapping resolution in crop species. In this study, we conducted GWAS to explore quantitative trait loci (QTL) for eight fruit traits using 162 tomato accessions with diverse genetic backgrounds. The eight traits included fruit weight, fruit width, fruit height, fruit shape index, pericarp thickness, locule number, fruit firmness, and brix. Phenotypic variations of these traits in the tomato collection were evaluated with three replicates in field trials over three years. We filtered 34,550 confident SNPs from the 51 K Axiom^® tomato array based on < 10% of missing data and > 5% of minor allele frequency for association analysis. The 162 tomato accessions were divided into seven clusters and their membership coefficients were used to account for population structure along with a kinship matrix. To identify marker-trait associations (MTAs), four phenotypic data sets representing each of three years and combined were independently analyzed in the multilocus mixed model (MLMM). A total of 30 significant MTAs was detected over data sets for eight fruit traits at P < 0.0005. The number of MTA per trait ranged from one (brix) to seven (fruit weight and fruit width). Two SNP markers on chromosomes 1 and 2 were significantly associated with multiple traits, suggesting pleiotropic effects of QTL. Furthermore, 16 of 30 MTAs suggest potential novel QTL for eight fruit traits. These results facilitate genetic dissection of tomato fruit traits and provide a useful resource to develop molecular tools for improving fruit traits via marker-assisted selection and genomic selection in tomato breeding programs.

Prospects for Trifolium Improvement Through Germplasm Characterisation and Pre-breeding in New Zealand and Beyond

Trifolium is the most used pastoral legume genus in temperate grassland systems, and a common feature in meadows and open space areas in cities and parks. Breeding of Trifolium spp. for pastoral production has been going on for over a century. However, the breeding targets have changed over the decades in response to different environmental and production pressures. Relatively small gains have been made in Trifolium breeding progress. Trifolium breeding programmes aim to maintain a broad genetic base to maximise variation. New Zealand is a global hub in Trifolium breeding, utilising exotic germplasm imported by the Margot Forde Germplasm Centre. This article describes the history of Trifolium breeding in New Zealand as well as the role and past successes of utilising genebanks in forage breeding. The impact of germplasm characterisation and evaluation in breeding programmes is also discussed. The history and challenges of Trifolium breeding and its effect on genetic gain can be used to inform future pre-breeding decisions in this genus, as well as being a model for other forage legumes.

Advances in Cereal Crop Genomics for Resilience under Climate Change

Adapting to climate change, providing sufficient human food and nutritional needs, and securing sufficient energy supplies will call for a radical transformation from the current conventional adaptation approaches to more broad-based and transformative alternatives. This entails diversifying the agricultural system and boosting productivity of major cereal crops through development of climate-resilient cultivars that can sustainably maintain higher yields under climate change conditions, expanding our focus to crop wild relatives, and better exploitation of underutilized crop species. This is facilitated by the recent developments in plant genomics, such as advances in genome sequencing, assembly, and annotation, as well as gene editing technologies, which have increased the availability of high-quality reference genomes for various model and non-model plant species. This has necessitated genomics-assisted breeding of crops, including underutilized species, consequently broadening genetic variation of the available germplasm; improving the discovery of novel alleles controlling important agronomic traits; and enhancing creation of new crop cultivars with improved tolerance to biotic and abiotic stresses and superior nutritive quality. Here, therefore, we summarize these recent developments in plant genomics and their application, with particular reference to cereal crops (including underutilized species). Particularly, we discuss genome sequencing approaches, quantitative trait loci (QTL) mapping and genome-wide association (GWAS) studies, directed mutagenesis, plant non-coding RNAs, precise gene editing technologies such as CRISPR-Cas9, and complementation of crop genotyping by crop phenotyping. We then conclude by providing an outlook that, as we step into the future, high-throughput phenotyping, pan-genomics, transposable elements analysis, and machine learning hold much promise for crop improvements related to climate resilience and nutritional superiority.

Using RNA-seq to characterize pollen-stigma interactions for pollination studies

Insects are essential for the reproduction of pollinator-dependent crops and contribute to the pollination of 87% of wild plants and 75% of the world’s food crops. Understanding pollen flow dynamics between plants and pollinators is thus essential to manage and conserve wild plants and ensure yields are maximized in food crops. However, the determination of pollen transfer in the field is complex and laborious. We developed a field experiment in a pollinator-dependent crop and used high throughput RNA sequencing (RNA-seq) to quantify pollen flow by measuring changes in gene expression between pollination treatments across different apple (Malus domestica Borkh.) cultivars. We tested three potential molecular indicators of successful pollination and validated these results with field data by observing single and multiple visits by honey bees (Apis mellifera) to apple flowers and measured fruit set in a commercial apple orchard. The first indicator of successful outcrossing was revealed via differential gene expression in the cross-pollination treatments after 6 h. The second indicator of successful outcrossing was revealed by the expression of specific genes related to pollen tube formation and defense response at three different time intervals in the stigma and the style following cross-pollination (i.e. after 6, 24, and 48 h). Finally, genotyping variants specific to donor pollen could be detected in cross-pollination treatments, providing a third indicator of successful outcrossing. Field data indicated that one or five flower visits by honey bees were insufficient and at least 10 honey bee flower visits were required to achieve a 25% probability of fruit set under orchard conditions. By combining the genotyping data, the differential expression analysis, and the traditional fruit set field experiments, it was possible to evaluate the pollination effectiveness of honey bee visits under orchards conditions. This is the first time that pollen-stigma-style mRNA expression analysis has been conducted after a pollinator visit (honey bee) to a plant (in vivo apple flowers). This study provides evidence that mRNA sequencing can be used to address complex questions related to stigma–pollen interactions over time in pollination ecology.

Genomics Armed With Diversity Leads the Way in Brassica Improvement in a Changing Global Environment

Meeting the needs of a growing world population in the face of imminent climate change is a challenge; breeding of vegetable and oilseed Brassica crops is part of the race in meeting these demands. Available genetic diversity constituting the foundation of breeding is essential in plant improvement. Elite varieties, land races, and crop wild species are important resources of useful variation and are available from existing genepools or genebanks. Conservation of diversity in genepools, genebanks, and even the wild is crucial in preventing the loss of variation for future breeding efforts. In addition, the identification of suitable parental lines and alleles is critical in ensuring the development of resilient Brassica crops. During the past two decades, an increasing number of high-quality nuclear and organellar Brassica genomes have been assembled. Whole-genome re-sequencing and the development of pan-genomes are overcoming the limitations of the single reference genome and provide the basis for further exploration. Genomic and complementary omic tools such as microarrays, transcriptomics, epigenetics, and reverse genetics facilitate the study of crop evolution, breeding histories, and the discovery of loci associated with highly sought-after agronomic traits. Furthermore, in genomic selection, predicted breeding values based on phenotype and genome-wide marker scores allow the preselection of promising genotypes, enhancing genetic gains and substantially quickening the breeding cycle. It is clear that genomics, armed with diversity, is set to lead the way in Brassica improvement; however, a multidisciplinary plant breeding approach that includes phenotype = genotype × environment × management interaction will ultimately ensure the selection of resilient Brassica varieties ready for climate change.

Transcriptomic Analysis of the Anthocyanin Biosynthetic Pathway Reveals the Molecular Mechanism Associated with Purple Color Formation in Dendrobium Nestor

Dendrobium nestor is a famous orchid species in the Orchidaceae family. There is a diversity of flower colorations in the Dendrobium species, but knowledge of the genes involved and molecular mechanism underlying the flower color formation in D. nestor is less studied. Therefore, we performed transcriptome profiling using Illumina sequencing to facilitate thorough studies of the purple color formation in petal samples collected at three developmental stages, namely-flower bud stage (F), half bloom stage (H), and full bloom stage (B) in D. nestor. In addition, we identified key genes and their biosynthetic pathways as well as the transcription factors (TFs) associated with purple flower color formation. We found that the phenylpropanoid-flavonoid-anthocyanin biosynthesis genes such as phenylalanine ammonia lyase, chalcone synthase, anthocyanidin synthase, and UDP-flavonoid glucosyl transferase, were largely up-regulated in the H and B samples as compared to the F samples. This upregulation might partly account for the accumulation of anthocyanins, which confer the purple coloration in these samples. We further identified several differentially expressed genes related to phytohormones such as auxin, ethylene, cytokinins, salicylic acid, brassinosteroid, and abscisic acid, as well as TFs such as MYB and bHLH, which might play important roles in color formation in D. nestor flower. Sturdy upregulation of anthocyanin biosynthetic structural genes might be a potential regulatory mechanism in purple color formation in D. nestor flowers. Several TFs were predicted to regulate the anthocyanin genes through a K-mean clustering analysis. Our study provides valuable resource for future studies to expand our understanding of flower color development mechanisms in D. nestor.

Identification of Allelic Variation in Drought Responsive Dehydrin Gene Based on Sequence Similarity in Chickpea (Cicer arietinum L.)

Chickpea (Cicer arietinum L.) is an economically important food legume grown in arid and semi-arid regions of the world. Chickpea is cultivated mainly in the rainfed, residual moisture, and restricted irrigation condition. The crop is always prone to drought stress which is resulting in flower drop, unfilled pods, and is a major yield reducer in many parts of the world. The present study elucidates the association between candidate gene and morpho-physiological traits for the screening of drought tolerance in chickpea. Abiotic stress-responsive gene Dehydrin (DHN) was identified in some of the chickpea genotypes based on the sequence similarity approach to play a major role in drought tolerance. Analysis of variance revealed a significant effect of drought on relative water content, membrane stability index, plant height, and yield traits. The genotypes Pusa1103, Pusa362, and ICC4958 were found most promising genotypes for drought tolerance as they maintained the higher value of osmotic regulations and yield characters. The results were further supported by a sequence similarity approach for the dehydrin gene when analyzed for the presence of single nucleotide polymorphisms (SNPs) and indels. Homozygous indels and single nucleotide polymorphisms were found after the sequencing in some of the selected genotypes.

Origin, Evolution, Breeding, and Omics of Chayote, an Important Cucurbitaceae Vegetable Crop

Chayote (Sechium edule), a member of the Cucurbitaceae family, is cultivated throughout tropical and subtropical regions of the world and utilized in pharmaceutical, cosmetic and food industries because it is an excellent source of minerals, dietary fibers, protein, vitamins, carotenoids, polysaccharides, phenolic and flavonoid compounds, and other nutrients. Chayote extracts process various medicinal properties, such as anti-cardiovascular, antidiabetic, antiobesity, antiulcer, and anticancer properties. With the rapid advancements of molecular biology and sequencing technology, studies on chayote have been carried out. Research advances, including molecular makers, breeding, genomic research, chemical composition, and pests and diseases, regarding chayote are reviewed in this paper. Future exploration and application trends are briefly described. This review provides a reference for basic and applied research on chayote, an important Cucurbitaceae vegetable crop.

Identification of Differentially Expressed Drought-Responsive Genes in Guar [Cyamopsis tetragonoloba (L.) Taub]

Drought remains one of the most serious environmental stresses because of the continuous reduction in soil moisture, which requires the improvement of crops with features such as drought tolerance. Guar [Cyamopsis tetragonoloba (L.) Taub], a forage and industrial crop, is a nonthirsty plant. However, the information on the transcriptome changes that occur under drought stress in guar is very limited; therefore, a gene expression analysis is necessary in this context. Here, we studied the differentially expressed genes (DEGs) in response to drought stress and their metabolic pathways. RNA-Seq via an expectation-maximization algorithm was used to estimate gene abundance. Subsequently, an Empirical Analysis of Digital Gene Expression Data in the R Bioconductor package was used to identify DEGs. Blast2GO, InterProScan, and the Kyoto Encyclopedia of Genes and Genomes were used to explore functional annotation, protein analysis, enzymes, and metabolic pathways. Transcription factors were identified using the PlantTFDB database. Our study identified 499 upregulated and 191 downregulated genes in response to drought stress. Of those, 32 upregulated and six downregulated genes were deemed as novel genes exclusive to guar. An aggregate of 137 protein families, 306 domains, 12 repeats, and two sites were upregulated. The proton-dependent oligopeptide transporter family and transferase, aquaporin transporter, calcium/calmodulin-dependent/calcium-dependent protein kinase, aspartic peptidase A1 family, UDP-glucuronosyl/UDP-glucosyltransferase, and major intrinsic protein were the most upregulated protein families. The upregulated unigenes were associated with 88 enzymes and 77 KEGG pathways. Finally, the MYB-related, MYB, and ERF transcription factor families were upregulated. These data may be useful for understanding the plant molecular response to drought stress.

The Toolbox for Fiber Flax Breeding: A Pipeline From Gene Expression to Fiber Quality

The goal of any plant breeding program is to improve quality of a target crop. Crop quality is a comprehensive feature largely determined by biological background. To improve the quality parameters of crops grown for the production of fiber, a functional approach was used to search for genes suitable for the effective manipulation of technical fiber quality. A key step was to identify genes with tissue and stage-specific pattern of expression in the developing fibers. In the current study, we investigated the relationship between gene expression evaluated in bast fibers of developing flax plants and the quality parameters of technical fibers measured after plant harvesting. Based on previously published transcriptomic data, two sets of genes that are upregulated in fibers during intrusive growth and tertiary cell wall deposition were selected. The expression level of the selected genes and fiber quality parameters were measured in fiber flax, linseed (oil flax) cultivars, and wild species that differ in type of yield and fiber quality parameters. Based on gene expression data, linear regression models for technical stem length, fiber tensile strength, and fiber flexibility were constructed, resulting in the identification of genes that have high potential for manipulating fiber quality. Chromosomal localization and single nucleotide polymorphism distribution in the selected genes were characterized for the efficacy of their use in conventional breeding and genome editing programs. Transcriptome-based selection is a highly targeted functional approach that could be used during the development of new cultivars of various crops.

ddRAD sequencing-based genotyping for population structure analysis in cultivated tomato provides new insights into the genomic diversity of Mediterranean 'da serbo' type long shelf-life germplasm

Double digest restriction-site associated sequencing (ddRAD-seq) is a flexible and cost-effective strategy for providing in-depth insights into the genetic architecture of germplasm collections. Using this methodology, we investigated the genomic diversity of a panel of 288 diverse tomato (Solanum lycopersicum L.) accessions enriched in 'da serbo' (called 'de penjar' in Spain) long shelf life (LSL) materials (152 accessions) mostly originating from Italy and Spain. The rest of the materials originate from different countries and include landraces for fresh consumption, elite cultivars, heirlooms, and breeding lines. Apart from their LSL trait, 'da serbo' landraces are of remarkable interest for their resilience. We identified 32,799 high-quality SNPs, which were used for model ancestry population structure and non-parametric hierarchical clustering. Six genetic subgroups were revealed, clearly separating most 'da serbo' landraces, but also the Spanish germplasm, suggesting a subdivision of the population based on type and geographical provenance. Linkage disequilibrium (LD) in the collection decayed very rapidly within <5 kb. We then investigated SNPs showing contrasted minor frequency allele (MAF) in 'da serbo' materials, resulting in the identification of high frequencies in this germplasm of several mutations in genes related to stress tolerance and fruit maturation such as CTR1 and JAR1. Finally, a mini-core collection of 58 accessions encompassing most of the diversity was selected for further exploitation of key traits. Our findings suggest the presence of a genetic footprint of the 'da serbo' germplasm selected in the Mediterranean basin. Moreover, we provide novel insights on LSL 'da serbo' germplasm as a promising source of alleles for tolerance to stresses.

Coupling day length data and genomic prediction tools for predicting time-related traits under complex scenarios

Genomic selection (GS) has proven to be an efficient tool for predicting crop-rank performance of untested genotypes; however, when the traits have intermediate optima (phenology stages), this implementation might not be the most convenient. GS might deliver high-rank correlations but incurring in serious bias. Days to heading (DTH) is a crucial development stage in rice for regional adaptability with a significant impact on yield potential. The objective of this research consisted in develop a novel method that accurately predicts time-related traits such as DTH in unobserved environments. For this, we propose an implementation that incorporates day length information (DL) in the prediction process for two relevant scenarios: CV0, predicting tested genotypes in unobserved environments (C method); and CV00, predicting untested genotypes in unobserved environments (CB method). The use of DL has advantages over weather data since it can be determined in advance just by knowing the location and planting date. The proposed methods showed that DL information significantly helps to improve the predictive ability of DTH in unobserved environments. Under CV0, the C method returned a root-mean-square error (RMSE) of 3.9 days, a Pearson correlation (PC) of 0.98 and the differences between the predicted and observed environmental means (EMD) ranged between -4.95 and 4.67 days. For CV00, the CB method returned an RMSE of 7.3 days, a PC of 0.93 and the EMD ranged between -6.4 and 4.1 days while the conventional GS implementation produced an RMSE of 18.1 days, a PC of 0.41 and the EMD ranged between -31.5 and 28.7 days.

Genetic diversity, SNP-trait associations and genomic selection accuracy in a west African collection of Kersting's groundnut [Macrotyloma geocarpum(Harms) Maréchal & Baudet]

Understanding the mechanisms governing complex traits variation is a requirement for efficient crop improvement. In this study, the molecular characterization, marker-trait associations and the possibility for genomic selection in a collection of 281 Kersting's groundnut accessions were carried out. The diversity panel was phenotyped using an Alpha lattice design with two replicates in two contrasting environments. Accessions were genotyped using genotyping by sequencing technology. Genome-wide association analyses were performed between single nucleotide polymorphism markers and yield-related traits across tested environments. SNP markers were used to calculate the observed (Ho) and expected heterozygosity (He), and the total gene diversity (Ht). Genetic differentiation among accessions across ecological regions of origin was analysed. Our results revealed 493 quality SNPs of which 113 had a minor allele frequency>0.05, a total gene diversity of 0.43 and average Ho and He values of 0.04 and 0.22, respectively. Four clusters, highly differentiated by seed coat colour (Fst = 0.79), were identified. The population structure analysis showed two subpopulations with high differentiation across ecological regions (Fst = 0.37). The GWAS revealed 10 significant marker-trait associations, of which six SNPs were consistent across environments. The genomic selection through cross-validation showed moderate to high prediction accuracies for leaflet length, seed dimension traits, 100 seed weight, days to 50% flowering and days to maturity. This demonstrates the existence of genetic variability within Kersting's groundnut and shows the potential for the improvement of the species. The findings also provide a first insight into the phenotype-to-genotype relationships in Kersting's groundnut, using SNP markers.

High-Density Genetic Linkage Mapping of Lepidium Based on Genotyping-by-Sequencing SNPs and Segregating Contig Tag Haplotypes

Lepidium campestre has been targeted for domestication as future oilseed and catch crop. Three hundred eighty plants comprising genotypes of L. campestre, Lepidium heterophyllum, and their interspecific F2 mapping population were genotyped using genotyping by sequencing (GBS), and the generated polymorphic markers were used for the construction of high-density genetic linkage map. TASSEL-GBS, a reference genome-based pipeline, was used for this analysis using a draft L. campestre whole genome sequence. The analysis resulted in 120,438 biallelic single-nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) above 0.01. The construction of genetic linkage map was conducted using MSTMap based on phased SNPs segregating in 1:2:1 ratio for the F2 individuals, followed by genetic mapping of segregating contig tag haplotypes as dominant markers against the linkage map. The final linkage map consisted of eight linkage groups (LGs) containing 2,330 SNP markers and spanned 881 Kosambi cM. Contigs (10,302) were genetically mapped to the eight LGs, which were assembled into pseudomolecules that covered a total of ∼120.6 Mbp. The final size of the pseudomolecules ranged from 9.4 Mbp (LG-4) to 20.4 Mpb (LG-7). The following major correspondence between the eight Lepidium LGs (LG-1 to LG-8) and the five Arabidopsis thaliana (At) chromosomes (Atx-1-Atx-5) was revealed through comparative genomics analysis: LG-1&2_Atx-1, LG-3_Atx-2&3, LG-4_Atx-2, LG-5_Atx-2&Atx-3, LG-6_Atx-4&5, LG-7_Atx-4, and LG-8_Atx-5. This analysis revealed that at least 66% of the sequences of the LGs showed high collinearity with At chromosomes. The sequence identity between the corresponding regions of the LGs and At chromosomes ranged from 80.6% (LG-6) to 86.4% (LG-8) with overall mean of 82.9%. The map positions on Lepidium LGs of the homologs of 24 genes that regulate various traits in A. thaliana were also identified. The eight LGs revealed in this study confirm the previously reported (1) haploid chromosome number of eight in L. campestre and L. heterophyllum and (2) chromosomal fusion, translocation, and inversion events during the evolution of n = 8 karyotype in ancestral species shared by Lepidium and Arabidopsis to n = 5 karyotype in A. thaliana. This study generated highly useful genomic tools and resources for Lepidium that can be used to accelerate its domestication.

Conventional and Molecular Techniques from Simple Breeding to Speed Breeding in Crop Plants: Recent Advances and Future Outlook

In most crop breeding programs, the rate of yield increment is insufficient to cope with the increased food demand caused by a rapidly expanding global population. In plant breeding, the development of improved crop varieties is limited by the very long crop duration. Given the many phases of crossing, selection, and testing involved in the production of new plant varieties, it can take one or two decades to create a new cultivar. One possible way of alleviating food scarcity problems and increasing food security is to develop improved plant varieties rapidly. Traditional farming methods practiced since quite some time have decreased the genetic variability of crops. To improve agronomic traits associated with yield, quality, and resistance to biotic and abiotic stresses in crop plants, several conventional and molecular approaches have been used, including genetic selection, mutagenic breeding, somaclonal variations, whole-genome sequence-based approaches, physical maps, and functional genomic tools. However, recent advances in genome editing technology using programmable nucleases, clustered regularly interspaced short palindromic repeats (CRISPR), and CRISPR-associated (Cas) proteins have opened the door to a new plant breeding era. Therefore, to increase the efficiency of crop breeding, plant breeders and researchers around the world are using novel strategies such as speed breeding, genome editing tools, and high-throughput phenotyping. In this review, we summarize recent findings on several aspects of crop breeding to describe the evolution of plant breeding practices, from traditional to modern speed breeding combined with genome editing tools, which aim to produce crop generations with desired traits annually.

Identifying and validating housekeeping hybrid Prunus spp. genes for root gene-expression studies

Prunus rootstock belonging to subgenera Amygdalus (peach), Prunus (plum) and Cerasus (cherry) are either from the same species as the scion or another one. The number of inter-species (including inter-subgenera) hybrids has increased as a result of broadening the genetic basis for stress (biotic and abiotic) resistance/tolerance. Identifying genes associated with important traits and responses requires expression analysis. Relative quantification is the simplest and most popular alternative, which requires reference genes (housekeeping) to normalize RT-qPCR data. However, there is a scarcity of validated housekeeping genes for hybrid Prunus rootstock species. This research aims to increase the number of housekeeping genes suitable for Prunus rootstock expression analysis. Twenty-one candidate housekeeping genes were pre-selected from previous RNAseq data that compared the response of root transcriptomes of two rootstocks subgenera to hypoxia treatment, 'Mariana 2624' (P. cerasifera Ehrh.× P. munsoniana W. Wight & Hedrick), and 'Mazzard F12/1' (P. avium L.). Representing groups of low, intermediate or high levels of expression, the genes were assayed by RT-qPCR at 72 hours of hypoxia treatment and analyzed with NormFinder software. A sub-set of seven housekeeping genes that presented the highest level of stability were selected, two with low levels of expression (Unknown 3, Unknown 7) and five with medium levels (GTB 1, TUA 3, ATPase P, PRT 6, RP II). The stability of these genes was evaluated under different stress conditions, cold and heat with the hybrid 'Mariana 2624' and N nutrition with the hybrids 'Colt' (P. avium × P. pseudocerasus Lindl.) and 'Garnem' [P. dulcis Mill.× (P. persica L.× P. davidiana Carr.)]. The algorithms of geNorm and BestKeeper software also were used to analyze the performance of these genes as housekeepers. Stability rankings varied according to treatments, genotypes and the software for evaluation, but the gene GBT 1 often had the highest ranking. However, most of the genes are suitable depending on the stressor and/or genotype to be evaluated. No optimal number of reference genes could be determined with geNorm software when all conditions and genotypes were considered. These results strongly suggest that relative RT-qPCR should be analyzed separately with their respective best housekeeper according to the treatment and/or genotypes in Prunus spp. rootstocks.

Microbial-assisted and genomic-assisted breeding: a two way approach for the improvement of nutritional quality traits in agricultural crops

Both human and animals, for their nutritional requirements, mainly rely on the plant-based foods, which provide a wide range of nutrients. Minerals, proteins, vitamins are among the nutrients which are essential and need to be available in adequate amount in edible portion of the staple crops. Increasing nutritional content in staple crops either through agronomic biofortification or through conventional plant-breeding strategies continue to be a huge task for scientists around the globe. Although some success has been achieved in recent past, in most cases, we have fallen short of expected targets. To maximize the nutrient uptake and partitioning to different economic part of plants, scientists have employed and tailored several biofortification strategies. But in present agricultural and environmental concerns, these approaches are not much effective. Henceforth, we are highlighting the recent developments and promising aspects of microbial-assisted and genomic-assisted breeding as candidate biofortification approach, that have contributed significantly in increasing nutritional content in grains of different crops. The methods used to date to accomplish nutrient enrichment with recently emerging strategies that we believe could be the most promising and holistic approach for future biofortification program. Results are encouraging, but for future perspective, the existing knowledge about the strategies needs to be confined. Concerted scientific investment are required to widen up these biofortification strategies, so that it could play an important role in ensuring nutritional security of ever-growing population in growing agricultural and environmental constraints.

Legume genomics and transcriptomics: From classic breeding to modern technologies

Legumes are essential and play a significant role in maintaining food standards and augmenting physiochemical soil properties through the biological nitrogen fixation process. Biotic and abiotic factors are the main factors limiting legume production. Classical breeding methodologies have been explored extensively about the problem of truncated yield in legumes but have not succeeded at the desired rate. Conventional breeding improved legume genotypes but with more resources and time. Recently, the invention of next-generation sequencing (NGS) and high-throughput methods for genotyping have opened new avenues for research and developments in legume studies. During the last decade, genome sequencing for many legume crops documented. Sequencing and re-sequencing of important legume species have made structural variation and functional genomics conceivable. NGS and other molecular techniques such as the development of markers; genotyping; high density genetic linkage maps; quantitative trait loci (QTLs) identification, expressed sequence tags (ESTs), single nucleotide polymorphisms (SNPs); and transcription factors incorporated into existing breeding technologies have made possible the accurate and accelerated delivery of information for researchers. The application of genome sequencing, RNA sequencing (transcriptome sequencing), and DNA sequencing (re-sequencing) provide considerable insights for legume development and improvement programs.

Moreover, RNA-Seq helps to characterize genes, including differentially expressed genes, and can be applied for functional genomics studies, especially when there is limited information available for the studied genomes. Genome-based crop development studies and the availability of genomics data as well as decision-making gears look be specific for breeding programs. This review mainly presents an overview of the path from classical breeding to new emerging genomics tools, which will trigger and accelerate genomics-assisted breeding for recognition of novel genes for yield and quality characters for sustainable legume crop production.

Genetic Diversity, Population Structure, and Linkage Disequilibrium of Pearl Millet

Mapping of GBS reads of 398 accessions to the draft genome sequence identified 82,112 SNPs Model-based clustering analysis revealed a hierarchical genetic structure of six subgroups Greater LD decay in the west-African subpopulation is likely due to long history of recombination Genetic differentiation analysis among subpopulations revealed variation in selection signatures Pearl millet [Cenchrus americanus (L.) Morrone syn. Pennisetum glaucum (L.) R. Br.] is one of the most extensively cultivated cereals in the world, after wheat (Triticum aestivum L.), maize (Zea mays L.), rice (Oryza sativa L.), barley (Hordeum vulgare L.), and sorghum [Sorghum bicolor (L.) Moench]. It is the main component of traditional farming systems and a staple food in the arid and semiarid regions of Africa and southern Asia. However, its genetic improvement is lagging behind other major cereals and the yield is still low. Genotyping-by-sequencing (GBS)-based single-nucleotide polymorphism (SNP) markers were screened on a total of 398 accessions from different geographic regions to assess genetic diversity, population structure, and linkage disequilibrium (LD). By mapping the GBS reads to the reference genome sequence, 82,112 genome-wide SNPs were discovered. The telomeric regions of the chromosomes have the higher SNP density than in pericentromeric regions. Model-based clustering analysis of the population revealed a hierarchical genetic structure of six subgroups that mostly overlap with the geographic origins or sources of the genotypes but with differing levels of admixtures. A neighbor-joining phylogeny analysis revealed that germplasm from western Africa rooted the dendrogram with much diversity within each subgroup. Greater LD decay was observed in the west-African subpopulation than in the other subpopulations, indicating a long history of recombination among landraces. Also, genome scan of genetic differentiatation detected different selection histories among subpopulations. These results have potential application in the development of genomic-assisted breeding in pearl millet and heterotic grouping of the lines for improved hybrid performance.

Construction of gene causal regulatory networks using microarray data with the coefficient of intrinsic dependence

BACKGROUND

In the past two decades, biologists have been able to identify the gene signatures associated with various phenotypes through the monitoring of gene expressions with high-throughput biotechnologies. These gene signatures have in turn been successfully applied to drug development, disease prevention, crop improvement, etc. However, ignoring the interactions among genes has weakened the predictive power of gene signatures in practical applications. Gene regulatory networks, in which genes are represented by nodes and the associations between genes are represented by edges, are typically constructed to analyze and visualize such gene interactions. More specifically, the present study sought to measure gene-gene associations by using the coefficient of intrinsic dependence (CID) to capture more nonlinear as well as cause-effect gene relationships.

RESULTS

A stepwise procedure using the CID along with the partial coefficient of intrinsic dependence (pCID) was demonstrated for the rebuilding of simulated networks and the well-known CBF-COR pathway under cold stress using Arabidopsis microarray data. The procedure was also applied to the construction of bHLH gene regulatory pathways under abiotic stresses using rice microarray data, in which OsbHLH104, a putative phytochrome-interacting factor (OsPIF14), and OsbHLH060, a positive regulator of iron homeostasis (OsPRI1) were inferred as the most affiliated genes. The inferred regulatory pathways were verified through literature reviews.

CONCLUSIONS

The proposed method can efficiently decipher gene regulatory pathways and may assist in achieving higher predictive power in practical applications. The lack of any mention in the literature of some of the regulatory event may have been due to the high complexity of the regulatory systems in the plant transcription, a possibility which could potentially be confirmed in the near future given ongoing rapid developments in bio-technology.

Prospects of genomic resources available at the global databases for the flora of United Arab Emirates

This article emphasizes available genomic resources at the global databases National Center for Biotechnology Information (NCBI) GenBank, Gramene and Phytozome for the selected 378 plant taxa of the United Arab Emirates (UAE). Germplasm of these species was collected and banked at the Sharjah Seed Bank and Herbarium (SSBH) along with their related information on habit, habitat and occurrence. The occurrence statistics exhibits almost 19.84% species under rare-to-very rare category, the GenBank search statistics for this category indicates 17.72% species as studied and 2.11% as not studied. Overall, from the global search statistics for 378 plant species, it seems that about 40 (10.58%) species remained unstudied. Most of the unstudied species were herbaceous plants belonging to the mountainous habitat. Moreover, full genomes were recorded for 7 species at NCBI GenBank, 2 species at Phytozome and 1 species at Gramene database. The local search statistics (for UAE) exhibits about 10.58% of the flora that still remained unstudied and only 11 (2.90%) of the recorded species were having genomic information at NCBI GenBank. It is necessary to prioritize studies on such species that could provide valuable insight on their genetic composition in order to understand their adaptation to the natural environment. At present, the SSBH is cataloguing UAE's flora using core barcode and assisted markers that could provide a robust DNA barcode library for native plants of UAE. Our study appeals researchers to recognize and prioritize the species that need attention to enrich their genomic resources at the global databases by supporting nucleotide libraries with their conspecifics. At present, genomic resources for UAE plant taxa are limited, but with the advent of low-cost sequencing technologies these resources would flourish in the near future. Nevertheless, the information generated through genomic studies could be utilized for conservation and management of threatened and endangered plant species, Crop Wild Relatives and medicinal plants. We hope this article will promote interest in conducting additional studies in genomics of desert plants by encouraging researchers to participate in this emerging field.

Modernising breeding for orphan crops: tools, methodologies, and beyond

In spite of the limited investment in orphan crops, access to new technologies such as bioinformatics and low-cost genotyping opens new doors to modernise their breeding effectively. Innovation in plant breeding is imperative to meet the world's growing demand for staple food and feed crops, and orphan crops can play a significant role in increasing productivity and quality, especially in developing countries. The short breeding history of most orphan crops implies that genetic gain should be achievable through easy-to-implement approaches such as forward breeding for simple traits or introgression of elite alleles at key target trait loci. However, limited financial support and access to sufficient, relevant and reliable phenotypic data continue to pose major challenges in terms of resources and capabilities. Digitalisation of orphan-crop breeding programmes can help not only to improve data quality and management, but also to mitigate data scarcity by allowing data to be accumulated and analysed over time and across teams. Bioinformatics tools and access to technologies such as molecular markers, some of them provided as services via specific platforms, allow breeders to implement modern strategies to improve breeding efficiency. In orphan crops, more marker-trait associations relevant to breeding germplasm are generally needed, but implementing digitalization, marker-based quality control or simple trait screening and introgression will help modernising breeding. Finally, the development of local capacities-of both people and infrastructure-remains a necessity to ensure the sustainable adoption of modern breeding approaches.

Transcriptome Landscape Variation in the Genus Thymus

Among the Lamiaceae family, the genus Thymus is an economically important genera due to its medicinal and aromatic properties. Most Thymus molecular research has focused on the determining the phylogenetic relationships between different species, but no published work has focused on the evolution of the transcriptome across the genus to elucidate genes involved in terpenoid biosynthesis. Hence, in this study, the transcriptomes of five different Thymus species were generated and analyzed to mine putative genes involved in thymol and carvacrol biosynthesis. High-throughput sequencing produced ~43 million high-quality reads per sample, which were assembled de novo using several tools, then further subjected to a quality evaluation. The best assembly for each species was used as queries to search within the UniProt, KEGG (Kyoto Encyclopedia of Genes and Genomes), COG (Clusters of Orthologous Groups) and TF (Transcription Factors) databases. Mining the transcriptomes resulted in the identification of 592 single-copy orthogroups used for phylogenetic analysis. The data showed strongly support a close genetic relationship between Thymus vulgaris and Thymus daenensis. Additionally, this study dates the speciation events between 1.5–2.1 and 9–10.2 MYA according to different methodologies. Our study provides a global overview of genes related to the terpenoid pathway in Thymus, and can help establish an understanding of the relationship that exists among Thymus species.

PRGdb 3.0: a comprehensive platform for prediction and analysis of plant disease resistance genes

The Plant Resistance Genes database (PRGdb; http://prgdb.org) has been redesigned with a new user interface, new sections, new tools and new data for genetic improvement, allowing easy access not only to the plant science research community but also to breeders who want to improve plant disease resistance. The home page offers an overview of easy-to-read search boxes that streamline data queries and directly show plant species for which data from candidate or cloned genes have been collected. Bulk data files and curated resistance gene annotations are made available for each plant species hosted. The new Gene Model view offers detailed information on each cloned resistance gene structure to highlight shared attributes with other genes. PRGdb 3.0 offers 153 reference resistance genes and 177 072 annotated candidate Pathogen Receptor Genes (PRGs). Compared to the previous release, the number of putative genes has been increased from 106 to 177 K from 76 sequenced Viridiplantae and algae genomes. The DRAGO 2 tool, which automatically annotates and predicts (PRGs) from DNA and amino acid with high accuracy and sensitivity, has been added. BLAST search has been implemented to offer users the opportunity to annotate and compare their own sequences. The improved section on plant diseases displays useful information linked to genes and genomes to connect complementary data and better address specific needs. Through, a revised and enlarged collection of data, the development of new tools and a renewed portal, PRGdb 3.0 engages the plant science community in developing a consensus plan to improve knowledge and strategies to fight diseases that afflict main crops and other plants.

Genome-wide transcriptome profiling of transgenic hop (Humulus lupulus L.) constitutively overexpressing HlWRKY1 and HlWDR1 transcription factors

Background

The hop plant (Humulus lupulus L.) is a valuable source of several secondary metabolites, such as flavonoids, bitter acids, and essential oils. These compounds are widely implicated in the beer brewing industry and are having potential biomedical applications. Several independent breeding programs around the world have been initiated to develop new cultivars with enriched lupulin and secondary metabolite contents but met with limited success due to several constraints. In the present work, a pioneering attempt has been made to overexpress master regulator binary transcription factor complex formed by HlWRKY1 and HlWDR1 using a plant expression vector to enhance the level of prenylflavonoid and bitter acid content in the hop. Subsequently, we performed transcriptional profiling using high-throughput RNA-Seq technology in leaves of resultant transformants and wild-type hop to gain in-depth information about the genome-wide functional changes induced by HlWRKY1 and HlWDR1 overexpression.

Results

The transgenic WW-lines exhibited an elevated expression of structural and regulatory genes involved in prenylflavonoid and bitter acid biosynthesis pathways. In addition, the comparative transcriptome analysis revealed a total of 522 transcripts involved in 30 pathways, including lipids and amino acids biosynthesis, primary carbon metabolism, phytohormone signaling and stress responses were differentially expressed in WW-transformants. It was apparent from the whole transcriptome sequencing that modulation of primary carbon metabolism and other pathways by HlWRKY1 and HlWDR1 overexpression resulted in enhanced substrate flux towards secondary metabolites pathway. The detailed analyses suggested that none of the pathways or genes, which have a detrimental effect on physiology, growth and development processes, were induced on a genome-wide scale in WW-transgenic lines.

Conclusions

Taken together, our results suggest that HlWRKY1 and HlWDR1 simultaneous overexpression positively regulates the prenylflavonoid and bitter acid biosynthesis pathways in the hop and thus these transgenes are presented as prospective candidates for achieving enhanced secondary metabolite content in the hop.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5125-8) contains supplementary material, which is available to authorized users.

Comparative Metabolic Phenotyping of Tomato (Solanum lycopersicum) for the Identification of Metabolic Signatures in Cultivars Differing in Resistance to Ralstonia solanacearum

Tomato (Solanum lycopersicum) is an important dietary source which contains numerous bioactive phytochemicals. Active breeding programs constantly produce new cultivars possessing superior and desirable traits. However, the underlying molecular signatures that functionally describe these traits are yet to be elucidated. Thus, in this study we used an untargeted metabolomic approach to describe differential metabolic profiles of four cultivars described as having high to intermediate resistance to Ralstonia solanacearum. Metabolites were methanol-extracted from leaves, stems and root tissues and analyzed by liquid chromatography coupled with high definition mass spectrometry. Multivariate data analysis revealed cultivar-related differential metabolic phenotypes. A total of 41 metabolites were statistically selected and annotated, consisting of amino acids, organic acids, lipids, derivatives of cinnamic acid and benzoic acids, flavonoids and steroidal glycoalkaloids which were especially prominent in the two highly resistant cultivars. Interestingly, the less resistant cultivars had various fatty acid derivatives in root extracts that contributed to the differentiated metabolic signatures. Moreover, the metabolic phenotype of the STAR9008 (8SC) cultivar with intermediate resistance, was characterized by derivatives of cinnamic acids and flavonoids but at lower levels compared to the resistant cultivars. The 8SC cultivar also exhibited a lack of hydroxybenzoic acid biomarkers, which may be attributed to its lower resistance. These metabolic phenotypes provide insights into the differential metabolic signatures underlying the metabolism of these four cultivars, defining their respective phenotypic traits such as their resistance, tolerance or susceptibility to Ralstonia solanacearum.

Identification of genomic regions associated with agronomic and biofortification traits in DH populations of rice

Rice provides energy and nutrition to more than half of the world’s population. Breeding rice varieties with the increased levels of bioavailable micronutrients is one of the most sustainable approaches to tackle micronutrient malnutrition. So, high zinc and iron content in the grain are primary targets in rice biofortification breeding. In this study, we conducted QTL mapping using doubled haploid (DH) populations, PSBRc82 x Joryeongbyeo and PSBRc82 x IR69428, phenotyped for agronomic traits and micronutrients during two growing seasons and using genotypic information from analysis with the 6K SNP chip. A number of DH lines were identified as having high grain Zn and Fe content in polished rice. Importantly, we identified 20 QTLs for agronomic traits and 59 QTLs for a number of biofortification traits. Of the 79 QTLs, 12 were large-effect QTLs (>25% PVE), nine QTLs were consistent across seasons in either population, and one QTL was identified in both populations. Moreover, at least two QTLs were clustered in defined regions of chromosomes 1, 2, 3, 4, 5, 7 and 9. Eight epistatic interactions were detected for Cu, Mg, Na, and Zn in population 1. Furthermore, we identified several candidate genes near QTLs for grain Zn (OsNRAMP, OsNAS, OsZIP, OsYSL, OsFER, and OsZIFL family) and grain yield (OsSPL14 and OsSPL16). These new QTLs and candidate genes help to further elucidate the genetic basis for grain micronutrient concentration, and may prove useful for marker assisted breeding for this important trait.

The State of "Omics" Research for Farmed Penaeids: Advances in Research and Impediments to Industry Utilization

Elucidating the underlying genetic drivers of production traits in agricultural and aquaculture species is critical to efforts to maximize farming efficiency. "Omics" based methods (i.e., transcriptomics, genomics, proteomics, and metabolomics) are increasingly being applied to gain unprecedented insight into the biology of many aquaculture species. While the culture of penaeid shrimp has increased markedly, the industry continues to be impeded in many regards by disease, reproductive dysfunction, and a poor understanding of production traits. Extensive effort has been, and continues to be, applied to develop critical genomic resources for many commercially important penaeids. However, the industry application of these genomic resources, and the translation of the knowledge derived from "omics" studies has not yet been completely realized. Integration between the multiple "omics" resources now available (i.e., genome assemblies, transcriptomes, linkage maps, optical maps, and proteomes) will prove critical to unlocking the full utility of these otherwise independently developed and isolated resources. Furthermore, emerging "omics" based techniques are now available to address longstanding issues with completing keystone genome assemblies (e.g., through long-read sequencing), and can provide cost-effective industrial scale genotyping tools (e.g., through low density SNP chips and genotype-by-sequencing) to undertake advanced selective breeding programs (i.e., genomic selection) and powerful genome-wide association studies. In particular, this review highlights the status, utility and suggested path forward for continued development, and improved use of "omics" resources in penaeid aquaculture.

Deep Learning: Individual Maize Segmentation From Terrestrial Lidar Data Using Faster R-CNN and Regional Growth Algorithms

The rapid development of light detection and ranging (Lidar) provides a promising way to obtain three-dimensional (3D) phenotype traits with its high ability of recording accurate 3D laser points. Recently, Lidar has been widely used to obtain phenotype data in the greenhouse and field with along other sensors. Individual maize segmentation is the prerequisite for high throughput phenotype data extraction at individual crop or leaf level, which is still a huge challenge. Deep learning, a state-of-the-art machine learning method, has shown high performance in object detection, classification, and segmentation. In this study, we proposed a method to combine deep leaning and regional growth algorithms to segment individual maize from terrestrial Lidar data. The scanned 3D points of the training site were sliced row and row with a fixed 3D window. Points within the window were compressed into deep images, which were used to train the Faster R-CNN (region-based convolutional neural network) model to learn the ability of detecting maize stem. Three sites of different planting densities were used to test the method. Each site was also sliced into many 3D windows, and the testing deep images were generated. The detected stem in the testing images can be mapped into 3D points, which were used as seed points for the regional growth algorithm to grow individual maize from bottom to up. The results showed that the method combing deep leaning and regional growth algorithms was promising in individual maize segmentation, and the values of r, p, and F of the three testing sites with different planting density were all over 0.9. Moreover, the height of the truly segmented maize was highly correlated to the manually measured height (R2> 0.9). This work shows the possibility of using deep leaning to solve the individual maize segmentation problem from Lidar data.

Natural variation in genes potentially involved in plant architecture and adaptation in switchgrass (Panicum virgatum L.)

Background

Advances in genomic technologies have expanded our ability to accurately and exhaustively detect natural genomic variants that can be applied in crop improvement and to increase our knowledge of plant evolution and adaptation. Switchgrass (Panicum virgatum L.), an allotetraploid (2n = 4× = 36) perennial C4 grass (Poaceae family) native to North America and a feedstock crop for cellulosic biofuel production, has a large potential for genetic improvement due to its high genotypic and phenotypic variation. In this study, we analyzed single nucleotide polymorphism (SNP) variation in 372 switchgrass genotypes belonging to 36 accessions for 12 genes putatively involved in biomass production to investigate signatures of selection that could have led to ecotype differentiation and to population adaptation to geographic zones.

Results

A total of 11,682 SNPs were mined from ~ 15 Gb of sequence data, out of which 251 SNPs were retained after filtering. Population structure analysis largely grouped upland accessions into one subpopulation and lowland accessions into two additional subpopulations. The most frequent SNPs were in homozygous state within accessions. Sixty percent of the exonic SNPs were non-synonymous and, of these, 45% led to non-conservative amino acid changes. The non-conservative SNPs were largely in linkage disequilibrium with one haplotype being predominantly present in upland accessions while the other haplotype was commonly present in lowland accessions. Tajima’s test of neutrality indicated that PHYB, a gene involved in photoperiod response, was under positive selection in the switchgrass population. PHYB carried a SNP leading to a non-conservative amino acid change in the PAS domain, a region that acts as a sensor for light and oxygen in signal transduction.

Conclusions

Several non-conservative SNPs in genes potentially involved in plant architecture and adaptation have been identified and led to population structure and genetic differentiation of ecotypes in switchgrass. We suggest here that PHYB is a key gene involved in switchgrass natural selection. Further analyses are needed to determine whether any of the non-conservative SNPs identified play a role in the differential adaptation of upland and lowland switchgrass.

Electronic supplementary material

The online version of this article (10.1186/s12862-018-1193-2) contains supplementary material, which is available to authorized users.

Efficient genome-wide genotyping strategies and data integration in crop plants

Next-generation sequencing (NGS) has revolutionized plant and animal research by providing powerful genotyping methods. This review describes and discusses the advantages, challenges and, most importantly, solutions to facilitate data processing, the handling of missing data, and cross-platform data integration. Next-generation sequencing technologies provide powerful and flexible genotyping methods to plant breeders and researchers. These methods offer a wide range of applications from genome-wide analysis to routine screening with a high level of accuracy and reproducibility. Furthermore, they provide a straightforward workflow to identify, validate, and screen genetic variants in a short time with a low cost. NGS-based genotyping methods include whole-genome re-sequencing, SNP arrays, and reduced representation sequencing, which are widely applied in crops. The main challenges facing breeders and geneticists today is how to choose an appropriate genotyping method and how to integrate genotyping data sets obtained from various sources. Here, we review and discuss the advantages and challenges of several NGS methods for genome-wide genetic marker development and genotyping in crop plants. We also discuss how imputation methods can be used to both fill in missing data in genotypic data sets and to integrate data sets obtained using different genotyping tools. It is our hope that this synthetic view of genotyping methods will help geneticists and breeders to integrate these NGS-based methods in crop plant breeding and research.